Disable setting user-agent, curl_cffi does that

Merge pull request #2445 from R5dan/contributing
Fix contributing.md
2025-05-06 19:28:17 +01:00 · 2025-05-05 14:19:47 +01:00 · 2025-05-04 19:39:24 +01:00 · 2025-05-03 12:14:48 +01:00 · 2025-05-03 11:19:43 +01:00 · 2025-05-03 11:18:20 +01:00
86 changed files with 4759 additions and 5330 deletions
--- a/.DS_Store
+++ b/.DS_Store
--- a/.github/ISSUE_TEMPLATE/bug_report.yaml
+++ b/.github/ISSUE_TEMPLATE/bug_report.yaml
@@ -54,7 +54,7 @@ body:
  - type: textarea
    id: debug-log
    attributes:
-      label: "Debug log"
+      label: "Debug log from yf.enable_debug_mode()"
      description: "Run code with debug logging enabled - `yf.enable_debug_mode()` - and post the full output. Context: https://github.com/ranaroussi/yfinance/tree/main#logging"
    validations:
      required: true
@@ -63,7 +63,7 @@ body:
    id: bad-data-proof
    attributes:
      label: "Bad data proof"
-      description: "If `yfinance` returning bad data, show proof here. Best is screenshot of finance.yahoo.com"
+      description: "If `yfinance` returning bad data, show proof of good data here. Best proof is screenshot of finance.yahoo.com"
    validations:
      required: false

--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -1,18 +0,0 @@
-name: ci
-on:
-  push:
-    branches:
-      - master
-      - main
-jobs:
-  deploy:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v4
-      - uses: actions/setup-python@v4
-        with:
-          python-version: 3.x
-      - run: pip install -r requirements.txt
-      - run: pip install mkdocstrings==0.14.0
-      - run: pip install mkdocs-material
-      - run: mkdocs gh-deploy --force
--- a/.github/workflows/pytest.yml.disabled
+++ b/.github/workflows/pytest.yml.disabled
@@ -0,0 +1,35 @@
+name: Pytest
+
+on:
+  pull_request:
+    branches:
+      - master
+      - main
+      - dev
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout code
+      uses: actions/checkout@v3
+
+    - name: Set up Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: "3.12"
+        cache: 'pip'
+
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install -r requirements.txt pytest
+
+    - name: Run non-cache tests
+      run: pytest tests/ --ignore tests/test_cache.py --ignore tests/test_price_repair.py
+
+    - name: Run cache tests
+      run: |
+        pytest tests/test_cache.py::TestCache
+        pytest tests/test_cache.py::TestCacheNoPermission
--- a/CHANGELOG.rst
+++ b/CHANGELOG.rst
@@ -1,6 +1,83 @@
 Change Log
 ===========

+0.2.58
+------
+Fix false rate-limit problem #2430
+Fix predefined screen size/count #2425
+
+0.2.57
+------
+Fix proxy msg & pass-thru #2418
+
+0.2.56
+------
+Features:
+- Ticker lookups #2364
+- Config #2391
+Fixes:
+- converting end epoch to localized dt #2378
+- info IndexError #2382
+- AttributeError: module 'requests.cookies' has no attribute 'update' #2388
+- fix_Yahoo_returning_live_separate() #2389
+
+0.2.55
+------
+Features
+- TTM financials #2321
+Fixes
+- info IndexError #2354
+- earnings dates TZ #2366
+- price repair tweaks & fixes #2368
+- history caching #2345
+- backup fetch TZ from info #2369
+Maintenance
+- log user agent #2326
+
+0.2.54
+------
+Hotfix user-agent #2277
+
+0.2.53
+------
+Fixes:
+- Fix: Failed to parse holders JSON data  #2234
+- Fix: Bad data in Holders #2244
+- Stop CSRF-cookie-fetch fail killing yfinance #2249
+- Fix Market Docs #2250
+- Fix: Broken "See also" links in documentation #2253
+- Fix: Interval check and error message formatting in multi.py #2256
+Improve:
+- Add pre- / post-stock prices (and other useful information) #2212
+- Warn user when use download() without specifying auto_adjust #2230
+- Refactor: Earnings Dates – Switch to API Fetching #2247
+- Improve prices div repair #2260
+Maintenance:
+- Add GitHub Actions workflow and fix failing tests #2233
+
+0.2.52
+------
+Features:
+- Improve Screener & docs #2207
+- Add Market summary & status #2175
+- Support custom period in Ticker.history() #2192
+- raise YfRateLimitError if rate limited #2108
+- add more options to Search #2191
+Fixes:
+- remove hardcoded keys in Analysis #2194
+- handle Yahoo changed Search response #2202
+Maintenance:
+- add optional dependencies to requirements.txt #2199
+
+0.2.51
+------
+Features:
+- Screener tweaks #2168
+- Search #2160
+- get_news() expose count #2173
+Fixes:
+- earnings_dates #2169
+
 0.2.50
 ------
 Fixes:
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -0,0 +1,77 @@
+# Contributing
+
+> [!NOTE]
+> This is a brief guide to contributing to yfinance.
+> For more information See the [Developer Guide](https://ranaroussi.github.io/yfinance/development) for more information.
+
+## Changes
+
+The list of changes can be found in the [Changelog](https://github.com/ranaroussi/yfinance/blob/main/CHANGELOG.rst)
+
+## Running a branch
+
+```bash
+pip install git+ranaroussi/yfinance.git@dev # dev branch
+```
+
+For more information, see the [Developer Guide](https://ranaroussi.github.io/yfinance/development/running.html).
+
+## Branches
+
+YFinance uses a two-layer branch model:
+
+* **dev**: new features & some bug-fixes merged here, tested together, conflicts fixed, etc.
+* **main**: stable branch where PIP releases are created.
+
+> [!NOTE]
+> By default, branches target **main**, but most contributions should target **dev**. 
+> Direct merges to **main** are allowed if:
+> * `yfinance` is massively broken
+> * Part of `yfinance` is broken, and the fix is simple and isolated
+> * Not updating the code (e.g. docs)
+
+> [!NOTE]
+> For more information, see the [Developer Guide](https://ranaroussi.github.io/yfinance/development/branches.html).
+
+### I'm a GitHub newbie, how do I contribute code?
+
+1. Fork this project. If already forked, remember to `Sync fork`
+
+2. Implement your change in your fork, ideally in a specific branch
+
+3. Create a Pull Request, from your fork to this project. If addressing an Issue, link to it
+
+> [!NOTE]
+> See the [Developer Guide](https://ranaroussi.github.io/yfinance/development/contributing.html) for more information.
+
+### [How to download & run a GitHub version of yfinance](#Running-a-branch)
+
+## Documentation website
+
+The new docs website [ranaroussi.github.io/yfinance/index.html](https://ranaroussi.github.io/yfinance/index.html) is generated automatically from code. 
+
+> [!NOTE]
+> See the [Developer Guide](https://ranaroussi.github.io/yfinance/development/documentation.html) for more information
+> Including how to build and run the docs locally.
+
+## Unit tests
+
+Tests have been written using the built-in Python module `unittest`. Examples:
+
+#### Run all tests: `python -m unittest discover -s tests`
+
+> [!NOTE]
+>
+> See the [Developer Guide](https://ranaroussi.github.io/yfinance/development/testing.html) for more information.
+
+## Git stuff
+### commits
+
+To keep the Git commit history and [network graph](https://github.com/ranaroussi/yfinance/network) compact please follow these two rules:
+
+* For long commit messages use this: `git commit -m "short sentence summary" -m "full commit message"`
+
+* `squash` tiny/negligible commits back with meaningful commits, or to combine successive related commits
+
+> [!NOTE]
+> See the [Developer Guide](https://ranaroussi.github.io/yfinance/development/contributing.html#GIT-STUFF) for more information.
--- a/README.md
+++ b/README.md
@@ -1,49 +1,50 @@
+<img src="./doc/yfinance-gh-logo-dark.webp#gh-dark-mode-only" height="100">
+<img src="./doc/yfinance-gh-logo-light.webp#gh-light-mode-only" height="100">
+
 # Download market data from Yahoo! Finance's API

-<table border=1 cellpadding=10><tr><td>
-
-#### \*\*\* IMPORTANT LEGAL DISCLAIMER \*\*\*
-
---
-
-**Yahoo!, Y!Finance, and Yahoo! finance are registered trademarks of
-Yahoo, Inc.**
-
-yfinance is **not** affiliated, endorsed, or vetted by Yahoo, Inc. It's
-an open-source tool that uses Yahoo's publicly available APIs, and is
-intended for research and educational purposes.
-
-**You should refer to Yahoo!'s terms of use**
-([here](https://policies.yahoo.com/us/en/yahoo/terms/product-atos/apiforydn/index.htm),
-[here](https://legal.yahoo.com/us/en/yahoo/terms/otos/index.html), and
-[here](https://policies.yahoo.com/us/en/yahoo/terms/index.htm)) **for
-details on your rights to use the actual data downloaded. Remember - the
-Yahoo! finance API is intended for personal use only.**
-
-</td></tr></table>
-
---
-
 <a target="new" href="https://pypi.python.org/pypi/yfinance"><img border=0 src="https://img.shields.io/badge/python-2.7,%203.6+-blue.svg?style=flat" alt="Python version"></a>
 <a target="new" href="https://pypi.python.org/pypi/yfinance"><img border=0 src="https://img.shields.io/pypi/v/yfinance.svg?maxAge=60%" alt="PyPi version"></a>
 <a target="new" href="https://pypi.python.org/pypi/yfinance"><img border=0 src="https://img.shields.io/pypi/status/yfinance.svg?maxAge=60" alt="PyPi status"></a>
 <a target="new" href="https://pypi.python.org/pypi/yfinance"><img border=0 src="https://img.shields.io/pypi/dm/yfinance.svg?maxAge=2592000&label=installs&color=%2327B1FF" alt="PyPi downloads"></a>
-<a target="new" href="https://www.codefactor.io/repository/github/ranaroussi/yfinance"><img border=0 src="https://www.codefactor.io/repository/github/ranaroussi/yfinance/badge" alt="CodeFactor"></a>
 <a target="new" href="https://github.com/ranaroussi/yfinance"><img border=0 src="https://img.shields.io/github/stars/ranaroussi/yfinance.svg?style=social&label=Star&maxAge=60" alt="Star this repo"></a>
-<a target="new" href="https://twitter.com/aroussi"><img border=0 src="https://img.shields.io/twitter/follow/aroussi.svg?style=social&label=Follow&maxAge=60" alt="Follow me on twitter"></a>
+<a target="new" href="https://x.com/intent/follow?screen_name=aroussi"><img border=0 src="https://img.shields.io/twitter/follow/aroussi.svg?style=social&label=Follow&maxAge=60" alt="Follow me on twitter"></a>
+
+

 **yfinance** offers a Pythonic way to fetch financial & market data from [Yahoo!Ⓡ finance](https://finance.yahoo.com).

+---
+
+> [!IMPORTANT]  
+> **Yahoo!, Y!Finance, and Yahoo! finance are registered trademarks of Yahoo, Inc.**
+>
+> yfinance is **not** affiliated, endorsed, or vetted by Yahoo, Inc. It's an open-source tool that uses Yahoo's publicly available APIs, and is intended for research and educational purposes.
+> 
+> **You should refer to Yahoo!'s terms of use** ([here](https://policies.yahoo.com/us/en/yahoo/terms/product-atos/apiforydn/index.htm), [here](https://legal.yahoo.com/us/en/yahoo/terms/otos/index.html), and [here](https://policies.yahoo.com/us/en/yahoo/terms/index.htm)) **for details on your rights to use the actual data downloaded.
+>
+> Remember - the Yahoo! finance API is intended for personal use only.**
+
+---
+
+> [!TIP]
+> THE NEW DOCUMENTATION WEBSITE IS NOW LIVE! 🤘
+> 
+> Visit [**ranaroussi.github.io/yfinance**](https://ranaroussi.github.io/yfinance)
+
+---
+
 ## Main components

 - `Ticker`: single ticker data
 - `Tickers`: multiple tickers' data
 - `download`: download market data for multiple tickers
+- `Market`: get information about a market
+- `WebSocket` and `AsyncWebSocket`: live streaming data
+- `Search`: quotes and news from search
 - `Sector` and `Industry`: sector and industry information
 - `EquityQuery` and `Screener`: build query to screen market

-## **NEW DOCUMENTATION WEBSITE**: [ranaroussi.github.io/yfinance](https://ranaroussi.github.io/yfinance/index.html)
-
 ## Installation

 Install `yfinance` from PYPI using `pip`:
@@ -52,11 +53,9 @@ Install `yfinance` from PYPI using `pip`:
 $ pip install yfinance
 ```

-The list of changes can be found in the [Changelog](https://github.com/ranaroussi/yfinance/blob/main/CHANGELOG.rst)
+---

-## Developers: want to contribute?
-
-`yfinance` relies on community to investigate bugs, review code, and contribute code. Developer guide: https://github.com/ranaroussi/yfinance/discussions/1084
+![Star History Chart](https://api.star-history.com/svg?repos=ranaroussi/yfinance)

 ---

--- a/doc/source/_static/logo-dark.webp
+++ b/doc/source/_static/logo-dark.webp
--- a/doc/source/_static/logo-light.webp
+++ b/doc/source/_static/logo-light.webp
--- a/doc/source/advanced/config.rst
+++ b/doc/source/advanced/config.rst
@@ -0,0 +1,15 @@
+******
+Config
+******
+
+`yfinance` has a new global config for sharing common values.
+
+Proxy
+-----
+
+Set proxy once in config, affects all yfinance data fetches.
+
+.. code-block:: python
+
+   import yfinance as yf
+   yf.set_config(proxy="PROXY_SERVER")
--- a/doc/source/advanced/index.rst
+++ b/doc/source/advanced/index.rst
@@ -6,6 +6,6 @@ Advanced
   :maxdepth: 2

   logging
-   proxy
+   config
   caching
   multi_level_columns
--- a/doc/source/advanced/proxy.rst
+++ b/doc/source/advanced/proxy.rst
@@ -1,11 +0,0 @@
-************
-Proxy Server
-************
-
-You can download data via a proxy:
-
-.. code-block:: python
-
-   msft = yf.Ticker("MSFT")
-   msft.history(..., proxy="PROXY_SERVER")
-
--- a/doc/source/conf.py
+++ b/doc/source/conf.py
@@ -10,8 +10,8 @@ sys.path.insert(0, os.path.abspath('../..'))
 # -- Project information -----------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information

-project = 'yfinance - market data downloader'
-copyright = '2017-2019 Ran Aroussi'
+project = 'yfinance / Pythonic access to market data'
+copyright = '2017-2025 Ran Aroussi'
 author = 'Ran Aroussi'

 # -- General configuration ---------------------------------------------------
@@ -29,7 +29,8 @@ exclude_patterns = []
 autoclass_content = 'both'
 autosummary_generate = True
 autodoc_default_options = {
-    'exclude-members': '__init__'
+    'exclude-members': '__init__',
+    'members': True,
 }

 # -- Options for HTML output -------------------------------------------------
@@ -39,7 +40,11 @@ html_title = 'yfinance'
 html_theme = 'pydata_sphinx_theme'
 html_theme_options = {
    "github_url": "https://github.com/ranaroussi/yfinance",
-    "navbar_align": "left"
+    "navbar_align": "left",
+    "logo": {
+      "image_light": "_static/logo-light.webp",
+      "image_dark": "_static/logo-dark.webp"
+   }
 }
 html_static_path = ['_static']
 html_css_files = ['yfinance.css']
--- a/doc/source/development/branches.rst
+++ b/doc/source/development/branches.rst
@@ -0,0 +1,40 @@
+Branches
+---------
+
+To support rapid development without breaking stable versions, this project uses a two-layer branch model:
+
+.. image:: assets/branches.png
+   :alt: Branching Model
+
+`Inspiration <https://miro.medium.com/max/700/1*2YagIpX6LuauC3ASpwHekg.png>`_
+
+- **dev**: New features and some bug fixes are merged here. This branch allows collective testing, conflict resolution, and further stabilization before merging into the stable branch.
+- **main**: Stable branch where PIP releases are created.
+
+By default, branches target **main**, but most contributions should target **dev**. 
+
+**Exceptions**:
+Direct merges to **main** are allowed if:
+
+- `yfinance` is massively broken
+- Part of `yfinance` is broken, and the fix is simple and isolated
+- Not updating the code (e.g. docs)
+
+Rebasing
+--------
+
+If asked to move your branch from **main** to **dev**:
+
+1. Ensure all relevant branches are pulled.
+2. Run:
+
+   .. code-block:: bash
+
+      git checkout {branch}
+      git rebase --onto dev main {brach}
+      git push --force-with-lease origin {branch}
+
+Running a branch
+----------------
+
+Please see `this page </development/running>`_.
--- a/doc/source/development/contributing.rst
+++ b/doc/source/development/contributing.rst
@@ -1,109 +1,61 @@
 ********************************
-Contributiong to yfinance
+Contributing to yfinance
 ********************************

-`yfinance` relies on the community to investigate bugs and contribute code. Here’s how you can help:
+`yfinance` relies on the community to investigate bugs and contribute code. Here&apos;s how you can help:

 Contributing
 ------------

-1. Fork the repository on GitHub.
+1. Fork the repository on GitHub. If already forked, remember to `Sync fork`
 2. Clone your forked repository:

   .. code-block:: bash

-      git clone https://github.com/your-username/yfinance.git
+      git clone https://github.com/{user}/{repo}.git

 3. Create a new branch for your feature or bug fix:

   .. code-block:: bash

-      git checkout -b feature-branch-name
+      git checkout -b {branch}

 4. Make your changes, commit them, and push your branch to GitHub. To keep the commit history and `network graph <https://github.com/ranaroussi/yfinance/network>`_ compact:

   Use short summaries for commits

-   .. code-block:: shell
+   .. code-block:: bash

      git commit -m "short summary" -m "full commit message"

   **Squash** tiny or negligible commits with meaningful ones.

-   .. code-block:: shell
+   .. code-block:: bash

      git rebase -i HEAD~2
-      git push --force-with-lease origin <branch-name>
+      git push --force-with-lease origin {branch}

-5. Open a pull request on the `yfinance` GitHub page.
+5. Open a pull request on the `yfinance` `Github <https://github.com/ranaroussi/yfinance/pulls>`_ page.

-For more information, see the `Developer Guide <https://github.com/ranaroussi/yfinance/discussions/1084>`_.
-
-Branches
+Git stuff
 ---------

-To support rapid development without breaking stable versions, this project uses a two-layer branch model:
+To keep the Git commit history and [network graph](https://github.com/ranaroussi/yfinance/network) compact please follow these two rules:

-.. image:: assets/branches.png
-   :alt: Branching Model
+- For long commit messages use this: `git commit -m "short sentence summary" -m "full commit message"`

-`Inspiration <https://miro.medium.com/max/700/1*2YagIpX6LuauC3ASpwHekg.png>`_
+- `squash` tiny/negligible commits back with meaningful commits, or to combine successive related commits. [Guide](https://docs.gitlab.com/ee/topics/git/git_rebase.html#interactive-rebase) but basically it's:

- **dev**: New features and some bug fixes are merged here. This branch allows collective testing, conflict resolution, and further stabilization before merging into the stable branch.
- **main**: Stable branch where PIP releases are created.
+.. code-block:: bash
+   git rebase -i HEAD~2
+   git push --force-with-lease origin {branch}

-By default, branches target **main**, but most contributions should target **dev**. 

-**Exceptions**:
-Direct merges to **main** are allowed if:
+### rebase
+ 
+You might be asked to move your branch from `main` to `dev`. Make sure you have pulled **all** relevant branches then run:

- `yfinance` is massively broken
- Part of `yfinance` is broken, and the fix is simple and isolated
-
-Unit Tests
----------
-
-Tests are written using Python’s `unittest` module. Here are some ways to run tests:
-
- **Run all price tests**:
-
-  .. code-block:: shell
-
-     python -m unittest tests.test_prices
-
- **Run a subset of price tests**:
-
-  .. code-block:: shell
-
-     python -m unittest tests.test_prices.TestPriceRepair
-
- **Run a specific test**:
-
-  .. code-block:: shell
-
-     python -m unittest tests.test_prices.TestPriceRepair.test_ticker_missing
-
- **Run all tests**:
-
-  .. code-block:: shell
-
-     python -m unittest discover -s tests
-
-Rebasing
--------------
-
-If asked to move your branch from **main** to **dev**:
-
-1. Ensure all relevant branches are pulled.
-2. Run:
-
-   .. code-block:: shell
-
-      git checkout <your-branch>
-      git rebase --onto dev main <branch-name>
-      git push --force-with-lease origin <branch-name>
-
-Running the GitHub Version of yfinance
--------------------------------------
-
-To download and run a GitHub version of `yfinance`, refer to `GitHub discussion <https://github.com/ranaroussi/yfinance/discussions/1080>`_
+.. code-block:: bash
+   git checkout {branch}
+   git rebase --onto dev main {brach}
+   git push --force-with-lease origin {branch}
--- a/doc/source/development/documentation.rst
+++ b/doc/source/development/documentation.rst
@@ -6,10 +6,10 @@ Contribution to the documentation
   :local:

 About documentation
------------------------
+-------------------
 * yfinance documentation is written in reStructuredText (rst) and built using Sphinx.
-* The documentation file is in `doc/source/..`.
-* Most of the notes under API References read from class and methods docstrings. These documentations, found in `doc/source/reference/api` is autogenerated by Sphinx and not included in git.
+* The documentation file is in ``doc/source/..``.
+* Most of the notes under API References read from class and methods docstrings. These documentations, found in ``doc/source/reference/api`` is autogenerated by Sphinx and not included in git.

 Building documentation locally
 -------------------------------
@@ -17,30 +17,35 @@ To build the documentation locally, follow these steps:

 1. **Install Required Dependencies**:

-   * Make sure `Sphinx` and any other dependencies are installed. If a `requirements.txt` file is available, you can install dependencies by running:
-   
-   .. code-block:: console
+   * Make sure ``Sphinx`` and any other dependencies are installed. If a ``requirements.txt`` file is available, you can install dependencies by running:
+
+   .. code-block:: bash

      pip install -r requirements.txt
-   
+      pip install Sphinx==8.0.2 pydata-sphinx-theme==0.15.4 Jinja2==3.1.4 sphinx-copybutton==0.5.2
+  

 2. **Build with Sphinx**:
    
   * After dependencies are installed, use the sphinx-build command to generate HTML documentation. 
-   * Go to `doc/` directory Run:
+   * Go to ``doc/`` directory Run:

-   .. code-block:: console
+   .. code-block:: bash

-      make clean && make html 
+      sphinx-build -b html doc/source doc/_build/html

 3. **View Documentation Locally**:

-   * Open `doc/build/html/index.html` in the browser to view the generated documentation.
+   ..code-block:: bash
+      python -m http.server -d ./doc/_build/html

-Building documentation on main 
-------------------------------
-The documentation updates are built on merge to `main` branch. This is done via GitHub Actions workflow based on `/yfinance/.github/workflows/deploy_doc.yml`.
+   Then open "localhost:8000" in browser

-1. Reivew the changes locally and push to `dev`.

-2. When `dev` gets merged to `main`, GitHub Actions workflow is automated to build documentation.
+Building documentation on main
+------------------------------
+The documentation updates are built on merge to ``main`` branch. This is done via GitHub Actions workflow based on ``/yfinance/.github/workflows/deploy_doc.yml``.
+
+1. Review the changes locally and push to ``dev``.
+
+2. When ``dev`` gets merged to ``main``, GitHub Actions workflow is automated to build documentation.
--- a/doc/source/development/index.rst
+++ b/doc/source/development/index.rst
@@ -7,4 +7,7 @@ Development

   contributing
   documentation
-   reporting_bug
+   reporting_bug
+   branches
+   testing
+   running
--- a/doc/source/development/running.rst
+++ b/doc/source/development/running.rst
@@ -0,0 +1,60 @@
+Running a branch
+================
+
+With PIP
+--------
+
+.. code-block:: bash
+    pip install git+https://github.com/{user}/{repo}.git@{branch}
+
+E.g.:
+
+.. code-block:: bash
+    pip install git+https://github.com/ranaroussi/yfinance.git@feature/name
+
+With Git
+--------
+
+1: Download from GitHub:
+
+.. code-block:: bash
+    git clone https://github.com/{user}/{repo}.git
+    pip install -r ./yfinance/requirements.txt
+
+Or if a specific branch:
+
+.. code-block:: bash
+    git clone -b {branch} https://github.com/{user}/{repo}.git
+    pip install -r ./yfinance/requirements.txt
+
+.. NOTE::
+    Only do the next part if you are installing globally
+
+    If you are installing for 1 specific project, then you can skip this step
+    and just `git clone` in the project directory
+
+2. Add download location to Python search path
+
+Two different ways, choose one:
+
+1) Add path to ``PYTHONPATH`` environment variable
+
+2) Add to top of Python file: 
+.. code-block:: python
+    import sys
+    sys.path.insert(0, "path/to/downloaded/yfinance")
+
+
+3: Verify
+
+.. code-block:: python
+    import yfinance
+    print(yfinance)
+
+Output should be:
+
+`<module 'yfinance' from 'path/to/downloaded/yfinance/yfinance/__init__.py'>`
+
+If output looks like this then you did step 2 wrong
+
+`<module 'yfinance' from '.../lib/python3.10/site-packages/yfinance/__init__.py'>`
--- a/doc/source/development/testing.rst
+++ b/doc/source/development/testing.rst
@@ -0,0 +1,50 @@
+Unit Tests
+----------
+
+Tests are written using Python&apos;s `unittest` module. Here are some ways to run tests:
+
+- **Run all price tests**:
+
+  .. code-block:: bash
+
+     python -m unittest tests.test_prices
+
+- **Run a subset of price tests**:
+
+  .. code-block:: bash
+
+     python -m unittest tests.test_prices.TestPriceRepair
+
+- **Run a specific test**:
+
+  .. code-block:: bash
+
+     python -m unittest tests.test_prices_repair.TestPriceRepair.test_ticker_missing
+
+- **General command**:
+
+  ..code-block:: bash
+
+     python -m unittest tests.{file}.{class}.{method}
+
+- **Run all tests**:
+
+  .. code-block:: bash
+
+     python -m unittest discover -s tests
+
+.. note::
+
+    The tests are currently failing already
+
+    Standard result:
+
+    **Failures:** 11
+
+    **Errors:** 93
+
+    **Skipped:** 1
+
+.. seealso::
+
+    See the ` ``unittest`` module <https://docs.python.org/3/library/unittest.html>`_ for more information.
--- a/doc/source/reference/examples/live_async.py
+++ b/doc/source/reference/examples/live_async.py
@@ -0,0 +1,23 @@
+import asyncio
+import yfinance as yf
+
+# define your message callback
+def message_handler(message):
+    print("Received message:", message)
+
+async def main():
+    # =======================
+    # With Context Manager
+    # =======================
+    async with yf.AsyncWebSocket() as ws:
+        await ws.subscribe(["AAPL", "BTC-USD"])
+        await ws.listen()
+
+    # =======================
+    # Without Context Manager
+    # =======================
+    ws = yf.AsyncWebSocket()
+    await ws.subscribe(["AAPL", "BTC-USD"])
+    await ws.listen()
+
+asyncio.run(main())
--- a/doc/source/reference/examples/live_sync.py
+++ b/doc/source/reference/examples/live_sync.py
@@ -0,0 +1,19 @@
+import yfinance as yf
+
+# define your message callback
+def message_handler(message):
+    print("Received message:", message)
+
+# =======================
+# With Context Manager
+# =======================
+with yf.WebSocket() as ws:
+    ws.subscribe(["AAPL", "BTC-USD"])
+    ws.listen(message_handler)
+
+# =======================
+# Without Context Manager
+# =======================
+ws = yf.WebSocket()
+ws.subscribe(["AAPL", "BTC-USD"])
+ws.listen(message_handler)
--- a/doc/source/reference/examples/lookup.py
+++ b/doc/source/reference/examples/lookup.py
@@ -0,0 +1,33 @@
+import yfinance as yf
+
+# Get All
+all = yf.Lookup("AAPL").all
+all = yf.Lookup("AAPL").get_all(count=100)
+
+# Get Stocks
+stock = yf.Lookup("AAPL").stock
+stock = yf.Lookup("AAPL").get_stock(count=100)
+
+# Get Mutual Funds
+mutualfund = yf.Lookup("AAPL").mutualfund
+mutualfund = yf.Lookup("AAPL").get_mutualfund(count=100)
+
+# Get ETFs
+etf = yf.Lookup("AAPL").etf
+etf = yf.Lookup("AAPL").get_etf(count=100)
+
+# Get Indices
+index = yf.Lookup("AAPL").index
+index = yf.Lookup("AAPL").get_index(count=100)
+
+# Get Futures
+future = yf.Lookup("AAPL").future
+future = yf.Lookup("AAPL").get_future(count=100)
+
+# Get Currencies
+currency = yf.Lookup("AAPL").currency
+currency = yf.Lookup("AAPL").get_currency(count=100)
+
+# Get Cryptocurrencies
+cryptocurrency = yf.Lookup("AAPL").cryptocurrency
+cryptocurrency = yf.Lookup("AAPL").get_cryptocurrency(count=100)
--- a/doc/source/reference/examples/market.py
+++ b/doc/source/reference/examples/market.py
@@ -0,0 +1,6 @@
+import yfinance as yf
+
+EUROPE = yf.Market("EUROPE")
+
+status = EUROPE.status
+summary = EUROPE.summary
--- a/doc/source/reference/examples/search.py
+++ b/doc/source/reference/examples/search.py
@@ -0,0 +1,10 @@
+import yfinance as yf
+
+# get list of quotes
+quotes = yf.Search("AAPL", max_results=10).quotes
+
+# get list of news
+news = yf.Search("Google", news_count=10).news
+
+# get list of related research
+research = yf.Search("apple", include_research=True).research
--- a/doc/source/reference/examples/ticker.py
+++ b/doc/source/reference/examples/ticker.py
@@ -20,3 +20,6 @@ dat.info

 # analysis
 dat.analyst_price_targets
+
+# websocket
+dat.live()
--- a/doc/source/reference/examples/tickers.py
+++ b/doc/source/reference/examples/tickers.py
@@ -5,4 +5,7 @@ tickers = yf.Tickers('msft aapl goog')
 # access each ticker using (example)
 tickers.tickers['MSFT'].info
 tickers.tickers['AAPL'].history(period="1mo")
-tickers.tickers['GOOG'].actions
+tickers.tickers['GOOG'].actions
+
+# websocket
+tickers.live()
--- a/doc/source/reference/index.rst
+++ b/doc/source/reference/index.rst
@@ -15,11 +15,18 @@ The following are the publicly available classes, and functions exposed by the `

 - :attr:`Ticker <yfinance.Ticker>`: Class for accessing single ticker data.
 - :attr:`Tickers <yfinance.Tickers>`: Class for handling multiple tickers.
+- :attr:`Market <yfinance.Market>`: Class for accessing market summary.
+- :attr:`download <yfinance.download>`: Function to download market data for multiple tickers.
+- :attr:`Search <yfinance.Search>`: Class for accessing search results.
+- :attr:`Lookup <yfinance.Lookup>`: Class for looking up tickers.
+- :class:`WebSocket <yfinance.WebSocket>`: Class for synchronously streaming live market data.
+- :class:`AsyncWebSocket <yfinance.AsyncWebSocket>`: Class for asynchronously streaming live market data.
 - :attr:`Sector <yfinance.Sector>`: Domain class for accessing sector information.
 - :attr:`Industry <yfinance.Industry>`: Domain class for accessing industry information.
- :attr:`download <yfinance.download>`: Function to download market data for multiple tickers.
- :attr:`EquityQuery <yfinance.EquityQuery>`: Class to build equity market query.
- :attr:`Screener <yfinance.Screener>`: Class to screen the market using defined query.
+- :attr:`Market <yfinance.Market>`: Class for accessing market status & summary.
+- :attr:`EquityQuery <yfinance.EquityQuery>`: Class to build equity query filters.
+- :attr:`FundQuery <yfinance.FundQuery>`: Class to build fund query filters.
+- :attr:`screen <yfinance.screen>`: Run equity/fund queries.
 - :attr:`enable_debug_mode <yfinance.enable_debug_mode>`: Function to enable debug mode for logging.
 - :attr:`set_tz_cache_location <yfinance.set_tz_cache_location>`: Function to set the timezone cache location.

@@ -30,9 +37,15 @@ The following are the publicly available classes, and functions exposed by the `

   yfinance.ticker_tickers
   yfinance.stock
+   yfinance.market
   yfinance.financials
   yfinance.analysis
+   yfinance.market
+   yfinance.search
+   yfinance.lookup
+   yfinance.websocket
   yfinance.sector_industry
+   yfinance.screener
   yfinance.functions

   yfinance.funds_data
--- a/doc/source/reference/yfinance.financials.rst
+++ b/doc/source/reference/yfinance.financials.rst
@@ -10,12 +10,16 @@ Financials

   get_income_stmt
   income_stmt
+   quarterly_income_stmt
+   ttm_income_stmt

   get_balance_sheet
   balance_sheet

   get_cashflow
   cashflow
+   quarterly_cashflow
+   ttm_cashflow

   get_earnings
   earnings
--- a/doc/source/reference/yfinance.functions.rst
+++ b/doc/source/reference/yfinance.functions.rst
@@ -13,25 +13,6 @@ The `download` function allows you to retrieve market data for multiple tickers

   download

-Query Market Data
-~~~~~~~~~~~~~~~~~~~~~
-The `Sector` and `Industry` modules allow you to access the sector and industry information.
-
-.. autosummary:: 
-   :toctree: api/
-
-   EquityQuery
-   Screener
-
-.. seealso::
-   :attr:`EquityQuery.valid_operand_fields <yfinance.EquityQuery.valid_operand_fields>`
-      supported operand values for query
-   :attr:`EquityQuery.valid_eq_operand_map <yfinance.EquityQuery.valid_eq_operand_map>`
-      supported `EQ query operand parameters`
-   :attr:`Screener.predefined_bodies <yfinance.Screener.predefined_bodies>`
-      supported predefined screens
-   
-
 Enable Debug Mode
 ~~~~~~~~~~~~~~~~~
 Enables logging of debug information for the `yfinance` package.
--- a/doc/source/reference/yfinance.market.rst
+++ b/doc/source/reference/yfinance.market.rst
@@ -0,0 +1,41 @@
+=====================
+Market
+=====================
+
+.. currentmodule:: yfinance
+
+
+Class
+------------
+The `Market` class, allows you to access market data in a Pythonic way.
+
+.. autosummary::
+   :toctree: api/
+
+   Market
+
+Market Sample Code
+------------------
+
+.. literalinclude:: examples/market.py
+   :language: python
+
+
+Markets
+------------
+There are 8 different markets available in Yahoo Finance.
+
+* US
+* GB
+
+\ 
+
+* ASIA
+* EUROPE
+
+\ 
+
+* RATES
+* COMMODITIES
+* CURRENCIES
+* CRYPTOCURRENCIES
--- a/doc/source/reference/yfinance.screener.rst
+++ b/doc/source/reference/yfinance.screener.rst
@@ -0,0 +1,27 @@
+=========================
+Screener & Query
+=========================
+
+.. currentmodule:: yfinance
+
+Query Market Data
+~~~~~~~~~~~~~~~~~~~~~
+The `Sector` and `Industry` modules allow you to access the sector and industry information.
+
+.. autosummary:: 
+   :toctree: api/
+
+   EquityQuery
+   FundQuery
+   screen
+
+.. seealso::
+   :attr:`EquityQuery.valid_fields <yfinance.EquityQuery.valid_fields>`
+      supported operand values for query
+   :attr:`EquityQuery.valid_values <yfinance.EquityQuery.valid_values>`
+      supported `EQ query operand parameters`
+   :attr:`FundQuery.valid_fields <yfinance.FundQuery.valid_fields>`
+      supported operand values for query
+   :attr:`FundQuery.valid_values <yfinance.FundQuery.valid_values>`
+      supported `EQ query operand parameters`
+   
--- a/doc/source/reference/yfinance.search.rst
+++ b/doc/source/reference/yfinance.search.rst
@@ -0,0 +1,34 @@
+=====================
+Search & Lookup
+=====================
+
+.. currentmodule:: yfinance
+
+
+Class
+------------
+The `Search` module, allows you to access search data in a Pythonic way.
+
+.. autosummary::
+   :toctree: api/
+
+   Search
+
+The `Lookup` module, allows you to look up tickers in a Pythonic way.
+
+.. autosummary::
+   :toctree: api/
+
+   Lookup
+
+Sample Code
+------------------
+The `Search` module, allows you to access search data in a Pythonic way.
+
+.. literalinclude:: examples/search.py
+   :language: python
+
+The `Lookup` module, allows you to look up tickers in a Pythonic way.
+
+.. literalinclude:: examples/lookup.py
+   :language: python
--- a/doc/source/reference/yfinance.websocket.rst
+++ b/doc/source/reference/yfinance.websocket.rst
@@ -0,0 +1,46 @@
+=====================
+WebSocket
+=====================
+
+.. currentmodule:: yfinance
+
+The `WebSocket` module allows you to stream live price data from Yahoo Finance using both synchronous and asynchronous clients.
+
+Classes
+------------
+
+.. autosummary::
+   :toctree: api/
+
+   WebSocket
+   AsyncWebSocket
+
+Synchronous WebSocket
+----------------------
+
+The `WebSocket` class provides a synchronous interface for subscribing to price updates.
+
+Sample Code:
+
+.. literalinclude:: examples/live_sync.py
+   :language: python
+
+Asynchronous WebSocket
+-----------------------
+
+The `AsyncWebSocket` class provides an asynchronous interface for subscribing to price updates.
+
+Sample Code:
+
+.. literalinclude:: examples/live_async.py
+   :language: python
+
+.. note::
+    If you're running asynchronous code in a Jupyter notebook, you may encounter issues with event loops. To resolve this, you need to import and apply `nest_asyncio` to allow nested event loops.
+
+    Add the following code before running asynchronous operations:
+
+    .. code-block:: python
+
+        import nest_asyncio
+        nest_asyncio.apply()
--- a/doc/yfinance-gh-icon-dark.webp
+++ b/doc/yfinance-gh-icon-dark.webp
--- a/doc/yfinance-gh-icon-light.webp
+++ b/doc/yfinance-gh-icon-light.webp
--- a/doc/yfinance-gh-logo-dark.webp
+++ b/doc/yfinance-gh-logo-dark.webp
--- a/doc/yfinance-gh-logo-light.webp
+++ b/doc/yfinance-gh-logo-light.webp
--- a/meta.yaml
+++ b/meta.yaml
@@ -1,5 +1,5 @@
 {% set name = "yfinance" %}
-{% set version = "0.2.50" %}
+{% set version = "0.2.58" %}

 package:
  name: "{{ name|lower }}"
@@ -26,8 +26,8 @@ requirements:
    - frozendict >=2.3.4
    - beautifulsoup4 >=4.11.1
    - html5lib >=1.1
+    - curl_cffi >=0.7
    - peewee >=3.16.2
-    # - pycryptodome >=3.6.6
    - pip
    - python

@@ -42,8 +42,8 @@ requirements:
    - frozendict >=2.3.4
    - beautifulsoup4 >=4.11.1
    - html5lib >=1.1
+    - curl_cffi >=0.7
    - peewee >=3.16.2
-    # - pycryptodome >=3.6.6
    - python

 test:
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -1,19 +0,0 @@
-# site_name: My Docs
-
-# # mkdocs.yml
-# theme:
-#   name: "material"
-
-# plugins:
-# - search
-# - mkdocstrings
-
-# nav:
-#   - Introduction: 'index.md'
-#   - Installation: 'installation.md'
-#   - Quick Start: 'quickstart.md'
-#   # - Ticker: 'Ticker.md'
-#   - TickerBase: 'TickerBase.md'
-#   # - Tickers: 'Tickers.md'
-#   - utils: 'utils.md'
-#   - multi: 'multi.md'
--- a/requirements.txt
+++ b/requirements.txt
@@ -2,10 +2,14 @@ pandas>=1.3.0
 numpy>=1.16.5
 requests>=2.31
 multitasking>=0.0.7
-lxml>=4.9.1
 platformdirs>=2.0.0
 pytz>=2022.5
 frozendict>=2.3.4
 beautifulsoup4>=4.11.1
-html5lib>=1.1
-peewee>=3.16.2
+peewee>=3.16.2
+requests_cache>=1.0
+requests_ratelimiter>=0.3.1
+scipy>=1.6.3
+curl_cffi>=0.7
+protobuf>=5.29.0,<6
+websockets>=11.0
--- a/setup.py
+++ b/setup.py
@@ -61,13 +61,19 @@ setup(
    packages=find_packages(exclude=['contrib', 'docs', 'tests', 'examples']),
    install_requires=['pandas>=1.3.0', 'numpy>=1.16.5',
                      'requests>=2.31', 'multitasking>=0.0.7',
-                      'lxml>=4.9.1', 'platformdirs>=2.0.0', 'pytz>=2022.5',
+                      'platformdirs>=2.0.0', 'pytz>=2022.5',
                      'frozendict>=2.3.4', 'peewee>=3.16.2',
-                      'beautifulsoup4>=4.11.1', 'html5lib>=1.1'],
+                      'beautifulsoup4>=4.11.1', 'curl_cffi>=0.7',
+                      'protobuf>=5.29.0,<6', 'websockets>=11.0'],
    extras_require={
        'nospam': ['requests_cache>=1.0', 'requests_ratelimiter>=0.3.1'],
        'repair': ['scipy>=1.6.3'],
    },
+    # Include protobuf files for websocket support
+    package_data={
+        'yfinance': ['pricing.proto', 'pricing_pb2.py'],
+    },
+    include_package_data=True,
    # Note: Pandas.read_html() needs html5lib & beautifulsoup4
    entry_points={
        'console_scripts': [
--- a/tests/context.py
+++ b/tests/context.py
@@ -5,9 +5,7 @@ import datetime as _dt
 import sys
 import os
 import yfinance
-from requests import Session
-from requests_cache import CacheMixin, SQLiteCache
-from requests_ratelimiter import LimiterMixin, MemoryQueueBucket
+from requests_ratelimiter import LimiterSession
 from pyrate_limiter import Duration, RequestRate, Limiter

 _parent_dp = os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))
@@ -27,19 +25,21 @@ if os.path.isdir(testing_cache_dirpath):
        import shutil
        shutil.rmtree(testing_cache_dirpath)

-
-# Setup a session to rate-limit and cache persistently:
-class CachedLimiterSession(CacheMixin, LimiterMixin, Session):
-    pass
-history_rate = RequestRate(1, Duration.SECOND*2)
+# Setup a session to only rate-limit
+history_rate = RequestRate(1, Duration.SECOND)
 limiter = Limiter(history_rate)
-cache_fp = os.path.join(testing_cache_dirpath, "unittests-cache")
-session_gbl = CachedLimiterSession(
-    limiter=limiter,
-    bucket_class=MemoryQueueBucket,
-    backend=SQLiteCache(cache_fp, expire_after=_dt.timedelta(hours=1)),
-)
-# Use this instead if only want rate-limiting:
-# from requests_ratelimiter import LimiterSession
-# session_gbl = LimiterSession(limiter=limiter)
+session_gbl = LimiterSession(limiter=limiter)

+# Use this instead if you also want caching:
+# from requests_cache import CacheMixin, SQLiteCache
+# from requests_ratelimiter import LimiterMixin
+# from requests import Session
+# from pyrate_limiter import MemoryQueueBucket
+# class CachedLimiterSession(CacheMixin, LimiterMixin, Session):
+#     pass
+# cache_fp = os.path.join(testing_cache_dirpath, "unittests-cache")
+# session_gbl = CachedLimiterSession(
+#     limiter=limiter,
+#     bucket_class=MemoryQueueBucket,
+#     backend=SQLiteCache(cache_fp, expire_after=_dt.timedelta(hours=1)),
+# )
--- a/tests/data/KWS-L-1d-bad-div-fixed.csv
+++ b/tests/data/KWS-L-1d-bad-div-fixed.csv
@@ -1,725 +0,0 @@
-Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits,Repaired?
-2022-01-04 00:00:00+00:00,29.46,29.98,28.52,28.66,20.53276113953462,169521.0,0.0,0.0,True
-2022-01-05 00:00:00+00:00,30.0,30.0,28.46,28.900000000000002,20.70470257643437,128698.0,0.0,0.0,True
-2022-01-06 00:00:00+00:00,28.2,28.560000000000002,27.5,27.82,19.930963478279654,374659.0,0.0,0.0,True
-2022-01-07 00:00:00+00:00,28.3,28.3,27.400000000000002,27.46,19.67305220029865,80410.0,0.0,0.0,True
-2022-01-10 00:00:00+00:00,28.16,28.240000000000002,26.2,26.580000000000002,19.042597925349927,135881.0,0.0,0.0,True
-2022-01-11 00:00:00+00:00,25.92,27.060000000000002,25.92,26.72,19.142895195909453,71414.0,0.0,0.0,True
-2022-01-12 00:00:00+00:00,26.72,26.96,26.060000000000002,26.8,19.200210178034187,68611.0,0.0,0.0,True
-2022-01-13 00:00:00+00:00,26.72,27.3239990234375,26.6,27.2,19.486779824446177,155917.0,0.0,0.0,True
-2022-01-14 00:00:00+00:00,27.52,27.52,26.36,26.560000000000002,19.028270495871666,66402.0,0.0,0.0,True
-2022-01-17 00:00:00+00:00,27.02,27.22,26.28,27.22,19.50111251813613,60092.0,0.0,0.0,True
-2022-01-18 00:00:00+00:00,27.66,27.66,26.0,26.86,19.243195975943426,128385.0,0.0,0.0,True
-2022-01-19 00:00:00+00:00,27.0,27.46,26.7,27.2,19.486779824446177,75141.0,0.0,0.0,True
-2022-01-20 00:00:00+00:00,26.900000000000002,27.7,26.81172119140625,27.54,19.730365427686156,99304.0,0.0,0.0,True
-2022-01-21 00:00:00+00:00,27.26,27.88,26.214208984375002,26.38,18.89931310214393,123570.0,0.0,0.0,True
-2022-01-24 00:00:00+00:00,26.14,26.261599121093752,24.72,24.88,17.824671663887276,148794.0,0.0,0.0,True
-2022-01-25 00:00:00+00:00,24.92,25.2,24.580000000000002,24.580000000000002,17.609746183815513,94318.0,0.0,0.0,True
-2022-01-26 00:00:00+00:00,25.52,25.52,24.400000000000002,24.66,17.667057656465794,265198.0,0.0,0.0,True
-2022-01-27 00:00:00+00:00,24.66,25.12669921875,24.400000000000002,24.82,17.78168762071526,248811.0,0.0,0.0,True
-2022-01-28 00:00:00+00:00,24.7,24.88,24.1,24.32,17.4234773174375,146209.0,0.0,0.0,True
-2022-01-31 00:00:00+00:00,25.3,25.46,24.3,25.2,18.05392983764899,495745.0,0.0,0.0,True
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-2024-10-28 00:00:00+00:00,,,,,,,0.0,0.0,False
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--- a/tests/data/KWS-L-1d-bad-div.csv
+++ b/tests/data/KWS-L-1d-bad-div.csv
@@ -1,725 +0,0 @@
-Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits
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-2024-10-24 00:00:00+01:00,,,,,,,0.0,0.0
-2024-10-25 00:00:00+01:00,,,,,,,0.0,0.0
-2024-10-28 00:00:00+00:00,,,,,,,0.0,0.0
-2024-10-29 00:00:00+00:00,,,,,,,0.0,0.0
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-2024-11-05 00:00:00+00:00,,,,,,,0.0,0.0
-2024-11-06 00:00:00+00:00,,,,,,,0.0,0.0
-2024-11-07 00:00:00+00:00,,,,,,,0.0,0.0
-2024-11-08 00:00:00+00:00,,,,,,,0.0,0.0
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-2024-11-12 00:00:00+00:00,,,,,,,0.0,0.0
-2024-11-13 00:00:00+00:00,,,,,,,0.0,0.0
-2024-11-14 00:00:00+00:00,,,,,,,0.0,0.0
--- a/tests/data/SCR-TO-1d-bad-div-fixed.csv
+++ b/tests/data/SCR-TO-1d-bad-div-fixed.csv
--- a/tests/data/SOLB-BR-1d-bad-div-fixed.csv
+++ b/tests/data/SOLB-BR-1d-bad-div-fixed.csv
@@ -1,741 +0,0 @@
-Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits,Repaired?
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--- a/tests/data/SOLB-BR-1d-bad-div.csv
+++ b/tests/data/SOLB-BR-1d-bad-div.csv
@@ -1,741 +0,0 @@
-Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits
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-2024-10-16 00:00:00+02:00,38.5,39.31999969482422,38.310001373291016,39.31999969482422,39.31999969482422,351315,0.0,0.0
-2024-10-17 00:00:00+02:00,39.27000045776367,39.310001373291016,37.95000076293945,38.439998626708984,38.439998626708984,336837,0.0,0.0
-2024-10-18 00:00:00+02:00,38.209999084472656,39.369998931884766,37.939998626708984,39.349998474121094,39.349998474121094,284589,0.0,0.0
-2024-10-21 00:00:00+02:00,39.11000061035156,39.13999938964844,38.43000030517578,39.099998474121094,39.099998474121094,176237,0.0,0.0
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-2024-10-28 00:00:00+01:00,38.560001373291016,38.81999969482422,37.84000015258789,38.25,38.25,156263,0.0,0.0
-2024-10-29 00:00:00+01:00,38.25,38.88999938964844,38.029998779296875,38.31999969482422,38.31999969482422,213012,0.0,0.0
-2024-10-30 00:00:00+01:00,37.75,38.04999923706055,37.029998779296875,37.029998779296875,37.029998779296875,397551,0.0,0.0
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-2024-11-01 00:00:00+01:00,36.84000015258789,37.43000030517578,36.84000015258789,37.2400016784668,37.2400016784668,81048,0.0,0.0
-2024-11-04 00:00:00+01:00,37.060001373291016,37.79999923706055,37.040000915527344,37.560001373291016,37.560001373291016,82632,0.0,0.0
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-2024-11-18 00:00:00+01:00,32.20000076293945,32.72999954223633,32.08000183105469,32.130001068115234,32.130001068115234,94641,0.0,0.0
-2024-11-19 00:00:00+01:00,32.099998474121094,32.650001525878906,31.06999969482422,31.920000076293945,31.920000076293945,159142,0.0,0.0
--- a/tests/test_cache.py
+++ b/tests/test_cache.py
@@ -0,0 +1,50 @@
+"""
+Tests for cache
+
+To run all tests in suite from commandline:
+   python -m unittest tests.cache
+
+Specific test class:
+   python -m unittest tests.cache.TestCache
+
+"""
+from tests.context import yfinance as yf
+
+import unittest
+import tempfile
+import os
+
+
+class TestCache(unittest.TestCase):
+    @classmethod
+    def setUpClass(cls):
+        cls.tempCacheDir = tempfile.TemporaryDirectory()
+        yf.set_tz_cache_location(cls.tempCacheDir.name)
+
+    @classmethod
+    def tearDownClass(cls):
+        yf.cache._TzDBManager.close_db()
+        cls.tempCacheDir.cleanup()
+
+    def test_storeTzNoRaise(self):
+        # storing TZ to cache should never raise exception
+        tkr = 'AMZN'
+        tz1 = "America/New_York"
+        tz2 = "London/Europe"
+        cache = yf.cache.get_tz_cache()
+        cache.store(tkr, tz1)
+        cache.store(tkr, tz2)
+
+    def test_setTzCacheLocation(self):
+        self.assertEqual(yf.cache._TzDBManager.get_location(), self.tempCacheDir.name)
+
+        tkr = 'AMZN'
+        tz1 = "America/New_York"
+        cache = yf.cache.get_tz_cache()
+        cache.store(tkr, tz1)
+
+        self.assertTrue(os.path.exists(os.path.join(self.tempCacheDir.name, "tkr-tz.db")))
+
+
+if __name__ == '__main__':
+    unittest.main()
--- a/tests/test_cache_noperms.py
+++ b/tests/test_cache_noperms.py
@@ -0,0 +1,52 @@
+"""
+Tests for cache
+
+To run all tests in suite from commandline:
+   python -m unittest tests.cache
+
+Specific test class:
+   python -m unittest tests.cache.TestCache
+
+"""
+from tests.context import yfinance as yf
+
+import unittest
+import os
+
+
+class TestCacheNoPermission(unittest.TestCase):
+    @classmethod
+    def setUpClass(cls):
+        if os.name == "nt":  # Windows
+            cls.cache_path = "C:\\Windows\\System32\\yf-cache"
+        else:  # Unix/Linux/MacOS
+            # Use a writable directory
+            cls.cache_path = "/yf-cache"
+        yf.set_tz_cache_location(cls.cache_path)
+
+    def test_tzCacheRootStore(self):
+        # Test that if cache path in read-only filesystem, no exception.
+        tkr = 'AMZN'
+        tz1 = "America/New_York"
+
+        # During attempt to store, will discover cannot write
+        yf.cache.get_tz_cache().store(tkr, tz1)
+
+        # Handling the store failure replaces cache with a dummy
+        cache = yf.cache.get_tz_cache()
+        self.assertTrue(cache.dummy)
+        cache.store(tkr, tz1)
+
+    def test_tzCacheRootLookup(self):
+        # Test that if cache path in read-only filesystem, no exception.
+        tkr = 'AMZN'
+        # During attempt to lookup, will discover cannot write
+        yf.cache.get_tz_cache().lookup(tkr)
+
+        # Handling the lookup failure replaces cache with a dummy
+        cache = yf.cache.get_tz_cache()
+        self.assertTrue(cache.dummy)
+        cache.lookup(tkr)
+
+if __name__ == '__main__':
+    unittest.main()
--- a/tests/test_live.py
+++ b/tests/test_live.py
@@ -0,0 +1,30 @@
+import unittest
+from unittest.mock import Mock
+
+from yfinance.live import BaseWebSocket
+
+
+class TestWebSocket(unittest.TestCase):
+    def test_decode_message_valid(self):
+        message = ("CgdCVEMtVVNEFYoMuUcYwLCVgIplIgNVU0QqA0NDQzApOAFFPWrEP0iAgOrxvANVx/25R12csrRHZYD8skR9/"
+                   "7i0R7ABgIDq8bwD2AEE4AGAgOrxvAPoAYCA6vG8A/IBA0JUQ4ECAAAAwPrjckGJAgAA2P5ZT3tC")
+
+        ws = BaseWebSocket(Mock())
+        decoded = ws._decode_message(message)
+
+        expected = {'id': 'BTC-USD', 'price': 94745.08, 'time': '1736509140000', 'currency': 'USD', 'exchange': 'CCC',
+                    'quote_type': 41, 'market_hours': 1, 'change_percent': 1.5344921, 'day_volume': '59712028672',
+                    'day_high': 95227.555, 'day_low': 92517.22, 'change': 1431.8906, 'open_price': 92529.99,
+                    'last_size': '59712028672', 'price_hint': '2', 'vol_24hr': '59712028672',
+                    'vol_all_currencies': '59712028672', 'from_currency': 'BTC', 'circulating_supply': 19808172.0,
+                    'market_cap': 1876726640000.0}
+
+        self.assertEqual(expected, decoded)
+
+    def test_decode_message_invalid(self):
+        websocket = BaseWebSocket(Mock())
+        base64_message = "invalid_base64_string"
+        decoded = websocket._decode_message(base64_message)
+        assert "error" in decoded
+        assert "raw_base64" in decoded
+        self.assertEqual(base64_message, decoded["raw_base64"])
--- a/tests/test_lookup.py
+++ b/tests/test_lookup.py
@@ -0,0 +1,69 @@
+import unittest
+
+import pandas as pd
+
+from tests.context import yfinance as yf, session_gbl
+
+
+class TestLookup(unittest.TestCase):
+    def setUp(self):
+        self.query = "A"  # Generic query to make sure all lookup types are returned
+        self.lookup = yf.Lookup(query=self.query, session=session_gbl)
+
+    def test_get_all(self):
+        result = self.lookup.get_all(count=5)
+
+        self.assertIsInstance(result, pd.DataFrame)
+        self.assertEqual(len(result), 5)
+
+    def test_get_stock(self):
+        result = self.lookup.get_stock(count=5)
+
+        self.assertIsInstance(result, pd.DataFrame)
+        self.assertEqual(len(result), 5)
+
+    def test_get_mutualfund(self):
+        result = self.lookup.get_mutualfund(count=5)
+
+        self.assertIsInstance(result, pd.DataFrame)
+        self.assertEqual(len(result), 5)
+
+    def test_get_etf(self):
+        result = self.lookup.get_etf(count=5)
+
+        self.assertIsInstance(result, pd.DataFrame)
+        self.assertEqual(len(result), 5)
+
+    def test_get_index(self):
+        result = self.lookup.get_index(count=5)
+
+        self.assertIsInstance(result, pd.DataFrame)
+        self.assertEqual(len(result), 5)
+
+    def test_get_future(self):
+        result = self.lookup.get_future(count=5)
+
+        self.assertIsInstance(result, pd.DataFrame)
+        self.assertEqual(len(result), 5)
+
+    def test_get_currency(self):
+        result = self.lookup.get_currency(count=5)
+
+        self.assertIsInstance(result, pd.DataFrame)
+        self.assertEqual(len(result), 5)
+
+    def test_get_cryptocurrency(self):
+        result = self.lookup.get_cryptocurrency(count=5)
+
+        self.assertIsInstance(result, pd.DataFrame)
+        self.assertEqual(len(result), 5)
+
+    def test_large_all(self):
+        result = self.lookup.get_all(count=1000)
+
+        self.assertIsInstance(result, pd.DataFrame)
+        self.assertEqual(len(result), 1000)
+
+
+if __name__ == "__main__":
+    unittest.main()
--- a/tests/test_price_repair.py
+++ b/tests/test_price_repair.py
@@ -361,15 +361,15 @@ class TestPriceRepair(unittest.TestCase):
        hist = dat._lazy_load_price_history()
        tz_exchange = dat.fast_info["timezone"]

-        df_bad = _pd.DataFrame(data={"Open":      [0,      102.04, 102.04],
-                                     "High":      [0,      102.1,  102.11],
-                                     "Low":       [0,      102.04, 102.04],
-                                     "Close":     [103.03, 102.05, 102.08],
-                                     "Adj Close": [102.03, 102.05, 102.08],
-                                     "Volume": [560, 137, 117]},
-                               index=_pd.to_datetime([_dt.datetime(2022, 11, 1),
-                                                      _dt.datetime(2022, 10, 31),
-                                                      _dt.datetime(2022, 10, 30)]))
+        df_bad = _pd.DataFrame(data={"Open":      [0,      114.37, 114.20],
+                                     "High":      [0,      114.40, 114.40],
+                                     "Low":       [0,      114.36, 114.20],
+                                     "Close":     [114.39, 114.38, 114.45],
+                                     "Adj Close": [114.39, 114.38, 114.45],
+                                     "Volume":    [9,      15666,  1094]},
+                               index=_pd.to_datetime([_dt.datetime(2025, 3, 17),
+                                                      _dt.datetime(2025, 3, 14),
+                                                      _dt.datetime(2025, 3, 13)]))
        df_bad = df_bad.sort_index()
        df_bad.index.name = "Date"
        df_bad.index = df_bad.index.tz_localize(tz_exchange)
@@ -377,11 +377,11 @@ class TestPriceRepair(unittest.TestCase):
        repaired_df = hist._fix_zeroes(df_bad, "1d", tz_exchange, prepost=False)

        correct_df = df_bad.copy()
-        correct_df.loc["2022-11-01", "Open"] = 102.080002
-        correct_df.loc["2022-11-01", "Low"] = 102.032501
-        correct_df.loc["2022-11-01", "High"] = 102.080002
+        correct_df.loc["2025-03-17", "Open"] = 114.62
+        correct_df.loc["2025-03-17", "High"] = 114.62
+        correct_df.loc["2025-03-17", "Low"] = 114.41
        for c in ["Open", "Low", "High", "Close"]:
-            self.assertTrue(_np.isclose(repaired_df[c], correct_df[c], rtol=1e-8).all())
+            self.assertTrue(_np.isclose(repaired_df[c], correct_df[c], rtol=1e-7).all())

        self.assertTrue("Repaired?" in repaired_df.columns)
        self.assertFalse(repaired_df["Repaired?"].isna().any())
@@ -390,19 +390,21 @@ class TestPriceRepair(unittest.TestCase):
        # Test that 'Adj Close' is reconstructed correctly,
        # particularly when a dividend occurred within 1 day.

+        self.skipTest("Currently failing because Yahoo returning slightly different data for interval 1d vs 1h on day Aug 6 2024")
+
        tkr = "INTC"
-        df = _pd.DataFrame(data={"Open":      [28.95, 28.65, 29.55, 29.62, 29.25],
-                                 "High":      [29.12, 29.27, 29.65, 31.17, 30.30],
-                                 "Low":       [28.21, 28.43, 28.61, 29.53, 28.80],
-                                 "Close":     [28.24, 29.05, 28.69, 30.32, 30.19],
-                                 "Adj Close": [28.12, 28.93, 28.57, 29.83, 29.70],
-                                 "Volume":    [36e6, 51e6, 49e6, 58e6, 62e6],
-                                 "Dividends": [0, 0, 0.365, 0, 0]},
-                           index=_pd.to_datetime([_dt.datetime(2023, 2, 8),
-                                                  _dt.datetime(2023, 2, 7),
-                                                  _dt.datetime(2023, 2, 6),
-                                                  _dt.datetime(2023, 2, 3),
-                                                  _dt.datetime(2023, 2, 2)]))
+        df = _pd.DataFrame(data={"Open":      [2.020000e+01, 2.032000e+01, 1.992000e+01, 1.910000e+01, 2.008000e+01],
+                                 "High":      [2.039000e+01, 2.063000e+01, 2.025000e+01, 2.055000e+01, 2.015000e+01],
+                                 "Low":       [1.929000e+01, 1.975000e+01, 1.895000e+01, 1.884000e+01, 1.950000e+01],
+                                 "Close":     [2.011000e+01, 1.983000e+01, 1.899000e+01, 2.049000e+01, 1.971000e+01],
+                                 "Adj Close": [1.998323e+01, 1.970500e+01, 1.899000e+01, 2.049000e+01, 1.971000e+01],
+                                 "Volume":    [1.473857e+08, 1.066704e+08, 9.797230e+07, 9.683680e+07, 7.639450e+07],
+                                 "Dividends": [0.000000e+00, 0.000000e+00, 1.250000e-01, 0.000000e+00, 0.000000e+00]},
+                           index=_pd.to_datetime([_dt.datetime(2024, 8, 9),
+                                                  _dt.datetime(2024, 8, 8),
+                                                  _dt.datetime(2024, 8, 7),
+                                                  _dt.datetime(2024, 8, 6),
+                                                  _dt.datetime(2024, 8, 5)]))
        df = df.sort_index()
        df.index.name = "Date"
        dat = yf.Ticker(tkr, session=self.session)
@@ -462,7 +464,7 @@ class TestPriceRepair(unittest.TestCase):
        # Stocks that split in 2022 but no problems in Yahoo data,
        # so repair should change nothing
        good_tkrs = ['AMZN', 'DXCM', 'FTNT', 'GOOG', 'GME', 'PANW', 'SHOP', 'TSLA']
-        good_tkrs += ['AEI', 'GHI', 'IRON', 'LXU', 'NUZE', 'RSLS', 'TISI']
+        good_tkrs += ['AEI', 'GHI', 'IRON', 'LXU', 'RSLS', 'TISI']
        good_tkrs += ['BOL.ST', 'TUI1.DE']
        intervals = ['1d', '1wk', '1mo', '3mo']
        for tkr in good_tkrs:
@@ -488,7 +490,7 @@ class TestPriceRepair(unittest.TestCase):
                        print(df_dbg[f_diff | _np.roll(f_diff, 1) | _np.roll(f_diff, -1)])
                        raise

-        bad_tkrs = ['4063.T', 'ALPHA.PA', 'AV.L', 'CNE.L', 'MOB.ST', 'SPM.MI']
+        bad_tkrs = ['4063.T', 'AV.L', 'CNE.L', 'MOB.ST', 'SPM.MI']
        bad_tkrs.append('LA.V')  # special case - stock split error is 3 years ago! why not fixed?
        for tkr in bad_tkrs:
            dat = yf.Ticker(tkr, session=self.session)
@@ -580,7 +582,6 @@ class TestPriceRepair(unittest.TestCase):
        # Div 100x
        bad_tkrs += ['ABDP.L']
        bad_tkrs += ['ELCO.L']
-        bad_tkrs += ['KWS.L']
        bad_tkrs += ['PSH.L']

        # Div 100x and adjust too big
@@ -598,7 +599,6 @@ class TestPriceRepair(unittest.TestCase):
        # Phantom divs
        bad_tkrs += ['KAP.IL']  # 1x 1d phantom div, and false positives 0.01x in 1wk
        bad_tkrs += ['SAND']
-        bad_tkrs += ['SOLB.BR']  # 1x phantom div, but some false-positive 100x. and had to improve phantom detection
        bad_tkrs += ['TEM.L']
        bad_tkrs += ['TEP.PA']

--- a/tests/test_prices.py
+++ b/tests/test_prices.py
@@ -46,7 +46,7 @@ class TestPriceHistory(unittest.TestCase):

    def test_download_multi_small_interval(self):
        use_tkrs = ["AAPL", "0Q3.DE", "ATVI"]
-        df = yf.download(use_tkrs, period="1d", interval="5m")
+        df = yf.download(use_tkrs, period="1d", interval="5m", auto_adjust=True)
        self.assertEqual(df.index.tz, _dt.timezone.utc)

    def test_download_with_invalid_ticker(self):
@@ -56,16 +56,17 @@ class TestPriceHistory(unittest.TestCase):
        invalid_tkrs = ["AAPL", "ATVI"] #AAPL exists and ATVI does not exist
        valid_tkrs = ["AAPL", "INTC"] #AAPL and INTC both exist

-        data_invalid_sym = yf.download(invalid_tkrs, start='2023-11-16', end='2023-11-17')
-        data_valid_sym = yf.download(valid_tkrs, start='2023-11-16', end='2023-11-17')
-
-        self.assertEqual(data_invalid_sym['Close']['AAPL']['2023-11-16'],data_valid_sym['Close']['AAPL']['2023-11-16'])
+        start_d = _dt.date.today() - _dt.timedelta(days=30)
+        data_invalid_sym = yf.download(invalid_tkrs, start=start_d, auto_adjust=True)
+        data_valid_sym = yf.download(valid_tkrs, start=start_d, auto_adjust=True)
+        dt_compare = data_valid_sym.index[0]
+        self.assertEqual(data_invalid_sym['Close']['AAPL'][dt_compare],data_valid_sym['Close']['AAPL'][dt_compare])

    def test_duplicatingHourly(self):
        tkrs = ["IMP.JO", "BHG.JO", "SSW.JO", "BP.L", "INTC"]
        for tkr in tkrs:
            dat = yf.Ticker(tkr, session=self.session)
-            tz = dat._get_ticker_tz(proxy=None, timeout=None)
+            tz = dat._get_ticker_tz(timeout=None)

            dt_utc = _pd.Timestamp.utcnow()
            dt = dt_utc.astimezone(_tz.timezone(tz))
@@ -85,7 +86,7 @@ class TestPriceHistory(unittest.TestCase):
        test_run = False
        for tkr in tkrs:
            dat = yf.Ticker(tkr, session=self.session)
-            tz = dat._get_ticker_tz(proxy=None, timeout=None)
+            tz = dat._get_ticker_tz(timeout=None)

            dt_utc = _pd.Timestamp.utcnow()
            dt = dt_utc.astimezone(_tz.timezone(tz))
@@ -111,7 +112,7 @@ class TestPriceHistory(unittest.TestCase):
        test_run = False
        for tkr in tkrs:
            dat = yf.Ticker(tkr, session=self.session)
-            tz = dat._get_ticker_tz(proxy=None, timeout=None)
+            tz = dat._get_ticker_tz(timeout=None)

            dt = _tz.timezone(tz).localize(_dt.datetime.now())
            if dt.date().weekday() not in [1, 2, 3, 4]:
@@ -185,7 +186,7 @@ class TestPriceHistory(unittest.TestCase):

            df_intraday_divs = df_intraday["Dividends"][df_intraday["Dividends"] != 0]
            df_intraday_divs.index = df_intraday_divs.index.floor('D')
-            self.assertTrue(df_daily_divs.equals(df_intraday_divs))
+            self.assertTrue(df_daily_divs.index.equals(df_intraday_divs.index))

            test_run = True

@@ -212,7 +213,7 @@ class TestPriceHistory(unittest.TestCase):

            df_intraday_divs = df_intraday["Dividends"][df_intraday["Dividends"] != 0]
            df_intraday_divs.index = df_intraday_divs.index.floor('D')
-            self.assertTrue(df_daily_divs.equals(df_intraday_divs))
+            self.assertTrue(df_daily_divs.index.equals(df_intraday_divs.index))

            test_run = True

@@ -401,7 +402,7 @@ class TestPriceHistory(unittest.TestCase):

        # Setup
        tkr = "AMZN"
-        special_day = _dt.date(2023, 11, 24)
+        special_day = _dt.date(2024, 11, 29)
        time_early_close = _dt.time(13)
        dat = yf.Ticker(tkr, session=self.session)

@@ -416,6 +417,8 @@ class TestPriceHistory(unittest.TestCase):
        start_d = _dt.date(special_day.year, 1, 1)
        end_d = _dt.date(special_day.year+1, 1, 1)
        df = dat.history(start=start_d, end=end_d, interval="1h", prepost=False, keepna=True)
+        if df.empty:
+            self.skipTest("TEST NEEDS UPDATE: 'special_day' needs to be LATEST Thanksgiving date")
        last_dts = _pd.Series(df.index).groupby(df.index.date).last()
        dfd = dat.history(start=start_d, end=end_d, interval='1d', prepost=False, keepna=True)
        self.assertTrue(_np.equal(dfd.index.date, _pd.to_datetime(last_dts.index).date).all())
@@ -423,12 +426,12 @@ class TestPriceHistory(unittest.TestCase):
    def test_prune_post_intraday_asx(self):
        # Setup
        tkr = "BHP.AX"
-        # No early closes in 2023
+        # No early closes in 2024
        dat = yf.Ticker(tkr, session=self.session)

        # Test no other afternoons (or mornings) were pruned
-        start_d = _dt.date(2023, 1, 1)
-        end_d = _dt.date(2023+1, 1, 1)
+        start_d = _dt.date(2024, 1, 1)
+        end_d = _dt.date(2024+1, 1, 1)
        df = dat.history(start=start_d, end=end_d, interval="1h", prepost=False, keepna=True)
        last_dts = _pd.Series(df.index).groupby(df.index.date).last()
        dfd = dat.history(start=start_d, end=end_d, interval='1d', prepost=False, keepna=True)
--- a/tests/test_screener.py
+++ b/tests/test_screener.py
@@ -1,133 +1,38 @@
 import unittest
 from unittest.mock import patch, MagicMock
-from yfinance.const import PREDEFINED_SCREENER_BODY_MAP
-from yfinance.screener.screener import Screener
-from yfinance.screener.screener_query import EquityQuery
+from yfinance.screener.screener import screen
+from yfinance.screener.query import EquityQuery


 class TestScreener(unittest.TestCase):

    @classmethod
    def setUpClass(self):
-        self.screener = Screener()
        self.query = EquityQuery('gt',['eodprice',3])
-
-    def test_set_default_body(self):
-        self.screener.set_default_body(self.query)
-
-        self.assertEqual(self.screener.body['offset'], 0)
-        self.assertEqual(self.screener.body['size'], 100)
-        self.assertEqual(self.screener.body['sortField'], 'ticker')
-        self.assertEqual(self.screener.body['sortType'], 'desc')
-        self.assertEqual(self.screener.body['quoteType'], 'equity')
-        self.assertEqual(self.screener.body['query'], self.query.to_dict())
-        self.assertEqual(self.screener.body['userId'], '')
-        self.assertEqual(self.screener.body['userIdType'], 'guid')
-
-    def test_set_predefined_body(self):
-        k = 'most_actives'
-        self.screener.set_predefined_body(k)
-        self.assertEqual(self.screener.body, PREDEFINED_SCREENER_BODY_MAP[k])
-
-    def test_set_predefined_body_invalid_key(self):
-        with self.assertRaises(ValueError):
-            self.screener.set_predefined_body('invalid_key')
-
-    def test_set_body(self):
-        body = {
-            "offset": 0,
-            "size": 100,
-            "sortField": "ticker",
-            "sortType": "desc",
-            "quoteType": "equity",
-            "query": self.query.to_dict(),
-            "userId": "",
-            "userIdType": "guid"
-        }
-        self.screener.set_body(body)
-
-        self.assertEqual(self.screener.body, body)
-
-    def test_set_body_missing_keys(self):
-        body = {
-            "offset": 0,
-            "size": 100,
-            "sortField": "ticker",
-            "sortType": "desc",
-            "quoteType": "equity"
-        }
-        with self.assertRaises(ValueError):
-            self.screener.set_body(body)
-
-    def test_set_body_extra_keys(self):
-        body = {
-            "offset": 0,
-            "size": 100,
-            "sortField": "ticker",
-            "sortType": "desc",
-            "quoteType": "equity",
-            "query": self.query.to_dict(),
-            "userId": "",
-            "userIdType": "guid",
-            "extraKey": "extraValue"
-        }
-        with self.assertRaises(ValueError):
-            self.screener.set_body(body)
-
-    def test_patch_body(self):
-        initial_body = {
-            "offset": 0,
-            "size": 100,
-            "sortField": "ticker",
-            "sortType": "desc",
-            "quoteType": "equity",
-            "query": self.query.to_dict(),
-            "userId": "",
-            "userIdType": "guid"
-        }
-        self.screener.set_body(initial_body)
-        patch_values = {"size": 50}
-        self.screener.patch_body(patch_values)
-
-        self.assertEqual(self.screener.body['size'], 50)
-        self.assertEqual(self.screener.body['query'], self.query.to_dict())
-
-    def test_patch_body_extra_keys(self):
-        initial_body = {
-            "offset": 0,
-            "size": 100,
-            "sortField": "ticker",
-            "sortType": "desc",
-            "quoteType": "equity",
-            "query": self.query.to_dict(),
-            "userId": "",
-            "userIdType": "guid"
-        }
-        self.screener.set_body(initial_body)
-        patch_values = {"extraKey": "extraValue"}
-        with self.assertRaises(ValueError):
-            self.screener.patch_body(patch_values)
+        self.predefined = 'aggressive_small_caps'

    @patch('yfinance.screener.screener.YfData.post')
-    def test_fetch(self, mock_post):
-        mock_response = MagicMock()
-        mock_response.json.return_value = {'finance': {'result': [{}]}}
-        mock_post.return_value = mock_response
+    def test_set_large_size_in_body(self, mock_post):
+        with self.assertRaises(ValueError):
+            screen(self.query, size=251)

-        self.screener.set_default_body(self.query)
-        response = self.screener._fetch()
-
-        self.assertEqual(response, {'finance': {'result': [{}]}})
-
-    @patch('yfinance.screener.screener.YfData.post')
-    def test_fetch_and_parse(self, mock_post):
+    @patch('yfinance.data.YfData.post')
+    def test_fetch_query(self, mock_post):
        mock_response = MagicMock()
        mock_response.json.return_value = {'finance': {'result': [{'key': 'value'}]}}
        mock_post.return_value = mock_response

-        self.screener.set_default_body(self.query)
-        self.screener._fetch_and_parse()
-        self.assertEqual(self.screener.response, {'key': 'value'})
+        response = screen(self.query)
+        self.assertEqual(response, {'key': 'value'})
+
+    @patch('yfinance.data.YfData.get')
+    def test_fetch_predefined(self, mock_get):
+        mock_response = MagicMock()
+        mock_response.json.return_value = {'finance': {'result': [{'key': 'value'}]}}
+        mock_get.return_value = mock_response
+
+        response = screen(self.predefined)
+        self.assertEqual(response, {'key': 'value'})

 if __name__ == '__main__':
    unittest.main()
--- a/tests/test_search.py
+++ b/tests/test_search.py
@@ -0,0 +1,42 @@
+import unittest
+
+from tests.context import yfinance as yf
+
+
+class TestSearch(unittest.TestCase):
+    def test_invalid_query(self):
+        search = yf.Search(query="XYZXYZ")
+
+        self.assertEqual(len(search.quotes), 0)
+        self.assertEqual(len(search.news), 0)
+        self.assertEqual(len(search.lists), 0)
+        self.assertEqual(len(search.nav), 0)
+        self.assertEqual(len(search.research), 0)
+
+    def test_empty_query(self):
+        search = yf.Search(query="")
+
+        self.assertEqual(len(search.quotes), 0)
+        self.assertEqual(len(search.news), 0)
+
+    def test_fuzzy_query(self):
+        search = yf.Search(query="Appel", enable_fuzzy_query=True)
+
+        # Check if the fuzzy search retrieves relevant results despite the typo
+        self.assertGreater(len(search.quotes), 0)
+        self.assertIn("AAPL", search.quotes[0]['symbol'])
+
+    def test_quotes(self):
+        search = yf.Search(query="AAPL", max_results=5)
+
+        self.assertEqual(len(search.quotes), 5)
+        self.assertIn("AAPL", search.quotes[0]['symbol'])
+
+    def test_news(self):
+        search = yf.Search(query="AAPL", news_count=3)
+
+        self.assertEqual(len(search.news), 3)
+
+    def test_research_reports(self):
+        search = yf.Search(query="AAPL", include_research=True)
+        self.assertEqual(len(search.research), 3)
--- a/tests/test_ticker.py
+++ b/tests/test_ticker.py
@@ -8,6 +8,8 @@ Specific test class:
   python -m unittest tests.ticker.TestTicker

 """
+from datetime import datetime, timedelta
+
 import pandas as pd

 from tests.context import yfinance as yf
@@ -35,10 +37,12 @@ ticker_attributes = (
    ("recommendations", Union[pd.DataFrame, dict]),
    ("recommendations_summary", Union[pd.DataFrame, dict]),
    ("upgrades_downgrades", Union[pd.DataFrame, dict]),
+    ("ttm_cashflow", pd.DataFrame),
    ("quarterly_cashflow", pd.DataFrame),
    ("cashflow", pd.DataFrame),
    ("quarterly_balance_sheet", pd.DataFrame),
    ("balance_sheet", pd.DataFrame),
+    ("ttm_income_stmt", pd.DataFrame),
    ("quarterly_income_stmt", pd.DataFrame),
    ("income_stmt", pd.DataFrame),
    ("analyst_price_targets", dict),
@@ -76,8 +80,6 @@ class TestTicker(unittest.TestCase):
    def setUpClass(cls):
        cls.session = session_gbl

-        cls.proxy = None
-
    @classmethod
    def tearDownClass(cls):
        if cls.session is not None:
@@ -91,7 +93,7 @@ class TestTicker(unittest.TestCase):

            # Test:
            dat = yf.Ticker(tkr, session=self.session)
-            tz = dat._get_ticker_tz(proxy=None, timeout=5)
+            tz = dat._get_ticker_tz(timeout=5)

            self.assertIsNotNone(tz)

@@ -133,8 +135,55 @@ class TestTicker(unittest.TestCase):
        with self.assertRaises(YFInvalidPeriodError):
            dat.history(period="2wks", interval="1d", raise_errors=True)
        with self.assertRaises(YFInvalidPeriodError):
-            dat.history(period="2mo", interval="1d", raise_errors=True)
+            dat.history(period="2mos", interval="1d", raise_errors=True)

+    def test_valid_custom_periods(self):
+        valid_periods = [
+            # Yahoo provided periods
+            ("1d", "1m"), ("5d", "15m"), ("1mo", "1d"), ("3mo", "1wk"),
+            ("6mo", "1d"), ("1y", "1mo"), ("5y", "1wk"), ("max", "1mo"),
+
+            # Custom periods
+            ("2d", "30m"), ("10mo", "1d"), ("1y", "1d"), ("3y", "1d"),
+            ("2wk", "15m"), ("6mo", "5d"), ("10y", "1wk")
+        ]
+
+        tkr = "AAPL"
+        dat = yf.Ticker(tkr, session=self.session)
+
+        for period, interval in valid_periods:
+            with self.subTest(period=period, interval=interval):
+                df = dat.history(period=period, interval=interval, raise_errors=True)
+                self.assertIsInstance(df, pd.DataFrame)
+                self.assertFalse(df.empty, f"No data returned for period={period}, interval={interval}")
+                self.assertIn("Close", df.columns, f"'Close' column missing for period={period}, interval={interval}")
+
+                # Validate date range
+                now = datetime.now()
+                if period != "max":  # Difficult to assert for "max", therefore we skip
+                    if period.endswith("d"):
+                        days = int(period[:-1])
+                        expected_start = now - timedelta(days=days)
+                    elif period.endswith("mo"):
+                        months = int(period[:-2])
+                        expected_start = now - timedelta(days=30 * months)
+                    elif period.endswith("y"):
+                        years = int(period[:-1])
+                        expected_start = now - timedelta(days=365 * years)
+                    elif period.endswith("wk"):
+                        weeks = int(period[:-2])
+                        expected_start = now - timedelta(weeks=weeks)
+                    else:
+                        continue
+
+                    actual_start = df.index[0].to_pydatetime().replace(tzinfo=None)
+                    expected_start = expected_start.replace(hour=0, minute=0, second=0, microsecond=0)
+
+                    # leeway added because of weekends
+                    self.assertGreaterEqual(actual_start, expected_start - timedelta(days=10),
+                                            f"Start date {actual_start} out of range for period={period}")
+                    self.assertLessEqual(df.index[-1].to_pydatetime().replace(tzinfo=None), now,
+                                         f"End date {df.index[-1]} out of range for period={period}")

    def test_prices_missing(self):
        # this test will need to be updated every time someone wants to run a test
@@ -176,10 +225,10 @@ class TestTicker(unittest.TestCase):

    def test_goodTicker_withProxy(self):
        tkr = "IBM"
-        dat = yf.Ticker(tkr, session=self.session, proxy=self.proxy)
+        dat = yf.Ticker(tkr, session=self.session)

-        dat._fetch_ticker_tz(proxy=None, timeout=5)
-        dat._get_ticker_tz(proxy=None, timeout=5)
+        dat._fetch_ticker_tz(timeout=5)
+        dat._get_ticker_tz(timeout=5)
        dat.history(period="5d")

        for attribute_name, attribute_type in ticker_attributes:
@@ -259,14 +308,13 @@ class TestTickerHistory(unittest.TestCase):
            actual_urls_called[i] = u
        actual_urls_called = tuple(actual_urls_called)

-        expected_urls = (
-            f"https://query2.finance.yahoo.com/v8/finance/chart/{symbol}?events=div%2Csplits%2CcapitalGains&includePrePost=False&interval=1d&range={period}",
-        )
-        self.assertEqual(
-            expected_urls,
-            actual_urls_called,
-            "Different than expected url used to fetch history."
-        )
+        expected_urls = [
+            f"https://query2.finance.yahoo.com/v8/finance/chart/{symbol}?interval=1d&range=1d",  # ticker's tz
+            f"https://query2.finance.yahoo.com/v8/finance/chart/{symbol}?events=div%2Csplits%2CcapitalGains&includePrePost=False&interval=1d&range={period}"
+        ]
+        for url in actual_urls_called:
+            self.assertTrue(url in expected_urls, f"Unexpected URL called: {url}")
+
    def test_dividends(self):
        data = self.ticker.dividends
        self.assertIsInstance(data, pd.Series, "data has wrong type")
@@ -282,6 +330,12 @@ class TestTickerHistory(unittest.TestCase):
        self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
        self.assertFalse(data.empty, "data is empty")

+    def test_chained_history_calls(self):
+        _ = self.ticker.history(period="2d")
+        data = self.ticker.dividends
+        self.assertIsInstance(data, pd.Series, "data has wrong type")
+        self.assertFalse(data.empty, "data is empty")
+

 class TestTickerEarnings(unittest.TestCase):
    session = None
@@ -309,7 +363,7 @@ class TestTickerEarnings(unittest.TestCase):
    def test_earnings_dates_with_limit(self):
        # use ticker with lots of historic earnings
        ticker = yf.Ticker("IBM")
-        limit = 110
+        limit = 100
        data = ticker.get_earnings_dates(limit=limit)
        self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
        self.assertFalse(data.empty, "data is empty")
@@ -506,6 +560,34 @@ class TestTickerMiscFinancials(unittest.TestCase):
        data = self.ticker.get_income_stmt(as_dict=True)
        self.assertIsInstance(data, dict, "data has wrong type")

+    def test_ttm_income_statement(self):
+        expected_keys = ["Total Revenue", "Pretax Income", "Normalized EBITDA"]
+
+        # Test contents of table
+        data = self.ticker.get_income_stmt(pretty=True, freq='trailing')
+        self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
+        self.assertFalse(data.empty, "data is empty")
+        for k in expected_keys:
+            self.assertIn(k, data.index, "Did not find expected row in index")
+        # Trailing 12 months there must be exactly one column
+        self.assertEqual(len(data.columns), 1, "Only one column should be returned on TTM income statement")
+
+        # Test property defaults
+        data2 = self.ticker.ttm_income_stmt
+        self.assertTrue(data.equals(data2), "property not defaulting to 'pretty=True'")
+
+        # Test pretty=False
+        expected_keys = [k.replace(' ', '') for k in expected_keys]
+        data = self.ticker.get_income_stmt(pretty=False, freq='trailing')
+        self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
+        self.assertFalse(data.empty, "data is empty")
+        for k in expected_keys:
+            self.assertIn(k, data.index, "Did not find expected row in index")
+
+        # Test to_dict
+        data = self.ticker.get_income_stmt(as_dict=True, freq='trailing')
+        self.assertIsInstance(data, dict, "data has wrong type")
+
    def test_balance_sheet(self):
        expected_keys = ["Total Assets", "Net PPE"]
        expected_periods_days = 365
@@ -622,6 +704,34 @@ class TestTickerMiscFinancials(unittest.TestCase):
        data = self.ticker.get_cashflow(as_dict=True)
        self.assertIsInstance(data, dict, "data has wrong type")

+    def test_ttm_cash_flow(self):
+        expected_keys = ["Operating Cash Flow", "Net PPE Purchase And Sale"]
+
+        # Test contents of table
+        data = self.ticker.get_cashflow(pretty=True, freq='trailing')
+        self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
+        self.assertFalse(data.empty, "data is empty")
+        for k in expected_keys:
+            self.assertIn(k, data.index, "Did not find expected row in index")
+        # Trailing 12 months there must be exactly one column
+        self.assertEqual(len(data.columns), 1, "Only one column should be returned on TTM cash flow")
+
+        # Test property defaults
+        data2 = self.ticker.ttm_cashflow
+        self.assertTrue(data.equals(data2), "property not defaulting to 'pretty=True'")
+
+        # Test pretty=False
+        expected_keys = [k.replace(' ', '') for k in expected_keys]
+        data = self.ticker.get_cashflow(pretty=False, freq='trailing')
+        self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
+        self.assertFalse(data.empty, "data is empty")
+        for k in expected_keys:
+            self.assertIn(k, data.index, "Did not find expected row in index")
+
+        # Test to_dict
+        data = self.ticker.get_cashflow(as_dict=True, freq='trailing')
+        self.assertIsInstance(data, dict, "data has wrong type")
+
    def test_income_alt_names(self):
        i1 = self.ticker.income_stmt
        i2 = self.ticker.incomestmt
@@ -647,6 +757,18 @@ class TestTickerMiscFinancials(unittest.TestCase):
        i3 = self.ticker.get_financials(freq="quarterly")
        self.assertTrue(i1.equals(i3))

+        i1 = self.ticker.ttm_income_stmt
+        i2 = self.ticker.ttm_incomestmt
+        self.assertTrue(i1.equals(i2))
+        i3 = self.ticker.ttm_financials
+        self.assertTrue(i1.equals(i3))
+
+        i1 = self.ticker.get_income_stmt(freq="trailing")
+        i2 = self.ticker.get_incomestmt(freq="trailing")
+        self.assertTrue(i1.equals(i2))
+        i3 = self.ticker.get_financials(freq="trailing")
+        self.assertTrue(i1.equals(i3))
+
    def test_balance_sheet_alt_names(self):
        i1 = self.ticker.balance_sheet
        i2 = self.ticker.balancesheet
@@ -681,6 +803,14 @@ class TestTickerMiscFinancials(unittest.TestCase):
        i2 = self.ticker.get_cashflow(freq="quarterly")
        self.assertTrue(i1.equals(i2))

+        i1 = self.ticker.ttm_cash_flow
+        i2 = self.ticker.ttm_cashflow
+        self.assertTrue(i1.equals(i2))
+
+        i1 = self.ticker.get_cash_flow(freq="trailing")
+        i2 = self.ticker.get_cashflow(freq="trailing")
+        self.assertTrue(i1.equals(i2))
+
    def test_bad_freq_value_raises_exception(self):
        self.assertRaises(ValueError, lambda: self.ticker.get_cashflow(freq="badarg"))

@@ -760,7 +890,7 @@ class TestTickerAnalysts(unittest.TestCase):
        self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
        self.assertFalse(data.empty, "data is empty")
        self.assertTrue(len(data.columns) == 4, "data has wrong number of columns")
-        self.assertEqual(data.columns.values.tolist(), ['Firm', 'ToGrade', 'FromGrade', 'Action'], "data has wrong column names")
+        self.assertCountEqual(data.columns.values.tolist(), ['Firm', 'ToGrade', 'FromGrade', 'Action'], "data has wrong column names")
        self.assertIsInstance(data.index, pd.DatetimeIndex, "data has wrong index type")

        data_cached = self.ticker.upgrades_downgrades
@@ -770,9 +900,6 @@ class TestTickerAnalysts(unittest.TestCase):
        data = self.ticker.analyst_price_targets
        self.assertIsInstance(data, dict, "data has wrong type")

-        keys = {'current', 'low', 'high', 'mean', 'median'}
-        self.assertEqual(data.keys(), keys, "data has wrong keys")
-
        data_cached = self.ticker.analyst_price_targets
        self.assertIs(data, data_cached, "data not cached")

@@ -781,12 +908,6 @@ class TestTickerAnalysts(unittest.TestCase):
        self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
        self.assertFalse(data.empty, "data is empty")

-        columns = ['numberOfAnalysts', 'avg', 'low', 'high', 'yearAgoEps', 'growth']
-        self.assertEqual(data.columns.values.tolist(), columns, "data has wrong column names")
-
-        index = ['0q', '+1q', '0y', '+1y']
-        self.assertEqual(data.index.values.tolist(), index, "data has wrong row names")
-
        data_cached = self.ticker.earnings_estimate
        self.assertIs(data, data_cached, "data not cached")

@@ -795,12 +916,6 @@ class TestTickerAnalysts(unittest.TestCase):
        self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
        self.assertFalse(data.empty, "data is empty")

-        columns = ['numberOfAnalysts', 'avg', 'low', 'high', 'yearAgoRevenue', 'growth']
-        self.assertEqual(data.columns.values.tolist(), columns, "data has wrong column names")
-
-        index = ['0q', '+1q', '0y', '+1y']
-        self.assertEqual(data.index.values.tolist(), index, "data has wrong row names")
-
        data_cached = self.ticker.revenue_estimate
        self.assertIs(data, data_cached, "data not cached")

@@ -809,8 +924,6 @@ class TestTickerAnalysts(unittest.TestCase):
        self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
        self.assertFalse(data.empty, "data is empty")

-        columns = ['epsEstimate', 'epsActual', 'epsDifference', 'surprisePercent']
-        self.assertEqual(data.columns.values.tolist(), columns, "data has wrong column names")
        self.assertIsInstance(data.index, pd.DatetimeIndex, "data has wrong index type")

        data_cached = self.ticker.earnings_history
@@ -821,12 +934,6 @@ class TestTickerAnalysts(unittest.TestCase):
        self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
        self.assertFalse(data.empty, "data is empty")

-        columns = ['current', '7daysAgo', '30daysAgo', '60daysAgo', '90daysAgo']
-        self.assertEqual(data.columns.values.tolist(), columns, "data has wrong column names")
-
-        index = ['0q', '+1q', '0y', '+1y']
-        self.assertEqual(data.index.values.tolist(), index, "data has wrong row names")
-
        data_cached = self.ticker.eps_trend
        self.assertIs(data, data_cached, "data not cached")

@@ -835,12 +942,6 @@ class TestTickerAnalysts(unittest.TestCase):
        self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
        self.assertFalse(data.empty, "data is empty")

-        columns = ['stock', 'industry', 'sector', 'index']
-        self.assertEqual(data.columns.values.tolist(), columns, "data has wrong column names")
-
-        index = ['0q', '+1q', '0y', '+1y']
-        self.assertEqual(data.index.values.tolist(), index, "data has wrong row names")
-
        data_cached = self.ticker.growth_estimates
        self.assertIs(data, data_cached, "data not cached")

@@ -883,6 +984,7 @@ class TestTickerInfo(unittest.TestCase):
        self.symbols.append("QCSTIX")  # good for testing, doesn't trade
        self.symbols += ["BTC-USD", "IWO", "VFINX", "^GSPC"]
        self.symbols += ["SOKE.IS", "ADS.DE"]  # detected bugs
+        self.symbols += ["EXTO", "NEPT" ] # Issues 2343 and 2363
        self.tickers = [yf.Ticker(s, session=self.session) for s in self.symbols]

    def tearDown(self):
@@ -913,6 +1015,37 @@ class TestTickerInfo(unittest.TestCase):
        data2 = self.tickers[2].info
        self.assertIsInstance(data2['trailingPegRatio'], float)

+    def test_isin_info(self):
+        isin_list = {"ES0137650018": True,
+                     "does_not_exist": True,  # Nonexistent but doesn't raise an error
+                     "INF209K01EN2": True,
+                     "INX846K01K35": False,    # Nonexistent and raises an error
+                     "INF846K01K35": True
+                     }
+        for isin in isin_list:
+            if not isin_list[isin]:
+                with self.assertRaises(ValueError) as context:
+                    ticker = yf.Ticker(isin)
+                self.assertIn(str(context.exception), [ f"Invalid ISIN number: {isin}", "Empty tickername" ])
+            else:
+                ticker = yf.Ticker(isin)
+            ticker.info
+            
+    def test_empty_info(self):
+        # Test issue 2343 (Empty result _fetch)
+        data = self.tickers[10].info
+        self.assertCountEqual(['quoteType', 'symbol', 'underlyingSymbol', 'uuid', 'maxAge', 'trailingPegRatio'], data.keys())
+        self.assertIn("trailingPegRatio", data.keys(), "Did not find expected key 'trailingPegRatio' in info dict")
+
+        # Test issue 2363 (Empty QuoteResponse)
+        data = self.tickers[11].info
+        expected_keys = ['maxAge', 'priceHint', 'previousClose', 'open', 'dayLow', 'dayHigh', 'regularMarketPreviousClose',
+                         'regularMarketOpen', 'regularMarketDayLow', 'regularMarketDayHigh', 'volume', 'regularMarketVolume',
+                         'bid', 'ask', 'bidSize', 'askSize', 'fiftyTwoWeekLow', 'fiftyTwoWeekHigh', 'currency', 'tradeable',
+                         'exchange', 'quoteType', 'symbol', 'underlyingSymbol', 'shortName', 'timeZoneFullName', 'timeZoneShortName',
+                         'uuid', 'gmtOffSetMilliseconds', 'trailingPegRatio']
+        self.assertCountEqual(expected_keys, data.keys())
+
    # def test_fast_info_matches_info(self):
    #     fast_info_keys = set()
    #     for ticker in self.tickers:
--- a/tests/test_utils.py
+++ b/tests/test_utils.py
@@ -12,74 +12,10 @@ from datetime import datetime
 from unittest import TestSuite

 import pandas as pd
-# import numpy as np
-
-from tests.context import yfinance as yf

 import unittest
-# import requests_cache
-import tempfile
-import os

-
-class TestCache(unittest.TestCase):
-    @classmethod
-    def setUpClass(cls):
-        cls.tempCacheDir = tempfile.TemporaryDirectory()
-        yf.set_tz_cache_location(cls.tempCacheDir.name)
-
-    @classmethod
-    def tearDownClass(cls):
-        cls.tempCacheDir.cleanup()
-
-    def test_storeTzNoRaise(self):
-        # storing TZ to cache should never raise exception
-        tkr = 'AMZN'
-        tz1 = "America/New_York"
-        tz2 = "London/Europe"
-        cache = yf.cache.get_tz_cache()
-        cache.store(tkr, tz1)
-        cache.store(tkr, tz2)
-
-    def test_setTzCacheLocation(self):
-        self.assertEqual(yf.cache._TzDBManager.get_location(), self.tempCacheDir.name)
-
-        tkr = 'AMZN'
-        tz1 = "America/New_York"
-        cache = yf.cache.get_tz_cache()
-        cache.store(tkr, tz1)
-
-        self.assertTrue(os.path.exists(os.path.join(self.tempCacheDir.name, "tkr-tz.db")))
-
-
-class TestCacheNoPermission(unittest.TestCase):
-    @classmethod
-    def setUpClass(cls):
-        yf.set_tz_cache_location("/root/yf-cache")
-
-    def test_tzCacheRootStore(self):
-        # Test that if cache path in read-only filesystem, no exception.
-        tkr = 'AMZN'
-        tz1 = "America/New_York"
-
-        # During attempt to store, will discover cannot write
-        yf.cache.get_tz_cache().store(tkr, tz1)
-
-        # Handling the store failure replaces cache with a dummy
-        cache = yf.cache.get_tz_cache()
-        self.assertTrue(cache.dummy)
-        cache.store(tkr, tz1)
-
-    def test_tzCacheRootLookup(self):
-        # Test that if cache path in read-only filesystem, no exception.
-        tkr = 'AMZN'
-        # During attempt to lookup, will discover cannot write
-        yf.cache.get_tz_cache().lookup(tkr)
-
-        # Handling the lookup failure replaces cache with a dummy
-        cache = yf.cache.get_tz_cache()
-        self.assertTrue(cache.dummy)
-        cache.lookup(tkr)
+from yfinance.utils import is_valid_period_format, _dts_in_same_interval


 class TestPandas(unittest.TestCase):
@@ -105,11 +41,142 @@ class TestPandas(unittest.TestCase):
            i += 1


+class TestUtils(unittest.TestCase):
+    def test_is_valid_period_format_valid(self):
+        self.assertTrue(is_valid_period_format("1d"))
+        self.assertTrue(is_valid_period_format("5wk"))
+        self.assertTrue(is_valid_period_format("12mo"))
+        self.assertTrue(is_valid_period_format("2y"))
+
+    def test_is_valid_period_format_invalid(self):
+        self.assertFalse(is_valid_period_format("1m"))    # Incorrect suffix
+        self.assertFalse(is_valid_period_format("2wks"))  # Incorrect suffix
+        self.assertFalse(is_valid_period_format("10"))    # Missing suffix
+        self.assertFalse(is_valid_period_format("abc"))   # Invalid string
+        self.assertFalse(is_valid_period_format(""))      # Empty string
+
+    def test_is_valid_period_format_edge_cases(self):
+        self.assertFalse(is_valid_period_format(None))    # None input
+        self.assertFalse(is_valid_period_format("0d"))    # Zero is invalid
+        self.assertTrue(is_valid_period_format("999mo"))  # Large number valid
+
+
+class TestDateIntervalCheck(unittest.TestCase):
+    def test_same_day(self):
+        dt1 = pd.Timestamp("2024-10-15 10:00:00")
+        dt2 = pd.Timestamp("2024-10-15 14:30:00")
+        self.assertTrue(_dts_in_same_interval(dt1, dt2, "1d"))
+        
+    def test_different_days(self):
+        dt1 = pd.Timestamp("2024-10-15 10:00:00")
+        dt2 = pd.Timestamp("2024-10-16 09:00:00")
+        self.assertFalse(_dts_in_same_interval(dt1, dt2, "1d"))
+    
+    def test_same_week_mid_week(self):
+        # Wednesday and Friday in same week
+        dt1 = pd.Timestamp("2024-10-16")  # Wednesday
+        dt2 = pd.Timestamp("2024-10-18")  # Friday
+        self.assertTrue(_dts_in_same_interval(dt1, dt2, "1wk"))
+    
+    def test_different_weeks(self):
+        dt1 = pd.Timestamp("2024-10-14")  # Monday week 42
+        dt2 = pd.Timestamp("2024-10-21")  # Monday week 43
+        self.assertFalse(_dts_in_same_interval(dt1, dt2, "1wk"))
+    
+    def test_week_year_boundary(self):
+        # Week 52 of 2024 spans into 2025
+        dt1 = pd.Timestamp("2024-12-30")  # Monday in week 1 (ISO calendar)
+        dt2 = pd.Timestamp("2025-01-03")  # Friday in week 1 (ISO calendar)
+        self.assertTrue(_dts_in_same_interval(dt1, dt2, "1wk"))
+    
+    def test_same_month(self):
+        dt1 = pd.Timestamp("2024-10-01")
+        dt2 = pd.Timestamp("2024-10-31")
+        self.assertTrue(_dts_in_same_interval(dt1, dt2, "1mo"))
+    
+    def test_different_months(self):
+        dt1 = pd.Timestamp("2024-10-31")
+        dt2 = pd.Timestamp("2024-11-01")
+        self.assertFalse(_dts_in_same_interval(dt1, dt2, "1mo"))
+    
+    def test_month_year_boundary(self):
+        dt1 = pd.Timestamp("2024-12-15")
+        dt2 = pd.Timestamp("2025-01-15")
+        self.assertFalse(_dts_in_same_interval(dt1, dt2, "1mo"))
+
+    def test_standard_quarters(self):
+        q1_start = datetime(2023, 1, 1)
+        self.assertTrue(_dts_in_same_interval(q1_start, datetime(2023, 1, 15), '3mo'))
+        self.assertTrue(_dts_in_same_interval(q1_start, datetime(2023, 3, 31), '3mo'))
+        self.assertFalse(_dts_in_same_interval(q1_start, datetime(2023, 4, 1), '3mo'))
+        self.assertFalse(_dts_in_same_interval(q1_start, datetime(2022, 1, 15), '3mo'))  # Previous year
+        self.assertFalse(_dts_in_same_interval(q1_start, datetime(2024, 1, 15), '3mo'))  # Next year
+        
+        q2_start = datetime(2023, 4, 1)
+        self.assertTrue(_dts_in_same_interval(q2_start, datetime(2023, 5, 15), '3mo'))
+        self.assertTrue(_dts_in_same_interval(q2_start, datetime(2023, 6, 30), '3mo'))
+        self.assertFalse(_dts_in_same_interval(q2_start, datetime(2023, 7, 1), '3mo'))
+    
+    def test_nonstandard_quarters(self):
+        q1_start = datetime(2023, 2, 1)
+        # Same quarter
+        self.assertTrue(_dts_in_same_interval(q1_start, datetime(2023, 3, 1), '3mo'))
+        self.assertTrue(_dts_in_same_interval(q1_start, datetime(2023, 4, 25), '3mo'))
+        # Different quarters
+        self.assertFalse(_dts_in_same_interval(q1_start, datetime(2023, 1, 25), '3mo'))  # Before quarter start
+        self.assertFalse(_dts_in_same_interval(q1_start, datetime(2023, 6, 1), '3mo'))  # Start of next quarter
+        self.assertFalse(_dts_in_same_interval(q1_start, datetime(2023, 9, 1), '3mo'))  # Start of Q3
+        
+        q2_start = datetime(2023, 5, 1)
+        self.assertTrue(_dts_in_same_interval(q2_start, datetime(2023, 6, 1), '3mo'))
+        self.assertTrue(_dts_in_same_interval(q2_start, datetime(2023, 7, 25), '3mo'))
+        self.assertFalse(_dts_in_same_interval(q2_start, datetime(2023, 8, 1), '3mo'))
+    
+    def test_cross_year_quarters(self):
+        q4_start = datetime(2023, 11, 1)
+        
+        # Same quarter, different year
+        self.assertTrue(_dts_in_same_interval(q4_start, datetime(2023, 11, 15), '3mo'))
+        self.assertTrue(_dts_in_same_interval(q4_start, datetime(2024, 1, 15), '3mo'))
+        self.assertTrue(_dts_in_same_interval(q4_start, datetime(2024, 1, 25), '3mo'))
+        
+        # Different quarters
+        self.assertFalse(_dts_in_same_interval(q4_start, datetime(2024, 2, 1), '3mo'))  # Start of next quarter
+        self.assertFalse(_dts_in_same_interval(q4_start, datetime(2023, 10, 14), '3mo'))  # Before quarter start
+    
+    def test_hourly_interval(self):
+        dt1 = pd.Timestamp("2024-10-15 14:00:00")
+        dt2 = pd.Timestamp("2024-10-15 14:59:59")
+        self.assertTrue(_dts_in_same_interval(dt1, dt2, "1h"))
+        
+        dt3 = pd.Timestamp("2024-10-15 15:00:00")
+        self.assertFalse(_dts_in_same_interval(dt1, dt3, "1h"))
+    
+    def test_custom_intervals(self):
+        # Test 4 hour interval
+        dt1 = pd.Timestamp("2024-10-15 10:00:00")
+        dt2 = pd.Timestamp("2024-10-15 13:59:59")
+        self.assertTrue(_dts_in_same_interval(dt1, dt2, "4h"))
+        
+        dt3 = pd.Timestamp("2024-10-15 14:00:00")
+        self.assertFalse(_dts_in_same_interval(dt1, dt3, "4h"))
+        
+    def test_minute_intervals(self):
+        dt1 = pd.Timestamp("2024-10-15 10:30:00")
+        dt2 = pd.Timestamp("2024-10-15 10:30:45")
+        self.assertTrue(_dts_in_same_interval(dt1, dt2, "1min"))
+        
+        dt3 = pd.Timestamp("2024-10-15 10:31:00")
+        self.assertFalse(_dts_in_same_interval(dt1, dt3, "1min"))
+
+if __name__ == "__main__":
+    unittest.main()
+
+
 def suite():
    ts: TestSuite = unittest.TestSuite()
-    ts.addTest(TestCache('Test cache'))
-    ts.addTest(TestCacheNoPermission('Test cache no permission'))
    ts.addTest(TestPandas("Test pandas"))
+    ts.addTest(TestUtils("Test utils"))
    return ts


--- a/yfinance/init.py
+++ b/yfinance/init.py
@@ -20,15 +20,21 @@
 #

 from . import version
+from .search import Search
+from .lookup import Lookup
 from .ticker import Ticker
 from .tickers import Tickers
 from .multi import download
+from .live import WebSocket, AsyncWebSocket
 from .utils import enable_debug_mode
 from .cache import set_tz_cache_location
 from .domain.sector import Sector
 from .domain.industry import Industry
-from .screener.screener import Screener
-from .screener.screener_query import EquityQuery
+from .domain.market import Market
+from .data import YfData
+
+from .screener.query import EquityQuery, FundQuery
+from .screener.screener import screen, PREDEFINED_SCREENER_QUERIES

 __version__ = version.version
 __author__ = "Ran Aroussi"
@@ -36,5 +42,13 @@ __author__ = "Ran Aroussi"
 import warnings
 warnings.filterwarnings('default', category=DeprecationWarning, module='^yfinance')

-__all__ = ['download', 'Ticker', 'Tickers', 'enable_debug_mode', 'set_tz_cache_location', 'Sector', 'Industry',
-           'EquityQuery','Screener']
+__all__ = ['download', 'Market', 'Search', 'Lookup', 'Ticker', 'Tickers', 'enable_debug_mode', 'set_tz_cache_location', 'Sector', 'Industry', 'WebSocket', 'AsyncWebSocket']
+# screener stuff:
+__all__ += ['EquityQuery', 'FundQuery', 'screen', 'PREDEFINED_SCREENER_QUERIES']
+
+# Config stuff:
+_NOTSET=object()
+def set_config(proxy=_NOTSET):
+    if proxy is not _NOTSET:
+        YfData(proxy=proxy)
+__all__ += ["set_config"]
--- a/yfinance/base.py
+++ b/yfinance/base.py
@@ -21,18 +21,20 @@

 from __future__ import print_function

-from io import StringIO
 import json as _json
 import warnings
 from typing import Optional, Union
 from urllib.parse import quote as urlencode

+import numpy as np
 import pandas as pd
-import requests
+from curl_cffi import requests
+

 from . import utils, cache
 from .data import YfData
-from .exceptions import YFEarningsDateMissing
+from .exceptions import YFEarningsDateMissing, YFRateLimitError
+from .live import WebSocket
 from .scrapers.analysis import Analysis
 from .scrapers.fundamentals import Fundamentals
 from .scrapers.holders import Holders
@@ -40,14 +42,15 @@ from .scrapers.quote import Quote, FastInfo
 from .scrapers.history import PriceHistory
 from .scrapers.funds import FundsData

-from .const import _BASE_URL_, _ROOT_URL_
+from .const import _BASE_URL_, _ROOT_URL_, _QUERY1_URL_, _SENTINEL_


+_tz_info_fetch_ctr = 0
+
 class TickerBase:
-    def __init__(self, ticker, session=None, proxy=None):
+    def __init__(self, ticker, session=None, proxy=_SENTINEL_):
        self.ticker = ticker.upper()
-        self.proxy = proxy
-        self.session = session
+        self.session = session or requests.Session(impersonate="chrome")
        self._tz = None

        self._isin = None
@@ -59,11 +62,21 @@ class TickerBase:
        self._earnings = None
        self._financials = None

+        # raise an error if user tries to give empty ticker
+        if self.ticker == "":
+            raise ValueError("Empty ticker name")
+
        # accept isin as ticker
        if utils.is_isin(self.ticker):
+            isin = self.ticker
            self.ticker = utils.get_ticker_by_isin(self.ticker, None, session)
+            if self.ticker == "":
+                raise ValueError(f"Invalid ISIN number: {isin}")

        self._data: YfData = YfData(session=session)
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)

        # self._price_history = PriceHistory(self._data, self.ticker)
        self._price_history = None  # lazy-load
@@ -75,6 +88,9 @@ class TickerBase:

        self._fast_info = None

+        self._message_handler = None
+        self.ws = None
+
    @utils.log_indent_decorator
    def history(self, *args, **kwargs) -> pd.DataFrame:
        return self._lazy_load_price_history().history(*args, **kwargs)
@@ -83,11 +99,10 @@ class TickerBase:

    def _lazy_load_price_history(self):
        if self._price_history is None:
-            self._price_history = PriceHistory(self._data, self.ticker, self._get_ticker_tz(self.proxy, timeout=10))
+            self._price_history = PriceHistory(self._data, self.ticker, self._get_ticker_tz(timeout=10))
        return self._price_history

-    def _get_ticker_tz(self, proxy, timeout):
-        proxy = proxy or self.proxy
+    def _get_ticker_tz(self, timeout):
        if self._tz is not None:
            return self._tz
        c = cache.get_tz_cache()
@@ -99,10 +114,20 @@ class TickerBase:
            tz = None

        if tz is None:
-            tz = self._fetch_ticker_tz(proxy, timeout)
-
+            tz = self._fetch_ticker_tz(timeout)
+            if tz is None:
+                # _fetch_ticker_tz works in 99.999% of cases.
+                # For rare fail get from info.
+                global _tz_info_fetch_ctr
+                if _tz_info_fetch_ctr < 2:
+                    # ... but limit. If _fetch_ticker_tz() always
+                    # failing then bigger problem.
+                    _tz_info_fetch_ctr += 1
+                    for k in ['exchangeTimezoneName', 'timeZoneFullName']:
+                        if k in self.info:
+                            tz = self.info[k]
+                            break
            if utils.is_valid_timezone(tz):
-                # info fetch is relatively slow so cache timezone
                c.store(self.ticker, tz)
            else:
                tz = None
@@ -111,9 +136,8 @@ class TickerBase:
        return tz

    @utils.log_indent_decorator
-    def _fetch_ticker_tz(self, proxy, timeout):
+    def _fetch_ticker_tz(self, timeout):
        # Query Yahoo for fast price data just to get returned timezone
-        proxy = proxy or self.proxy
        logger = utils.get_yf_logger()

        params = {"range": "1d", "interval": "1d"}
@@ -122,8 +146,11 @@ class TickerBase:
        url = f"{_BASE_URL_}/v8/finance/chart/{self.ticker}"

        try:
-            data = self._data.cache_get(url=url, params=params, proxy=proxy, timeout=timeout)
+            data = self._data.cache_get(url=url, params=params, timeout=timeout)
            data = data.json()
+        except YFRateLimitError:
+            # Must propagate this
+            raise
        except Exception as e:
            logger.error(f"Failed to get ticker '{self.ticker}' reason: {e}")
            return None
@@ -143,95 +170,136 @@ class TickerBase:
                    logger.debug("-------------")
        return None

-    def get_recommendations(self, proxy=None, as_dict=False):
+    def get_recommendations(self, proxy=_SENTINEL_, as_dict=False):
        """
        Returns a DataFrame with the recommendations
        Columns: period  strongBuy  buy  hold  sell  strongSell
        """
-        self._quote.proxy = proxy or self.proxy
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        data = self._quote.recommendations
        if as_dict:
            return data.to_dict()
        return data

-    def get_recommendations_summary(self, proxy=None, as_dict=False):
-        return self.get_recommendations(proxy=proxy, as_dict=as_dict)
+    def get_recommendations_summary(self, proxy=_SENTINEL_, as_dict=False):
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)

-    def get_upgrades_downgrades(self, proxy=None, as_dict=False):
+        return self.get_recommendations(as_dict=as_dict)
+
+    def get_upgrades_downgrades(self, proxy=_SENTINEL_, as_dict=False):
        """
        Returns a DataFrame with the recommendations changes (upgrades/downgrades)
        Index: date of grade
        Columns: firm toGrade fromGrade action
        """
-        self._quote.proxy = proxy or self.proxy
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        data = self._quote.upgrades_downgrades
        if as_dict:
            return data.to_dict()
        return data

-    def get_calendar(self, proxy=None) -> dict:
-        self._quote.proxy = proxy or self.proxy
+    def get_calendar(self, proxy=_SENTINEL_) -> dict:
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        return self._quote.calendar

-    def get_sec_filings(self, proxy=None) -> dict:
-        self._quote.proxy = proxy or self.proxy
+    def get_sec_filings(self, proxy=_SENTINEL_) -> dict:
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        return self._quote.sec_filings

-    def get_major_holders(self, proxy=None, as_dict=False):
-        self._holders.proxy = proxy or self.proxy
+    def get_major_holders(self, proxy=_SENTINEL_, as_dict=False):
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        data = self._holders.major
        if as_dict:
            return data.to_dict()
        return data

-    def get_institutional_holders(self, proxy=None, as_dict=False):
-        self._holders.proxy = proxy or self.proxy
+    def get_institutional_holders(self, proxy=_SENTINEL_, as_dict=False):
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        data = self._holders.institutional
        if data is not None:
            if as_dict:
                return data.to_dict()
            return data

-    def get_mutualfund_holders(self, proxy=None, as_dict=False):
-        self._holders.proxy = proxy or self.proxy
+    def get_mutualfund_holders(self, proxy=_SENTINEL_, as_dict=False):
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        data = self._holders.mutualfund
        if data is not None:
            if as_dict:
                return data.to_dict()
            return data

-    def get_insider_purchases(self, proxy=None, as_dict=False):
-        self._holders.proxy = proxy or self.proxy
+    def get_insider_purchases(self, proxy=_SENTINEL_, as_dict=False):
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        data = self._holders.insider_purchases
        if data is not None:
            if as_dict:
                return data.to_dict()
            return data

-    def get_insider_transactions(self, proxy=None, as_dict=False):
-        self._holders.proxy = proxy or self.proxy
+    def get_insider_transactions(self, proxy=_SENTINEL_, as_dict=False):
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        data = self._holders.insider_transactions
        if data is not None:
            if as_dict:
                return data.to_dict()
            return data

-    def get_insider_roster_holders(self, proxy=None, as_dict=False):
-        self._holders.proxy = proxy or self.proxy
+    def get_insider_roster_holders(self, proxy=_SENTINEL_, as_dict=False):
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        data = self._holders.insider_roster
        if data is not None:
            if as_dict:
                return data.to_dict()
            return data

-    def get_info(self, proxy=None) -> dict:
-        self._quote.proxy = proxy or self.proxy
+    def get_info(self, proxy=_SENTINEL_) -> dict:
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        data = self._quote.info
        return data

-    def get_fast_info(self, proxy=None):
+    def get_fast_info(self, proxy=_SENTINEL_):
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        if self._fast_info is None:
-            self._fast_info = FastInfo(self, proxy=proxy)
+            self._fast_info = FastInfo(self)
        return self._fast_info

    @property
@@ -239,89 +307,113 @@ class TickerBase:
        warnings.warn("'Ticker.basic_info' is deprecated and will be removed in future, Switch to 'Ticker.fast_info'", DeprecationWarning)
        return self.fast_info

-    def get_sustainability(self, proxy=None, as_dict=False):
-        self._quote.proxy = proxy or self.proxy
+    def get_sustainability(self, proxy=_SENTINEL_, as_dict=False):
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        data = self._quote.sustainability
        if as_dict:
            return data.to_dict()
        return data

-    def get_analyst_price_targets(self, proxy=None) -> dict:
+    def get_analyst_price_targets(self, proxy=_SENTINEL_) -> dict:
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        """
        Keys:   current  low  high  mean  median
        """
-        self._analysis.proxy = proxy or self.proxy
        data = self._analysis.analyst_price_targets
        return data

-    def get_earnings_estimate(self, proxy=None, as_dict=False):
+    def get_earnings_estimate(self, proxy=_SENTINEL_, as_dict=False):
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        """
        Index:      0q  +1q  0y  +1y
        Columns:    numberOfAnalysts  avg  low  high  yearAgoEps  growth
        """
-        self._analysis.proxy = proxy or self.proxy
        data = self._analysis.earnings_estimate
        return data.to_dict() if as_dict else data

-    def get_revenue_estimate(self, proxy=None, as_dict=False):
+    def get_revenue_estimate(self, proxy=_SENTINEL_, as_dict=False):
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        """
        Index:      0q  +1q  0y  +1y
        Columns:    numberOfAnalysts  avg  low  high  yearAgoRevenue  growth
        """
-        self._analysis.proxy = proxy or self.proxy
        data = self._analysis.revenue_estimate
        return data.to_dict() if as_dict else data

-    def get_earnings_history(self, proxy=None, as_dict=False):
+    def get_earnings_history(self, proxy=_SENTINEL_, as_dict=False):
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        """
        Index:      pd.DatetimeIndex
        Columns:    epsEstimate  epsActual  epsDifference  surprisePercent
        """
-        self._analysis.proxy = proxy or self.proxy
        data = self._analysis.earnings_history
        return data.to_dict() if as_dict else data

-    def get_eps_trend(self, proxy=None, as_dict=False):
+    def get_eps_trend(self, proxy=_SENTINEL_, as_dict=False):
        """
        Index:      0q  +1q  0y  +1y
        Columns:    current  7daysAgo  30daysAgo  60daysAgo  90daysAgo
        """
-        self._analysis.proxy = proxy or self.proxy
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        data = self._analysis.eps_trend
        return data.to_dict() if as_dict else data

-    def get_eps_revisions(self, proxy=None, as_dict=False):
+    def get_eps_revisions(self, proxy=_SENTINEL_, as_dict=False):
        """
        Index:      0q  +1q  0y  +1y
        Columns:    upLast7days  upLast30days  downLast7days  downLast30days
        """
-        self._analysis.proxy = proxy or self.proxy
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        data = self._analysis.eps_revisions
        return data.to_dict() if as_dict else data

-    def get_growth_estimates(self, proxy=None, as_dict=False):
+    def get_growth_estimates(self, proxy=_SENTINEL_, as_dict=False):
        """
        Index:      0q  +1q  0y  +1y +5y -5y
        Columns:    stock  industry  sector  index
        """
-        self._analysis.proxy = proxy or self.proxy
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        data = self._analysis.growth_estimates
        return data.to_dict() if as_dict else data

-    def get_earnings(self, proxy=None, as_dict=False, freq="yearly"):
+    def get_earnings(self, proxy=_SENTINEL_, as_dict=False, freq="yearly"):
        """
        :Parameters:
            as_dict: bool
                Return table as Python dict
                Default is False
            freq: str
-                "yearly" or "quarterly"
+                "yearly" or "quarterly" or "trailing"
                Default is "yearly"
-            proxy: str
-                Optional. Proxy server URL scheme
-                Default is None
        """
-        self._fundamentals.proxy = proxy or self.proxy
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        if self._fundamentals.earnings is None:
            return None
        data = self._fundamentals.earnings[freq]
@@ -332,7 +424,7 @@ class TickerBase:
            return dict_data
        return data

-    def get_income_stmt(self, proxy=None, as_dict=False, pretty=False, freq="yearly"):
+    def get_income_stmt(self, proxy=_SENTINEL_, as_dict=False, pretty=False, freq="yearly"):
        """
        :Parameters:
            as_dict: bool
@@ -342,15 +434,14 @@ class TickerBase:
                Format row names nicely for readability
                Default is False
            freq: str
-                "yearly" or "quarterly"
+                "yearly" or "quarterly" or "trailing"
                Default is "yearly"
-            proxy: str
-                Optional. Proxy server URL scheme
-                Default is None
        """
-        self._fundamentals.proxy = proxy or self.proxy
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)

-        data = self._fundamentals.financials.get_income_time_series(freq=freq, proxy=proxy)
+        data = self._fundamentals.financials.get_income_time_series(freq=freq)

        if pretty:
            data = data.copy()
@@ -359,13 +450,21 @@ class TickerBase:
            return data.to_dict()
        return data

-    def get_incomestmt(self, proxy=None, as_dict=False, pretty=False, freq="yearly"):
+    def get_incomestmt(self, proxy=_SENTINEL_, as_dict=False, pretty=False, freq="yearly"):
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        return self.get_income_stmt(proxy, as_dict, pretty, freq)

-    def get_financials(self, proxy=None, as_dict=False, pretty=False, freq="yearly"):
+    def get_financials(self, proxy=_SENTINEL_, as_dict=False, pretty=False, freq="yearly"):
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        return self.get_income_stmt(proxy, as_dict, pretty, freq)

-    def get_balance_sheet(self, proxy=None, as_dict=False, pretty=False, freq="yearly"):
+    def get_balance_sheet(self, proxy=_SENTINEL_, as_dict=False, pretty=False, freq="yearly"):
        """
        :Parameters:
            as_dict: bool
@@ -377,13 +476,13 @@ class TickerBase:
            freq: str
                "yearly" or "quarterly"
                Default is "yearly"
-            proxy: str
-                Optional. Proxy server URL scheme
-                Default is None
        """
-        self._fundamentals.proxy = proxy or self.proxy
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)

-        data = self._fundamentals.financials.get_balance_sheet_time_series(freq=freq, proxy=proxy)
+
+        data = self._fundamentals.financials.get_balance_sheet_time_series(freq=freq)

        if pretty:
            data = data.copy()
@@ -392,10 +491,14 @@ class TickerBase:
            return data.to_dict()
        return data

-    def get_balancesheet(self, proxy=None, as_dict=False, pretty=False, freq="yearly"):
+    def get_balancesheet(self, proxy=_SENTINEL_, as_dict=False, pretty=False, freq="yearly"):
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        return self.get_balance_sheet(proxy, as_dict, pretty, freq)

-    def get_cash_flow(self, proxy=None, as_dict=False, pretty=False, freq="yearly") -> Union[pd.DataFrame, dict]:
+    def get_cash_flow(self, proxy=_SENTINEL_, as_dict=False, pretty=False, freq="yearly") -> Union[pd.DataFrame, dict]:
        """
        :Parameters:
            as_dict: bool
@@ -407,13 +510,13 @@ class TickerBase:
            freq: str
                "yearly" or "quarterly"
                Default is "yearly"
-            proxy: str
-                Optional. Proxy server URL scheme
-                Default is None
        """
-        self._fundamentals.proxy = proxy or self.proxy
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)

-        data = self._fundamentals.financials.get_cash_flow_time_series(freq=freq, proxy=proxy)
+
+        data = self._fundamentals.financials.get_cash_flow_time_series(freq=freq)

        if pretty:
            data = data.copy()
@@ -422,34 +525,56 @@ class TickerBase:
            return data.to_dict()
        return data

-    def get_cashflow(self, proxy=None, as_dict=False, pretty=False, freq="yearly"):
+    def get_cashflow(self, proxy=_SENTINEL_, as_dict=False, pretty=False, freq="yearly"):
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
        return self.get_cash_flow(proxy, as_dict, pretty, freq)

-    def get_dividends(self, proxy=None) -> pd.Series:
-        return self._lazy_load_price_history().get_dividends(proxy)
+    def get_dividends(self, proxy=_SENTINEL_, period="max") -> pd.Series:
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+        return self._lazy_load_price_history().get_dividends(period=period)

-    def get_capital_gains(self, proxy=None) -> pd.Series:
-        return self._lazy_load_price_history().get_capital_gains(proxy)
+    def get_capital_gains(self, proxy=_SENTINEL_, period="max") -> pd.Series:
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+        return self._lazy_load_price_history().get_capital_gains(period=period)

-    def get_splits(self, proxy=None) -> pd.Series:
-        return self._lazy_load_price_history().get_splits(proxy)
+    def get_splits(self, proxy=_SENTINEL_, period="max") -> pd.Series:
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+        return self._lazy_load_price_history().get_splits(period=period)

-    def get_actions(self, proxy=None) -> pd.Series:
-        return self._lazy_load_price_history().get_actions(proxy)
+    def get_actions(self, proxy=_SENTINEL_, period="max") -> pd.Series:
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+        return self._lazy_load_price_history().get_actions(period=period)
+
+    def get_shares(self, proxy=_SENTINEL_, as_dict=False) -> Union[pd.DataFrame, dict]:
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)

-    def get_shares(self, proxy=None, as_dict=False) -> Union[pd.DataFrame, dict]:
-        self._fundamentals.proxy = proxy or self.proxy
        data = self._fundamentals.shares
        if as_dict:
            return data.to_dict()
        return data

    @utils.log_indent_decorator
-    def get_shares_full(self, start=None, end=None, proxy=None):
+    def get_shares_full(self, start=None, end=None, proxy=_SENTINEL_):
        logger = utils.get_yf_logger()

+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        # Process dates
-        tz = self._get_ticker_tz(proxy=proxy, timeout=10)
+        tz = self._get_ticker_tz(timeout=10)
        dt_now = pd.Timestamp.utcnow().tz_convert(tz)
        if start is not None:
            start_ts = utils._parse_user_dt(start, tz)
@@ -471,7 +596,7 @@ class TickerBase:
        ts_url_base = f"https://query2.finance.yahoo.com/ws/fundamentals-timeseries/v1/finance/timeseries/{self.ticker}?symbol={self.ticker}"
        shares_url = f"{ts_url_base}&period1={int(start.timestamp())}&period2={int(end.timestamp())}"
        try:
-            json_data = self._data.cache_get(url=shares_url, proxy=proxy)
+            json_data = self._data.cache_get(url=shares_url)
            json_data = json_data.json()
        except (_json.JSONDecodeError, requests.exceptions.RequestException):
            logger.error(f"{self.ticker}: Yahoo web request for share count failed")
@@ -497,7 +622,11 @@ class TickerBase:
        df = df.sort_index()
        return df

-    def get_isin(self, proxy=None) -> Optional[str]:
+    def get_isin(self, proxy=_SENTINEL_) -> Optional[str]:
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        # *** experimental ***
        if self._isin is not None:
            return self._isin
@@ -510,7 +639,6 @@ class TickerBase:

        q = ticker

-        self._quote.proxy = proxy or self.proxy
        if self._quote.info is None:
            # Don't print error message cause self._quote.info will print one
            return None
@@ -518,7 +646,7 @@ class TickerBase:
            q = self._quote.info['shortName']

        url = f'https://markets.businessinsider.com/ajax/SearchController_Suggest?max_results=25&query={urlencode(q)}'
-        data = self._data.cache_get(url=url, proxy=proxy).text
+        data = self._data.cache_get(url=url).text

        search_str = f'"{ticker}|'
        if search_str not in data:
@@ -534,30 +662,53 @@ class TickerBase:
        self._isin = data.split(search_str)[1].split('"')[0].split('|')[0]
        return self._isin

-    def get_news(self, proxy=None) -> list:
+    def get_news(self, count=10, tab="news", proxy=_SENTINEL_) -> list:
+        """Allowed options for tab: "news", "all", "press releases"""
        if self._news:
            return self._news

-        # Getting data from json
-        url = f"{_BASE_URL_}/v1/finance/search?q={self.ticker}"
-        data = self._data.cache_get(url=url, proxy=proxy)
+        logger = utils.get_yf_logger()
+
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
+        tab_queryrefs = {
+            "all": "newsAll",
+            "news": "latestNews",
+            "press releases": "pressRelease",
+        }
+
+        query_ref = tab_queryrefs.get(tab.lower())
+        if not query_ref:
+            raise ValueError(f"Invalid tab name '{tab}'. Choose from: {', '.join(tab_queryrefs.keys())}")
+
+        url = f"{_ROOT_URL_}/xhr/ncp?queryRef={query_ref}&serviceKey=ncp_fin"
+        payload = {
+            "serviceConfig": {
+                "snippetCount": count,
+                "s": [self.ticker]
+            }
+        }
+
+        data = self._data.post(url, body=payload)
        if data is None or "Will be right back" in data.text:
            raise RuntimeError("*** YAHOO! FINANCE IS CURRENTLY DOWN! ***\n"
                               "Our engineers are working quickly to resolve "
                               "the issue. Thank you for your patience.")
        try:
            data = data.json()
-        except (_json.JSONDecodeError): 
-            logger = utils.get_yf_logger()
+        except _json.JSONDecodeError:
            logger.error(f"{self.ticker}: Failed to retrieve the news and received faulty response instead.")
            data = {}

-        # parse news
-        self._news = data.get("news", [])
+        news = data.get("data", {}).get("tickerStream", {}).get("stream", [])
+
+        self._news = [article for article in news if not article.get('ad', [])]
        return self._news

    @utils.log_indent_decorator
-    def get_earnings_dates(self, limit=12, proxy=None) -> Optional[pd.DataFrame]:
+    def get_earnings_dates(self, limit=12, proxy=_SENTINEL_) -> Optional[pd.DataFrame]:
        """
        Get earning dates (future and historic)
        
@@ -565,96 +716,91 @@ class TickerBase:
            limit (int): max amount of upcoming and recent earnings dates to return.
                Default value 12 should return next 4 quarters and last 8 quarters.
                Increase if more history is needed.
-            proxy: requests proxy to use.
-        
        Returns:
            pd.DataFrame
        """
-        if self._earnings_dates and limit in self._earnings_dates:
-            return self._earnings_dates[limit]
-
        logger = utils.get_yf_logger()

-        page_size = min(limit, 100)  # YF caps at 100, don't go higher
-        page_offset = 0
-        dates = None
-        while True:
-            url = f"{_ROOT_URL_}/calendar/earnings?symbol={self.ticker}&offset={page_offset}&size={page_size}"
-            data = self._data.cache_get(url=url, proxy=proxy).text
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)

-            if "Will be right back" in data:
-                raise RuntimeError("*** YAHOO! FINANCE IS CURRENTLY DOWN! ***\n"
-                                   "Our engineers are working quickly to resolve "
-                                   "the issue. Thank you for your patience.")
+        clamped_limit = min(limit, 100)  # YF caps at 100, don't go higher

-            try:
-                data = pd.read_html(StringIO(data))[0]
-            except ValueError:
-                if page_offset == 0:
-                    # Should not fail on first page
-                    if "Showing Earnings for:" in data:
-                        # Actually YF was successful, problem is company doesn't have earnings history
-                        dates = utils.empty_earnings_dates_df()
-                break
-            if dates is None:
-                dates = data
-            else:
-                dates = pd.concat([dates, data], axis=0)
+        if self._earnings_dates and clamped_limit in self._earnings_dates:
+            return self._earnings_dates[clamped_limit]

-            page_offset += page_size
-            # got less data then we asked for or already fetched all we requested, no need to fetch more pages
-            if len(data) < page_size or len(dates) >= limit:
-                dates = dates.iloc[:limit]
-                break
-            else:
-                # do not fetch more than needed next time
-                page_size = min(limit - len(dates), page_size)
+        # Fetch data
+        url = f"{_QUERY1_URL_}/v1/finance/visualization"
+        params = {"lang": "en-US", "region": "US"}
+        body = {
+            "size": clamped_limit,
+            "query": {
+                "operator": "and",
+                "operands": [
+                    {"operator": "eq", "operands": ["ticker", self.ticker]},
+                    {"operator": "eq", "operands": ["eventtype", "2"]}
+                ]
+            },
+            "sortField": "startdatetime",
+            "sortType": "DESC",
+            "entityIdType": "earnings",
+            "includeFields": ["startdatetime", "timeZoneShortName", "epsestimate", "epsactual", "epssurprisepct"]
+        }
+        response = self._data.post(url, params=params, body=body)
+        json_data = response.json()

-        if dates is None or dates.shape[0] == 0:
+        # Extract data
+        columns = [row['label'] for row in json_data['finance']['result'][0]['documents'][0]['columns']]
+        rows = json_data['finance']['result'][0]['documents'][0]['rows']
+        df = pd.DataFrame(rows, columns=columns)
+
+        if df.empty:
            _exception = YFEarningsDateMissing(self.ticker)
            err_msg = str(_exception)
            logger.error(f'{self.ticker}: {err_msg}')
            return None
-        dates = dates.reset_index(drop=True)

-        # Drop redundant columns
-        dates = dates.drop(["Symbol", "Company"], axis=1)
+        # Calculate earnings date
+        df['Earnings Date'] = pd.to_datetime(df['Event Start Date'])
+        tz = self._get_ticker_tz(timeout=30)
+        if df['Earnings Date'].dt.tz is None:
+            df['Earnings Date'] = df['Earnings Date'].dt.tz_localize(tz)
+        else:
+            df['Earnings Date'] = df['Earnings Date'].dt.tz_convert(tz)

        # Convert types
-        for cn in ["EPS Estimate", "Reported EPS", "Surprise(%)"]:
-            dates.loc[dates[cn] == '-', cn] = float("nan")
-            dates[cn] = dates[cn].astype(float)
+        columns_to_update = ['Surprise (%)', 'EPS Estimate', 'Reported EPS']
+        df[columns_to_update] = df[columns_to_update].astype('float64').replace(0.0, np.nan)

-        # Convert % to range 0->1:
-        dates["Surprise(%)"] *= 0.01
+        # Format the dataframe
+        df.drop(['Event Start Date', 'Timezone short name'], axis=1, inplace=True)
+        df.set_index('Earnings Date', inplace=True)
+        df.rename(columns={'Surprise (%)': 'Surprise(%)'}, inplace=True)  # Compatibility

-        # Parse earnings date string
-        cn = "Earnings Date"
-        # - remove AM/PM and timezone from date string
-        tzinfo = dates[cn].str.extract('([AP]M[a-zA-Z]*)$')
-        dates[cn] = dates[cn].replace(' [AP]M[a-zA-Z]*$', '', regex=True)
-        # - split AM/PM from timezone
-        tzinfo = tzinfo[0].str.extract('([AP]M)([a-zA-Z]*)', expand=True)
-        tzinfo.columns = ["AM/PM", "TZ"]
-        # - combine and parse
-        dates[cn] = dates[cn] + ' ' + tzinfo["AM/PM"]
-        dates[cn] = pd.to_datetime(dates[cn], format="%b %d, %Y, %I %p")
-        # - instead of attempting decoding of ambiguous timezone abbreviation, just use 'info':
-        self._quote.proxy = proxy or self.proxy
-        tz = self._get_ticker_tz(proxy=proxy, timeout=30)
-        dates[cn] = dates[cn].dt.tz_localize(tz)
+        self._earnings_dates[clamped_limit] = df
+        return df

-        dates = dates.set_index("Earnings Date")
+    def get_history_metadata(self, proxy=_SENTINEL_) -> dict:
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)

-        self._earnings_dates[limit] = dates
-
-        return dates
-
-    def get_history_metadata(self, proxy=None) -> dict:
        return self._lazy_load_price_history().get_history_metadata(proxy)

-    def get_funds_data(self, proxy=None) -> Optional[FundsData]:
+    def get_funds_data(self, proxy=_SENTINEL_) -> Optional[FundsData]:
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        if not self._funds_data:
            self._funds_data = FundsData(self._data, self.ticker)
        
-        return self._funds_data
+        return self._funds_data
+
+    def live(self, message_handler=None, verbose=True):
+        self._message_handler = message_handler
+
+        self.ws = WebSocket(verbose=verbose)
+        self.ws.subscribe(self.ticker)
+        self.ws.listen(self._message_handler)
--- a/yfinance/const.py
+++ b/yfinance/const.py
@@ -2,6 +2,8 @@ _QUERY1_URL_ = 'https://query1.finance.yahoo.com'
 _BASE_URL_ = 'https://query2.finance.yahoo.com'
 _ROOT_URL_ = 'https://finance.yahoo.com'

+_SENTINEL_ = object()
+
 fundamentals_keys = {
    'financials': ["TaxEffectOfUnusualItems", "TaxRateForCalcs", "NormalizedEBITDA", "NormalizedDilutedEPS",
                   "NormalizedBasicEPS", "TotalUnusualItems", "TotalUnusualItemsExcludingGoodwill",
@@ -305,21 +307,92 @@ SECTOR_INDUSTY_MAPPING = {
                    'utilities-independent-power-producers',
                    'utilities-regulated-water'}
 }
+
+def merge_two_level_dicts(dict1, dict2):
+    result = dict1.copy()
+    for key, value in dict2.items():
+        if key in result:
+            # If both are sets, merge them
+            if isinstance(value, set) and isinstance(result[key], set):
+                result[key] = result[key] | value
+            # If both are dicts, merge their contents
+            elif isinstance(value, dict) and isinstance(result[key], dict):
+                result[key] = {
+                    k: (result[key].get(k, set()) | v if isinstance(v, set) 
+                        else v) if k in result[key]
+                    else v
+                    for k, v in value.items()
+                }
+        else:
+            result[key] = value
+    return result
+
 EQUITY_SCREENER_EQ_MAP = {
-    "region": {
-        "za", "ve", "vn", "us", "tw", "th", "tr", "sr", "sg", "sa", "se", "ru", "ro", "qa", "pt", "pk", "pl",
-        "ph", "nz", "nl", "mx", "pe", "no", "my", "lv", "lt", "kw", "jp", "is", "il", "lk", "kr", "it", "in",
-        "ie", "hu", "id", "hk", "gb", "fi", "eg", "dk", "gr", "fr", "es", "ee", "de", "cz", "cl", "ca", "be",
-        "at", "cn", "br", "au", "ar", "ch"
+    "exchange": {
+        'ar': {'BUE'},
+        'at': {'VIE'},
+        'au': {'ASX'},
+        'be': {'BRU'},
+        'br': {'SAO'},
+        'ca': {'CNQ', 'NEO', 'TOR', 'VAN'},
+        'ch': {'EBS'},
+        'cl': {'SGO'},
+        'cn': {'SHH', 'SHZ'},
+        'co': {'BVC'},
+        'cz': {'PRA'},
+        'de': {'BER', 'DUS', 'FRA', 'HAM', 'GER', 'MUN', 'STU'},
+        'dk': {'CPH'},
+        'ee': {'TAL'},
+        'eg': {'CAI'},
+        'es': {'MCE'},
+        'fi': {'HEL'},
+        'fr': {'PAR'},
+        'gb': {'AQS', 'IOB', 'LSE'},
+        'gr': {'ATH'},
+        'hk': {'HKG'},
+        'hu': {'BUD'},
+        'id': {'JKT'},
+        'ie': {'ISE'},
+        'il': {'TLV'},
+        'in': {'BSE', 'NSI'},
+        'is': {'ICE'},
+        'it': {'MIL'},
+        'jp': {'FKA', 'JPX', 'SAP'},
+        'kr': {'KOE', 'KSC'},
+        'kw': {'KUW'},
+        'lk': {},
+        'lt': {'LIT'},
+        'lv': {'RIS'},
+        'mx': {'MEX'},
+        'my': {'KLS'},
+        'nl': {'AMS'},
+        'no': {'OSL'},
+        'nz': {'NZE'},
+        'pe': {},
+        'ph': {'PHP', 'PHS'},
+        'pk': {},
+        'pl': {'WSE'},
+        'pt': {'LIS'},
+        'qa': {'DOH'},
+        'ro': {'BVB'},
+        'ru': {},
+        'sa': {'SAU'},
+        'se': {'STO'},
+        'sg': {'SES'},
+        'sr': {},
+        'th': {'SET'},
+        'tr': {'IST'},
+        'tw': {'TAI', 'TWO'},
+        'us': {'ASE', 'BTS', 'CXI', 'NCM', 'NGM', 'NMS', 'NYQ', 'OEM', 'OQB', 'OQX', 'PCX', 'PNK', 'YHD'},
+        've': {'CCS'},
+        'vn': {},
+        'za': {'JNB'}
    },
    "sector": {
        "Basic Materials", "Industrials", "Communication Services", "Healthcare",
        "Real Estate", "Technology", "Energy", "Utilities", "Financial Services",
        "Consumer Defensive", "Consumer Cyclical"
    },
-    "exchanges": {
-        "NMS", "NAS", "YHD", "NYQ", "NGM", "NCM", "BSE"
-    },
    "peer_group": {
        "US Fund Equity Energy",
        "US CE Convertibles",
@@ -426,20 +499,42 @@ EQUITY_SCREENER_EQ_MAP = {
        "Banks"
    }
 }
+EQUITY_SCREENER_EQ_MAP['region'] = EQUITY_SCREENER_EQ_MAP['exchange'].keys()
+ordered_keys = ['region'] + [k for k in EQUITY_SCREENER_EQ_MAP.keys() if k != 'region']
+EQUITY_SCREENER_EQ_MAP = {k:EQUITY_SCREENER_EQ_MAP[k] for k in ordered_keys}
+FUND_SCREENER_EQ_MAP = {
+    "exchange": {
+        'us': {'NAS'}
+    }
+}
+COMMON_SCREENER_FIELDS = {
+    "price":{
+        "eodprice",
+        "intradaypricechange",
+        "intradayprice"
+    },
+    "eq_fields": {
+        "exchange"}, 
+}
+FUND_SCREENER_FIELDS = {
+    "eq_fields": {
+        "categoryname",
+        "performanceratingoverall",
+        "initialinvestment", 
+        "annualreturnnavy1categoryrank", 
+        "riskratingoverall"}
+}
+FUND_SCREENER_FIELDS = merge_two_level_dicts(FUND_SCREENER_FIELDS, COMMON_SCREENER_FIELDS)
 EQUITY_SCREENER_FIELDS = {
    "eq_fields": {
        "region",
        "sector",
-        "peer_group",
-        "exchanges"}, 
+        "peer_group"}, 
    "price":{
-        "eodprice",
-        "intradaypricechange",
        "lastclosemarketcap.lasttwelvemonths",
        "percentchange",
        "lastclose52weekhigh.lasttwelvemonths",
        "fiftytwowkpercentchange",
-        "intradayprice",
        "lastclose52weeklow.lasttwelvemonths",
        "intradaymarketcap"},
    "trading":{
@@ -530,21 +625,22 @@ EQUITY_SCREENER_FIELDS = {
        "social_score",
        "highest_controversy"}
 }
+EQUITY_SCREENER_FIELDS = merge_two_level_dicts(EQUITY_SCREENER_FIELDS, COMMON_SCREENER_FIELDS)

-PREDEFINED_SCREENER_BODY_MAP = {
-    'aggressive_small_caps': {"offset":0,"size":25,"sortField":"eodvolume","sortType":"desc","quoteType":"equity","query":{"operator":"and","operands":[{"operator":"or","operands":[{"operator":"eq","operands":["exchange","NMS"]},{"operator":"eq","operands":["exchange","NYQ"]}]},{"operator":"or","operands":[{"operator":"LT","operands":["epsgrowth.lasttwelvemonths",15]}]}]},"userId":"","userIdType":"guid"},
-    'day_gainers': {"offset":0,"size":25,"sortField":"percentchange","sortType":"DESC","quoteType":"EQUITY","query":{"operator":"AND","operands":[{"operator":"gt","operands":["percentchange",3]},{"operator":"eq","operands":["region","us"]},{"operator":"or","operands":[{"operator":"BTWN","operands":["intradaymarketcap",2000000000,10000000000]},{"operator":"BTWN","operands":["intradaymarketcap",10000000000,100000000000]},{"operator":"GT","operands":["intradaymarketcap",100000000000]}]},{"operator":"gte","operands":["intradayprice",5]},{"operator":"gt","operands":["dayvolume",15000]}]},"userId":"","userIdType":"guid"},
-    'day_losers': {"offset":0,"size":25,"sortField":"percentchange","sortType":"ASC","quoteType":"EQUITY","query":{"operator":"AND","operands":[{"operator":"lt","operands":["percentchange",-2.5]},{"operator":"eq","operands":["region","us"]},{"operator":"or","operands":[{"operator":"BTWN","operands":["intradaymarketcap",2000000000,10000000000]},{"operator":"BTWN","operands":["intradaymarketcap",10000000000,100000000000]},{"operator":"GT","operands":["intradaymarketcap",100000000000]}]},{"operator":"gte","operands":["intradayprice",5]},{"operator":"gt","operands":["dayvolume",20000]}]},"userId":"","userIdType":"guid"},
-    'growth_technology_stocks': {"offset":0,"size":25,"sortField":"eodvolume","sortType":"desc","quoteType":"equity","query":{"operator":"and","operands":[{"operator":"or","operands":[{"operator":"BTWN","operands":["quarterlyrevenuegrowth.quarterly",50,100]},{"operator":"GT","operands":["quarterlyrevenuegrowth.quarterly",100]},{"operator":"BTWN","operands":["quarterlyrevenuegrowth.quarterly",25,50]}]},{"operator":"or","operands":[{"operator":"BTWN","operands":["epsgrowth.lasttwelvemonths",25,50]},{"operator":"BTWN","operands":["epsgrowth.lasttwelvemonths",50,100]},{"operator":"GT","operands":["epsgrowth.lasttwelvemonths",100]}]},{"operator":"eq","operands":["sector","Technology"]},{"operator":"or","operands":[{"operator":"eq","operands":["exchange","NMS"]},{"operator":"eq","operands":["exchange","NYQ"]}]}]},"userId":"","userIdType":"guid"},
-    'most_actives': {"offset":0,"size":25,"sortField":"dayvolume","sortType":"DESC","quoteType":"EQUITY","query":{"operator":"AND","operands":[{"operator":"eq","operands":["region","us"]},{"operator":"or","operands":[{"operator":"BTWN","operands":["intradaymarketcap",10000000000,100000000000]},{"operator":"GT","operands":["intradaymarketcap",100000000000]},{"operator":"BTWN","operands":["intradaymarketcap",2000000000,10000000000]}]},{"operator":"gt","operands":["dayvolume",5000000]}]},"userId":"","userIdType":"guid"},
-    'most_shorted_stocks': {"size":25,"offset":0,"sortField":"short_percentage_of_shares_outstanding.value","sortType":"DESC","quoteType":"EQUITY","topOperator":"AND","query":{"operator":"AND","operands":[{"operator":"or","operands":[{"operator":"EQ","operands":["region","us"]}]},{"operator":"gt","operands":["intradayprice",1]},{"operator":"gt","operands":["avgdailyvol3m",200000]}]},"userId":"","userIdType":"guid"},
-    'small_cap_gainers': {"offset":0,"size":25,"sortField":"eodvolume","sortType":"desc","quoteType":"equity","query":{"operator":"and","operands":[{"operator":"lt","operands":["intradaymarketcap",2000000000]},{"operator":"or","operands":[{"operator":"eq","operands":["exchange","NMS"]},{"operator":"eq","operands":["exchange","NYQ"]}]}]},"userId":"","userIdType":"guid"},
-    'undervalued_growth_stocks': {"offset":0,"size":25,"sortType":"DESC","sortField":"eodvolume","quoteType":"EQUITY","query":{"operator":"and","operands":[{"operator":"or","operands":[{"operator":"BTWN","operands":["peratio.lasttwelvemonths",0,20]}]},{"operator":"or","operands":[{"operator":"LT","operands":["pegratio_5y",1]}]},{"operator":"or","operands":[{"operator":"BTWN","operands":["epsgrowth.lasttwelvemonths",25,50]},{"operator":"BTWN","operands":["epsgrowth.lasttwelvemonths",50,100]},{"operator":"GT","operands":["epsgrowth.lasttwelvemonths",100]}]},{"operator":"or","operands":[{"operator":"eq","operands":["exchange","NMS"]},{"operator":"eq","operands":["exchange","NYQ"]}]}]},"userId":"","userIdType":"guid"},
-    'undervalued_large_caps': {"offset":0,"size":25,"sortField":"eodvolume","sortType":"desc","quoteType":"equity","query":{"operator":"and","operands":[{"operator":"or","operands":[{"operator":"BTWN","operands":["peratio.lasttwelvemonths",0,20]}]},{"operator":"lt","operands":["pegratio_5y",1]},{"operator":"btwn","operands":["intradaymarketcap",10000000000,100000000000]},{"operator":"or","operands":[{"operator":"eq","operands":["exchange","NMS"]},{"operator":"eq","operands":["exchange","NYQ"]}]}]},"userId":"","userIdType":"guid"},
-    'conservative_foreign_funds': {"offset":0,"size":25,"sortType":"DESC","sortField":"fundnetassets","quoteType":"MUTUALFUND","query":{"operator":"and","operands":[{"operator":"or","operands":[{"operator":"EQ","operands":["categoryname","Foreign Large Value"]},{"operator":"EQ","operands":["categoryname","Foreign Large Blend"]},{"operator":"EQ","operands":["categoryname","Foreign Large Growth"]},{"operator":"EQ","operands":["categoryname","Foreign Small/Mid Growth"]},{"operator":"EQ","operands":["categoryname","Foreign Large Blend"]},{"operator":"EQ","operands":["categoryname","Foreign Small/Mid Blend"]},{"operator":"EQ","operands":["categoryname","Foreign Small/Mid Value"]},{"operator":"EQ","operands":["categoryname","Foreign Small/Mid Blend"]},{"operator":"EQ","operands":["categoryname","Foreign Small/Mid Value"]},{"operator":"EQ","operands":["categoryname","Foreign Small/Mid Blend"]},{"operator":"EQ","operands":["categoryname","Foreign Small/Mid Value"]},{"operator":"EQ","operands":["categoryname","Foreign Small/Mid Blend"]},{"operator":"EQ","operands":["categoryname","Foreign Small/Mid Value"]}]},{"operator":"or","operands":[{"operator":"EQ","operands":["performanceratingoverall",4]},{"operator":"EQ","operands":["performanceratingoverall",5]}]},{"operator":"lt","operands":["initialinvestment",100001]},{"operator":"lt","operands":["annualreturnnavy1categoryrank",50]},{"operator":"or","operands":[{"operator":"EQ","operands":["riskratingoverall",1]},{"operator":"EQ","operands":["riskratingoverall",3]},{"operator":"EQ","operands":["riskratingoverall",2]}]},{"operator":"or","operands":[{"operator":"eq","operands":["exchange","NAS"]}]}]},"userId":"","userIdType":"guid"},
-    'high_yield_bond': {"offset":0,"size":25,"sortType":"DESC","sortField":"fundnetassets","quoteType":"MUTUALFUND","query":{"operator":"and","operands":[{"operator":"or","operands":[{"operator":"EQ","operands":["performanceratingoverall",4]},{"operator":"EQ","operands":["performanceratingoverall",5]}]},{"operator":"lt","operands":["initialinvestment",100001]},{"operator":"lt","operands":["annualreturnnavy1categoryrank",50]},{"operator":"or","operands":[{"operator":"EQ","operands":["riskratingoverall",1]},{"operator":"EQ","operands":["riskratingoverall",3]},{"operator":"EQ","operands":["riskratingoverall",2]}]},{"operator":"or","operands":[{"operator":"EQ","operands":["categoryname","High Yield Bond"]}]},{"operator":"or","operands":[{"operator":"eq","operands":["exchange","NAS"]}]}]},"userId":"","userIdType":"guid"},
-    'portfolio_anchors': {"offset":0,"size":25,"sortType":"DESC","sortField":"fundnetassets","quoteType":"MUTUALFUND","query":{"operator":"and","operands":[{"operator":"or","operands":[{"operator":"EQ","operands":["categoryname","Large Blend"]}]},{"operator":"or","operands":[{"operator":"EQ","operands":["performanceratingoverall",4]},{"operator":"EQ","operands":["performanceratingoverall",5]}]},{"operator":"lt","operands":["initialinvestment",100001]},{"operator":"lt","operands":["annualreturnnavy1categoryrank",50]},{"operator":"or","operands":[{"operator":"eq","operands":["exchange","NAS"]}]}]},"userId":"","userIdType":"guid"},
-    'solid_large_growth_funds': {"offset":0,"size":25,"sortType":"DESC","sortField":"fundnetassets","quoteType":"MUTUALFUND","query":{"operator":"and","operands":[{"operator":"or","operands":[{"operator":"EQ","operands":["categoryname","Large Growth"]}]},{"operator":"or","operands":[{"operator":"EQ","operands":["performanceratingoverall",5]},{"operator":"EQ","operands":["performanceratingoverall",4]}]},{"operator":"lt","operands":["initialinvestment",100001]},{"operator":"lt","operands":["annualreturnnavy1categoryrank",50]},{"operator":"or","operands":[{"operator":"eq","operands":["exchange","NAS"]}]}]},"userId":"","userIdType":"guid"},
-    'solid_midcap_growth_funds': {"offset":0,"size":25,"sortType":"DESC","sortField":"fundnetassets","quoteType":"MUTUALFUND","query":{"operator":"and","operands":[{"operator":"or","operands":[{"operator":"EQ","operands":["categoryname","Mid-Cap Growth"]}]},{"operator":"or","operands":[{"operator":"EQ","operands":["performanceratingoverall",5]},{"operator":"EQ","operands":["performanceratingoverall",4]}]},{"operator":"lt","operands":["initialinvestment",100001]},{"operator":"lt","operands":["annualreturnnavy1categoryrank",50]},{"operator":"or","operands":[{"operator":"eq","operands":["exchange","NAS"]}]}]},"userId":"","userIdType":"guid"},
-    'top_mutual_funds': {"offset":0,"size":25,"sortType":"DESC","sortField":"percentchange","quoteType":"MUTUALFUND","query":{"operator":"and","operands":[{"operator":"gt","operands":["intradayprice",15]},{"operator":"or","operands":[{"operator":"EQ","operands":["performanceratingoverall",5]},{"operator":"EQ","operands":["performanceratingoverall",4]}]},{"operator":"gt","operands":["initialinvestment",1000]},{"operator":"or","operands":[{"operator":"eq","operands":["exchange","NAS"]}]}]},"userId":"","userIdType":"guid"}
-}
+USER_AGENTS = [
+    # Chrome
+    "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36",
+    "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36",
+    "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36",
+
+    # Firefox
+    "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:135.0) Gecko/20100101 Firefox/135.0",
+    "Mozilla/5.0 (Macintosh; Intel Mac OS X 14.7; rv:135.0) Gecko/20100101 Firefox/135.0",
+    "Mozilla/5.0 (X11; Linux i686; rv:135.0) Gecko/20100101 Firefox/135.0",
+
+    # Safari
+    "Mozilla/5.0 (Macintosh; Intel Mac OS X 14_7_4) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/18.3 Safari/605.1.15",
+
+    # Edge
+    "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36 Edg/131.0.2903.86"
+]
--- a/yfinance/data.py
+++ b/yfinance/data.py
@@ -1,7 +1,7 @@
 import functools
 from functools import lru_cache

-import requests as requests
+from curl_cffi import requests
 from bs4 import BeautifulSoup
 import datetime

@@ -10,6 +10,8 @@ from frozendict import frozendict
 from . import utils, cache
 import threading

+from .exceptions import YFRateLimitError
+
 cache_maxsize = 64


@@ -47,7 +49,13 @@ class SingletonMeta(type):
                instance = super().__call__(*args, **kwargs)
                cls._instances[cls] = instance
            else:
-                cls._instances[cls]._set_session(*args, **kwargs)
+                # Update the existing instance
+                if 'session' in kwargs or (args and len(args) > 0):
+                    session = kwargs.get('session') if 'session' in kwargs else args[0]
+                    cls._instances[cls]._set_session(session)
+                if 'proxy' in kwargs or (args and len(args) > 1):
+                    proxy = kwargs.get('proxy') if 'proxy' in kwargs else args[1]
+                    cls._instances[cls]._set_proxy(proxy)
            return cls._instances[cls]


@@ -56,10 +64,8 @@ class YfData(metaclass=SingletonMeta):
    Have one place to retrieve data from Yahoo API in order to ease caching and speed up operations.
    Singleton means one session one cookie shared by all threads.
    """
-    user_agent_headers = {
-        'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36'}

-    def __init__(self, session=None):
+    def __init__(self, session=None, proxy=None):
        self._crumb = None
        self._cookie = None

@@ -70,13 +76,17 @@ class YfData(metaclass=SingletonMeta):

        self._cookie_lock = threading.Lock()

-        self._set_session(session or requests.Session())
+        self._session, self._proxy = None, None
+        self._set_session(session or requests.Session(impersonate="chrome"))
+        self._set_proxy(proxy)

    def _set_session(self, session):
        if session is None:
            return
        with self._cookie_lock:
            self._session = session
+            if self._proxy is not None:
+                self._session.proxies = self._proxy

        try:
            self._session.cache
@@ -91,6 +101,15 @@ class YfData(metaclass=SingletonMeta):
            from requests_cache import DO_NOT_CACHE
            self._expire_after = DO_NOT_CACHE

+    def _set_proxy(self, proxy=None):
+        with self._cookie_lock:
+            if proxy is not None:
+                proxy = {'http': proxy, 'https': proxy} if isinstance(proxy, str) else proxy
+            else:
+                proxy = {}
+            self._proxy = proxy
+            self._session.proxies = proxy
+
    def _set_cookie_strategy(self, strategy, have_lock=False):
        if strategy == self._cookie_strategy:
            return
@@ -147,50 +166,23 @@ class YfData(metaclass=SingletonMeta):
        utils.get_yf_logger().debug('loaded persistent cookie')
        return cookie_dict['cookie']

-    def _get_cookie_basic(self, proxy=None, timeout=30):
-        if self._cookie is not None:
-            utils.get_yf_logger().debug('reusing cookie')
-            return self._cookie
-
-        self._cookie = self._load_cookie_basic()
-        if self._cookie is not None:
-            return self._cookie
-
+    def _get_cookie_basic(self, timeout=30):
        # To avoid infinite recursion, do NOT use self.get()
        # - 'allow_redirects' copied from @psychoz971 solution - does it help USA?
-        response = self._session.get(
+        self._session.get(
            url='https://fc.yahoo.com',
-            headers=self.user_agent_headers,
-            proxies=proxy,
            timeout=timeout,
            allow_redirects=True)

-        if not response.cookies:
-            utils.get_yf_logger().debug("response.cookies = None")
-            return None
-        self._cookie = list(response.cookies)[0]
-        if self._cookie == '':
-            utils.get_yf_logger().debug("list(response.cookies)[0] = ''")
-            return None
-        self._save_cookie_basic(self._cookie)
-        utils.get_yf_logger().debug(f"fetched basic cookie = {self._cookie}")
-        return self._cookie
-
-    def _get_crumb_basic(self, proxy=None, timeout=30):
+    def _get_crumb_basic(self, timeout=30):
        if self._crumb is not None:
            utils.get_yf_logger().debug('reusing crumb')
            return self._crumb

-        cookie = self._get_cookie_basic()
-        if cookie is None:
-            return None
-
+        self._get_cookie_basic()        
        # - 'allow_redirects' copied from @psychoz971 solution - does it help USA?
        get_args = {
            'url': "https://query1.finance.yahoo.com/v1/test/getcrumb",
-            'headers': self.user_agent_headers,
-            'cookies': {cookie.name: cookie.value},
-            'proxies': proxy,
            'timeout': timeout,
            'allow_redirects': True
        }
@@ -208,12 +200,12 @@ class YfData(metaclass=SingletonMeta):
        return self._crumb

    @utils.log_indent_decorator
-    def _get_cookie_and_crumb_basic(self, proxy, timeout):
-        cookie = self._get_cookie_basic(proxy, timeout)
-        crumb = self._get_crumb_basic(proxy, timeout)
-        return cookie, crumb
+    def _get_cookie_and_crumb_basic(self, timeout):
+        self._get_cookie_basic(timeout)
+        crumb = self._get_crumb_basic(timeout)
+        return crumb

-    def _get_cookie_csrf(self, proxy, timeout):
+    def _get_cookie_csrf(self, timeout):
        if self._cookie is not None:
            utils.get_yf_logger().debug('reusing cookie')
            return True
@@ -224,16 +216,19 @@ class YfData(metaclass=SingletonMeta):
            return True

        base_args = {
-            'headers': self.user_agent_headers,
-            'proxies': proxy,
            'timeout': timeout}

        get_args = {**base_args, 'url': 'https://guce.yahoo.com/consent'}
-        if self._session_is_caching:
-            get_args['expire_after'] = self._expire_after
-            response = self._session.get(**get_args)
-        else:
-            response = self._session.get(**get_args)
+        try:
+            if self._session_is_caching:
+                get_args['expire_after'] = self._expire_after
+                response = self._session.get(**get_args)
+            else:
+                response = self._session.get(**get_args)
+        except requests.exceptions.ChunkedEncodingError:
+            # No idea why happens, but handle nicely so can switch to other cookie method.
+            utils.get_yf_logger().debug('_get_cookie_csrf() encountering requests.exceptions.ChunkedEncodingError, aborting')
+            return False

        soup = BeautifulSoup(response.content, 'html.parser')
        csrfTokenInput = soup.find('input', attrs={'name': 'csrfToken'})
@@ -262,34 +257,36 @@ class YfData(metaclass=SingletonMeta):
        get_args = {**base_args,
            'url': f'https://guce.yahoo.com/copyConsent?sessionId={sessionId}',
            'data': data}
-        if self._session_is_caching:
-            post_args['expire_after'] = self._expire_after
-            get_args['expire_after'] = self._expire_after
-            self._session.post(**post_args)
-            self._session.get(**get_args)
-        else:
-            self._session.post(**post_args)
-            self._session.get(**get_args)
+        try:
+            if self._session_is_caching:
+                post_args['expire_after'] = self._expire_after
+                get_args['expire_after'] = self._expire_after
+                self._session.post(**post_args)
+                self._session.get(**get_args)
+            else:
+                self._session.post(**post_args)
+                self._session.get(**get_args)
+        except requests.exceptions.ChunkedEncodingError:
+            # No idea why happens, but handle nicely so can switch to other cookie method.
+            utils.get_yf_logger().debug('_get_cookie_csrf() encountering requests.exceptions.ChunkedEncodingError, aborting')
        self._cookie = True
        self._save_session_cookies()
        return True

    @utils.log_indent_decorator
-    def _get_crumb_csrf(self, proxy=None, timeout=30):
+    def _get_crumb_csrf(self, timeout=30):
        # Credit goes to @bot-unit #1729

        if self._crumb is not None:
            utils.get_yf_logger().debug('reusing crumb')
            return self._crumb

-        if not self._get_cookie_csrf(proxy, timeout):
+        if not self._get_cookie_csrf(timeout):
            # This cookie stored in session
            return None

        get_args = {
            'url': 'https://query2.finance.yahoo.com/v1/test/getcrumb',
-            'headers': self.user_agent_headers,
-            'proxies': proxy,
            'timeout': timeout}
        if self._session_is_caching:
            get_args['expire_after'] = self._expire_after
@@ -306,8 +303,8 @@ class YfData(metaclass=SingletonMeta):
        return self._crumb

    @utils.log_indent_decorator
-    def _get_cookie_and_crumb(self, proxy=None, timeout=30):
-        cookie, crumb, strategy = None, None, None
+    def _get_cookie_and_crumb(self, timeout=30):
+        crumb, strategy = None, None

        utils.get_yf_logger().debug(f"cookie_mode = '{self._cookie_strategy}'")

@@ -317,27 +314,27 @@ class YfData(metaclass=SingletonMeta):
                if crumb is None:
                    # Fail
                    self._set_cookie_strategy('basic', have_lock=True)
-                    cookie, crumb = self._get_cookie_and_crumb_basic(proxy, timeout)
+                    crumb = self._get_cookie_and_crumb_basic(timeout)
            else:
                # Fallback strategy
-                cookie, crumb = self._get_cookie_and_crumb_basic(proxy, timeout)
-                if cookie is None or crumb is None:
+                crumb = self._get_cookie_and_crumb_basic(timeout)
+                if crumb is None:
                    # Fail
                    self._set_cookie_strategy('csrf', have_lock=True)
                    crumb = self._get_crumb_csrf()
            strategy = self._cookie_strategy
-        return cookie, crumb, strategy
+        return crumb, strategy

    @utils.log_indent_decorator
-    def get(self, url, user_agent_headers=None, params=None, proxy=None, timeout=30):
-        return self._make_request(url, request_method = self._session.get, user_agent_headers=user_agent_headers, params=params, proxy=proxy, timeout=timeout)
+    def get(self, url, params=None, timeout=30):
+        return self._make_request(url, request_method = self._session.get, params=params, timeout=timeout)
    
    @utils.log_indent_decorator
-    def post(self, url, body, user_agent_headers=None, params=None, proxy=None, timeout=30):
-        return self._make_request(url, request_method = self._session.post, user_agent_headers=user_agent_headers, body=body, params=params, proxy=proxy, timeout=timeout)
+    def post(self, url, body, params=None, timeout=30):
+        return self._make_request(url, request_method = self._session.post, body=body, params=params, timeout=timeout)
    
    @utils.log_indent_decorator
-    def _make_request(self, url, request_method, user_agent_headers=None, body=None, params=None, proxy=None, timeout=30):
+    def _make_request(self, url, request_method, body=None, params=None, timeout=30):
        # Important: treat input arguments as immutable.

        if len(url) > 200:
@@ -345,31 +342,22 @@ class YfData(metaclass=SingletonMeta):
        else:
            utils.get_yf_logger().debug(f'url={url}')
        utils.get_yf_logger().debug(f'params={params}')
-        proxy = self._get_proxy(proxy)

        if params is None:
            params = {}
        if 'crumb' in params:
            raise Exception("Don't manually add 'crumb' to params dict, let data.py handle it")

-        cookie, crumb, strategy = self._get_cookie_and_crumb()
+        crumb, strategy = self._get_cookie_and_crumb()
        if crumb is not None:
            crumbs = {'crumb': crumb}
        else:
            crumbs = {}
-        if strategy == 'basic' and cookie is not None:
-            # Basic cookie strategy adds cookie to GET parameters
-            cookies = {cookie.name: cookie.value}
-        else:
-            cookies = None

        request_args = {
            'url': url,
            'params': {**params, **crumbs},
-            'cookies': cookies,
-            'proxies': proxy,
-            'timeout': timeout,
-            'headers': user_agent_headers or self.user_agent_headers
+            'timeout': timeout
        }

        if body:
@@ -383,30 +371,24 @@ class YfData(metaclass=SingletonMeta):
                self._set_cookie_strategy('csrf')
            else:
                self._set_cookie_strategy('basic')
-            cookie, crumb, strategy = self._get_cookie_and_crumb(proxy, timeout)
+            crumb, strategy = self._get_cookie_and_crumb(timeout)
            request_args['params']['crumb'] = crumb
-            if strategy == 'basic':
-                request_args['cookies'] = {cookie.name: cookie.value}
            response = request_method(**request_args)
            utils.get_yf_logger().debug(f'response code={response.status_code}')

+            # Raise exception if rate limited
+            if response.status_code == 429:
+                raise YFRateLimitError()
+
        return response

    @lru_cache_freezeargs
    @lru_cache(maxsize=cache_maxsize)
-    def cache_get(self, url, user_agent_headers=None, params=None, proxy=None, timeout=30):
-        return self.get(url, user_agent_headers, params, proxy, timeout)
+    def cache_get(self, url, params=None, timeout=30):
+        return self.get(url, params, timeout)

-    def _get_proxy(self, proxy):
-        # setup proxy in requests format
-        if proxy is not None:
-            if isinstance(proxy, (dict, frozendict)) and "https" in proxy:
-                proxy = proxy["https"]
-            proxy = {"https": proxy}
-        return proxy
-
-    def get_raw_json(self, url, user_agent_headers=None, params=None, proxy=None, timeout=30):
+    def get_raw_json(self, url, params=None, timeout=30):
        utils.get_yf_logger().debug(f'get_raw_json(): {url}')
-        response = self.get(url, user_agent_headers=user_agent_headers, params=params, proxy=proxy, timeout=timeout)
+        response = self.get(url, params=params, timeout=timeout)
        response.raise_for_status()
        return response.json()
--- a/yfinance/domain/domain.py
+++ b/yfinance/domain/domain.py
@@ -1,7 +1,8 @@
 from abc import ABC, abstractmethod
 from ..ticker import Ticker
-from ..const import _QUERY1_URL_
+from ..const import _QUERY1_URL_, _SENTINEL_
 from ..data import YfData
+from ..utils import print_once
 from typing import Dict, List, Optional
 import pandas as _pd

@@ -13,20 +14,21 @@ class Domain(ABC):
    and methods for fetching and parsing data. Derived classes must implement the `_fetch_and_parse()` method.
    """

-    def __init__(self, key: str, session=None, proxy=None):
+    def __init__(self, key: str, session=None, proxy=_SENTINEL_):
        """
        Initializes the Domain object with a key, session, and proxy.

        Args:
            key (str): Unique key identifying the domain entity.
            session (Optional[requests.Session]): Session object for HTTP requests. Defaults to None.
-            proxy (Optional[Dict]): Proxy settings. Defaults to None.
        """
        self._key: str = key
-        self.proxy = proxy
        self.session = session
        self._data: YfData = YfData(session=session)
-        
+        if proxy is not _SENTINEL_:
+            print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        self._name: Optional[str] = None
        self._symbol: Optional[str] = None
        self._overview: Optional[Dict] = None
@@ -109,19 +111,18 @@ class Domain(ABC):
        self._ensure_fetched(self._research_reports)
        return self._research_reports

-    def _fetch(self, query_url, proxy) -> Dict:
+    def _fetch(self, query_url) -> Dict:
        """
        Fetches data from the given query URL.

        Args:
            query_url (str): The URL used for the data query.
-            proxy (Dict): Proxy settings for the request.

        Returns:
            Dict: The JSON response data from the request.
        """
        params_dict = {"formatted": "true", "withReturns": "true", "lang": "en-US", "region": "US"}
-        result = self._data.get_raw_json(query_url, user_agent_headers=self._data.user_agent_headers, params=params_dict, proxy=proxy)
+        result = self._data.get_raw_json(query_url, params=params_dict)
        return result

    def _parse_and_assign_common(self, data) -> None:
@@ -194,4 +195,4 @@ class Domain(ABC):
            attribute: The attribute to check and potentially fetch.
        """
        if attribute is None:
-            self._fetch_and_parse()
+            self._fetch_and_parse()
--- a/yfinance/domain/industry.py
+++ b/yfinance/domain/industry.py
@@ -5,20 +5,24 @@ import pandas as _pd

 from .domain import Domain, _QUERY_URL_
 from .. import utils
+from ..data import YfData
+from ..const import _SENTINEL_

 class Industry(Domain):
    """
    Represents an industry within a sector.
    """

-    def __init__(self, key, session=None, proxy=None):
+    def __init__(self, key, session=None, proxy=_SENTINEL_):
        """
        Args:
            key (str): The key identifier for the industry.
            session (optional): The session to use for requests.
-            proxy (optional): The proxy to use for requests.
        """
-        super(Industry, self).__init__(key, session, proxy)
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            YfData(session=session, proxy=proxy)
+        super(Industry, self).__init__(key, session)
        self._query_url = f'{_QUERY_URL_}/industries/{self._key}'

        self._sector_key = None
@@ -129,7 +133,7 @@ class Industry(Domain):
        result = None
        
        try:
-            result = self._fetch(self._query_url, self.proxy)
+            result = self._fetch(self._query_url)
            data = result['data']
            self._parse_and_assign_common(data)

@@ -145,4 +149,4 @@ class Industry(Domain):
            logger.debug("Got response: ")
            logger.debug("-------------")
            logger.debug(f" {result}")
-            logger.debug("-------------")
+            logger.debug("-------------")
--- a/yfinance/domain/market.py
+++ b/yfinance/domain/market.py
@@ -0,0 +1,103 @@
+import datetime as dt
+
+from ..data import YfData
+from ..data import utils
+from ..const import _QUERY1_URL_, _SENTINEL_
+import json as _json
+
+class Market:
+    def __init__(self, market:'str', session=None, proxy=_SENTINEL_, timeout=30):
+        self.market = market
+        self.session = session
+        self.timeout = timeout
+
+        self._data = YfData(session=self.session)
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
+        self._logger = utils.get_yf_logger()
+        
+        self._status = None
+        self._summary = None
+
+    def _fetch_json(self, url, params):
+        data = self._data.cache_get(url=url, params=params, timeout=self.timeout)
+        if data is None or "Will be right back" in data.text:
+            raise RuntimeError("*** YAHOO! FINANCE IS CURRENTLY DOWN! ***\n"
+                               "Our engineers are working quickly to resolve "
+                               "the issue. Thank you for your patience.")
+        try:
+            return data.json()
+        except _json.JSONDecodeError:
+            self._logger.error(f"{self.market}: Failed to retrieve market data and recieved faulty data.")
+            return {}
+        
+    def _parse_data(self):
+        # Fetch both to ensure they are at the same time
+        if (self._status is not None) and (self._summary is not None):
+            return
+        
+        self._logger.debug(f"{self.market}: Parsing market data")
+
+        # Summary
+
+        summary_url = f"{_QUERY1_URL_}/v6/finance/quote/marketSummary"
+        summary_fields = ["shortName", "regularMarketPrice", "regularMarketChange", "regularMarketChangePercent"]
+        summary_params = {
+            "fields": ",".join(summary_fields),
+            "formatted": False,
+            "lang": "en-US",
+            "market": self.market
+        }
+
+        status_url = f"{_QUERY1_URL_}/v6/finance/markettime"
+        status_params = {
+            "formatted": True,
+            "key": "finance",
+            "lang": "en-US",
+            "market": self.market
+        }
+
+        self._summary = self._fetch_json(summary_url, summary_params)
+        self._status = self._fetch_json(status_url, status_params)
+
+        try:
+            self._summary = self._summary['marketSummaryResponse']['result']
+            self._summary = {x['exchange']:x for x in self._summary}
+        except Exception as e:
+            self._logger.error(f"{self.market}: Failed to parse market summary")
+            self._logger.debug(f"{type(e)}: {e}")
+
+
+        try:
+            # Unpack
+            self._status = self._status['finance']['marketTimes'][0]['marketTime'][0]
+            self._status['timezone'] = self._status['timezone'][0]
+            del self._status['time']  # redundant
+            try:
+                self._status.update({
+                    "open": dt.datetime.fromisoformat(self._status["open"]),
+                    "close": dt.datetime.fromisoformat(self._status["close"]),
+                    "tz": dt.timezone(dt.timedelta(hours=int(self._status["timezone"]["gmtoffset"]))/1000, self._status["timezone"]["short"])
+                })
+            except Exception as e:
+                self._logger.error(f"{self.market}: Failed to update market status")
+                self._logger.debug(f"{type(e)}: {e}")
+        except Exception as e:
+            self._logger.error(f"{self.market}: Failed to parse market status")
+            self._logger.debug(f"{type(e)}: {e}")
+
+
+
+
+    @property
+    def status(self):
+        self._parse_data()
+        return self._status
+
+
+    @property
+    def summary(self):
+        self._parse_data()
+        return self._summary
--- a/yfinance/domain/sector.py
+++ b/yfinance/domain/sector.py
@@ -1,12 +1,13 @@
 from __future__ import print_function
 from typing import Dict, Optional
 from ..utils import dynamic_docstring, generate_list_table_from_dict
-from ..const import SECTOR_INDUSTY_MAPPING
+from ..const import SECTOR_INDUSTY_MAPPING, _SENTINEL_

 import pandas as _pd

 from .domain import Domain, _QUERY_URL_
 from .. import utils
+from ..data import YfData

 class Sector(Domain):
    """
@@ -14,7 +15,7 @@ class Sector(Domain):
    such as top ETFs, top mutual funds, and industry data.
    """

-    def __init__(self, key, session=None, proxy=None):
+    def __init__(self, key, session=None, proxy=_SENTINEL_):
        """
        Args:
            key (str): The key representing the sector.
@@ -26,7 +27,11 @@ class Sector(Domain):
            :attr:`Sector.industries <yfinance.Sector.industries>`
                Map of sector and industry
        """
-        super(Sector, self).__init__(key, session, proxy)
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            YfData(session=session, proxy=proxy)
+
+        super(Sector, self).__init__(key, session)
        self._query_url: str = f'{_QUERY_URL_}/sectors/{self._key}'
        self._top_etfs: Optional[Dict] = None
        self._top_mutual_funds: Optional[Dict] = None
@@ -133,7 +138,7 @@ class Sector(Domain):
        result = None
        
        try:
-            result = self._fetch(self._query_url, self.proxy)
+            result = self._fetch(self._query_url)
            data = result['data']
            self._parse_and_assign_common(data)

@@ -147,4 +152,4 @@ class Sector(Domain):
            logger.debug("Got response: ")
            logger.debug("-------------")
            logger.debug(f" {result}")
-            logger.debug("-------------")
+            logger.debug("-------------")
--- a/yfinance/exceptions.py
+++ b/yfinance/exceptions.py
@@ -44,4 +44,10 @@ class YFInvalidPeriodError(YFException):
        self.ticker = ticker
        self.invalid_period = invalid_period
        self.valid_ranges = valid_ranges
-        super().__init__(f"{self.ticker}: Period '{invalid_period}' is invalid, must be one of {valid_ranges}")
+        super().__init__(f"{self.ticker}: Period '{invalid_period}' is invalid, "
+                         f"must be of the format {valid_ranges}, etc.")
+
+
+class YFRateLimitError(YFException):
+    def __init__(self):
+        super().__init__("Too Many Requests. Rate limited. Try after a while.")
--- a/yfinance/live.py
+++ b/yfinance/live.py
@@ -0,0 +1,335 @@
+import asyncio
+import base64
+import json
+from typing import List, Optional, Callable
+
+from websockets.sync.client import connect as sync_connect
+from websockets.asyncio.client import connect as async_connect
+
+from yfinance import utils
+from yfinance.pricing_pb2 import PricingData
+from google.protobuf.json_format import MessageToDict
+
+
+class BaseWebSocket:
+    def __init__(self, url: str = "wss://streamer.finance.yahoo.com/?version=2", verbose=True):
+        self.url = url
+        self.verbose = verbose
+        self.logger = utils.get_yf_logger()
+        self._ws = None
+        self._subscriptions = set()
+        self._subscription_interval = 15  # seconds
+
+    def _decode_message(self, base64_message: str) -> dict:
+        try:
+            decoded_bytes = base64.b64decode(base64_message)
+            pricing_data = PricingData()
+            pricing_data.ParseFromString(decoded_bytes)
+            return MessageToDict(pricing_data, preserving_proto_field_name=True)
+        except Exception as e:
+            self.logger.error("Failed to decode message: %s", e, exc_info=True)
+            if self.verbose:
+                print("Failed to decode message: %s", e)
+            return {
+                'error': str(e),
+                'raw_base64': base64_message
+            }
+
+
+class AsyncWebSocket(BaseWebSocket):
+    """
+    Asynchronous WebSocket client for streaming real time pricing data.
+    """
+
+    def __init__(self, url: str = "wss://streamer.finance.yahoo.com/?version=2", verbose=True):
+        """
+        Initialize the AsyncWebSocket client.
+
+        Args:
+            url (str): The WebSocket server URL. Defaults to Yahoo Finance's WebSocket URL.
+            verbose (bool): Flag to enable or disable print statements. Defaults to True.
+        """
+        super().__init__(url, verbose)
+        self._message_handler = None  # Callable to handle messages
+        self._heartbeat_task = None  # Task to send heartbeat subscribe
+
+    async def _connect(self):
+        try:
+            if self._ws is None:
+                self._ws = await async_connect(self.url)
+                self.logger.info("Connected to WebSocket.")
+                if self.verbose:
+                    print("Connected to WebSocket.")
+        except Exception as e:
+            self.logger.error("Failed to connect to WebSocket: %s", e, exc_info=True)
+            if self.verbose:
+                print(f"Failed to connect to WebSocket: {e}")
+            self._ws = None
+            raise
+
+    async def _periodic_subscribe(self):
+        while True:
+            try:
+                await asyncio.sleep(self._subscription_interval)
+
+                if self._subscriptions:
+                    message = {"subscribe": list(self._subscriptions)}
+                    await self._ws.send(json.dumps(message))
+
+                    if self.verbose:
+                        print(f"Heartbeat subscription sent for symbols: {self._subscriptions}")
+            except Exception as e:
+                self.logger.error("Error in heartbeat subscription: %s", e, exc_info=True)
+                if self.verbose:
+                    print(f"Error in heartbeat subscription: {e}")
+                break
+
+    async def subscribe(self, symbols: str | List[str]):
+        """
+        Subscribe to a stock symbol or a list of stock symbols.
+
+        Args:
+            symbols (str | List[str]): Stock symbol(s) to subscribe to.
+        """
+        await self._connect()
+
+        if isinstance(symbols, str):
+            symbols = [symbols]
+
+        self._subscriptions.update(symbols)
+
+        message = {"subscribe": list(self._subscriptions)}
+        await self._ws.send(json.dumps(message))
+
+        # Start heartbeat subscription task
+        if self._heartbeat_task is None:
+            self._heartbeat_task = asyncio.create_task(self._periodic_subscribe())
+
+        self.logger.info(f"Subscribed to symbols: {symbols}")
+        if self.verbose:
+            print(f"Subscribed to symbols: {symbols}")
+
+    async def unsubscribe(self, symbols: str | List[str]):
+        """
+        Unsubscribe from a stock symbol or a list of stock symbols.
+
+        Args:
+            symbols (str | List[str]): Stock symbol(s) to unsubscribe from.
+        """
+        await self._connect()
+
+        if isinstance(symbols, str):
+            symbols = [symbols]
+
+        self._subscriptions.difference_update(symbols)
+
+        message = {"unsubscribe": symbols}
+        await self._ws.send(json.dumps(message))
+
+        self.logger.info(f"Unsubscribed from symbols: {symbols}")
+        if self.verbose:
+            print(f"Unsubscribed from symbols: {symbols}")
+
+    async def listen(self, message_handler=None):
+        """
+        Start listening to messages from the WebSocket server.
+
+        Args:
+            message_handler (Optional[Callable[[dict], None]]): Optional function to handle received messages.
+        """
+        await self._connect()
+        self._message_handler = message_handler
+
+        self.logger.info("Listening for messages...")
+        if self.verbose:
+            print("Listening for messages...")
+
+        # Start heartbeat subscription task
+        if self._heartbeat_task is None:
+            self._heartbeat_task = asyncio.create_task(self._periodic_subscribe())
+
+        while True:
+            try:
+                async for message in self._ws:
+                    message_json = json.loads(message)
+                    encoded_data = message_json.get("message", "")
+                    decoded_message = self._decode_message(encoded_data)
+
+                    if self._message_handler:
+                        try:
+                            if asyncio.iscoroutinefunction(self._message_handler):
+                                await self._message_handler(decoded_message)
+                            else:
+                                self._message_handler(decoded_message)
+                        except Exception as handler_exception:
+                            self.logger.error("Error in message handler: %s", handler_exception, exc_info=True)
+                            if self.verbose:
+                                print("Error in message handler:", handler_exception)
+                    else:
+                        print(decoded_message)
+
+            except (KeyboardInterrupt, asyncio.CancelledError):
+                self.logger.info("WebSocket listening interrupted. Closing connection...")
+                if self.verbose:
+                    print("WebSocket listening interrupted. Closing connection...")
+                await self.close()
+                break
+
+            except Exception as e:
+                self.logger.error("Error while listening to messages: %s", e, exc_info=True)
+                if self.verbose:
+                    print("Error while listening to messages: %s", e)
+
+                # Attempt to reconnect if connection drops
+                self.logger.info("Attempting to reconnect...")
+                if self.verbose:
+                    print("Attempting to reconnect...")
+                await asyncio.sleep(3)  # backoff
+                await self._connect()
+
+    async def close(self):
+        """Close the WebSocket connection."""
+        if self._heartbeat_task:
+            self._heartbeat_task.cancel()
+
+        if self._ws is not None:  # and not self._ws.closed:
+            await self._ws.close()
+            self.logger.info("WebSocket connection closed.")
+            if self.verbose:
+                print("WebSocket connection closed.")
+
+    async def __aenter__(self):
+        await self._connect()
+        return self
+
+    async def __aexit__(self, exc_type, exc_value, traceback):
+        await self.close()
+
+
+class WebSocket(BaseWebSocket):
+    """
+    Synchronous WebSocket client for streaming real time pricing data.
+    """
+
+    def __init__(self, url: str = "wss://streamer.finance.yahoo.com/?version=2", verbose=True):
+        """
+        Initialize the WebSocket client.
+
+        Args:
+            url (str): The WebSocket server URL. Defaults to Yahoo Finance's WebSocket URL.
+            verbose (bool): Flag to enable or disable print statements. Defaults to True.
+        """
+        super().__init__(url, verbose)
+
+    def _connect(self):
+        try:
+            if self._ws is None:
+                self._ws = sync_connect(self.url)
+                self.logger.info("Connected to WebSocket.")
+                if self.verbose:
+                    print("Connected to WebSocket.")
+        except Exception as e:
+            self.logger.error("Failed to connect to WebSocket: %s", e, exc_info=True)
+            if self.verbose:
+                print(f"Failed to connect to WebSocket: {e}")
+            self._ws = None
+            raise
+
+    def subscribe(self, symbols: str | List[str]):
+        """
+        Subscribe to a stock symbol or a list of stock symbols.
+
+        Args:
+            symbols (str | List[str]): Stock symbol(s) to subscribe to.
+        """
+        self._connect()
+
+        if isinstance(symbols, str):
+            symbols = [symbols]
+
+        self._subscriptions.update(symbols)
+
+        message = {"subscribe": list(self._subscriptions)}
+        self._ws.send(json.dumps(message))
+
+        self.logger.info(f"Subscribed to symbols: {symbols}")
+        if self.verbose:
+            print(f"Subscribed to symbols: {symbols}")
+
+    def unsubscribe(self, symbols: str | List[str]):
+        """
+        Unsubscribe from a stock symbol or a list of stock symbols.
+
+        Args:
+            symbols (str | List[str]): Stock symbol(s) to unsubscribe from.
+        """
+        self._connect()
+
+        if isinstance(symbols, str):
+            symbols = [symbols]
+
+        self._subscriptions.difference_update(symbols)
+
+        message = {"unsubscribe": symbols}
+        self._ws.send(json.dumps(message))
+
+        self.logger.info(f"Unsubscribed from symbols: {symbols}")
+        if self.verbose:
+            print(f"Unsubscribed from symbols: {symbols}")
+
+    def listen(self, message_handler: Optional[Callable[[dict], None]] = None):
+        """
+        Start listening to messages from the WebSocket server.
+
+        Args:
+            message_handler (Optional[Callable[[dict], None]]): Optional function to handle received messages.
+        """
+        self._connect()
+
+        self.logger.info("Listening for messages...")
+        if self.verbose:
+            print("Listening for messages...")
+
+        while True:
+            try:
+                message = self._ws.recv()
+                message_json = json.loads(message)
+                encoded_data = message_json.get("message", "")
+                decoded_message = self._decode_message(encoded_data)
+
+                if message_handler:
+                    try:
+                        message_handler(decoded_message)
+                    except Exception as handler_exception:
+                        self.logger.error("Error in message handler: %s", handler_exception, exc_info=True)
+                        if self.verbose:
+                            print("Error in message handler:", handler_exception)
+                else:
+                    print(decoded_message)
+
+            except KeyboardInterrupt:
+                if self.verbose:
+                    print("Received keyboard interrupt.")
+                self.close()
+                break
+
+            except Exception as e:
+                self.logger.error("Error while listening to messages: %s", e, exc_info=True)
+                if self.verbose:
+                    print("Error while listening to messages: %s", e)
+                break
+
+    def close(self):
+        """Close the WebSocket connection."""
+        if self._ws is not None:
+            self._ws.close()
+            self.logger.info("WebSocket connection closed.")
+            if self.verbose:
+                print("WebSocket connection closed.")
+
+    def __enter__(self):
+        self._connect()
+        return self
+
+    def __exit__(self, exc_type, exc_value, traceback):
+        self.close()
--- a/yfinance/lookup.py
+++ b/yfinance/lookup.py
@@ -0,0 +1,224 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+#
+# yfinance - market data downloader
+# https://github.com/ranaroussi/yfinance
+#
+# Copyright 2017-2019 Ran Aroussi
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import json as _json
+
+import pandas as pd
+
+from . import utils
+from .const import _QUERY1_URL_, _SENTINEL_
+from .data import YfData
+from .exceptions import YFException
+
+LOOKUP_TYPES = ["all", "equity", "mutualfund", "etf", "index", "future", "currency", "cryptocurrency"]
+
+
+class Lookup:
+    """
+    Fetches quote (ticker) lookups from Yahoo Finance.
+
+    :param query: The search query for financial data lookup.
+    :type query: str
+    :param session: Custom HTTP session for requests (default None).
+    :param proxy: Proxy settings for requests (default None).
+    :param timeout: Request timeout in seconds (default 30).
+    :param raise_errors: Raise exceptions on error (default True).
+    """
+
+    def __init__(self, query: str, session=None, proxy=None, timeout=30, raise_errors=True):
+        self.session = session
+        self._data = YfData(session=self.session)
+
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
+        self.query = query
+
+        self.timeout = timeout
+        self.raise_errors = raise_errors
+
+        self._logger = utils.get_yf_logger()
+
+        self._cache = {}
+
+    def _fetch_lookup(self, lookup_type="all", count=25) -> dict:
+        cache_key = (lookup_type, count)
+        if cache_key in self._cache:
+            return self._cache[cache_key]
+
+        url = f"{_QUERY1_URL_}/v1/finance/lookup"
+        params = {
+            "query": self.query,
+            "type": lookup_type,
+            "start": 0,
+            "count": count,
+            "formatted": False,
+            "fetchPricingData": True,
+            "lang": "en-US",
+            "region": "US"
+        }
+
+        self._logger.debug(f'GET Lookup for ticker ({self.query}) with parameters: {str(dict(params))}')
+
+        data = self._data.get(url=url, params=params, timeout=self.timeout)
+        if data is None or "Will be right back" in data.text:
+            raise RuntimeError("*** YAHOO! FINANCE IS CURRENTLY DOWN! ***\n"
+                               "Our engineers are working quickly to resolve "
+                               "the issue. Thank you for your patience.")
+        try:
+            data = data.json()
+        except _json.JSONDecodeError:
+            self._logger.error(f"{self.query}: Failed to retrieve lookup results and received faulty response instead.")
+            data = {}
+
+        # Error returned
+        if data.get("finance", {}).get("error", {}):
+            raise YFException(data.get("finance", {}).get("error", {}))
+
+        self._cache[cache_key] = data
+        return data
+
+    @staticmethod
+    def _parse_response(response: dict) -> pd.DataFrame:
+        finance = response.get("finance", {})
+        result = finance.get("result", [])
+        result = result[0] if len(result) > 0 else {}
+        documents = result.get("documents", [])
+        df = pd.DataFrame(documents)
+        if "symbol" not in df.columns:
+            return pd.DataFrame()
+        return df.set_index("symbol")
+
+    def _get_data(self, lookup_type: str, count: int = 25) -> pd.DataFrame:
+        return self._parse_response(self._fetch_lookup(lookup_type, count))
+
+    def get_all(self, count=25) -> pd.DataFrame:
+        """
+        Returns all available financial instruments.
+
+        :param count: The number of results to retrieve.
+        :type count: int
+        """
+        return self._get_data("all", count)
+
+    def get_stock(self, count=25) -> pd.DataFrame:
+        """
+        Returns stock related financial instruments.
+
+        :param count: The number of results to retrieve.
+        :type count: int
+        """
+        return self._get_data("equity", count)
+
+    def get_mutualfund(self, count=25) -> pd.DataFrame:
+        """
+        Returns mutual funds related financial instruments.
+
+        :param count: The number of results to retrieve.
+        :type count: int
+        """
+        return self._get_data("mutualfund", count)
+
+    def get_etf(self, count=25) -> pd.DataFrame:
+        """
+        Returns ETFs related financial instruments.
+
+        :param count: The number of results to retrieve.
+        :type count: int
+        """
+        return self._get_data("etf", count)
+
+    def get_index(self, count=25) -> pd.DataFrame:
+        """
+        Returns Indices related financial instruments.
+
+        :param count: The number of results to retrieve.
+        :type count: int
+        """
+        return self._get_data("index", count)
+
+    def get_future(self, count=25) -> pd.DataFrame:
+        """
+        Returns Futures related financial instruments.
+
+        :param count: The number of results to retrieve.
+        :type count: int
+        """
+        return self._get_data("future", count)
+
+    def get_currency(self, count=25) -> pd.DataFrame:
+        """
+        Returns Currencies related financial instruments.
+
+        :param count: The number of results to retrieve.
+        :type count: int
+        """
+        return self._get_data("currency", count)
+
+    def get_cryptocurrency(self, count=25) -> pd.DataFrame:
+        """
+        Returns Cryptocurrencies related financial instruments.
+
+        :param count: The number of results to retrieve.
+        :type count: int
+        """
+        return self._get_data("cryptocurrency", count)
+
+    @property
+    def all(self) -> pd.DataFrame:
+        """Returns all available financial instruments."""
+        return self._get_data("all")
+
+    @property
+    def stock(self) -> pd.DataFrame:
+        """Returns stock related financial instruments."""
+        return self._get_data("equity")
+
+    @property
+    def mutualfund(self) -> pd.DataFrame:
+        """Returns mutual funds related financial instruments."""
+        return self._get_data("mutualfund")
+
+    @property
+    def etf(self) -> pd.DataFrame:
+        """Returns ETFs related financial instruments."""
+        return self._get_data("etf")
+
+    @property
+    def index(self) -> pd.DataFrame:
+        """Returns Indices related financial instruments."""
+        return self._get_data("index")
+
+    @property
+    def future(self) -> pd.DataFrame:
+        """Returns Futures related financial instruments."""
+        return self._get_data("future")
+
+    @property
+    def currency(self) -> pd.DataFrame:
+        """Returns Currencies related financial instruments."""
+        return self._get_data("currency")
+
+    @property
+    def cryptocurrency(self) -> pd.DataFrame:
+        """Returns Cryptocurrencies related financial instruments."""
+        return self._get_data("cryptocurrency")
--- a/yfinance/multi.py
+++ b/yfinance/multi.py
@@ -28,17 +28,18 @@ from typing import Union

 import multitasking as _multitasking
 import pandas as _pd
+from curl_cffi import requests

 from . import Ticker, utils
 from .data import YfData
 from . import shared
-
+from .const import _SENTINEL_

@utils.log_indent_decorator
 def download(tickers, start=None, end=None, actions=False, threads=True,
-             ignore_tz=None, group_by='column', auto_adjust=False, back_adjust=False,
+             ignore_tz=None, group_by='column', auto_adjust=None, back_adjust=False,
             repair=False, keepna=False, progress=True, period="max", interval="1d",
-             prepost=False, proxy=None, rounding=False, timeout=10, session=None,
+             prepost=False, proxy=_SENTINEL_, rounding=False, timeout=10, session=None,
             multi_level_index=True) -> Union[_pd.DataFrame, None]:
    """
    Download yahoo tickers
@@ -65,7 +66,7 @@ def download(tickers, start=None, end=None, actions=False, threads=True,
            Include Pre and Post market data in results?
            Default is False
        auto_adjust: bool
-            Adjust all OHLC automatically? Default is False
+            Adjust all OHLC automatically? Default is True
        repair: bool
            Detect currency unit 100x mixups and attempt repair
            Default is False
@@ -79,8 +80,6 @@ def download(tickers, start=None, end=None, actions=False, threads=True,
        ignore_tz: bool
            When combining from different timezones, ignore that part of datetime.
            Default depends on interval. Intraday = False. Day+ = True.
-        proxy: str
-            Optional. Proxy server URL scheme. Default is None
        rounding: bool
            Optional. Round values to 2 decimal places?
        timeout: None or float
@@ -92,6 +91,12 @@ def download(tickers, start=None, end=None, actions=False, threads=True,
            Optional. Always return a MultiIndex DataFrame? Default is True
    """
    logger = utils.get_yf_logger()
+    session = session or requests.Session(impersonate="chrome")
+
+    if auto_adjust is None:
+        # Warn users that default has changed to True
+        utils.print_once("YF.download() has changed argument auto_adjust default to True")
+        auto_adjust = True

    if logger.isEnabledFor(logging.DEBUG):
        if threads:
@@ -106,7 +111,7 @@ def download(tickers, start=None, end=None, actions=False, threads=True,

    if ignore_tz is None:
        # Set default value depending on interval
-        if interval[1:] in ['m', 'h']:
+        if interval[-1] in ['m', 'h']:
            # Intraday
            ignore_tz = False
        else:
@@ -122,7 +127,7 @@ def download(tickers, start=None, end=None, actions=False, threads=True,
    for ticker in tickers:
        if utils.is_isin(ticker):
            isin = ticker
-            ticker = utils.get_ticker_by_isin(ticker, proxy, session=session)
+            ticker = utils.get_ticker_by_isin(ticker, session=session)
            shared._ISINS[ticker] = isin
        _tickers_.append(ticker)

@@ -139,7 +144,11 @@ def download(tickers, start=None, end=None, actions=False, threads=True,
    shared._TRACEBACKS = {}

    # Ensure data initialised with session.
-    YfData(session=session)
+    if proxy is not _SENTINEL_:
+        utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+        YfData(session=session, proxy=proxy)
+    else:
+        YfData(session=session)

    # download using threads
    if threads:
@@ -151,7 +160,7 @@ def download(tickers, start=None, end=None, actions=False, threads=True,
                                   start=start, end=end, prepost=prepost,
                                   actions=actions, auto_adjust=auto_adjust,
                                   back_adjust=back_adjust, repair=repair, keepna=keepna,
-                                   progress=(progress and i > 0), proxy=proxy,
+                                   progress=(progress and i > 0),
                                   rounding=rounding, timeout=timeout)
        while len(shared._DFS) < len(tickers):
            _time.sleep(0.01)
@@ -162,7 +171,6 @@ def download(tickers, start=None, end=None, actions=False, threads=True,
                                 start=start, end=end, prepost=prepost,
                                 actions=actions, auto_adjust=auto_adjust,
                                 back_adjust=back_adjust, repair=repair, keepna=keepna,
-                                 proxy=proxy,
                                 rounding=rounding, timeout=timeout)
            if progress:
                shared._PROGRESS_BAR.animate()
@@ -180,7 +188,7 @@ def download(tickers, start=None, end=None, actions=False, threads=True,
        errors = {}
        for ticker in shared._ERRORS:
            err = shared._ERRORS[ticker]
-            err = err.replace(f'{ticker}', '%ticker%')
+            err = err.replace(f'${ticker}: ', '')
            if err not in errors:
                errors[err] = [ticker]
            else:
@@ -192,7 +200,7 @@ def download(tickers, start=None, end=None, actions=False, threads=True,
        tbs = {}
        for ticker in shared._TRACEBACKS:
            tb = shared._TRACEBACKS[ticker]
-            tb = tb.replace(f'{ticker}', '%ticker%')
+            tb = tb.replace(f'${ticker}: ', '')
            if tb not in tbs:
                tbs[tb] = [ticker]
            else:
@@ -253,10 +261,10 @@ def _realign_dfs():
 def _download_one_threaded(ticker, start=None, end=None,
                           auto_adjust=False, back_adjust=False, repair=False,
                           actions=False, progress=True, period="max",
-                           interval="1d", prepost=False, proxy=None,
+                           interval="1d", prepost=False,
                           keepna=False, rounding=False, timeout=10):
    _download_one(ticker, start, end, auto_adjust, back_adjust, repair,
-                         actions, period, interval, prepost, proxy, rounding,
+                         actions, period, interval, prepost, rounding,
                         keepna, timeout)
    if progress:
        shared._PROGRESS_BAR.animate()
@@ -265,7 +273,7 @@ def _download_one_threaded(ticker, start=None, end=None,
 def _download_one(ticker, start=None, end=None,
                  auto_adjust=False, back_adjust=False, repair=False,
                  actions=False, period="max", interval="1d",
-                  prepost=False, proxy=None, rounding=False,
+                  prepost=False, rounding=False,
                  keepna=False, timeout=10):
    data = None
    try:
@@ -273,7 +281,7 @@ def _download_one(ticker, start=None, end=None,
                period=period, interval=interval,
                start=start, end=end, prepost=prepost,
                actions=actions, auto_adjust=auto_adjust,
-                back_adjust=back_adjust, repair=repair, proxy=proxy,
+                back_adjust=back_adjust, repair=repair,
                rounding=rounding, keepna=keepna, timeout=timeout,
                raise_errors=True
        )
--- a/yfinance/pricing.proto
+++ b/yfinance/pricing.proto
@@ -0,0 +1,37 @@
+syntax = "proto3";
+
+message PricingData {
+    string id = 1;
+    float price = 2;
+    sint64 time = 3;
+    string currency = 4;
+    string exchange = 5;
+    int32 quote_type = 6;
+    int32 market_hours = 7;
+    float change_percent = 8;
+    sint64 day_volume = 9;
+    float day_high = 10;
+    float day_low = 11;
+    float change = 12;
+    string short_name = 13;
+    sint64 expire_date = 14;
+    float open_price = 15;
+    float previous_close = 16;
+    float strike_price = 17;
+    string underlying_symbol = 18;
+    sint64 open_interest = 19;
+    sint64 options_type = 20;
+    sint64 mini_option = 21;
+    sint64 last_size = 22;
+    float bid = 23;
+    sint64 bid_size = 24;
+    float ask = 25;
+    sint64 ask_size = 26;
+    sint64 price_hint = 27;
+    sint64 vol_24hr = 28;
+    sint64 vol_all_currencies = 29;
+    string from_currency = 30;
+    string last_market = 31;
+    double circulating_supply = 32;
+    double market_cap = 33;
+}
--- a/yfinance/pricing_pb2.py
+++ b/yfinance/pricing_pb2.py
@@ -0,0 +1,36 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# NO CHECKED-IN PROTOBUF GENCODE
+# source: yfinance/pricing.proto
+# Protobuf Python Version: 5.29.0
+"""Generated protocol buffer code."""
+from google.protobuf import descriptor as _descriptor
+from google.protobuf import descriptor_pool as _descriptor_pool
+from google.protobuf import runtime_version as _runtime_version
+from google.protobuf import symbol_database as _symbol_database
+from google.protobuf.internal import builder as _builder
+_runtime_version.ValidateProtobufRuntimeVersion(
+    _runtime_version.Domain.PUBLIC,
+    5,
+    29,
+    0,
+    '',
+    'yfinance/pricing.proto'
+)
+# @@protoc_insertion_point(imports)
+
+_sym_db = _symbol_database.Default()
+
+
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x16yfinance/pricing.proto\"\x9a\x05\n\x0bPricingData\x12\n\n\x02id\x18\x01 \x01(\t\x12\r\n\x05price\x18\x02 \x01(\x02\x12\x0c\n\x04time\x18\x03 \x01(\x12\x12\x10\n\x08\x63urrency\x18\x04 \x01(\t\x12\x10\n\x08\x65xchange\x18\x05 \x01(\t\x12\x12\n\nquote_type\x18\x06 \x01(\x05\x12\x14\n\x0cmarket_hours\x18\x07 \x01(\x05\x12\x16\n\x0e\x63hange_percent\x18\x08 \x01(\x02\x12\x12\n\nday_volume\x18\t \x01(\x12\x12\x10\n\x08\x64\x61y_high\x18\n \x01(\x02\x12\x0f\n\x07\x64\x61y_low\x18\x0b \x01(\x02\x12\x0e\n\x06\x63hange\x18\x0c \x01(\x02\x12\x12\n\nshort_name\x18\r \x01(\t\x12\x13\n\x0b\x65xpire_date\x18\x0e \x01(\x12\x12\x12\n\nopen_price\x18\x0f \x01(\x02\x12\x16\n\x0eprevious_close\x18\x10 \x01(\x02\x12\x14\n\x0cstrike_price\x18\x11 \x01(\x02\x12\x19\n\x11underlying_symbol\x18\x12 \x01(\t\x12\x15\n\ropen_interest\x18\x13 \x01(\x12\x12\x14\n\x0coptions_type\x18\x14 \x01(\x12\x12\x13\n\x0bmini_option\x18\x15 \x01(\x12\x12\x11\n\tlast_size\x18\x16 \x01(\x12\x12\x0b\n\x03\x62id\x18\x17 \x01(\x02\x12\x10\n\x08\x62id_size\x18\x18 \x01(\x12\x12\x0b\n\x03\x61sk\x18\x19 \x01(\x02\x12\x10\n\x08\x61sk_size\x18\x1a \x01(\x12\x12\x12\n\nprice_hint\x18\x1b \x01(\x12\x12\x10\n\x08vol_24hr\x18\x1c \x01(\x12\x12\x1a\n\x12vol_all_currencies\x18\x1d \x01(\x12\x12\x15\n\rfrom_currency\x18\x1e \x01(\t\x12\x13\n\x0blast_market\x18\x1f \x01(\t\x12\x1a\n\x12\x63irculating_supply\x18  \x01(\x01\x12\x12\n\nmarket_cap\x18! \x01(\x01\x62\x06proto3')
+
+_globals = globals()
+_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
+_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'yfinance.pricing_pb2', _globals)
+if not _descriptor._USE_C_DESCRIPTORS:
+  DESCRIPTOR._loaded_options = None
+  _globals['_PRICINGDATA']._serialized_start=27
+  _globals['_PRICINGDATA']._serialized_end=693
+# @@protoc_insertion_point(module_scope)
--- a/yfinance/scrapers/analysis.py
+++ b/yfinance/scrapers/analysis.py
@@ -3,17 +3,19 @@ import requests

 from yfinance import utils
 from yfinance.data import YfData
-from yfinance.const import quote_summary_valid_modules
+from yfinance.const import quote_summary_valid_modules, _SENTINEL_
 from yfinance.scrapers.quote import _QUOTE_SUMMARY_URL_
 from yfinance.exceptions import YFException

-
 class Analysis:

-    def __init__(self, data: YfData, symbol: str, proxy=None):
+    def __init__(self, data: YfData, symbol: str, proxy=_SENTINEL_):
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            data._set_proxy(proxy)
+
        self._data = data
        self._symbol = symbol
-        self.proxy = proxy

        # In quoteSummary the 'earningsTrend' module contains most of the data below.
        # The format of data is not optimal so each function will process it's part of the data.
@@ -28,6 +30,50 @@ class Analysis:
        self._eps_revisions = None
        self._growth_estimates = None

+    def _get_periodic_df(self, key) -> pd.DataFrame:
+        if self._earnings_trend is None:
+            self._fetch_earnings_trend()
+
+        data = []
+        for item in self._earnings_trend[:4]:
+            row = {'period': item['period']}
+            for k, v in item[key].items():
+                if not isinstance(v, dict) or len(v) == 0:
+                    continue
+                row[k] = v['raw']
+            data.append(row)
+        if len(data) == 0:
+            return pd.DataFrame()
+        return pd.DataFrame(data).set_index('period')
+
+    @property
+    def earnings_estimate(self) -> pd.DataFrame:
+        if self._earnings_estimate is not None:
+            return self._earnings_estimate
+        self._earnings_estimate = self._get_periodic_df('earningsEstimate')
+        return self._earnings_estimate
+
+    @property
+    def revenue_estimate(self) -> pd.DataFrame:
+        if self._revenue_estimate is not None:
+            return self._revenue_estimate
+        self._revenue_estimate = self._get_periodic_df('revenueEstimate')
+        return self._revenue_estimate
+
+    @property
+    def eps_trend(self) -> pd.DataFrame:
+        if self._eps_trend is not None:
+            return self._eps_trend
+        self._eps_trend = self._get_periodic_df('epsTrend')
+        return self._eps_trend
+
+    @property
+    def eps_revisions(self) -> pd.DataFrame:
+        if self._eps_revisions is not None:
+            return self._eps_revisions
+        self._eps_revisions = self._get_periodic_df('epsRevisions')
+        return self._eps_revisions
+
    @property
    def analyst_price_targets(self) -> dict:
        if self._analyst_price_targets is not None:
@@ -40,73 +86,17 @@ class Analysis:
            self._analyst_price_targets = {}
            return self._analyst_price_targets

-        keys = [
-            ('currentPrice', 'current'),
-            ('targetLowPrice', 'low'),
-            ('targetHighPrice', 'high'),
-            ('targetMeanPrice', 'mean'),
-            ('targetMedianPrice', 'median'),
-        ]
+        result = {}
+        for key, value in data.items():
+            if key.startswith('target'):
+                new_key = key.replace('target', '').lower().replace('price', '').strip()
+                result[new_key] = value
+            elif key == 'currentPrice':
+                result['current'] = value

-        self._analyst_price_targets = {newKey: data.get(oldKey, None) for oldKey, newKey in keys}
+        self._analyst_price_targets = result
        return self._analyst_price_targets

-    @property
-    def earnings_estimate(self) -> pd.DataFrame:
-        if self._earnings_estimate is not None:
-            return self._earnings_estimate
-
-        if self._earnings_trend is None:
-            self._fetch_earnings_trend()
-
-        data_dict = {
-            'numberOfAnalysts': [],
-            'avg': [],
-            'low': [],
-            'high': [],
-            'yearAgoEps': [],
-            'growth': []
-        }
-        periods = []
-
-        for item in self._earnings_trend[:4]:
-            periods.append(item['period'])
-            earnings_estimate = item.get('earningsEstimate', {})
-
-            for key in data_dict.keys():
-                data_dict[key].append(earnings_estimate.get(key, {}).get('raw', None))
-
-        self._earnings_estimate = pd.DataFrame(data_dict, index=periods)
-        return self._earnings_estimate
-
-    @property
-    def revenue_estimate(self) -> pd.DataFrame:
-        if self._revenue_estimate is not None:
-            return self._revenue_estimate
-
-        if self._earnings_trend is None:
-            self._fetch_earnings_trend()
-
-        data_dict = {
-            'numberOfAnalysts': [],
-            'avg': [],
-            'low': [],
-            'high': [],
-            'yearAgoRevenue': [],
-            'growth': []
-        }
-        periods = []
-
-        for item in self._earnings_trend[:4]:
-            periods.append(item['period'])
-            revenue_estimate = item.get('revenueEstimate', {})
-
-            for key in data_dict.keys():
-                data_dict[key].append(revenue_estimate.get(key, {}).get('raw', None))
-
-        self._revenue_estimate = pd.DataFrame(data_dict, index=periods)
-        return self._revenue_estimate
-
    @property
    def earnings_history(self) -> pd.DataFrame:
        if self._earnings_history is not None:
@@ -119,77 +109,27 @@ class Analysis:
            self._earnings_history = pd.DataFrame()
            return self._earnings_history

-        data_dict = {
-            'epsEstimate': [],
-            'epsActual': [],
-            'epsDifference': [],
-            'surprisePercent': []
-        }
-        quarters = []
-
+        rows = []
        for item in data:
-            quarters.append(item.get('quarter', {}).get('fmt', None))
+            row = {'quarter': item.get('quarter', {}).get('fmt', None)}
+            for k, v in item.items():
+                if k == 'quarter':
+                    continue
+                if not isinstance(v, dict) or len(v) == 0:
+                    continue
+                row[k] = v.get('raw', None)
+            rows.append(row)
+        if len(data) == 0:
+            return pd.DataFrame()

-            for key in data_dict.keys():
-                data_dict[key].append(item.get(key, {}).get('raw', None))
-        
-        datetime_index = pd.to_datetime(quarters, format='%Y-%m-%d')
-        self._earnings_history = pd.DataFrame(data_dict, index=datetime_index)
+        df = pd.DataFrame(rows)
+        if 'quarter' in df.columns:
+            df['quarter'] = pd.to_datetime(df['quarter'], format='%Y-%m-%d')
+            df.set_index('quarter', inplace=True)
+
+        self._earnings_history = df
        return self._earnings_history

-    @property
-    def eps_trend(self) -> pd.DataFrame:
-        if self._eps_trend is not None:
-            return self._eps_trend
-
-        if self._earnings_trend is None:
-            self._fetch_earnings_trend()
-
-        data_dict = {
-            'current': [],
-            '7daysAgo': [],
-            '30daysAgo': [],
-            '60daysAgo': [],
-            '90daysAgo': []
-        }
-        periods = []
-
-        for item in self._earnings_trend[:4]:
-            periods.append(item['period'])
-            eps_trend = item.get('epsTrend', {})
-
-            for key in data_dict.keys():
-                data_dict[key].append(eps_trend.get(key, {}).get('raw', None))
-
-        self._eps_trend = pd.DataFrame(data_dict, index=periods)
-        return self._eps_trend
-
-    @property
-    def eps_revisions(self) -> pd.DataFrame:
-        if self._eps_revisions is not None:
-            return self._eps_revisions
-
-        if self._earnings_trend is None:
-            self._fetch_earnings_trend()
-
-        data_dict = {
-            'upLast7days': [],
-            'upLast30days': [],
-            'downLast7days': [],
-            'downLast30days': []
-        }
-        periods = []
-
-        for item in self._earnings_trend[:4]:
-            periods.append(item['period'])
-            eps_revisions = item.get('epsRevisions', {})
-
-            for key in data_dict.keys():
-                data_dict[key].append(eps_revisions.get(key, {}).get('raw', None))
-
-        self._eps_revisions = pd.DataFrame(data_dict, index=periods)
-        return self._eps_revisions
-
    @property
    def growth_estimates(self) -> pd.DataFrame:
        if self._growth_estimates is not None:
@@ -205,48 +145,26 @@ class Analysis:
            self._growth_estimates = pd.DataFrame()
            return self._growth_estimates

-        # LTG is not defined in yahoo finance front-end as at 2024-11-14.
-        # But its addition is breaking the retrieval of growth estimates.
-        # Also, support for 5 year seem to have dropped.
-        # TODO: Revisit this change and consider permanently removing these keys.
-        data_dict = {
-            '0q': [],
-            '+1q': [],
-            '0y': [],
-            '+1y': [],
-            # 'LTG': [],
-            # '+5y': [],
-            # '-5y': []
-        }
-
-        # make sure no column is empty
-        dummy_trend = [{'period': key, 'growth': None} for key in data_dict.keys()]
-        industry_trend = trends['industryTrend']['estimates'] or dummy_trend
-        sector_trend = trends['sectorTrend']['estimates'] or dummy_trend
-        index_trend = trends['indexTrend']['estimates'] or dummy_trend
-
+        data = []
        for item in self._earnings_trend:
            period = item['period']
-            if period in data_dict:
-                data_dict[period].append(item.get('growth', {}).get('raw', None))
+            row = {'period': period, 'stockTrend': item.get('growth', {}).get('raw', None)}
+            data.append(row)

-        for item in industry_trend:
-            period = item['period']
-            if period in data_dict:
-                data_dict[period].append(item.get('growth', None))
+        for trend_name, trend_info in trends.items():
+            if trend_info.get('estimates'):
+                for estimate in trend_info['estimates']:
+                    period = estimate['period']
+                    existing_row = next((row for row in data if row['period'] == period), None)
+                    if existing_row:
+                        existing_row[trend_name] = estimate.get('growth')
+                    else:
+                        row = {'period': period, trend_name: estimate.get('growth')}
+                        data.append(row)
+        if len(data) == 0:
+            return pd.DataFrame()

-        for item in sector_trend:
-            period = item['period']
-            if period in data_dict:
-                data_dict[period].append(item.get('growth', None))
-
-        for item in index_trend:
-            period = item['period']
-            if period in data_dict:
-                data_dict[period].append(item.get('growth', None))
-
-        cols = ['stock', 'industry', 'sector', 'index']
-        self._growth_estimates = pd.DataFrame(data_dict, index=cols).T
+        self._growth_estimates = pd.DataFrame(data).set_index('period').dropna(how='all')
        return self._growth_estimates

    # modified version from quote.py
@@ -259,7 +177,7 @@ class Analysis:
            raise YFException("No valid modules provided, see available modules using `valid_modules`")
        params_dict = {"modules": modules, "corsDomain": "finance.yahoo.com", "formatted": "false", "symbol": self._symbol}
        try:
-            result = self._data.get_raw_json(_QUOTE_SUMMARY_URL_ + f"/{self._symbol}", user_agent_headers=self._data.user_agent_headers, params=params_dict, proxy=self.proxy)
+            result = self._data.get_raw_json(_QUOTE_SUMMARY_URL_ + f"/{self._symbol}", params=params_dict)
        except requests.exceptions.HTTPError as e:
            utils.get_yf_logger().error(str(e))
            return None
--- a/yfinance/scrapers/fundamentals.py
+++ b/yfinance/scrapers/fundamentals.py
@@ -10,10 +10,13 @@ from yfinance.exceptions import YFException, YFNotImplementedError

 class Fundamentals:

-    def __init__(self, data: YfData, symbol: str, proxy=None):
+    def __init__(self, data: YfData, symbol: str, proxy=const._SENTINEL_):
+        if proxy is not const._SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            data._set_proxy(proxy)
+
        self._data = data
        self._symbol = symbol
-        self.proxy = proxy

        self._earnings = None
        self._financials = None
@@ -48,40 +51,55 @@ class Financials:
        self._balance_sheet_time_series = {}
        self._cash_flow_time_series = {}

-    def get_income_time_series(self, freq="yearly", proxy=None) -> pd.DataFrame:
+    def get_income_time_series(self, freq="yearly", proxy=const._SENTINEL_) -> pd.DataFrame:
+        if proxy is not const._SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        res = self._income_time_series
        if freq not in res:
-            res[freq] = self._fetch_time_series("income", freq, proxy)
+            res[freq] = self._fetch_time_series("income", freq)
        return res[freq]

-    def get_balance_sheet_time_series(self, freq="yearly", proxy=None) -> pd.DataFrame:
+    def get_balance_sheet_time_series(self, freq="yearly", proxy=const._SENTINEL_) -> pd.DataFrame:
+        if proxy is not const._SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        res = self._balance_sheet_time_series
        if freq not in res:
-            res[freq] = self._fetch_time_series("balance-sheet", freq, proxy)
+            res[freq] = self._fetch_time_series("balance-sheet", freq)
        return res[freq]

-    def get_cash_flow_time_series(self, freq="yearly", proxy=None) -> pd.DataFrame:
+    def get_cash_flow_time_series(self, freq="yearly", proxy=const._SENTINEL_) -> pd.DataFrame:
+        if proxy is not const._SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        res = self._cash_flow_time_series
        if freq not in res:
-            res[freq] = self._fetch_time_series("cash-flow", freq, proxy)
+            res[freq] = self._fetch_time_series("cash-flow", freq)
        return res[freq]

    @utils.log_indent_decorator
-    def _fetch_time_series(self, name, timescale, proxy=None):
+    def _fetch_time_series(self, name, timescale):
        # Fetching time series preferred over scraping 'QuoteSummaryStore',
        # because it matches what Yahoo shows. But for some tickers returns nothing,
        # despite 'QuoteSummaryStore' containing valid data.

        allowed_names = ["income", "balance-sheet", "cash-flow"]
-        allowed_timescales = ["yearly", "quarterly"]
+        allowed_timescales = ["yearly", "quarterly", "trailing"]

        if name not in allowed_names:
            raise ValueError(f"Illegal argument: name must be one of: {allowed_names}")
        if timescale not in allowed_timescales:
            raise ValueError(f"Illegal argument: timescale must be one of: {allowed_timescales}")
+        if timescale == "trailing" and name not in ('income', 'cash-flow'):
+            raise ValueError("Illegal argument: frequency 'trailing'" +
+                             " only available for cash-flow or income data.")

        try:
-            statement = self._create_financials_table(name, timescale, proxy)
+            statement = self._create_financials_table(name, timescale)

            if statement is not None:
                return statement
@@ -89,7 +107,7 @@ class Financials:
            utils.get_yf_logger().error(f"{self._symbol}: Failed to create {name} financials table for reason: {e}")
        return pd.DataFrame()

-    def _create_financials_table(self, name, timescale, proxy):
+    def _create_financials_table(self, name, timescale):
        if name == "income":
            # Yahoo stores the 'income' table internally under 'financials' key
            name = "financials"
@@ -97,12 +115,12 @@ class Financials:
        keys = const.fundamentals_keys[name]

        try:
-            return self.get_financials_time_series(timescale, keys, proxy)
+            return self._get_financials_time_series(timescale, keys)
        except Exception:
            pass

-    def get_financials_time_series(self, timescale, keys: list, proxy=None) -> pd.DataFrame:
-        timescale_translation = {"yearly": "annual", "quarterly": "quarterly"}
+    def _get_financials_time_series(self, timescale, keys: list) -> pd.DataFrame:
+        timescale_translation = {"yearly": "annual", "quarterly": "quarterly", "trailing": "trailing"}
        timescale = timescale_translation[timescale]

        # Step 2: construct url:
@@ -114,7 +132,7 @@ class Financials:
        url += f"&period1={int(start_dt.timestamp())}&period2={int(end.timestamp())}"

        # Step 3: fetch and reshape data
-        json_str = self._data.cache_get(url=url, proxy=proxy).text
+        json_str = self._data.cache_get(url=url).text
        json_data = json.loads(json_str)
        data_raw = json_data["timeseries"]["result"]
        # data_raw = [v for v in data_raw if len(v) > 1] # Discard keys with no data
@@ -145,4 +163,8 @@ class Financials:
        df = df.reindex([k for k in keys if k in df.index])
        df = df[sorted(df.columns, reverse=True)]

+        # Trailing 12 months return only the first column.
+        if (timescale == "trailing"):
+            df = df.iloc[:, [0]]
+
        return df
--- a/yfinance/scrapers/funds.py
+++ b/yfinance/scrapers/funds.py
@@ -1,7 +1,7 @@
 import pandas as pd

 from yfinance.data import YfData
-from yfinance.const import _BASE_URL_
+from yfinance.const import _BASE_URL_, _SENTINEL_
 from yfinance.exceptions import YFDataException
 from yfinance import utils

@@ -17,16 +17,17 @@ class FundsData:
    Notes: 
    - fundPerformance module is not implemented as better data is queryable using history
    """
-    def __init__(self, data: YfData, symbol: str, proxy=None):
+    def __init__(self, data: YfData, symbol: str, proxy=_SENTINEL_):
        """
        Args:
            data (YfData): The YfData object for fetching data.
            symbol (str): The symbol of the fund.
-            proxy (optional): Proxy settings for fetching data.
        """
        self._data = data
        self._symbol = symbol
-        self.proxy = proxy
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
        
        # quoteType
        self._quote_type = None
@@ -165,26 +166,23 @@ class FundsData:
            self._fetch_and_parse()
        return self._sector_weightings

-    def _fetch(self, proxy):
+    def _fetch(self):
        """
        Fetches the raw JSON data from the API.

-        Args:
-            proxy: Proxy settings for fetching data.
-
        Returns:
            dict: The raw JSON data.
        """
        modules = ','.join(["quoteType", "summaryProfile", "topHoldings", "fundProfile"])
        params_dict = {"modules": modules, "corsDomain": "finance.yahoo.com", "symbol": self._symbol, "formatted": "false"}
-        result = self._data.get_raw_json(_QUOTE_SUMMARY_URL_+self._symbol, user_agent_headers=self._data.user_agent_headers, params=params_dict, proxy=proxy)
+        result = self._data.get_raw_json(_QUOTE_SUMMARY_URL_+self._symbol, params=params_dict)
        return result

    def _fetch_and_parse(self) -> None:
        """
        Fetches and parses the data from the API.
        """
-        result = self._fetch(self.proxy)
+        result = self._fetch()
        try:
            data = result["quoteSummary"]["result"][0]
            # check quote type
@@ -334,4 +332,4 @@ class FundsData:
                self._parse_raw_values(_fund_operations_cat.get("annualHoldingsTurnover", pd.NA)),
                self._parse_raw_values(_fund_operations_cat.get("totalNetAssets", pd.NA))
            ]
-        }).set_index("Attributes")
+        }).set_index("Attributes")
--- a/yfinance/scrapers/history.py
+++ b/yfinance/scrapers/history.py
@@ -6,20 +6,23 @@ import pandas as pd
 from math import isclose
 import time as _time
 import bisect
+from curl_cffi import requests

 from yfinance import shared, utils
-from yfinance.const import _BASE_URL_, _PRICE_COLNAMES_
-from yfinance.exceptions import YFInvalidPeriodError, YFPricesMissingError, YFTzMissingError
+from yfinance.const import _BASE_URL_, _PRICE_COLNAMES_, _SENTINEL_
+from yfinance.exceptions import YFInvalidPeriodError, YFPricesMissingError, YFTzMissingError, YFRateLimitError

 class PriceHistory:
-    def __init__(self, data, ticker, tz, session=None, proxy=None):
+    def __init__(self, data, ticker, tz, session=None, proxy=_SENTINEL_):
        self._data = data
        self.ticker = ticker.upper()
        self.tz = tz
-        self.proxy = proxy
-        self.session = session
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+        self.session = session or requests.Session(impersonate="chrome")

-        self._history = None
+        self._history_cache = {}
        self._history_metadata = None
        self._history_metadata_formatted = False

@@ -30,7 +33,7 @@ class PriceHistory:
    def history(self, period="1mo", interval="1d",
                start=None, end=None, prepost=False, actions=True,
                auto_adjust=True, back_adjust=False, repair=False, keepna=False,
-                proxy=None, rounding=False, timeout=10,
+                proxy=_SENTINEL_, rounding=False, timeout=10,
                raise_errors=False) -> pd.DataFrame:
        """
        :Parameters:
@@ -61,8 +64,6 @@ class PriceHistory:
            keepna: bool
                Keep NaN rows returned by Yahoo?
                Default is False
-            proxy: str
-                Optional. Proxy server URL scheme. Default is None
            rounding: bool
                Round values to 2 decimal places?
                Optional. Default is False = precision suggested by Yahoo!
@@ -74,11 +75,14 @@ class PriceHistory:
                If True, then raise errors as Exceptions instead of logging.
        """
        logger = utils.get_yf_logger()
-        proxy = proxy or self.proxy
+
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)

        interval_user = interval
        period_user = period
-        if repair and interval in ['5d', '1wk', '1mo', '3mo']:
+        if repair and interval in ["5d", "1wk", "1mo", "3mo"]:
            # Yahoo's way of adjusting mutiday intervals is fundamentally broken.
            # Have to fetch 1d, adjust, then resample.
            if interval == '5d':
@@ -175,7 +179,6 @@ class PriceHistory:
            data = get_fn(
                url=url,
                params=params,
-                proxy=proxy,
                timeout=timeout
            )
            if "Will be right back" in data.text or data is None:
@@ -184,6 +187,9 @@ class PriceHistory:
                                   "the issue. Thank you for your patience.")

            data = data.json()
+        # Special case for rate limits
+        except YFRateLimitError:
+            raise
        except Exception:
            if raise_errors:
                raise
@@ -229,10 +235,9 @@ class PriceHistory:
        elif "chart" not in data or data["chart"]["result"] is None or not data["chart"]["result"] or not data["chart"]["result"][0]["indicators"]["quote"][0]:
            _exception = YFPricesMissingError(self.ticker, _price_data_debug)
            fail = True
-        elif period is not None and period not in self._history_metadata["validRanges"]:
-            # even if timestamp is in the data, the data doesn't encompass the period requested
-            # User provided a bad period. The minimum should be '1d', but sometimes Yahoo accepts '1h'.
-            _exception = YFInvalidPeriodError(self.ticker, period, self._history_metadata['validRanges'])
+        elif period and period not in self._history_metadata['validRanges'] and not utils.is_valid_period_format(period):
+            # User provided a bad period
+            _exception = YFInvalidPeriodError(self.ticker, period, ", ".join(self._history_metadata['validRanges']))
            fail = True

        if fail:
@@ -247,13 +252,26 @@ class PriceHistory:
                self._reconstruct_start_interval = None
            return utils.empty_df()

+        # Select useful info from metadata
+        quote_type = self._history_metadata["instrumentType"]
+        expect_capital_gains = quote_type in ('MUTUALFUND', 'ETF')
+        tz_exchange = self._history_metadata["exchangeTimezoneName"]
+        currency = self._history_metadata["currency"]
+
+        # Process custom periods
+        if period and period not in self._history_metadata.get("validRanges", []):
+            end = int(_time.time())
+            end_dt = pd.Timestamp(end, unit='s').tz_localize("UTC")
+            start = _datetime.date.fromtimestamp(end)
+            start -= utils._interval_to_timedelta(period)
+            start -= _datetime.timedelta(days=4)
+
        # parse quotes
        quotes = utils.parse_quotes(data["chart"]["result"][0])
        # Yahoo bug fix - it often appends latest price even if after end date
        if end and not quotes.empty:
-            endDt = pd.to_datetime(end, unit='s')
-            if quotes.index[quotes.shape[0] - 1] >= endDt:
-                quotes = quotes.iloc[0:quotes.shape[0] - 1]
+            if quotes.index[-1] >= end_dt.tz_convert('UTC').tz_localize(None):
+                quotes = quotes.drop(quotes.index[-1])
        if quotes.empty:
            msg = f'{self.ticker}: yfinance received OHLC data: EMPTY'
        elif len(quotes) == 1:
@@ -280,12 +298,6 @@ class PriceHistory:
            except Exception:
                pass

-        # Select useful info from metadata
-        quote_type = self._history_metadata["instrumentType"]
-        expect_capital_gains = quote_type in ('MUTUALFUND', 'ETF')
-        tz_exchange = self._history_metadata["exchangeTimezoneName"]
-        currency = self._history_metadata["currency"]
-
        # Note: ordering is important. If you change order, run the tests!
        quotes = utils.set_df_tz(quotes, params["interval"], tz_exchange)
        quotes = utils.fix_Yahoo_dst_issue(quotes, params["interval"])
@@ -318,21 +330,22 @@ class PriceHistory:
            capital_gains = utils.set_df_tz(capital_gains, interval, tz_exchange)
        if start is not None:
            if not quotes.empty:
-                startDt = quotes.index[0].floor('D')
+                start_d = quotes.index[0].floor('D')
                if dividends is not None:
-                    dividends = dividends.loc[startDt:]
+                    dividends = dividends.loc[start_d:]
                if capital_gains is not None:
-                    capital_gains = capital_gains.loc[startDt:]
+                    capital_gains = capital_gains.loc[start_d:]
                if splits is not None:
-                    splits = splits.loc[startDt:]
+                    splits = splits.loc[start_d:]
        if end is not None:
-            endDt = pd.Timestamp(end, unit='s').tz_localize(tz)
+            # -1 because date-slice end is inclusive
+            end_dt_sub1 = end_dt - pd.Timedelta(1)
            if dividends is not None:
-                dividends = dividends[dividends.index < endDt]
+                dividends = dividends[:end_dt_sub1]
            if capital_gains is not None:
-                capital_gains = capital_gains[capital_gains.index < endDt]
+                capital_gains = capital_gains[:end_dt_sub1]
            if splits is not None:
-                splits = splits[splits.index < endDt]
+                splits = splits[:end_dt_sub1]

        # Prepare for combine
        intraday = params["interval"][-1] in ("m", 'h')
@@ -374,7 +387,9 @@ class PriceHistory:
            msg = f'{self.ticker}: OHLC after combining events: {df.index[0]} -> {df.index[-1]}'
        logger.debug(msg)

-        df = utils.fix_Yahoo_returning_live_separate(df, params["interval"], tz_exchange, repair=repair, currency=currency)
+        df, last_trade = utils.fix_Yahoo_returning_live_separate(df, params["interval"], tz_exchange, prepost, repair=repair, currency=currency)
+        if last_trade is not None:
+            self._history_metadata['lastTrade'] = {'Price':last_trade['Close'], "Time":last_trade.name}

        df = df[~df.index.duplicated(keep='first')]  # must do before repair

@@ -392,10 +407,11 @@ class PriceHistory:
            df = self._fix_bad_div_adjust(df, interval, currency)

            # Need the latest/last row to be repaired before 100x/split repair:
-            df_last = self._fix_zeroes(df.iloc[-1:], interval, tz_exchange, prepost)
-            if 'Repaired?' not in df.columns:
-                df['Repaired?'] = False
-            df = pd.concat([df.drop(df.index[-1]), df_last])
+            if not df.empty:
+                df_last = self._fix_zeroes(df.iloc[-1:], interval, tz_exchange, prepost)
+                if 'Repaired?' not in df.columns:
+                    df['Repaired?'] = False
+                df = pd.concat([df.drop(df.index[-1]), df_last])

            df = self._fix_unit_mixups(df, interval, tz_exchange, prepost)
            df = self._fix_bad_stock_splits(df, interval, tz_exchange)
@@ -430,8 +446,6 @@ class PriceHistory:
        else:
            df.index.name = "Date"

-        self._history = df.copy()
-
        # missing rows cleanup
        if not actions:
            df = df.drop(columns=["Dividends", "Stock Splits", "Capital Gains"], errors='ignore')
@@ -456,10 +470,23 @@ class PriceHistory:
            self._reconstruct_start_interval = None
        return df

-    def get_history_metadata(self, proxy=None) -> dict:
-        if self._history_metadata is None:
-            # Request intraday data, because then Yahoo returns exchange schedule.
-            self.history(period="5d", interval="1h", prepost=True, proxy=proxy)
+    def _get_history_cache(self, period="max", interval="1d") -> pd.DataFrame:
+        cache_key = (interval, period)
+        if cache_key in self._history_cache:
+            return self._history_cache[cache_key]
+
+        df = self.history(period=period, interval=interval, prepost=True)
+        self._history_cache[cache_key] = df
+        return df
+
+    def get_history_metadata(self, proxy=_SENTINEL_) -> dict:
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
+        if self._history_metadata is None or 'tradingPeriods' not in self._history_metadata:
+            # Request intraday data, because then Yahoo returns exchange schedule (tradingPeriods).
+            self._get_history_cache(period="5d", interval="1h")

        if self._history_metadata_formatted is False:
            self._history_metadata = utils.format_history_metadata(self._history_metadata)
@@ -467,38 +494,56 @@ class PriceHistory:

        return self._history_metadata

-    def get_dividends(self, proxy=None) -> pd.Series:
-        if self._history is None:
-            self.history(period="max", proxy=proxy)
-        if self._history is not None and "Dividends" in self._history:
-            dividends = self._history["Dividends"]
+    def get_dividends(self, period="max", proxy=_SENTINEL_) -> pd.Series:
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
+        df = self._get_history_cache(period=period)
+        if "Dividends" in df.columns:
+            dividends = df["Dividends"]
            return dividends[dividends != 0]
        return pd.Series()

-    def get_capital_gains(self, proxy=None) -> pd.Series:
-        if self._history is None:
-            self.history(period="max", proxy=proxy)
-        if self._history is not None and "Capital Gains" in self._history:
-            capital_gains = self._history["Capital Gains"]
+    def get_capital_gains(self, period="max", proxy=_SENTINEL_) -> pd.Series:
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
+        df = self._get_history_cache(period=period)
+        if "Capital Gains" in df.columns:
+            capital_gains = df["Capital Gains"]
            return capital_gains[capital_gains != 0]
        return pd.Series()

-    def get_splits(self, proxy=None) -> pd.Series:
-        if self._history is None:
-            self.history(period="max", proxy=proxy)
-        if self._history is not None and "Stock Splits" in self._history:
-            splits = self._history["Stock Splits"]
+    def get_splits(self, period="max", proxy=_SENTINEL_) -> pd.Series:
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
+        df = self._get_history_cache(period=period)
+        if "Stock Splits" in df.columns:
+            splits = df["Stock Splits"]
            return splits[splits != 0]
        return pd.Series()

-    def get_actions(self, proxy=None) -> pd.Series:
-        if self._history is None:
-            self.history(period="max", proxy=proxy)
-        if self._history is not None and "Dividends" in self._history and "Stock Splits" in self._history:
-            action_columns = ["Dividends", "Stock Splits"]
-            if "Capital Gains" in self._history:
-                action_columns.append("Capital Gains")
-            actions = self._history[action_columns]
+    def get_actions(self, period="max", proxy=_SENTINEL_) -> pd.Series:
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
+        df = self._get_history_cache(period=period)
+
+        action_columns = []
+        if "Dividends" in df.columns:
+            action_columns.append("Dividends")
+        if "Stock Splits" in df.columns:
+            action_columns.append("Stock Splits")
+        if "Capital Gains" in df.columns:
+            action_columns.append("Capital Gains")
+
+        if action_columns:
+            actions = df[action_columns]
            return actions[actions != 0].dropna(how='all').fillna(0)
        return pd.Series()

@@ -1295,7 +1340,7 @@ class PriceHistory:

        if df is None or df.empty:
            return df
-        if interval != '1d':
+        if interval in ['1wk', '1mo', '3mo', '1y']:
            return df

        logger = utils.get_yf_logger()
@@ -1605,9 +1650,9 @@ class PriceHistory:
        checks += ['adj_missing', 'adj_exceeds_div', 'div_exceeds_adj']

        div_status_df['phantom'] = False
-        phantom_proximity_threshold = _datetime.timedelta(days=7)
+        phantom_proximity_threshold = _datetime.timedelta(days=17)
        f = div_status_df[['div_too_big', 'div_exceeds_adj']].any(axis=1)
-        if f.any():
+        if f.any() and len(div_status_df) > 1:
            # One/some of these may be phantom dividends. Clue is if another correct dividend is very close
            indices = np.where(f)[0]
            dts_to_check = div_status_df.index[f]
@@ -1616,37 +1661,24 @@ class PriceHistory:
                div_dt = div.name
                phantom_dt = None
                if i > 0:
-                    prev_div = div_status_df.iloc[i-1]
-                    ratio1 = (div['div']/currency_divide) / prev_div['div']
-                    ratio2 = div['div'] / prev_div['div']
-                    divergence = min(abs(ratio1-1.0), abs(ratio2-1.0))
-                    if abs(div_dt-prev_div.name) <= phantom_proximity_threshold and not prev_div['phantom'] and divergence < 0.01:
-                        if prev_div.name in dts_to_check:
-                            # Both this and previous are anomalous, so mark smallest drop as phantom
-                            drop = div['drop']
-                            drop_prev = prev_div['drop']
-                            if drop > 1.5*drop_prev:
-                                phantom_dt = prev_div.name
-                            else:
-                                phantom_dt = div_dt
-                        else:
-                            phantom_dt = div_dt
-                elif i < len(div_status_df)-1:
-                    next_div = div_status_df.iloc[i+1]
-                    ratio1 = (div['div']/currency_divide) / next_div['div']
-                    ratio2 = div['div'] / next_div['div']
-                    divergence = min(abs(ratio1-1.0), abs(ratio2-1.0))
-                    if abs(div_dt-next_div.name) <= phantom_proximity_threshold and divergence < 0.01:
-                        if next_div.name in dts_to_check:
-                            # Both this and previous are anomalous, so mark smallest drop as phantom
-                            drop = div['drop']
-                            drop_next = next_div['drop']
-                            if drop > 1.5*drop_next:
-                                phantom_dt = next_div.name
-                            else:
-                                phantom_dt = div_dt
+                    other_div = div_status_df.iloc[i-1]
+                else:
+                    other_div = div_status_df.iloc[i+1]
+                ratio1 = (div['div']/currency_divide) / other_div['div']
+                ratio2 = div['div'] / other_div['div']
+                divergence = min(abs(ratio1-1.0), abs(ratio2-1.0))
+                if abs(div_dt-other_div.name) <= phantom_proximity_threshold and not other_div['phantom'] and divergence < 0.01:
+                    if other_div.name in dts_to_check:
+                        # Both this and previous are anomalous, so mark smallest drop as phantom
+                        drop = div['drop']
+                        drop_next = other_div['drop']
+                        if drop > 1.5*drop_next:
+                            phantom_dt = other_div.name
                        else:
                            phantom_dt = div_dt
+                    else:
+                        phantom_dt = div_dt
+
                if phantom_dt:
                    div_status_df.loc[phantom_dt, 'phantom'] = True
                    for c in checks:
@@ -1745,7 +1777,7 @@ class PriceHistory:
            lookahead_idx = bisect.bisect_left(df2.index, lookahead_date)
            lookahead_idx = min(lookahead_idx, len(df2)-1)
            # In rare cases, the price dropped 1 day before dividend (DVD.OL @ 2024-05-15)
-            lookback_idx = div_idx-2 if div_idx > 1 else div_idx-1
+            lookback_idx = max(0, div_idx-14)
            # Check for bad stock splits in the lookahead period - 
            # if present, reduce lookahead to before.
            future_changes = df2['Close'].iloc[div_idx:lookahead_idx+1].pct_change()
@@ -1767,8 +1799,6 @@ class PriceHistory:
                adjDeltas = x['Adj Low'].iloc[1:].to_numpy() - x['Adj Close'].iloc[:-1].to_numpy()
                adjDeltas = np.append([0.0], adjDeltas)
                x['adjDelta'] = adjDeltas
-                for i in np.where(x['Dividends']>0)[0]:
-                    x.loc[x.index[i], 'adjDelta'] += x['Dividends'].iloc[i]*x['Adj'].iloc[i]
                deltas = x[['delta', 'adjDelta']]
                if div_pct > 0.05 and div_pct < 1.0:
                    adjDiv = div * x['Adj'].iloc[0]
@@ -1903,7 +1933,7 @@ class PriceHistory:
                pct_fail = n_fail / n
                if c == 'div_too_big':
                    true_threshold = 1.0
-                    fals_threshold = 0.2
+                    fals_threshold = 0.25

                    if 'div_date_wrong' in cluster.columns and (cluster[c] == cluster['div_date_wrong']).all():
                        continue
@@ -1982,10 +2012,42 @@ class PriceHistory:
                if c == 'div_date_wrong':
                    # Fine, these should be rare
                    continue
-                if c == 'div_pre_split':
+                if c in ['div_pre_split', 'div_too_big_and_pre_split']:
                    # Fine, these should be rare
                    continue

+        if 'div_too_big' in checks and 'div_exceeds_adj' in checks:
+            c = "adj_too_small"
+            div_status_df[c] = False
+            for i in range(len(div_status_df)):
+                dt = div_status_df.index[i]
+                row = div_status_df.iloc[i]
+                if row['div_too_big'] and row['div_exceeds_adj']:
+                    # Check if div_too_big AND adj-too-small-for-prices
+                    div_yield = row['div']
+                    pct = row['%']
+                    close = div_yield/pct
+                    adj_present = row['present adj']
+                    implied_div_yield = (1-adj_present)*close
+                    ratio = div_yield/implied_div_yield
+                    also_correct_adj = abs(ratio-(currency_divide*currency_divide)) < currency_divide
+                    if also_correct_adj:
+                        div_status_df.loc[dt, c] = True
+            if not div_status_df[c].any():
+                div_status_df = div_status_df.drop(c, axis=1)
+            else:
+                checks.append(c)
+
+        if 'div_too_big_and_pre_split' in div_status_df.columns:
+            for c in ['div_too_big', 'div_pre_split']:
+                if c in div_status_df:
+                    div_status_df[c] = div_status_df[c] | div_status_df['div_too_big_and_pre_split']
+                else:
+                    div_status_df[c] = div_status_df['div_too_big_and_pre_split']
+                    checks.append(c)
+            div_status_df = div_status_df.drop('div_too_big_and_pre_split', axis=1)
+            checks.remove('div_too_big_and_pre_split')
+
        div_status_df = div_status_df.sort_index()

        # Discard dividends with no problems
@@ -2017,6 +2079,7 @@ class PriceHistory:
                # div_too_small_and_pre_split = 'div_too_small_and_pre_split' in row and row['div_too_small_and_pre_split']  # not happened yet
                # div_too_big_and_pre_split = 'div_too_big_and_pre_split' in row and row['div_too_big_and_pre_split']  # not happened yet
                div_date_wrong = 'div_date_wrong' in row and row['div_date_wrong']
+                adj_too_small = 'adj_too_small' in row and row['adj_too_small']
                n_failed_checks = np.sum([row[c] for c in checks if c in row])

                if div_too_big and adj_exceeds_prices and n_failed_checks == 2:
@@ -2182,23 +2245,13 @@ class PriceHistory:
                        cluster.loc[dt, 'Fixed?'] = True

                    elif div_too_big and div_exceeds_adj:
+                        div = row['div']
+                        close = div/row['%']
+                        adj_present = row['present adj']
                        # Adj Close is correct, just need to fix Dividend.
                        # Probably just a currency unit mixup.
                        df2.loc[dt, 'Dividends'] /= currency_divide
-                        k = 'too-big div'
-                        if 'FX was repaired' in row and row['FX was repaired']:
-                            # Complication: not just a currency unit mixup, but
-                            # mixed up the local currency with $. So need to 
-                            # recalculate adjustment.
-                            msg = None
-                            div_adj = 1.0 - (row['%']/currency_divide)
-                            adj_correction = div_adj / row['present adj']
-                            df2.loc[    :enddt, 'Adj Close'] *= adj_correction
-                            df2.loc[    :enddt, 'Repaired?'] = True
-                            df2_nan.loc[:enddt, 'Adj Close'] *= adj_correction
-                            df2_nan.loc[:enddt, 'Repaired?'] = True
-                            # Currently not logging this FX-fix event, since I refactored fixing.
-                            k += " and FX mixup"
+                        k = 'div-too-big'
                        div_repairs.setdefault(k, []).append(dt)
                        cluster.loc[dt, 'Fixed?'] = True

@@ -2218,6 +2271,68 @@ class PriceHistory:
                        df2_nan.loc[:enddt, 'Repaired?'] = True
                        cluster.loc[dt, 'Fixed?'] = True

+                    elif div_too_small and adj_exceeds_div:
+                        # Adj Close is correct, just need to fix Dividend.
+                        # Probably just a currency unit mixup.
+                        df2.loc[dt, 'Dividends'] *= currency_divide
+                        k = 'too-small div'
+                        if 'FX was repaired' in row and row['FX was repaired']:
+                            # Complication: not just a currency unit mixup, but
+                            # mixed up the local currency with $. So need to 
+                            # recalculate adjustment.
+                            msg = None
+                            div_adj = 1.0 - (row['%']*currency_divide)
+                            adj_correction = div_adj / row['present adj']
+                            df2.loc[    :enddt, 'Adj Close'] *= adj_correction
+                            df2.loc[    :enddt, 'Repaired?'] = True
+                            df2_nan.loc[:enddt, 'Adj Close'] *= adj_correction
+                            df2_nan.loc[:enddt, 'Repaired?'] = True
+                            # Currently not logging this FX-fix event, since I refactored fixing.
+                            k += " and FX mixup"
+                        div_repairs.setdefault(k, []).append(dt)
+                        cluster.loc[dt, 'Fixed?'] = True
+
+                elif n_failed_checks == 3:
+                    if div_too_big and div_exceeds_adj and div_pre_split:
+                        k = 'too-big div & pre-split'
+                        correction = (1.0/currency_divide) * (1.0/df2['Stock Splits'].loc[dt])
+                        correct_div = row['div'] * correction
+                        df2.loc[dt, 'Dividends'] = correct_div
+
+                        target_div_pct = row['%'] * correction
+                        target_adj = 1.0 - target_div_pct
+                        present_adj = row['present adj']
+                        # Also correct adjustment to match corrected dividend
+                        k += ' & div-adjust'
+                        adj_correction = target_adj / present_adj
+                        df2.loc[    :enddt, 'Adj Close'] *= adj_correction
+                        df2.loc[    :enddt, 'Repaired?'] = True
+                        df2_nan.loc[:enddt, 'Adj Close'] *= adj_correction
+                        df2_nan.loc[:enddt, 'Repaired?'] = True
+                        cluster.loc[dt, 'Fixed?'] = True
+                        div_repairs.setdefault(k, []).append(dt)
+
+                    elif div_too_big and div_exceeds_adj and adj_too_small:
+                        # Need to fix dividend AND adj close.
+                        # Probably just a currency unit mixup.
+                        div = row['div']
+                        close = div/row['%']
+                        adj_present = row['present adj']
+                        k = 'div-too-big and adj-too-small'
+                        #
+                        div_true = div/currency_divide
+                        pct_true = div_true / close
+                        df2.loc[dt, 'Dividends'] = div_true
+                        #
+                        adj_correct = 1.0 - pct_true
+                        adj_correction = adj_correct / adj_present
+                        df2.loc[    :enddt, 'Adj Close'] *= adj_correction
+                        df2.loc[    :enddt, 'Repaired?'] = True
+                        df2_nan.loc[:enddt, 'Adj Close'] *= adj_correction
+                        df2_nan.loc[:enddt, 'Repaired?'] = True
+                        div_repairs.setdefault(k, []).append(dt)
+                        cluster.loc[dt, 'Fixed?'] = True
+
            if cluster.empty:
                continue

@@ -2381,7 +2496,12 @@ class PriceHistory:

        # Update: if a VERY large dividend is paid out, then can be mistaken for a 1:2 stock split.
        # Fix = use adjusted prices
-        adj = df2['Adj Close'].to_numpy() / df2['Close'].to_numpy()
+        f_zero = df2['Close'] == 0
+        if f_zero.any():
+            adj = np.ones(len(df2))
+            adj[~f_zero] = df2['Adj Close'].to_numpy()[~f_zero] / df2['Close'].to_numpy()[~f_zero]
+        else:
+            adj = df2['Adj Close'].to_numpy() / df2['Close'].to_numpy()
        df_dtype = price_data.dtype
        if df_dtype == np.int64:
            price_data = price_data.astype('float')
@@ -2473,14 +2593,14 @@ class PriceHistory:

        r = _1d_change_x / split_rcp
        f_down = _1d_change_x < 1.0 / threshold
-        if f_down.any():
-            # Discard where triggered by negative Adj Close after dividend
-            f_neg = _1d_change_x < 0.0
-            f_div = (df2['Dividends']>0).to_numpy()
-            f_div_before = np.roll(f_div, 1)
-            if f_down.ndim == 2:
-                f_div_before = f_div_before[:, np.newaxis].repeat(f_down.shape[1], axis=1)
-            f_down = f_down & ~(f_neg + f_div_before)
+        # if f_down.any():
+        #     # Discard where triggered by negative Adj Close after dividend
+        #     f_neg = _1d_change_x < 0.0
+        #     f_div = (df2['Dividends']>0).to_numpy()
+        #     f_div_before = np.roll(f_div, 1)
+        #     if f_down.ndim == 2:
+        #         f_div_before = f_div_before[:, np.newaxis].repeat(f_down.shape[1], axis=1)
+        #     f_down = f_down & ~(f_neg + f_div_before)
        f_up = _1d_change_x > threshold
        f_up_ndims = len(f_up.shape)
        f_up_shifts = f_up if f_up_ndims==1 else f_up.any(axis=1)
@@ -2503,7 +2623,7 @@ class PriceHistory:
                        # assume false positive
                        continue
                    avg_vol_after = df2['Volume'].iloc[lookback:i-1].mean()
-                    if not np.isnan(avg_vol_after) and v/avg_vol_after < 2.0:
+                    if not np.isnan(avg_vol_after) and avg_vol_after > 0 and v/avg_vol_after < 2.0:
                        # volume spike is actually a step-change, so 
                        # probably missing stock split
                        continue
@@ -2550,7 +2670,13 @@ class PriceHistory:
                    threshold = _dateutil.relativedelta.relativedelta(days=threshold_days)
                else:
                    threshold = _datetime.timedelta(days=threshold_days)
-                if gap_td < threshold:
+                if isinstance(threshold, _dateutil.relativedelta.relativedelta) and isinstance(gap_td, _dateutil.relativedelta.relativedelta):
+                    idx = np.where(gaps==gap_min)[0][0]
+                    dt = df2.index[idx]
+                    within_threshold = (dt + gap_td) < (dt + threshold)
+                else:
+                    within_threshold = gap_td < threshold
+                if within_threshold:
                    logger.info('100x changes are too soon after stock split events, aborting', extra=log_extras)
                    return df

--- a/yfinance/scrapers/holders.py
+++ b/yfinance/scrapers/holders.py
@@ -1,23 +1,22 @@
-# from io import StringIO
-
 import pandas as pd
 import requests

 from yfinance import utils
 from yfinance.data import YfData
-from yfinance.const import _BASE_URL_
+from yfinance.const import _BASE_URL_, _SENTINEL_
 from yfinance.exceptions import YFDataException

-_QUOTE_SUMMARY_URL_ = f"{_BASE_URL_}/v10/finance/quoteSummary/"
-
+_QUOTE_SUMMARY_URL_ = f"{_BASE_URL_}/v10/finance/quoteSummary"

 class Holders:
    _SCRAPE_URL_ = 'https://finance.yahoo.com/quote'

-    def __init__(self, data: YfData, symbol: str, proxy=None):
+    def __init__(self, data: YfData, symbol: str, proxy=_SENTINEL_):
        self._data = data
        self._symbol = symbol
-        self.proxy = proxy
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            data._set_proxy(proxy)

        self._major = None
        self._major_direct_holders = None
@@ -31,55 +30,49 @@ class Holders:
    @property
    def major(self) -> pd.DataFrame:
        if self._major is None:
-            # self._scrape(self.proxy)
            self._fetch_and_parse()
        return self._major

    @property
    def institutional(self) -> pd.DataFrame:
        if self._institutional is None:
-            # self._scrape(self.proxy)
            self._fetch_and_parse()
        return self._institutional

    @property
    def mutualfund(self) -> pd.DataFrame:
        if self._mutualfund is None:
-            # self._scrape(self.proxy)
            self._fetch_and_parse()
        return self._mutualfund

    @property
    def insider_transactions(self) -> pd.DataFrame:
        if self._insider_transactions is None:
-            # self._scrape_insider_transactions(self.proxy)
            self._fetch_and_parse()
        return self._insider_transactions

    @property
    def insider_purchases(self) -> pd.DataFrame:
        if self._insider_purchases is None:
-            # self._scrape_insider_transactions(self.proxy)
            self._fetch_and_parse()
        return self._insider_purchases

    @property
    def insider_roster(self) -> pd.DataFrame:
        if self._insider_roster is None:
-            # self._scrape_insider_ros(self.proxy)
            self._fetch_and_parse()
        return self._insider_roster

-    def _fetch(self, proxy):
+    def _fetch(self):
        modules = ','.join(
            ["institutionOwnership", "fundOwnership", "majorDirectHolders", "majorHoldersBreakdown", "insiderTransactions", "insiderHolders", "netSharePurchaseActivity"])
        params_dict = {"modules": modules, "corsDomain": "finance.yahoo.com", "formatted": "false"}
-        result = self._data.get_raw_json(f"{_QUOTE_SUMMARY_URL_}/{self._symbol}", user_agent_headers=self._data.user_agent_headers, params=params_dict, proxy=proxy)
+        result = self._data.get_raw_json(f"{_QUOTE_SUMMARY_URL_}/{self._symbol}", params=params_dict)
        return result

    def _fetch_and_parse(self):
        try:
-            result = self._fetch(self.proxy)
+            result = self._fetch()
        except requests.exceptions.HTTPError as e:
            utils.get_yf_logger().error(str(e))

@@ -187,8 +180,10 @@ class Holders:
            del owner["maxAge"]
        df = pd.DataFrame(holders)
        if not df.empty:
-            df["positionDirectDate"] = pd.to_datetime(df["positionDirectDate"], unit="s")
-            df["latestTransDate"] = pd.to_datetime(df["latestTransDate"], unit="s")
+            if "positionDirectDate" in df:
+                df["positionDirectDate"] = pd.to_datetime(df["positionDirectDate"], unit="s")
+            if "latestTransDate" in df:
+                df["latestTransDate"] = pd.to_datetime(df["latestTransDate"], unit="s")

            df.rename(columns={
                "name": "Name",
--- a/yfinance/scrapers/quote.py
+++ b/yfinance/scrapers/quote.py
@@ -7,7 +7,7 @@ import requests

 from yfinance import utils
 from yfinance.data import YfData
-from yfinance.const import quote_summary_valid_modules, _BASE_URL_
+from yfinance.const import quote_summary_valid_modules, _BASE_URL_, _QUERY1_URL_, _SENTINEL_
 from yfinance.exceptions import YFDataException, YFException

 info_retired_keys_price = {"currentPrice", "dayHigh", "dayLow", "open", "previousClose", "volume", "volume24Hr"}
@@ -26,9 +26,11 @@ _QUOTE_SUMMARY_URL_ = f"{_BASE_URL_}/v10/finance/quoteSummary"
 class FastInfo:
    # Contain small subset of info[] items that can be fetched faster elsewhere.
    # Imitates a dict.
-    def __init__(self, tickerBaseObject, proxy=None):
+    def __init__(self, tickerBaseObject, proxy=_SENTINEL_):
        self._tkr = tickerBaseObject
-        self.proxy = proxy
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._tkr._data._set_proxy(proxy)

        self._prices_1y = None
        self._prices_1wk_1h_prepost = None
@@ -128,8 +130,8 @@ class FastInfo:

    def _get_1y_prices(self, fullDaysOnly=False):
        if self._prices_1y is None:
-            self._prices_1y = self._tkr.history(period="1y", auto_adjust=False, keepna=True, proxy=self.proxy)
-            self._md = self._tkr.get_history_metadata(proxy=self.proxy)
+            self._prices_1y = self._tkr.history(period="1y", auto_adjust=False, keepna=True)
+            self._md = self._tkr.get_history_metadata()
            try:
                ctp = self._md["currentTradingPeriod"]
                self._today_open = pd.to_datetime(ctp["regular"]["start"], unit='s', utc=True).tz_convert(self.timezone)
@@ -154,12 +156,12 @@ class FastInfo:

    def _get_1wk_1h_prepost_prices(self):
        if self._prices_1wk_1h_prepost is None:
-            self._prices_1wk_1h_prepost = self._tkr.history(period="5d", interval="1h", auto_adjust=False, prepost=True, proxy=self.proxy)
+            self._prices_1wk_1h_prepost = self._tkr.history(period="5d", interval="1h", auto_adjust=False, prepost=True)
        return self._prices_1wk_1h_prepost

    def _get_1wk_1h_reg_prices(self):
        if self._prices_1wk_1h_reg is None:
-            self._prices_1wk_1h_reg = self._tkr.history(period="5d", interval="1h", auto_adjust=False, prepost=False, proxy=self.proxy)
+            self._prices_1wk_1h_reg = self._tkr.history(period="5d", interval="1h", auto_adjust=False, prepost=False)
        return self._prices_1wk_1h_reg

    def _get_exchange_metadata(self):
@@ -167,7 +169,7 @@ class FastInfo:
            return self._md

        self._get_1y_prices()
-        self._md = self._tkr.get_history_metadata(proxy=self.proxy)
+        self._md = self._tkr.get_history_metadata()
        return self._md

    def _exchange_open_now(self):
@@ -198,7 +200,7 @@ class FastInfo:
        if self._currency is not None:
            return self._currency

-        md = self._tkr.get_history_metadata(proxy=self.proxy)
+        md = self._tkr.get_history_metadata()
        self._currency = md["currency"]
        return self._currency

@@ -207,7 +209,7 @@ class FastInfo:
        if self._quote_type is not None:
            return self._quote_type

-        md = self._tkr.get_history_metadata(proxy=self.proxy)
+        md = self._tkr.get_history_metadata()
        self._quote_type = md["instrumentType"]
        return self._quote_type

@@ -232,7 +234,7 @@ class FastInfo:
        if self._shares is not None:
            return self._shares

-        shares = self._tkr.get_shares_full(start=pd.Timestamp.utcnow().date()-pd.Timedelta(days=548), proxy=self.proxy)
+        shares = self._tkr.get_shares_full(start=pd.Timestamp.utcnow().date()-pd.Timedelta(days=548))
        # if shares is None:
        #     # Requesting 18 months failed, so fallback to shares which should include last year
        #     shares = self._tkr.get_shares()
@@ -484,11 +486,12 @@ class FastInfo:


 class Quote:
-
-    def __init__(self, data: YfData, symbol: str, proxy=None):
+    def __init__(self, data: YfData, symbol: str, proxy=_SENTINEL_):
        self._data = data
        self._symbol = symbol
-        self.proxy = proxy
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)

        self._info = None
        self._retired_info = None
@@ -505,15 +508,15 @@ class Quote:
    @property
    def info(self) -> dict:
        if self._info is None:
-            self._fetch_info(self.proxy)
-            self._fetch_complementary(self.proxy)
+            self._fetch_info()
+            self._fetch_complementary()

        return self._info

    @property
    def sustainability(self) -> pd.DataFrame:
        if self._sustainability is None:
-            result = self._fetch(self.proxy, modules=['esgScores'])
+            result = self._fetch(modules=['esgScores'])
            if result is None:
                self._sustainability = pd.DataFrame()
            else:
@@ -527,7 +530,7 @@ class Quote:
    @property
    def recommendations(self) -> pd.DataFrame:
        if self._recommendations is None:
-            result = self._fetch(self.proxy, modules=['recommendationTrend'])
+            result = self._fetch(modules=['recommendationTrend'])
            if result is None:
                self._recommendations = pd.DataFrame()
            else:
@@ -541,7 +544,7 @@ class Quote:
    @property
    def upgrades_downgrades(self) -> pd.DataFrame:
        if self._upgrades_downgrades is None:
-            result = self._fetch(self.proxy, modules=['upgradeDowngradeHistory'])
+            result = self._fetch(modules=['upgradeDowngradeHistory'])
            if result is None:
                self._upgrades_downgrades = pd.DataFrame()
            else:
@@ -575,7 +578,7 @@ class Quote:
    def valid_modules():
        return quote_summary_valid_modules

-    def _fetch(self, proxy, modules: list):
+    def _fetch(self, modules: list):
        if not isinstance(modules, list):
            raise YFException("Should provide a list of modules, see available modules using `valid_modules`")

@@ -584,39 +587,61 @@ class Quote:
            raise YFException("No valid modules provided, see available modules using `valid_modules`")
        params_dict = {"modules": modules, "corsDomain": "finance.yahoo.com", "formatted": "false", "symbol": self._symbol}
        try:
-            result = self._data.get_raw_json(_QUOTE_SUMMARY_URL_ + f"/{self._symbol}", user_agent_headers=self._data.user_agent_headers, params=params_dict, proxy=proxy)
+            result = self._data.get_raw_json(_QUOTE_SUMMARY_URL_ + f"/{self._symbol}", params=params_dict)
        except requests.exceptions.HTTPError as e:
            utils.get_yf_logger().error(str(e))
            return None
        return result

-    def _fetch_info(self, proxy):
+    def _fetch_additional_info(self):
+        params_dict = {"symbols": self._symbol, "formatted": "false"}
+        try:
+            result = self._data.get_raw_json(f"{_QUERY1_URL_}/v7/finance/quote?", params=params_dict)
+        except requests.exceptions.HTTPError as e:
+            utils.get_yf_logger().error(str(e))
+            return None
+        return result
+
+    def _fetch_info(self):
        if self._already_fetched:
            return
        self._already_fetched = True
        modules = ['financialData', 'quoteType', 'defaultKeyStatistics', 'assetProfile', 'summaryDetail']
-        result = self._fetch(proxy, modules=modules)
-        if result is None:
-            self._info = {}
-            return
+        result = self._fetch(modules=modules)
+        additional_info = self._fetch_additional_info()
+        if additional_info is not None and result is not None:
+            result.update(additional_info)
+        else:
+            result = additional_info
+
+        query1_info = {}
+        for quote in ["quoteSummary", "quoteResponse"]:
+            if quote in result and len(result[quote]["result"]) > 0:
+                result[quote]["result"][0]["symbol"] = self._symbol
+                query_info = next(
+                    (info for info in result.get(quote, {}).get("result", [])
+                    if info["symbol"] == self._symbol),
+                    None,
+                )
+                if query_info:
+                    query1_info.update(query_info)
+
+        # Normalize and flatten nested dictionaries while converting maxAge from days (1) to seconds (86400).
+        # This handles Yahoo Finance API inconsistency where maxAge is sometimes expressed in days instead of seconds.
+        processed_info = {}
+        for k, v in query1_info.items():
+
+            # Handle nested dictionary
+            if isinstance(v, dict):
+                for k1, v1 in v.items():
+                    if v1 is not None:
+                        processed_info[k1] = 86400 if k1 == "maxAge" and v1 == 1 else v1
+
+            elif v is not None:
+                processed_info[k] = v
+
+        query1_info = processed_info

-        result["quoteSummary"]["result"][0]["symbol"] = self._symbol
-        query1_info = next(
-            (info for info in result.get("quoteSummary", {}).get("result", []) if info["symbol"] == self._symbol),
-            None,
-        )
-        # Most keys that appear in multiple dicts have same value. Except 'maxAge' because
-        # Yahoo not consistent with days vs seconds. Fix it here:
-        for k in query1_info:
-            if "maxAge" in query1_info[k] and query1_info[k]["maxAge"] == 1:
-                query1_info[k]["maxAge"] = 86400
-        query1_info = {
-            k1: v1
-            for k, v in query1_info.items()
-            if isinstance(v, dict)
-            for k1, v1 in v.items()
-            if v1
-        }
        # recursively format but only because of 'companyOfficers'

        def _format(k, v):
@@ -631,17 +656,15 @@ class Quote:
            else:
                v2 = v
            return v2
-        for k, v in query1_info.items():
-            query1_info[k] = _format(k, v)
-        self._info = query1_info

-    def _fetch_complementary(self, proxy):
+        self._info = {k: _format(k, v) for k, v in query1_info.items()}
+
+    def _fetch_complementary(self):
        if self._already_fetched_complementary:
            return
        self._already_fetched_complementary = True

-        # self._scrape(proxy)  # decrypt broken
-        self._fetch_info(proxy)
+        self._fetch_info()
        if self._info is None:
            return

@@ -654,7 +677,7 @@ class Quote:
            # p = _re.compile(r'root\.App\.main = (.*);')
            # url = 'https://finance.yahoo.com/quote/{}/key-statistics?p={}'.format(self._ticker.ticker, self._ticker.ticker)
            # try:
-            #     r = session.get(url, headers=utils.user_agent_headers)
+            #     r = session.get(url)
            #     data = _json.loads(p.findall(r.text)[0])
            #     key_stats = data['context']['dispatcher']['stores']['QuoteTimeSeriesStore']["timeSeries"]
            #     for k in keys:
@@ -680,7 +703,7 @@ class Quote:
            end = int(end.timestamp())
            url += f"&period1={start}&period2={end}"

-            json_str = self._data.cache_get(url=url, proxy=proxy).text
+            json_str = self._data.cache_get(url=url).text
            json_data = json.loads(json_str)
            json_result = json_data.get("timeseries") or json_data.get("finance")
            if json_result["error"] is not None:
@@ -694,7 +717,7 @@ class Quote:

    def _fetch_calendar(self):
        # secFilings return too old data, so not requesting it for now
-        result = self._fetch(self.proxy, modules=['calendarEvents'])
+        result = self._fetch(modules=['calendarEvents'])
        if result is None:
            self._calendar = {}
            return
@@ -721,7 +744,7 @@ class Quote:


    def _fetch_sec_filings(self):
-        result = self._fetch(self.proxy, modules=['secFilings'])
+        result = self._fetch(modules=['secFilings'])
        if result is None:
            return None

--- a/yfinance/screener/init.py
+++ b/yfinance/screener/init.py
@@ -1,4 +1,4 @@
-from .screener import Screener
-from .screener_query import EquityQuery
+from .query import EquityQuery
+from .screener import screen, PREDEFINED_SCREENER_QUERIES

-__all__ = ['EquityQuery', 'Screener']
+__all__ = ['EquityQuery', 'FundQuery', 'screen', 'PREDEFINED_SCREENER_QUERIES']
--- a/yfinance/screener/query.py
+++ b/yfinance/screener/query.py
@@ -0,0 +1,218 @@
+from abc import ABC, abstractmethod
+import numbers
+from typing import List, Union, Dict, TypeVar, Tuple
+
+from yfinance.const import EQUITY_SCREENER_EQ_MAP, EQUITY_SCREENER_FIELDS
+from yfinance.const import FUND_SCREENER_EQ_MAP, FUND_SCREENER_FIELDS
+from yfinance.exceptions import YFNotImplementedError
+from ..utils import dynamic_docstring, generate_list_table_from_dict_universal
+
+T = TypeVar('T', bound=Union[str, numbers.Real])
+
+class QueryBase(ABC):
+    def __init__(self, operator: str, operand: Union[ List['QueryBase'], Tuple[str, Tuple[Union[str, numbers.Real],  ...]] ]):
+        operator = operator.upper()
+
+        if not isinstance(operand, list):
+            raise TypeError('Invalid operand type')
+        if len(operand) <= 0:
+            raise ValueError('Invalid field for EquityQuery')
+            
+        if operator == 'IS-IN':
+            self._validate_isin_operand(operand)
+        elif operator in {'OR','AND'}: 
+            self._validate_or_and_operand(operand)
+        elif operator == 'EQ': 
+            self._validate_eq_operand(operand)
+        elif operator == 'BTWN': 
+            self._validate_btwn_operand(operand)
+        elif operator in {'GT','LT','GTE','LTE'}: 
+            self._validate_gt_lt(operand)
+        else: 
+            raise ValueError('Invalid Operator Value')
+
+        self.operator = operator
+        self.operands = operand
+
+    @property
+    @abstractmethod
+    def valid_fields(self) -> List:
+        raise YFNotImplementedError('valid_fields() needs to be implemented by child')
+
+    @property
+    @abstractmethod
+    def valid_values(self) -> Dict:
+        raise YFNotImplementedError('valid_values() needs to be implemented by child')
+
+    def _validate_or_and_operand(self, operand: List['QueryBase']) -> None:
+        if len(operand) <= 1: 
+            raise ValueError('Operand must be length longer than 1')
+        if all(isinstance(e, QueryBase) for e in operand) is False: 
+            raise TypeError(f'Operand must be type {type(self)} for OR/AND')
+
+    def _validate_eq_operand(self, operand: List[Union[str, numbers.Real]]) -> None:
+        if len(operand) != 2:
+            raise ValueError('Operand must be length 2 for EQ')
+        
+        if  not any(operand[0] in fields_by_type for fields_by_type in self.valid_fields.values()):
+            raise ValueError(f'Invalid field for {type(self)} "{operand[0]}"')
+        if operand[0] in self.valid_values:
+            vv = self.valid_values[operand[0]]
+            if isinstance(vv, dict):
+                # this data structure is slightly different to generate better docs, 
+                # need to unpack here.
+                vv = set().union(*[e for e in vv.values()])
+            if operand[1] not in vv:
+                raise ValueError(f'Invalid EQ value "{operand[1]}"')
+    
+    def _validate_btwn_operand(self, operand: List[Union[str, numbers.Real]]) -> None:
+        if len(operand) != 3: 
+            raise ValueError('Operand must be length 3 for BTWN')
+        if  not any(operand[0] in fields_by_type for fields_by_type in self.valid_fields.values()):
+            raise ValueError(f'Invalid field for {type(self)}')
+        if isinstance(operand[1], numbers.Real) is False:
+            raise TypeError('Invalid comparison type for BTWN')
+        if isinstance(operand[2], numbers.Real) is False:
+            raise TypeError('Invalid comparison type for BTWN')
+
+    def _validate_gt_lt(self, operand: List[Union[str, numbers.Real]]) -> None:
+        if len(operand) != 2:
+            raise ValueError('Operand must be length 2 for GT/LT')
+        if  not any(operand[0] in fields_by_type for fields_by_type in self.valid_fields.values()):
+            raise ValueError(f'Invalid field for {type(self)} "{operand[0]}"')
+        if isinstance(operand[1], numbers.Real) is False:
+            raise TypeError('Invalid comparison type for GT/LT')
+
+    def _validate_isin_operand(self, operand: List['QueryBase']) -> None:
+        if len(operand) < 2:
+            raise ValueError('Operand must be length 2+ for IS-IN')
+        
+        if  not any(operand[0] in fields_by_type for fields_by_type in self.valid_fields.values()):
+            raise ValueError(f'Invalid field for {type(self)} "{operand[0]}"')
+        if operand[0] in self.valid_values:
+            vv = self.valid_values[operand[0]]
+            if isinstance(vv, dict):
+                # this data structure is slightly different to generate better docs, 
+                # need to unpack here.
+                vv = set().union(*[e for e in vv.values()])
+            for i in range(1, len(operand)):
+                if operand[i] not in vv:
+                    raise ValueError(f'Invalid EQ value "{operand[i]}"')
+
+    def to_dict(self) -> Dict:
+        op = self.operator
+        ops = self.operands
+        if self.operator == 'IS-IN':
+            # Expand to OR of EQ queries
+            op = 'OR'
+            ops = [type(self)('EQ', [self.operands[0], v]) for v in self.operands[1:]]
+        return {
+            "operator": op,
+            "operands": [o.to_dict() if isinstance(o, QueryBase) else o for o in ops]
+        }
+
+    def __repr__(self, indent=0) -> str:
+        indent_str = "  " * indent
+        class_name = self.__class__.__name__
+
+        if isinstance(self.operands, list):
+            # For list operands, check if they contain any QueryBase objects
+            if any(isinstance(op, QueryBase) for op in self.operands):
+                # If there are nested queries, format them with newlines
+                operands_str = ",\n".join(
+                    f"{indent_str}  {op.__repr__(indent + 1) if isinstance(op, QueryBase) else repr(op)}"
+                    for op in self.operands
+                )
+                return f"{class_name}({self.operator}, [\n{operands_str}\n{indent_str}])"
+            else:
+                # For lists of simple types, keep them on one line
+                return f"{class_name}({self.operator}, {repr(self.operands)})"
+        else:
+            # Handle single operand
+            return f"{class_name}({self.operator}, {repr(self.operands)})"
+
+    def __str__(self) -> str:
+        return self.__repr__()
+
+
+class EquityQuery(QueryBase):
+    """
+    The `EquityQuery` class constructs filters for stocks based on specific criteria such as region, sector, exchange, and peer group.
+
+    Start with value operations: `EQ` (equals), `IS-IN` (is in), `BTWN` (between), `GT` (greater than), `LT` (less than), `GTE` (greater or equal), `LTE` (less or equal).
+
+    Combine them with logical operations: `AND`, `OR`.
+
+    Example:
+        Predefined Yahoo query `aggressive_small_caps`:
+        
+        .. code-block:: python
+
+            from yfinance import EquityQuery
+
+            EquityQuery('and', [
+                EquityQuery('is-in', ['exchange', 'NMS', 'NYQ']), 
+                EquityQuery('lt', ["epsgrowth.lasttwelvemonths", 15])
+            ])
+    """
+
+    @dynamic_docstring({"valid_operand_fields_table": generate_list_table_from_dict_universal(EQUITY_SCREENER_FIELDS)})
+    @property
+    def valid_fields(self) -> Dict:
+        """
+        Valid operands, grouped by category.
+        {valid_operand_fields_table}
+        """
+        return EQUITY_SCREENER_FIELDS
+    
+    @dynamic_docstring({"valid_values_table": generate_list_table_from_dict_universal(EQUITY_SCREENER_EQ_MAP, concat_keys=['exchange'])})
+    @property
+    def valid_values(self) -> Dict:
+        """
+        Most operands take number values, but some have a restricted set of valid values.
+        {valid_values_table}
+        """
+        return EQUITY_SCREENER_EQ_MAP
+
+
+class FundQuery(QueryBase):
+    """
+    The `FundQuery` class constructs filters for mutual funds based on specific criteria such as region, sector, exchange, and peer group.
+
+    Start with value operations: `EQ` (equals), `IS-IN` (is in), `BTWN` (between), `GT` (greater than), `LT` (less than), `GTE` (greater or equal), `LTE` (less or equal).
+
+    Combine them with logical operations: `AND`, `OR`.
+
+    Example:
+        Predefined Yahoo query `solid_large_growth_funds`:
+        
+        .. code-block:: python
+
+            from yfinance import FundQuery
+            
+            FundQuery('and', [
+                FundQuery('eq', ['categoryname', 'Large Growth']), 
+                FundQuery('is-in', ['performanceratingoverall', 4, 5]), 
+                FundQuery('lt', ['initialinvestment', 100001]), 
+                FundQuery('lt', ['annualreturnnavy1categoryrank', 50]), 
+                FundQuery('eq', ['exchange', 'NAS'])
+            ])
+    """
+    @dynamic_docstring({"valid_operand_fields_table": generate_list_table_from_dict_universal(FUND_SCREENER_FIELDS)})
+    @property
+    def valid_fields(self) -> Dict:
+        """
+        Valid operands, grouped by category.
+        {valid_operand_fields_table}
+        """
+        return FUND_SCREENER_FIELDS
+    
+    @dynamic_docstring({"valid_values_table": generate_list_table_from_dict_universal(FUND_SCREENER_EQ_MAP)})
+    @property
+    def valid_values(self) -> Dict:
+        """
+        Most operands take number values, but some have a restricted set of valid values.
+        {valid_values_table}
+        """
+        return FUND_SCREENER_EQ_MAP
+
--- a/yfinance/screener/screener.py
+++ b/yfinance/screener/screener.py
@@ -1,188 +1,195 @@
-from typing import Dict
+from .query import EquityQuery as EqyQy
+from .query import FundQuery as FndQy
+from .query import QueryBase, EquityQuery, FundQuery

-from yfinance import utils
+from yfinance.const import _QUERY1_URL_, _SENTINEL_
 from yfinance.data import YfData
-from yfinance.const import _BASE_URL_, PREDEFINED_SCREENER_BODY_MAP
-from .screener_query import Query
-from ..utils import dynamic_docstring, generate_list_table_from_dict_of_dict

-_SCREENER_URL_ = f"{_BASE_URL_}/v1/finance/screener"
+from ..utils import dynamic_docstring, generate_list_table_from_dict_universal, print_once

-class Screener:
+from typing import Union
+import requests
+
+_SCREENER_URL_ = f"{_QUERY1_URL_}/v1/finance/screener"
+_PREDEFINED_URL_ = f"{_SCREENER_URL_}/predefined/saved"
+
+PREDEFINED_SCREENER_BODY_DEFAULTS = {
+    "offset":0, "count":25, "userId":"","userIdType":"guid"
+}
+
+PREDEFINED_SCREENER_QUERIES = {
+    'aggressive_small_caps': {"sortField":"eodvolume", "sortType":"desc",
+                            "query": EqyQy('and', [EqyQy('is-in', ['exchange', 'NMS', 'NYQ']), EqyQy('lt', ["epsgrowth.lasttwelvemonths", 15])])},
+    'day_gainers': {"sortField":"percentchange", "sortType":"DESC",
+                    "query": EqyQy('and', [EqyQy('gt', ['percentchange', 3]), EqyQy('eq', ['region', 'us']), EqyQy('gte', ['intradaymarketcap', 2000000000]), EqyQy('gte', ['intradayprice', 5]), EqyQy('gt', ['dayvolume', 15000])])},
+    'day_losers': {"sortField":"percentchange", "sortType":"ASC",
+                    "query": EqyQy('and', [EqyQy('lt', ['percentchange', -2.5]), EqyQy('eq', ['region', 'us']), EqyQy('gte', ['intradaymarketcap', 2000000000]), EqyQy('gte', ['intradayprice', 5]), EqyQy('gt', ['dayvolume', 20000])])},
+    'growth_technology_stocks': {"sortField":"eodvolume", "sortType":"desc",
+                                "query": EqyQy('and', [EqyQy('gte', ['quarterlyrevenuegrowth.quarterly', 25]), EqyQy('gte', ['epsgrowth.lasttwelvemonths', 25]), EqyQy('eq', ['sector', 'Technology']), EqyQy('is-in', ['exchange', 'NMS', 'NYQ'])])},
+    'most_actives': {"sortField":"dayvolume", "sortType":"DESC",
+                    "query": EqyQy('and', [EqyQy('eq', ['region', 'us']), EqyQy('gte', ['intradaymarketcap', 2000000000]), EqyQy('gt', ['dayvolume', 5000000])])},
+    'most_shorted_stocks': {"count":25, "offset":0, "sortField":"short_percentage_of_shares_outstanding.value", "sortType":"DESC", 
+                            "query": EqyQy('and', [EqyQy('eq', ['region', 'us']), EqyQy('gt', ['intradayprice', 1]), EqyQy('gt', ['avgdailyvol3m', 200000])])},
+    'small_cap_gainers': {"sortField":"eodvolume", "sortType":"desc", 
+                        "query": EqyQy("and", [EqyQy("lt", ["intradaymarketcap",2000000000]), EqyQy("is-in", ["exchange", "NMS", "NYQ"])])},
+    'undervalued_growth_stocks': {"sortType":"DESC", "sortField":"eodvolume", 
+                                "query": EqyQy('and', [EqyQy('btwn', ['peratio.lasttwelvemonths', 0, 20]), EqyQy('lt', ['pegratio_5y', 1]), EqyQy('gte', ['epsgrowth.lasttwelvemonths', 25]), EqyQy('is-in', ['exchange', 'NMS', 'NYQ'])])},
+    'undervalued_large_caps': {"sortField":"eodvolume", "sortType":"desc", 
+                            "query": EqyQy('and', [EqyQy('btwn', ['peratio.lasttwelvemonths', 0, 20]), EqyQy('lt', ['pegratio_5y', 1]), EqyQy('btwn', ['intradaymarketcap', 10000000000, 100000000000]), EqyQy('is-in', ['exchange', 'NMS', 'NYQ'])])},
+    'conservative_foreign_funds': {"sortType":"DESC", "sortField":"fundnetassets",
+                                "query": FndQy('and', [FndQy('is-in', ['categoryname', 'Foreign Large Value', 'Foreign Large Blend', 'Foreign Large Growth', 'Foreign Small/Mid Growth', 'Foreign Small/Mid Blend', 'Foreign Small/Mid Value']), FndQy('is-in', ['performanceratingoverall', 4, 5]), FndQy('lt', ['initialinvestment', 100001]), FndQy('lt', ['annualreturnnavy1categoryrank', 50]), FndQy('is-in', ['riskratingoverall', 1, 2, 3]), FndQy('eq', ['exchange', 'NAS'])])},
+    'high_yield_bond': {"sortType":"DESC", "sortField":"fundnetassets",
+                        "query": FndQy('and', [FndQy('is-in', ['performanceratingoverall', 4, 5]), FndQy('lt', ['initialinvestment', 100001]), FndQy('lt', ['annualreturnnavy1categoryrank', 50]), FndQy('is-in', ['riskratingoverall', 1, 2, 3]), FndQy('eq', ['categoryname', 'High Yield Bond']), FndQy('eq', ['exchange', 'NAS'])])},
+    'portfolio_anchors': {"sortType":"DESC", "sortField":"fundnetassets",
+                        "query": FndQy('and', [FndQy('eq', ['categoryname', 'Large Blend']), FndQy('is-in', ['performanceratingoverall', 4, 5]), FndQy('lt', ['initialinvestment', 100001]), FndQy('lt', ['annualreturnnavy1categoryrank', 50]), FndQy('eq', ['exchange', 'NAS'])])},
+    'solid_large_growth_funds': {"sortType":"DESC", "sortField":"fundnetassets",
+                                "query": FndQy('and', [FndQy('eq', ['categoryname', 'Large Growth']), FndQy('is-in', ['performanceratingoverall', 4, 5]), FndQy('lt', ['initialinvestment', 100001]), FndQy('lt', ['annualreturnnavy1categoryrank', 50]), FndQy('eq', ['exchange', 'NAS'])])},
+    'solid_midcap_growth_funds': {"sortType":"DESC", "sortField":"fundnetassets",
+                                "query": FndQy('and', [FndQy('eq', ['categoryname', 'Mid-Cap Growth']), FndQy('is-in', ['performanceratingoverall', 4, 5]), FndQy('lt', ['initialinvestment', 100001]), FndQy('lt', ['annualreturnnavy1categoryrank', 50]), FndQy('eq', ['exchange', 'NAS'])])},
+    'top_mutual_funds': {"sortType":"DESC", "sortField":"percentchange",
+                        "query": FndQy('and', [FndQy('gt', ['intradayprice', 15]), FndQy('is-in', ['performanceratingoverall', 4, 5]), FndQy('gt', ['initialinvestment', 1000]), FndQy('eq', ['exchange', 'NAS'])])}
+}
+
+@dynamic_docstring({"predefined_screeners": generate_list_table_from_dict_universal(PREDEFINED_SCREENER_QUERIES, bullets=True, title='Predefined queries (Dec-2024)')})
+def screen(query: Union[str, EquityQuery, FundQuery],
+            offset: int = None, 
+            size: int = None,
+            count: int = None,
+            sortField: str = None, 
+            sortAsc: bool = None,
+            userId: str = None, 
+            userIdType: str = None, 
+            session = None, proxy = _SENTINEL_):
    """
-    The `Screener` class is used to execute the queries and return the filtered results.
+    Run a screen: predefined query, or custom query.

-    The Screener class provides methods to set and manipulate the body of a screener request,
-    fetch and parse the screener results, and access predefined screener bodies.
+    :Parameters:
+        * Defaults only apply if query = EquityQuery or FundQuery
+        query : str | Query:
+            The query to execute, either name of predefined or custom query.
+            For predefined list run yf.PREDEFINED_SCREENER_QUERIES.keys()
+        offset : int
+            The offset for the results. Default 0.
+        size : int
+            number of results to return. Default 100, maximum 250 (Yahoo)
+            Use count instead for predefined queries.
+        count : int
+            number of results to return. Default 25, maximum 250 (Yahoo)
+            Use size instead for custom queries.
+        sortField : str
+            field to sort by. Default "ticker"
+        sortAsc : bool
+            Sort ascending? Default False
+        userId : str
+            The user ID. Default empty.
+        userIdType : str
+            Type of user ID (e.g., "guid"). Default "guid".
+
+    Example: predefined query
+        .. code-block:: python
+
+            import yfinance as yf
+            response = yf.screen("aggressive_small_caps")
+
+    Example: custom query
+        .. code-block:: python
+
+            import yfinance as yf
+            from yfinance import EquityQuery
+            q = EquityQuery('and', [
+                   EquityQuery('gt', ['percentchange', 3]), 
+                   EquityQuery('eq', ['region', 'us'])
+            ])
+            response = yf.screen(q, sortField = 'percentchange', sortAsc = True)
+
+    To access predefineds query code
+        .. code-block:: python
+
+            import yfinance as yf
+            query = yf.PREDEFINED_SCREENER_QUERIES['aggressive_small_caps']
+
+    {predefined_screeners}
    """
-    def __init__(self, session=None, proxy=None):
-        """
-        Args:
-            session (requests.Session, optional): A requests session object to be used for making HTTP requests. Defaults to None.
-            proxy (str, optional): A proxy URL to be used for making HTTP requests. Defaults to None.
-        
-        .. seealso::

-            :attr:`Screener.predefined_bodies <yfinance.Screener.predefined_bodies>`
-                supported predefined screens
-        """
-        self.proxy = proxy
-        self.session = session
+    if proxy is not _SENTINEL_:
+        print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+        _data = YfData(session=session, proxy=proxy)
+    else:
+        _data = YfData(session=session)

-        self._data: YfData = YfData(session=session)
-        self._body: Dict = {}
-        self._response: Dict = {}
-        self._body_updated = False
-        self._accepted_body_keys = {"offset","size","sortField","sortType","quoteType","query","userId","userIdType"}
-        self._predefined_bodies = PREDEFINED_SCREENER_BODY_MAP.keys()
+    # Only use defaults when user NOT give a predefined, because
+    # Yahoo's predefined endpoint auto-applies defaults. Also,
+    # that endpoint might be ignoring these fields.
+    defaults = {
+        'offset': 0,
+        'count': 25,
+        'sortField': 'ticker',
+        'sortAsc': False,
+        'userId': "",
+        'userIdType': "guid"
+    }

-    @property
-    def body(self) -> Dict:
-        return self._body
-    
-    @property
-    def response(self) -> Dict:
-        """
-        Fetch screen result
+    if count is not None and count > 250:
+        raise ValueError("Yahoo limits query count to 250, reduce count.")

-        Example:
+    if size is not None and size > 250:
+        raise ValueError("Yahoo limits query size to 250, reduce size.")

-            .. code-block:: python
+    fields = {'offset': offset, 'count': count, "size": size, 'sortField': sortField, 'sortAsc': sortAsc, 'userId': userId, 'userIdType': userIdType}

-                result = screener.response
-                symbols = [quote['symbol'] for quote in result['quotes']]
-        """
-        if self._body_updated or self._response is None:
-            self._fetch_and_parse()
-        
-        self._body_updated = False
-        return self._response
-    
-    @dynamic_docstring({"predefined_screeners": generate_list_table_from_dict_of_dict(PREDEFINED_SCREENER_BODY_MAP,bullets=False)})
-    @property
-    def predefined_bodies(self) -> Dict:
-        """
-        Predefined Screeners
-        {predefined_screeners}
-        """
-        return self._predefined_bodies
+    params_dict = {"corsDomain": "finance.yahoo.com", "formatted": "false", "lang": "en-US", "region": "US"}

-    def set_default_body(self, query: Query, offset: int = 0, size: int = 100, sortField: str = "ticker", sortType: str = "desc", quoteType: str = "equity", userId: str = "", userIdType: str = "guid") -> None:
-        """
-        Set the default body using a custom query
+    post_query = None
+    if isinstance(query, str):
+        # post_query = PREDEFINED_SCREENER_QUERIES[query]
+        # Switch to Yahoo's predefined endpoint

-        Example:
+        if size is not None:
+            print_once("YF deprecation warning: 'size' argument is deprecated for predefined screens, set 'count' instead.")
+            count = size
+            size = None
+            fields['count'] = fields['size']
+            del fields['size']

-            .. code-block:: python
-
-                screener.set_default_body(qf)
-        """
-        self._body_updated = True
-
-        self._body = {
-            "offset": offset,
-            "size": size,
-            "sortField": sortField,
-            "sortType": sortType,
-            "quoteType": quoteType,
-            "query": query.to_dict(),
-            "userId": userId,
-            "userIdType": userIdType
-        }
-
-    def set_predefined_body(self, k: str) -> None:
-        """
-        Set a predefined body
-
-        Example:
-
-            .. code-block:: python
-
-                screener.set_predefined_body('day_gainers')
-        
-                
-        .. seealso::
-
-            :attr:`Screener.predefined_bodies <yfinance.Screener.predefined_bodies>`
-                supported predefined screens
-        """
-        body = PREDEFINED_SCREENER_BODY_MAP.get(k, None)
-        if not body:
-            raise ValueError(f'Invalid key {k} provided for predefined screener')
-        
-        self._body_updated = True
-        self._body = body
-
-    def set_body(self, body: Dict) -> None:
-        """
-        Set the fully custom body 
-        
-        Example:
-
-            .. code-block:: python
-
-                screener.set_body({
-                    "offset": 0,
-                    "size": 100,
-                    "sortField": "ticker",
-                    "sortType": "desc",
-                    "quoteType": "equity",
-                    "query": qf.to_dict(),
-                    "userId": "",
-                    "userIdType": "guid"
-                })
-        """
-        missing_keys = [key for key in self._accepted_body_keys if key not in body]
-        if missing_keys:
-            raise ValueError(f"Missing required keys in body: {missing_keys}")
-
-        extra_keys = [key for key in body if key not in self._accepted_body_keys]
-        if extra_keys:
-            raise ValueError(f"Body contains extra keys: {extra_keys}")
-
-        self._body_updated = True
-        self._body = body
-
-
-    def patch_body(self, values: Dict) -> None:
-        """
-        Patch parts of the body
-
-        Example:
-
-            .. code-block:: python
-
-                screener.patch_body({"offset": 100})
-        """
-        extra_keys = [key for key in values if key not in self._accepted_body_keys]
-        if extra_keys:
-            raise ValueError(f"Body contains extra keys: {extra_keys}")
-        
-        self._body_updated = True
-        for k in values:
-            self._body[k] = values[k]
-
-    def _validate_body(self) -> None:
-        if not all(k in self._body for k in self._accepted_body_keys):
-            raise ValueError("Missing required keys in body")
-
-    def _fetch(self) -> Dict:
-        params_dict = {"corsDomain": "finance.yahoo.com", "formatted": "false", "lang": "en-US", "region": "US"}
-        response = self._data.post(_SCREENER_URL_, body=self.body, user_agent_headers=self._data.user_agent_headers, params=params_dict, proxy=self.proxy)
-        response.raise_for_status()
-        return response.json()
-    
-    def _fetch_and_parse(self) -> None:
-        response = None
-        self._validate_body()
-        
+        params_dict['scrIds'] = query
+        for k,v in fields.items():
+            if v is not None:
+                params_dict[k] = v
+        resp = _data.get(url=_PREDEFINED_URL_, params=params_dict)
        try:
-            response = self._fetch()
-            self._response = response['finance']['result'][0]
-        except Exception as e:
-            logger = utils.get_yf_logger()
-            logger.error(f"Failed to get screener data for '{self._body.get('query', 'query not set')}' reason: {e}")
-            logger.debug("Got response: ")
-            logger.debug("-------------")
-            logger.debug(f" {response}")
-            logger.debug("-------------")
+            resp.raise_for_status()
+        except requests.exceptions.HTTPError:
+            if query not in PREDEFINED_SCREENER_QUERIES:
+                print(f"yfinance.screen: '{query}' is probably not a predefined query.")
+            raise
+        return resp.json()["finance"]["result"][0]
+
+    elif isinstance(query, QueryBase):
+        # Prepare other fields
+        for k in defaults:
+            if k not in fields or fields[k] is None:
+                fields[k] = defaults[k]
+        fields['sortType'] = 'ASC' if fields['sortAsc'] else 'DESC'
+        del fields['sortAsc']
+
+        post_query = fields
+        post_query['query'] = query
+
+    else:
+        raise ValueError(f'Query must be type str or QueryBase, not "{type(query)}"')
+
+    if query is None:
+        raise ValueError('No query provided')
+
+    if isinstance(post_query['query'], EqyQy):
+        post_query['quoteType'] = 'EQUITY'
+    elif isinstance(post_query['query'], FndQy):
+        post_query['quoteType'] = 'MUTUALFUND'
+    post_query['query'] = post_query['query'].to_dict()
+
+    # Fetch
+    response = _data.post(_SCREENER_URL_, 
+                            body=post_query, 
+                            params=params_dict)
+    response.raise_for_status()
+    return response.json()['finance']['result'][0]
--- a/yfinance/screener/screener_query.py
+++ b/yfinance/screener/screener_query.py
@@ -1,145 +0,0 @@
-from abc import ABC, abstractmethod
-import numbers
-from typing import List, Union, Dict
-
-from yfinance.const import EQUITY_SCREENER_EQ_MAP, EQUITY_SCREENER_FIELDS
-from yfinance.exceptions import YFNotImplementedError
-from ..utils import dynamic_docstring, generate_list_table_from_dict
-
-class Query(ABC):
-    def __init__(self, operator: str, operand: Union[numbers.Real, str, List['Query']]):
-        self.operator = operator
-        self.operands = operand
-
-    @abstractmethod
-    def to_dict(self) -> Dict:
-        raise YFNotImplementedError('to_dict() needs to be implemented by children classes')
-
-class EquityQuery(Query):
-    """
-    The `EquityQuery` class constructs filters for stocks based on specific criteria such as region, sector, exchange, and peer group.
-
-    The queries support operators: `GT` (greater than), `LT` (less than), `BTWN` (between), `EQ` (equals), and logical operators `AND` and `OR` for combining multiple conditions.
-
-    Example:
-        Screen for stocks where the end-of-day price is greater than 3.
-        
-        .. code-block:: python
-
-            gt = yf.EquityQuery('gt', ['eodprice', 3])
-
-        Screen for stocks where the average daily volume over the last 3 months is less than a very large number.
-
-        .. code-block:: python
-
-            lt = yf.EquityQuery('lt', ['avgdailyvol3m', 99999999999])
-
-        Screen for stocks where the intraday market cap is between 0 and 100 million.
-
-        .. code-block:: python
-
-            btwn = yf.EquityQuery('btwn', ['intradaymarketcap', 0, 100000000])
-
-        Screen for stocks in the Technology sector.
-
-        .. code-block:: python
-
-            eq = yf.EquityQuery('eq', ['sector', 'Technology'])
-
-        Combine queries using AND/OR.
-
-        .. code-block:: python
-
-            qt = yf.EquityQuery('and', [gt, lt])
-            qf = yf.EquityQuery('or', [qt, btwn, eq])
-    """
-    def __init__(self, operator: str, operand: Union[numbers.Real, str, List['EquityQuery']]):
-        """
-        .. seealso::
-            
-            :attr:`EquityQuery.valid_operand_fields <yfinance.EquityQuery.valid_operand_fields>`
-                supported operand values for query
-            :attr:`EquityQuery.valid_eq_operand_map <yfinance.EquityQuery.valid_eq_operand_map>`
-                supported `EQ query operand parameters`
-        """
-        operator = operator.upper()
-
-        if not isinstance(operand, list):
-            raise TypeError('Invalid operand type')
-        if len(operand) <= 0:
-            raise ValueError('Invalid field for Screener')
-            
-        if operator in {'OR','AND'}: 
-            self._validate_or_and_operand(operand)
-        elif operator == 'EQ': 
-            self._validate_eq_operand(operand)
-        elif operator == 'BTWN': 
-            self._validate_btwn_operand(operand)
-        elif operator in {'GT','LT'}: 
-            self._validate_gt_lt(operand)
-        else: 
-            raise ValueError('Invalid Operator Value')
-
-        self.operator = operator
-        self.operands = operand
-        self._valid_eq_operand_map = EQUITY_SCREENER_EQ_MAP
-        self._valid_operand_fields = EQUITY_SCREENER_FIELDS
-    
-    @dynamic_docstring({"valid_eq_operand_map_table": generate_list_table_from_dict(EQUITY_SCREENER_EQ_MAP)})
-    @property
-    def valid_eq_operand_map(self) -> Dict:
-        """
-        Valid Operand Map for Operator "EQ"
-        {valid_eq_operand_map_table}
-        """
-        return self._valid_eq_operand_map
-
-    @dynamic_docstring({"valid_operand_fields_table": generate_list_table_from_dict(EQUITY_SCREENER_FIELDS)})
-    @property
-    def valid_operand_fields(self) -> Dict:
-        """
-        Valid Operand Fields
-        {valid_operand_fields_table}
-        """
-        return self._valid_operand_fields
-    
-    def _validate_or_and_operand(self, operand: List['EquityQuery']) -> None:
-        if len(operand) <= 1: 
-            raise ValueError('Operand must be length longer than 1')
-        if all(isinstance(e, EquityQuery) for e in operand) is False: 
-            raise TypeError('Operand must be type EquityQuery for OR/AND')
-
-    def _validate_eq_operand(self, operand: List[Union[str, numbers.Real]]) -> None:
-        if len(operand) != 2:
-            raise ValueError('Operand must be length 2 for EQ')
-        
-        if  not any(operand[0] in fields_by_type for fields_by_type in EQUITY_SCREENER_FIELDS.values()):
-            raise ValueError('Invalid field for Screener')
-        if operand[0] not in EQUITY_SCREENER_EQ_MAP:
-            raise ValueError('Invalid EQ key')
-        if operand[1] not in EQUITY_SCREENER_EQ_MAP[operand[0]]:
-            raise ValueError('Invalid EQ value')
-    
-    def _validate_btwn_operand(self, operand: List[Union[str, numbers.Real]]) -> None:
-        if len(operand) != 3: 
-            raise ValueError('Operand must be length 3 for BTWN')
-        if  not any(operand[0] in fields_by_type for fields_by_type in EQUITY_SCREENER_FIELDS.values()):
-            raise ValueError('Invalid field for Screener')
-        if isinstance(operand[1], numbers.Real) is False:
-            raise TypeError('Invalid comparison type for BTWN')
-        if isinstance(operand[2], numbers.Real) is False:
-            raise TypeError('Invalid comparison type for BTWN')
-
-    def _validate_gt_lt(self, operand: List[Union[str, numbers.Real]]) -> None:
-        if len(operand) != 2:
-            raise ValueError('Operand must be length 2 for GT/LT')
-        if  not any(operand[0] in fields_by_type for fields_by_type in EQUITY_SCREENER_FIELDS.values()):
-            raise ValueError('Invalid field for Screener')
-        if isinstance(operand[1], numbers.Real) is False:
-            raise TypeError('Invalid comparison type for GT/LT')
-
-    def to_dict(self) -> Dict:
-        return {
-            "operator": self.operator,
-            "operands": [operand.to_dict() if isinstance(operand, EquityQuery) else operand for operand in self.operands]
-        }
--- a/yfinance/search.py
+++ b/yfinance/search.py
@@ -0,0 +1,161 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+#
+# yfinance - market data downloader
+# https://github.com/ranaroussi/yfinance
+#
+# Copyright 2017-2019 Ran Aroussi
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import json as _json
+
+from . import utils
+from .const import _BASE_URL_, _SENTINEL_
+from .data import YfData
+
+
+class Search:
+    def __init__(self, query, max_results=8, news_count=8, lists_count=8, include_cb=True, include_nav_links=False,
+                 include_research=False, include_cultural_assets=False, enable_fuzzy_query=False, recommended=8,
+                 session=None, proxy=_SENTINEL_, timeout=30, raise_errors=True):
+        """
+        Fetches and organizes search results from Yahoo Finance, including stock quotes and news articles.
+
+        Args:
+            query: The search query (ticker symbol or company name).
+            max_results: Maximum number of stock quotes to return (default 8).
+            news_count: Number of news articles to include (default 8).
+            lists_count: Number of lists to include (default 8).
+            include_cb: Include the company breakdown (default True).
+            include_nav_links: Include the navigation links (default False).
+            include_research: Include the research reports (default False).
+            include_cultural_assets: Include the cultural assets (default False).
+            enable_fuzzy_query: Enable fuzzy search for typos (default False).
+            recommended: Recommended number of results to return (default 8).
+            session: Custom HTTP session for requests (default None).
+            timeout: Request timeout in seconds (default 30).
+            raise_errors: Raise exceptions on error (default True).
+        """
+        self.session = session
+        self._data = YfData(session=self.session)
+        
+        if proxy is not _SENTINEL_:
+            utils.print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
+        self.query = query
+        self.max_results = max_results
+        self.enable_fuzzy_query = enable_fuzzy_query
+        self.news_count = news_count
+        self.timeout = timeout
+        self.raise_errors = raise_errors
+
+        self.lists_count = lists_count
+        self.include_cb = include_cb
+        self.nav_links = include_nav_links
+        self.enable_research = include_research
+        self.enable_cultural_assets = include_cultural_assets
+        self.recommended = recommended
+
+        self._logger = utils.get_yf_logger()
+
+        self._response = {}
+        self._all = {}
+        self._quotes = []
+        self._news = []
+        self._lists = []
+        self._research = []
+        self._nav = []
+
+        self.search()
+
+    def search(self) -> 'Search':
+        """Search using the query parameters defined in the constructor."""
+        url = f"{_BASE_URL_}/v1/finance/search"
+        params = {
+            "q": self.query,
+            "quotesCount": self.max_results,
+            "enableFuzzyQuery": self.enable_fuzzy_query,
+            "newsCount": self.news_count,
+            "quotesQueryId": "tss_match_phrase_query",
+            "newsQueryId": "news_cie_vespa",
+            "listsCount": self.lists_count,
+            "enableCb": self.include_cb,
+            "enableNavLinks": self.nav_links,
+            "enableResearchReports": self.enable_research,
+            "enableCulturalAssets": self.enable_cultural_assets,
+            "recommendedCount": self.recommended
+        }
+
+        self._logger.debug(f'{self.query}: Yahoo GET parameters: {str(dict(params))}')
+
+        data = self._data.cache_get(url=url, params=params, timeout=self.timeout)
+        if data is None or "Will be right back" in data.text:
+            raise RuntimeError("*** YAHOO! FINANCE IS CURRENTLY DOWN! ***\n"
+                               "Our engineers are working quickly to resolve "
+                               "the issue. Thank you for your patience.")
+        try:
+            data = data.json()
+        except _json.JSONDecodeError:
+            self._logger.error(f"{self.query}: Failed to retrieve search results and received faulty response instead.")
+            data = {}
+
+        self._response = data
+        # Filter quotes to only include symbols
+        self._quotes = [quote for quote in data.get("quotes", []) if "symbol" in quote]
+        self._news = data.get("news", [])
+        self._lists = data.get("lists", [])
+        self._research = data.get("researchReports", [])
+        self._nav = data.get("nav", [])
+
+        self._all = {"quotes": self._quotes, "news": self._news, "lists": self._lists, "research": self._research,
+                     "nav": self._nav}
+
+        return self
+
+    @property
+    def quotes(self) -> 'list':
+        """Get the quotes from the search results."""
+        return self._quotes
+
+    @property
+    def news(self) -> 'list':
+        """Get the news from the search results."""
+        return self._news
+
+    @property
+    def lists(self) -> 'list':
+        """Get the lists from the search results."""
+        return self._lists
+
+    @property
+    def research(self) -> 'list':
+        """Get the research reports from the search results."""
+        return self._research
+
+    @property
+    def nav(self) -> 'list':
+        """Get the navigation links from the search results."""
+        return self._nav
+
+    @property
+    def all(self) -> 'dict[str,list]':
+        """Get all the results from the search results: filtered down version of response."""
+        return self._all
+
+    @property
+    def response(self) -> 'dict':
+        """Get the raw response from the search results."""
+        return self._response
--- a/yfinance/ticker.py
+++ b/yfinance/ticker.py
@@ -27,11 +27,11 @@ from .scrapers.funds import FundsData
 import pandas as _pd

 from .base import TickerBase
-from .const import _BASE_URL_
+from .const import _BASE_URL_, _SENTINEL_


 class Ticker(TickerBase):
-    def __init__(self, ticker, session=None, proxy=None):
+    def __init__(self, ticker, session=None, proxy=_SENTINEL_):
        super(Ticker, self).__init__(ticker, session=session, proxy=proxy)
        self._expirations = {}
        self._underlying  = {}
@@ -45,7 +45,7 @@ class Ticker(TickerBase):
        else:
            url = f"{_BASE_URL_}/v7/finance/options/{self.ticker}?date={date}"

-        r = self._data.get(url=url, proxy=self.proxy).json()
+        r = self._data.get(url=url).json()
        if len(r.get('optionChain', {}).get('result', [])) > 0:
            for exp in r['optionChain']['result'][0]['expirationDates']:
                self._expirations[_pd.Timestamp(exp, unit='s').strftime('%Y-%m-%d')] = exp
@@ -201,6 +201,10 @@ class Ticker(TickerBase):
    def quarterly_income_stmt(self) -> _pd.DataFrame:
        return self.get_income_stmt(pretty=True, freq='quarterly')

+    @property
+    def ttm_income_stmt(self) -> _pd.DataFrame:
+        return self.get_income_stmt(pretty=True, freq='trailing')
+
    @property
    def incomestmt(self) -> _pd.DataFrame:
        return self.income_stmt
@@ -209,6 +213,10 @@ class Ticker(TickerBase):
    def quarterly_incomestmt(self) -> _pd.DataFrame:
        return self.quarterly_income_stmt

+    @property
+    def ttm_incomestmt(self) -> _pd.DataFrame:
+        return self.ttm_income_stmt
+
    @property
    def financials(self) -> _pd.DataFrame:
        return self.income_stmt
@@ -217,6 +225,10 @@ class Ticker(TickerBase):
    def quarterly_financials(self) -> _pd.DataFrame:
        return self.quarterly_income_stmt

+    @property
+    def ttm_financials(self) -> _pd.DataFrame:
+        return self.ttm_income_stmt
+
    @property
    def balance_sheet(self) -> _pd.DataFrame:
        return self.get_balance_sheet(pretty=True)
@@ -241,6 +253,10 @@ class Ticker(TickerBase):
    def quarterly_cash_flow(self) -> _pd.DataFrame:
        return self.get_cash_flow(pretty=True, freq='quarterly')

+    @property
+    def ttm_cash_flow(self) -> _pd.DataFrame:
+        return self.get_cash_flow(pretty=True, freq='trailing')
+
    @property
    def cashflow(self) -> _pd.DataFrame:
        return self.cash_flow
@@ -249,6 +265,10 @@ class Ticker(TickerBase):
    def quarterly_cashflow(self) -> _pd.DataFrame:
        return self.quarterly_cash_flow

+    @property
+    def ttm_cashflow(self) -> _pd.DataFrame:
+        return self.ttm_cash_flow
+
    @property
    def analyst_price_targets(self) -> dict:
        return self.get_analyst_price_targets()
@@ -301,4 +321,4 @@ class Ticker(TickerBase):

    @property
    def funds_data(self) -> FundsData:
-        return self.get_funds_data()
+        return self.get_funds_data()
--- a/yfinance/tickers.py
+++ b/yfinance/tickers.py
@@ -22,9 +22,10 @@
 from __future__ import print_function

 from . import Ticker, multi
-
-
-# from collections import namedtuple as _namedtuple
+from .live import WebSocket
+from .utils import print_once
+from .data import YfData
+from .const import _SENTINEL_


 class Tickers:
@@ -38,6 +39,11 @@ class Tickers:
        self.symbols = [ticker.upper() for ticker in tickers]
        self.tickers = {ticker: Ticker(ticker, session=session) for ticker in self.symbols}

+        self._data = YfData(session=session)
+
+        self._message_handler = None
+        self.ws = None
+
        # self.tickers = _namedtuple(
        #     "Tickers", ticker_objects.keys(), rename=True
        # )(*ticker_objects.values())
@@ -45,10 +51,14 @@ class Tickers:
    def history(self, period="1mo", interval="1d",
                start=None, end=None, prepost=False,
                actions=True, auto_adjust=True, repair=False,
-                proxy=None,
+                proxy=_SENTINEL_,
                threads=True, group_by='column', progress=True,
                timeout=10, **kwargs):

+        if proxy is not _SENTINEL_:
+            print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        return self.download(
            period, interval,
            start, end, prepost,
@@ -60,10 +70,14 @@ class Tickers:
    def download(self, period="1mo", interval="1d",
                 start=None, end=None, prepost=False,
                 actions=True, auto_adjust=True, repair=False, 
-                 proxy=None,
+                 proxy=_SENTINEL_,
                 threads=True, group_by='column', progress=True,
                 timeout=10, **kwargs):

+        if proxy is not _SENTINEL_:
+            print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+            self._data._set_proxy(proxy)
+
        data = multi.download(self.symbols,
                              start=start, end=end,
                              actions=actions,
@@ -72,7 +86,6 @@ class Tickers:
                              period=period,
                              interval=interval,
                              prepost=prepost,
-                              proxy=proxy,
                              group_by='ticker',
                              threads=threads,
                              progress=progress,
@@ -90,3 +103,10 @@ class Tickers:

    def news(self):
        return {ticker: [item for item in Ticker(ticker).news] for ticker in self.symbols}
+
+    def live(self, message_handler=None, verbose=True):
+        self._message_handler = message_handler
+
+        self.ws = WebSocket(verbose=verbose)
+        self.ws.subscribe(self.symbols)
+        self.ws.listen(self._message_handler)
--- a/yfinance/utils.py
+++ b/yfinance/utils.py
@@ -23,6 +23,7 @@ from __future__ import print_function

 import datetime as _datetime
 import logging
+import re
 import re as _re
 import sys as _sys
 import threading
@@ -34,16 +35,10 @@ from typing import List, Optional
 import numpy as _np
 import pandas as _pd
 import pytz as _tz
-import requests as _requests
 from dateutil.relativedelta import relativedelta
 from pytz import UnknownTimeZoneError

 from yfinance import const
-from .const import _BASE_URL_
-
-user_agent_headers = {
-    'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36'}
-

 # From https://stackoverflow.com/a/59128615
 def attributes(obj):
@@ -186,40 +181,46 @@ def is_isin(string):
    return bool(_re.match("^([A-Z]{2})([A-Z0-9]{9})([0-9])$", string))


-def get_all_by_isin(isin, proxy=None, session=None):
+def get_all_by_isin(isin, proxy=const._SENTINEL_, session=None):
    if not (is_isin(isin)):
        raise ValueError("Invalid ISIN number")
-    session = session or _requests
-    url = f"{_BASE_URL_}/v1/finance/search?q={isin}"
-    data = session.get(url=url, proxies=proxy, headers=user_agent_headers)
-    try:
-        data = data.json()
-        ticker = data.get('quotes', [{}])[0]
-        return {
-            'ticker': {
-                'symbol': ticker['symbol'],
-                'shortname': ticker['shortname'],
-                'longname': ticker.get('longname',''),
-                'type': ticker['quoteType'],
-                'exchange': ticker['exchDisp'],
-            },
-            'news': data.get('news', [])
-        }
-    except Exception:
-        return {}
+
+    if proxy is not const._SENTINEL_:
+        print_once("YF deprecation warning: set proxy via new config function: yf.set_config(proxy=proxy)")
+        proxy = None
+
+    # Deferred this to prevent circular imports
+    from .search import Search
+
+    search = Search(query=isin, max_results=1, session=session, proxy=proxy)
+
+    # Extract the first quote and news
+    ticker = search.quotes[0] if search.quotes else {}
+    news = search.news
+
+    return {
+        'ticker': {
+            'symbol': ticker.get('symbol', ''),
+            'shortname': ticker.get('shortname', ''),
+            'longname': ticker.get('longname', ''),
+            'type': ticker.get('quoteType', ''),
+            'exchange': ticker.get('exchDisp', ''),
+        },
+        'news': news
+    }


-def get_ticker_by_isin(isin, proxy=None, session=None):
+def get_ticker_by_isin(isin, proxy=const._SENTINEL_, session=None):
    data = get_all_by_isin(isin, proxy, session)
    return data.get('ticker', {}).get('symbol', '')


-def get_info_by_isin(isin, proxy=None, session=None):
+def get_info_by_isin(isin, proxy=const._SENTINEL_, session=None):
    data = get_all_by_isin(isin, proxy, session)
    return data.get('ticker', {})


-def get_news_by_isin(isin, proxy=None, session=None):
+def get_news_by_isin(isin, proxy=const._SENTINEL_, session=None):
    data = get_all_by_isin(isin, proxy, session)
    return data.get('news', {})

@@ -427,26 +428,28 @@ def _parse_user_dt(dt, exchange_tz):


 def _interval_to_timedelta(interval):
-    if interval == "1mo":
-        return relativedelta(months=1)
-    elif interval == "3mo":
-        return relativedelta(months=3)
-    elif interval == "6mo":
-        return relativedelta(months=6)
-    elif interval == "1y":
-        return relativedelta(years=1)
-    elif interval == "2y":
-        return relativedelta(years=2)
-    elif interval == "5y":
-        return relativedelta(years=5)
-    elif interval == "10y":
-        return relativedelta(years=10)
-    elif interval == "1wk":
-        return _pd.Timedelta(days=7)
+    if interval[-1] == "d":
+        return relativedelta(days=int(interval[:-1]))
+    elif interval[-2:] == "wk":
+        return relativedelta(weeks=int(interval[:-2]))
+    elif interval[-2:] == "mo":
+        return relativedelta(months=int(interval[:-2]))
+    elif interval[-1] == "y":
+        return relativedelta(years=int(interval[:-1]))
    else:
        return _pd.Timedelta(interval)


+def is_valid_period_format(period):
+    """Check if the provided period has a valid format."""
+    if period is None:
+        return False
+
+    # Regex pattern to match valid period formats like '1d', '2wk', '3mo', '1y'
+    valid_pattern = r"^[1-9]\d*(d|wk|mo|y)$"
+    return bool(re.match(valid_pattern, period))
+
+
 def auto_adjust(data):
    col_order = data.columns
    df = data.copy()
@@ -521,7 +524,7 @@ def parse_actions(data):
    splits = None

    if "events" in data:
-        if "dividends" in data["events"]:
+        if "dividends" in data["events"] and len(data["events"]['dividends']) > 0:
            dividends = _pd.DataFrame(
                data=list(data["events"]["dividends"].values()))
            dividends.set_index("date", inplace=True)
@@ -529,7 +532,7 @@ def parse_actions(data):
            dividends.sort_index(inplace=True)
            dividends.columns = ["Dividends"]

-        if "capitalGains" in data["events"]:
+        if "capitalGains" in data["events"] and len(data["events"]['capitalGains']) > 0:
            capital_gains = _pd.DataFrame(
                data=list(data["events"]["capitalGains"].values()))
            capital_gains.set_index("date", inplace=True)
@@ -537,7 +540,7 @@ def parse_actions(data):
            capital_gains.sort_index(inplace=True)
            capital_gains.columns = ["Capital Gains"]

-        if "splits" in data["events"]:
+        if "splits" in data["events"] and len(data["events"]['splits']) > 0:
            splits = _pd.DataFrame(
                data=list(data["events"]["splits"].values()))
            splits.set_index("date", inplace=True)
@@ -594,15 +597,40 @@ def fix_Yahoo_returning_prepost_unrequested(quotes, interval, tradingPeriods):
    return quotes


-def fix_Yahoo_returning_live_separate(quotes, interval, tz_exchange, repair=False, currency=None):
+def _dts_in_same_interval(dt1, dt2, interval):
+    # Check if second date dt2 in interval starting at dt1
+
+    if interval == '1d':
+        last_rows_same_interval = dt1.date() == dt2.date()
+    elif interval == "1wk":
+        last_rows_same_interval = (dt2 - dt1).days < 7
+    elif interval == "1mo":
+        last_rows_same_interval = dt1.month == dt2.month
+    elif interval == "3mo":
+        shift = (dt1.month % 3) - 1
+        q1 = (dt1.month - shift - 1) // 3 + 1
+        q2 = (dt2.month - shift - 1) // 3 + 1
+        year_diff = dt2.year - dt1.year
+        quarter_diff = q2 - q1 + 4*year_diff
+        last_rows_same_interval = quarter_diff == 0
+    else:
+        last_rows_same_interval = (dt2 - dt1) < _pd.Timedelta(interval)
+    return last_rows_same_interval
+
+
+def fix_Yahoo_returning_live_separate(quotes, interval, tz_exchange, prepost, repair=False, currency=None):
    # Yahoo bug fix. If market is open today then Yahoo normally returns
    # todays data as a separate row from rest-of week/month interval in above row.
    # Seems to depend on what exchange e.g. crypto OK.
    # Fix = merge them together
-    n = quotes.shape[0]
-    if n > 1:
-        dt1 = quotes.index[n - 1]
-        dt2 = quotes.index[n - 2]
+
+    if interval[-1] not in ['m', 'h']:
+        prepost = False
+
+    dropped_row = None
+    if len(quotes) > 1:
+        dt1 = quotes.index[-1]
+        dt2 = quotes.index[-2]
        if quotes.index.tz is None:
            dt1 = dt1.tz_localize("UTC")
            dt2 = dt2.tz_localize("UTC")
@@ -613,25 +641,23 @@ def fix_Yahoo_returning_live_separate(quotes, interval, tz_exchange, repair=Fals
            # - exception is volume, *slightly* greater on final row (and matches website)
            if dt1.date() == dt2.date():
                # Last two rows are on same day. Drop second-to-last row
+                dropped_row = quotes.iloc[-2]
                quotes = _pd.concat([quotes.iloc[:-2], quotes.iloc[-1:]])
        else:
-            if interval == "1wk":
-                last_rows_same_interval = dt1.year == dt2.year and dt1.week == dt2.week
-            elif interval == "1mo":
-                last_rows_same_interval = dt1.month == dt2.month
-            elif interval == "3mo":
-                last_rows_same_interval = dt1.year == dt2.year and dt1.quarter == dt2.quarter
-            else:
-                last_rows_same_interval = (dt1 - dt2) < _pd.Timedelta(interval)
-
-            if last_rows_same_interval:
+            if _dts_in_same_interval(dt2, dt1, interval):
                # Last two rows are within same interval
-                idx1 = quotes.index[n - 1]
-                idx2 = quotes.index[n - 2]
+                idx1 = quotes.index[-1]
+                idx2 = quotes.index[-2]
                if idx1 == idx2:
                    # Yahoo returning last interval duplicated, which means
                    # Yahoo is not returning live data (phew!)
-                    return quotes
+                    return quotes, None
+
+                if prepost:
+                    # Possibly dt1 is just start of post-market
+                    if dt1.second == 0:
+                        # assume post-market interval
+                        return quotes, None

                ss = quotes['Stock Splits'].iloc[-2:].replace(0,1).prod()
                if repair:
@@ -654,31 +680,30 @@ def fix_Yahoo_returning_live_separate(quotes, interval, tz_exchange, repair=Fals
                            for c in const._PRICE_COLNAMES_:
                                quotes.loc[idx2, c] *= 0.01

-                # quotes.loc[idx2, 'Stock Splits'] = 2  # wtf? why doing this?
-
                if _np.isnan(quotes.loc[idx2, "Open"]):
-                    quotes.loc[idx2, "Open"] = quotes["Open"].iloc[n - 1]
+                    quotes.loc[idx2, "Open"] = quotes["Open"].iloc[-1]
                # Note: nanmax() & nanmin() ignores NaNs, but still need to check not all are NaN to avoid warnings
-                if not _np.isnan(quotes["High"].iloc[n - 1]):
-                    quotes.loc[idx2, "High"] = _np.nanmax([quotes["High"].iloc[n - 1], quotes["High"].iloc[n - 2]])
+                if not _np.isnan(quotes["High"].iloc[-1]):
+                    quotes.loc[idx2, "High"] = _np.nanmax([quotes["High"].iloc[-1], quotes["High"].iloc[-2]])
                    if "Adj High" in quotes.columns:
-                        quotes.loc[idx2, "Adj High"] = _np.nanmax([quotes["Adj High"].iloc[n - 1], quotes["Adj High"].iloc[n - 2]])
+                        quotes.loc[idx2, "Adj High"] = _np.nanmax([quotes["Adj High"].iloc[-1], quotes["Adj High"].iloc[-2]])

-                if not _np.isnan(quotes["Low"].iloc[n - 1]):
-                    quotes.loc[idx2, "Low"] = _np.nanmin([quotes["Low"].iloc[n - 1], quotes["Low"].iloc[n - 2]])
+                if not _np.isnan(quotes["Low"].iloc[-1]):
+                    quotes.loc[idx2, "Low"] = _np.nanmin([quotes["Low"].iloc[-1], quotes["Low"].iloc[-2]])
                    if "Adj Low" in quotes.columns:
-                        quotes.loc[idx2, "Adj Low"] = _np.nanmin([quotes["Adj Low"].iloc[n - 1], quotes["Adj Low"].iloc[n - 2]])
+                        quotes.loc[idx2, "Adj Low"] = _np.nanmin([quotes["Adj Low"].iloc[-1], quotes["Adj Low"].iloc[-2]])

-                quotes.loc[idx2, "Close"] = quotes["Close"].iloc[n - 1]
+                quotes.loc[idx2, "Close"] = quotes["Close"].iloc[-1]
                if "Adj Close" in quotes.columns:
-                    quotes.loc[idx2, "Adj Close"] = quotes["Adj Close"].iloc[n - 1]
-                quotes.loc[idx2, "Volume"] += quotes["Volume"].iloc[n - 1]
-                quotes.loc[idx2, "Dividends"] += quotes["Dividends"].iloc[n - 1]
+                    quotes.loc[idx2, "Adj Close"] = quotes["Adj Close"].iloc[-1]
+                quotes.loc[idx2, "Volume"] += quotes["Volume"].iloc[-1]
+                quotes.loc[idx2, "Dividends"] += quotes["Dividends"].iloc[-1]
                if ss != 1.0:
                    quotes.loc[idx2, "Stock Splits"] = ss
-                quotes = quotes.drop(quotes.index[n - 1])
+                dropped_row = quotes.iloc[-1]
+                quotes = quotes.drop(quotes.index[-1])

-    return quotes
+    return quotes, dropped_row


 def safe_merge_dfs(df_main, df_sub, interval):
@@ -949,10 +974,12 @@ def dynamic_docstring(placeholders: dict):
        return func
    return decorator

-def _generate_table_configurations() -> str:
+def _generate_table_configurations(title = None) -> str:
    import textwrap
-    table = textwrap.dedent("""
-    .. list-table:: Permitted Keys/Values
+    if title is None:
+        title = "Permitted Keys/Values"
+    table = textwrap.dedent(f"""
+    .. list-table:: {title}
       :widths: 25 75
       :header-rows: 1

@@ -962,34 +989,134 @@ def _generate_table_configurations() -> str:

    return table

-def generate_list_table_from_dict(data: dict, bullets: bool=True) -> str:
+def generate_list_table_from_dict(data: dict, bullets: bool=True, title: str=None) -> str:
    """
    Generate a list-table for the docstring showing permitted keys/values.
    """
-    table = _generate_table_configurations()
-    for key, values in data.items():
-        value_str = ', '.join(sorted(values))
-        table += f"   * - {key}\n"
-        if bullets:
-            table += "     -\n"
+    table = _generate_table_configurations(title)
+    for k in sorted(data.keys()):
+        values = data[k]
+        table += ' '*3 + f"* - {k}\n"
+        lengths = [len(str(v)) for v in values]
+        if bullets and max(lengths) > 5:
+            table += ' '*5 + "-\n"
            for value in sorted(values):
-                table += f"       - {value}\n"
+                table += ' '*7 + f"- {value}\n"
        else:
-            table += f"     - {value_str}\n"
+            value_str = ', '.join(sorted(values))
+            table += ' '*5 + f"- {value_str}\n"
    return table

-def generate_list_table_from_dict_of_dict(data: dict, bullets: bool=True) -> str:
+# def generate_list_table_from_dict_of_dict(data: dict, bullets: bool=True, title: str=None) -> str:
+#     """
+#     Generate a list-table for the docstring showing permitted keys/values.
+#     """
+#     table = _generate_table_configurations(title)
+#     for k in sorted(data.keys()):
+#         values = data[k]
+#         table += ' '*3 + f"* - {k}\n"
+#         if bullets:
+#             table += ' '*5 + "-\n"
+#             for value in sorted(values):
+#                 table += ' '*7 + f"- {value}\n"
+#         else:
+#             table += ' '*5 + f"- {values}\n"
+#     return table
+
+
+def generate_list_table_from_dict_universal(data: dict, bullets: bool=True, title: str=None, concat_keys=[]) -> str:
    """
    Generate a list-table for the docstring showing permitted keys/values.
    """
-    table = _generate_table_configurations()
-    for key, values in data.items():
-        value_str = values
-        table += f"   * - {key}\n"
-        if bullets:
-            table += "     -\n"
-            for value in sorted(values):
-                table += f"       - {value}\n"
+    table = _generate_table_configurations(title)
+    for k in data.keys():
+        values = data[k]
+
+        table += ' '*3 + f"* - {k}\n"
+        if isinstance(values, dict):
+            table_add = ''
+
+            concat_short_lines = k in concat_keys
+
+            if bullets:
+                k_keys = sorted(list(values.keys()))
+                current_line = ''
+                block_format = 'query' in k_keys
+                for i in range(len(k_keys)):
+                    k2 = k_keys[i]
+                    k2_values = values[k2]
+                    k2_values_str = None
+                    if isinstance(k2_values, set):
+                        k2_values = list(k2_values)
+                    elif isinstance(k2_values, dict) and len(k2_values) == 0:
+                        k2_values = []
+                    if isinstance(k2_values, list):
+                        k2_values = sorted(k2_values)
+                        all_scalar = all(isinstance(k2v, (int, float, str)) for k2v in k2_values)
+                        if all_scalar:
+                            k2_values_str = _re.sub(r"[{}\[\]']", "", str(k2_values))
+
+                    if k2_values_str is None:
+                        k2_values_str = str(k2_values)
+
+                    if len(current_line) > 0 and (len(current_line) + len(k2_values_str) > 40):
+                        # new line
+                        table_add += current_line + '\n'
+                        current_line = ''
+
+                    if concat_short_lines:
+                        if current_line == '':
+                            current_line += ' '*5
+                            if i == 0:
+                                # Only add dash to first
+                                current_line += "- "
+                            else:
+                                current_line += "  "
+                            # Don't draw bullet points:
+                            current_line += '| '
+                        else:
+                            current_line += '.  '
+                        current_line += f"{k2}: " + k2_values_str
+                    else:
+                        table_add += ' '*5
+                        if i == 0:
+                            # Only add dash to first
+                            table_add += "- "
+                        else:
+                            table_add += "  "
+
+                        if '\n' in k2_values_str:
+                            # Block format multiple lines
+                            table_add += '| ' + f"{k2}: " + "\n"
+                            k2_values_str_lines = k2_values_str.split('\n')
+                            for j in range(len(k2_values_str_lines)):
+                                line = k2_values_str_lines[j]
+                                table_add += ' '*7 + '|' + ' '*5 + line
+                                if j < len(k2_values_str_lines)-1:
+                                    table_add += "\n"
+                        else:
+                            if block_format:
+                                table_add += '| '
+                            else:
+                                table_add += '* '
+                            table_add += f"{k2}: " + k2_values_str
+
+                        table_add += "\n"
+                if current_line != '':
+                    table_add += current_line + '\n'
+            else:
+                table_add += ' '*5 + f"- {values}\n"
+
+            table += table_add
+
        else:
-            table += f"     - {value_str}\n"
-    return table
+            lengths = [len(str(v)) for v in values]
+            if bullets and max(lengths) > 5:
+                table += ' '*5 + "-\n"
+                for value in sorted(values):
+                    table += ' '*7 + f"- {value}\n"
+            else:
+                value_str = ', '.join(sorted(values))
+                table += ' '*5 + f"- {value_str}\n"
+
+    return table
--- a/yfinance/version.py
+++ b/yfinance/version.py
@@ -1 +1 @@
-version = "0.2.50"
+version = "0.2.58"
Author	SHA1	Message	Date
ValueRaider	6f0f408880	Disable setting user-agent, curl_cffi does that	2025-05-06 19:28:17 +01:00
ValueRaider	2608f3660c	Merge pull request #2445 from R5dan/contributing Fix contributing.md	2025-05-05 14:19:47 +01:00
R5dan	e614e6b8ff	Fix contributing.md	2025-05-04 19:39:24 +01:00
ValueRaider	4c609b42c6	fix typo in setup.py	2025-05-03 12:14:48 +01:00
ValueRaider	8ad7b89a9a	fix ruff	2025-05-03 11:19:43 +01:00
ValueRaider	615db18a96	Merge branch 'dev' into main	2025-05-03 11:18:20 +01:00
ValueRaider	537dd468f2	Version 0.2.58	2025-05-02 23:18:26 +01:00
ValueRaider	5fd0d0f66f	Merge pull request #2430 from bretsky/fix/curl-cffi-cookies Incorporate curl_cffi to avoid rate limiting and cookie errors	2025-05-02 22:47:14 +01:00
ValueRaider	fcecf2aa59	Merge pull request #2433 from R5dan/contributing Contributing	2025-05-02 21:40:41 +01:00
ValueRaider	ad33ab9b77	Reduce curl_cffi min version	2025-05-02 21:36:07 +01:00
bretsky	5a3ab9c044	Use curl_cffi impersonate for requests	2025-05-02 21:28:58 +01:00
R5dan	7db2572799	Update docs url	2025-05-02 19:30:43 +01:00
R5dan	11ef919e88	Add how to run	2025-05-02 10:18:40 +01:00
R5dan	0e5fb9614f	Contributing	2025-05-02 10:10:54 +01:00
ValueRaider	af87fbbd53	Merge pull request #2425 from R5dan/fix-screener Fix Screener	2025-05-01 22:52:53 +01:00
R5dan	d07e2061a3	Fix screener size/count for predefined.	2025-05-01 22:51:38 +01:00
ValueRaider	40aa002867	Version 0.2.57	2025-04-28 21:54:13 +01:00
ValueRaider	71e692a268	Merge pull request #2418 from ranaroussi/hotfix/proxy-deprecation-msg Fix 'proxy deprecation' msg	2025-04-28 21:49:14 +01:00
ValueRaider	45e8d6f6f7	Also fix Tickers proxy pass-thru	2025-04-28 21:11:09 +01:00
ValueRaider	1fcf8ad57e	Fix 'proxy deprecation' msg	2025-04-28 20:16:24 +01:00
ValueRaider	2c93db3a79	Merge pull request #2201 from dhruvan2006/feature/websocket Feature: WebSocket Client for Live Data Streaming	2025-04-27 21:36:56 +01:00
Dhruvan Gnanadhandayuthapani	fc5d29558b	Add WebSocket support	2025-04-27 20:39:20 +02:00
Dhruvan Gnanadhandayuthapani	290bf9b7cf	Add protobuf files	2025-04-27 20:35:05 +02:00
ValueRaider	13b26a99d0	README: fix docs url	2025-04-23 22:31:56 +01:00
ValueRaider	c399feabe6	Version 0.2.56	2025-04-23 22:20:32 +01:00
ValueRaider	e0fdd5823f	Merge pull request #2410 from ranaroussi/dev sync dev -> main	2025-04-23 22:18:43 +01:00
ValueRaider	1ed7c39e94	Prices fix: improve handling empty data	2025-04-23 21:48:40 +01:00
ValueRaider	fee9af07ce	Fix tests and a typo	2025-04-23 21:46:36 +01:00
ValueRaider	d64777c6e7	Add new config to RST docs	2025-04-23 19:15:35 +01:00
ValueRaider	cfc7142c56	Merge pull request #2391 from ranaroussi/feature/config Config	2025-04-01 19:36:44 +01:00
ValueRaider	89f1934bd6	Config 1st version: just proxy	2025-03-31 19:06:43 +01:00
ValueRaider	07651ed2f4	Merge pull request #2389 from ranaroussi/fix/prices-live-combine Fix fix_Yahoo_returning_live_separate()	2025-03-31 19:06:06 +01:00
ValueRaider	b1bb75113c	Merge pull request #2364 from dhruvan2006/feature/lookup Feature: Ticker lookups	2025-03-30 21:26:57 +01:00
ValueRaider	a358c8848f	Merge pull request #2388 from JanMkl/fix-issue-2301 Fixes issues 2301 and 2383 AttributeError: module 'requests.cookies' has no attribute 'update'	2025-03-30 21:20:05 +01:00
ValueRaider	fbe9f8f119	Fix fix_Yahoo_returning_live_separate() Was not handling live row on/just-after New Years. Also fixed prepost interval being merged, incorrectly.	2025-03-30 20:38:11 +01:00
Jan Melen	00fec80f63	Merge branch 'dev' into fix-issue-2301	2025-03-30 09:02:59 +03:00
Jan Melen	81c6b2d2e6	Fixes issues 2301 and 2383 AttributeError - In utils.py line 165 if the session is None then _requests is mistakenly passed to as session to data.py which causes attribute error: module 'requests.cookies' has no attribute 'update' - The above condition happens only when searching tickers with ISIN numbers - Added tests with ISIN numbers - Added tickerBase to raise an ValueError if an empty tickername is passed or isin search results in to empty ticker. This is to have consistent behaviour with utils.get_all_by_isin() - Corrected ruff check failures - Rebasing to latest upstream/dev - Updated the value error to contain the ISIN number that wasn't found	2025-03-26 23:57:00 +02:00
ValueRaider	29162bdd01	Merge pull request #2382 from JanMkl/fix-issue-2343 Fixes issue 2343 and 2363 Empty result and QuoteResponse	2025-03-26 21:03:02 +00:00
Jan Melen	587fdd032b	Fixes issue 2343 and 2363 Empty result and QuoteResponse - Check that if result from _fetch was None and either update the result with additional info or set the result as the additional info. - Added test_empty_info test case to protect if the behavior in Yahoo changes. - Fixed typo on line 1024	2025-03-26 06:26:28 +02:00
ValueRaider	8cc002ecbf	Merge pull request #2378 from ranaroussi/fix/prices-end Fix converting end epoch to localized dt	2025-03-23 16:08:16 +00:00
ValueRaider	092a0c8193	Fix converting end epoch to localized dt	2025-03-23 16:07:22 +00:00
Dhruvan Gnanadhandayuthapani	8908724f3c	Add Lookup module documentation and examples	2025-03-23 15:06:17 +01:00
Ran Aroussi	4ecd6a67cf	Updated link	2025-03-22 13:21:44 +00:00
ValueRaider	f3f6739153	README: fix docs link	2025-03-22 11:09:55 +00:00
ValueRaider	9c9f305b0a	Merge pull request #2375 from ranaroussi/main sync main -> dev	2025-03-20 20:44:18 +00:00
ValueRaider	509a33b71d	Merge pull request #2374 from ranaroussi/dev-documented sync Sphinx docs -> dev	2025-03-20 20:42:20 +00:00
ValueRaider	6af17db77d	Merge pull request #2373 from ranaroussi/dev sync dev -> Sphinx docs	2025-03-20 20:39:07 +00:00
ValueRaider	5cc1197c5f	Version 0.2.55	2025-03-20 20:31:28 +00:00
ValueRaider	21a80ec719	Merge pull request #2372 from ranaroussi/dev sync dev -> main	2025-03-20 20:27:45 +00:00
ValueRaider	ca011b0738	Merge pull request #2369 from ranaroussi/fix/prices-tz-fetch-backup In very rare case _fetch_ticker_tz() fails, get TZ from info	2025-03-19 21:15:39 +00:00
ValueRaider	f26b436e0a	In very rare case _fetch_ticker_tz() fails, get TZ from info	2025-03-19 21:11:59 +00:00
ValueRaider	f208f09336	Merge pull request #2345 from dhruvan2006/fix/history-cache Fix: History caching	2025-03-19 19:49:32 +00:00
Dhruvan Gnanadhandayuthapani	f831ac2c1b	Fix history caching and allow period in data retrieval	2025-03-19 12:54:30 +01:00
ValueRaider	e195f2c6c5	Merge pull request #2368 from ranaroussi/fix/price-repair-various Price repair tweaks & fixes	2025-03-17 21:41:19 +00:00
ValueRaider	db5d0c9207	Price repair tweaks & fixes Div repair - new check for div-too-big AND adjust-too-small - improve handling div_too_big_and_pre_split _fix_prices_sudden_change - fix divide-by-zero error - special handling for comparing 'relativedelta' with another Tests - remove delisted tickers - update intraday test data so fetches work - fix intraday div-merge tests	2025-03-17 21:40:29 +00:00
ValueRaider	918eb31583	Merge pull request #2366 from ranaroussi/fix/earnings-dates-tz Fix earnings dates tz	2025-03-17 21:37:24 +00:00
ValueRaider	390422fe6b	Yahoo now returning earnings dates in UTC, stop assuming it's in exchange TZ	2025-03-16 15:55:40 +00:00
Dhruvan Gnanadhandayuthapani	3a7b802b20	Add unit tests for Lookup functionality	2025-03-16 03:07:57 +01:00
Dhruvan Gnanadhandayuthapani	287536ad15	Add Lookup class for Yahoo Finance ticker lookups	2025-03-16 02:57:27 +01:00
ValueRaider	25035a0ff3	Merge pull request #2354 from JanMkl/fix-issue-2343 Fixes issue 2343	2025-03-12 18:29:02 +00:00
Jan Melen	383b60d349	Fixes issue 2343 - Check that result is not zero length before appending it to query_info	2025-03-12 06:31:02 +02:00
ValueRaider	f28284a42d	Merge pull request #2321 from JanMkl/dev Direct TTM Financial Data Retrieval Feature	2025-03-02 19:38:10 +00:00
ValueRaider	fa3094daed	Bug report formatting	2025-03-01 18:02:38 +00:00
Jan Melen	102e266eab	Direct TTM Financial Data Retrieval Feature - Fetches the TTM values for cash flow and income statement from Yahoo. - Added tests test_ttm_income_statement and test_ttm_cash_flow. - When trailing 12 months income statement is fetched Yahoo returns income statement for last 5 quarters out of which only the latest is fully populated. Rest have NaN values and can be ignored. - get_financials_time_series when called with timescale trailing removes from data frame the extra columns. - Added quarterly_income_stmt to financials documentation - Added ttm_income_stmt to financials documentation - Added quarterly_cashflow to financials documentation - Added ttm_cashflow to financials documentation	2025-02-27 18:33:32 +02:00
ValueRaider	31cc2439f7	Merge pull request #2326 from dhruvan2006/refactor/log-user-agent Log user agent	2025-02-24 19:54:03 +00:00
Dhruvan Gnanadhandayuthapani	9b74b4e11f	Add debug log for user-agent header	2025-02-24 20:40:49 +01:00
Ran Aroussi	41426f6678	added star history :)	2025-02-23 21:33:26 +00:00
Ran Aroussi	f09bc07ecc	Update conf.py with logo	2025-02-22 22:35:52 +00:00
Ran Aroussi	dba0cba00b	yfinance logos	2025-02-22 22:34:35 +00:00
Ran Aroussi	eeb2d483d3	Update conf.py	2025-02-22 22:21:27 +00:00
Ran Aroussi	9a6f147de5	Update conf.py	2025-02-22 22:17:21 +00:00
Ran Aroussi	7be3069b6f	Added docs logo	2025-02-22 22:16:13 +00:00
Ran Aroussi	70c84a3482	Set docs domain to yfinance-python.org	2025-02-22 22:10:50 +00:00
Ran Aroussi	ae8720f007	Delete .DS_Store	2025-02-22 19:26:14 +00:00
Ran Aroussi	c388ca73e8	Minor design changes to readme file	2025-02-22 19:25:06 +00:00
Ran Aroussi	7709bc6ae3	yfinance "logo"	2025-02-22 19:06:11 +00:00
Ran Aroussi	9b33910a98	yfinance "logo"	2025-02-22 18:57:12 +00:00
ValueRaider	0ed941c2f5	Merge pull request #2268 from sshcli/PR1 Update README.md	2025-02-22 17:23:44 +00:00
ValueRaider	f2a8d01a13	Merge pull request #2313 from ranaroussi/main sync main -> dev	2025-02-22 13:02:49 +00:00
ValueRaider	403607c721	Version 0.2.54	2025-02-18 22:16:14 +00:00
ValueRaider	604f74ea5e	Merge pull request #2277 from dhruvan2006/fix/user-agent Fix: Change user-agent headers to resolve yfinance download issues	2025-02-18 22:14:43 +00:00
Dhruvan Gnanadhandayuthapani	95b59a7d53	Randomly pick User-Agent header on startup	2025-02-18 23:07:04 +01:00
sshcli	0b8ae726cb	Update README.md	2025-02-17 01:16:52 +00:00
ValueRaider	1ddc38c04f	Version 0.2.53	2025-02-15 18:16:37 +00:00
ValueRaider	fcab4ea37e	Merge pull request #2264 from ranaroussi/dev sync dev -> main	2025-02-15 18:14:44 +00:00
ValueRaider	90053ab7c3	Merge pull request #2265 from ranaroussi/dev sync dev -> Sphinx docs	2025-02-15 18:14:33 +00:00
ValueRaider	d40ad6282a	Merge pull request #2260 from ranaroussi/fix/price-div-repair-tweaks Improve prices div repair	2025-02-15 17:25:21 +00:00
ValueRaider	c95c02fdfc	Improve prices div repair Extend div-repair to intraday Increase lookbacks for 'div date wrong' and 'phantom div' Slightly loosen default 'false threshold' for cluster of mixed False/True Fix bugs in: - detect 'phantom div' - handle div-too-big-and-missing-split Stop checking for down-changes after negative adj-close Handle avg-volume=0%	2025-02-15 17:10:07 +00:00
ValueRaider	5fb9cab817	Disable pytest.yml, need to mock all GETs to restore	2025-02-15 17:00:38 +00:00
ValueRaider	1c39ca4762	Merge pull request #2256 from dhruvan2006/fix/multi-bugs Fix: Interval check and error message formatting in `multi.py`	2025-02-02 17:32:47 +00:00
Dhruvan Gnanadhandayuthapani	27868a4677	Fix interval check and error message formatting in multi.py	2025-02-02 14:15:50 +01:00
ValueRaider	0da75493dc	Merge pull request #2233 from dhruvan2006/fix/tests Add GitHub Actions workflow and fix failing tests	2025-02-01 14:59:14 +00:00
ValueRaider	14c6d05854	Merge pull request #2253 from dhruvan2006/fix/doc-see-also-links Fix: Broken "See also" links in documentation	2025-02-01 13:31:23 +00:00
ValueRaider	8e369a2736	Merge pull request #2250 from R5dan/fix-market-doc Fix Market Docs	2025-02-01 13:25:38 +00:00
R5dan	e09f77eb06	Fix	2025-01-31 22:45:08 +00:00
R5dan	7db798e900	Fix docs	2025-01-31 22:45:08 +00:00
ValueRaider	3b7758b3ab	Version 0.2.52	2025-01-31 22:42:19 +00:00
Dhruvan Gnanadhandayuthapani	b729bcb1df	Fix broken 'See also' links in docs	2025-01-31 15:12:36 +01:00
ValueRaider	6d7c5b6f4c	Merge pull request #2249 from ranaroussi/fix/cookie-csrf-exception Stop CSRF-cookie-fetch fail killing yfinance	2025-01-30 20:25:32 +00:00
ValueRaider	45568fd765	Stop CSRF-cookie-fetch fail killing yfinance	2025-01-30 20:20:43 +00:00
ValueRaider	fc020d953a	Merge pull request #2247 from dhruvan2006/refactor/earnings-dates Refactor: Earnings Dates – Switch to API Fetching	2025-01-29 21:55:27 +00:00
Dhruvan Gnanadhandayuthapani	bc645bb7dd	Refactor earnings dates to use API instead of HTML	2025-01-29 21:53:58 +01:00
Dhruvan Gnanadhandayuthapani	74198aeed4	Add new test workflow	2025-01-27 23:53:36 +01:00
Dhruvan Gnanadhandayuthapani	890922f68b	Fix tests	2025-01-27 23:53:29 +01:00
ValueRaider	44ef4a73ac	Merge pull request #2244 from dhruvan2006/fix/holders-bad-data Fix: Bad data in Holders	2025-01-26 21:23:19 +00:00
ValueRaider	c745df183a	Merge pull request #2212 from ocp1006/ocp1006/fix_pre_post_fetch Add pre- / post-stock prices (and other useful information)	2025-01-26 21:19:54 +00:00
Dhruvan Gnanadhandayuthapani	0e069dbbff	Fix bad data in Holders	2025-01-26 21:27:43 +01:00
ValueRaider	25144351a4	Merge pull request #2230 from ranaroussi/feature/download-warn-autoadjust Warn user when use download() without specifying auto_adjust	2025-01-25 20:59:14 +00:00
ValueRaider	3dd7e40df2	Merge pull request #2234 from dhruvan2006/fix/holders Fix: Failed to parse holders JSON data	2025-01-22 21:50:05 +00:00
Dhruvan Gnanadhandayuthapani	5bbcedfe2e	Fix failed to parse holders JSON data	2025-01-22 19:31:16 +01:00
ValueRaider	fc049e1e0d	Warn user when use download() without specifying auto_adjust	2025-01-19 20:30:35 +00:00
ValueRaider	92c3b9066a	Merge pull request #2229 from ranaroussi/dev sync dev -> Sphinx docs #3	2025-01-18 16:29:12 +00:00
ValueRaider	00a44a8132	Fix dead links in docs API index.rst	2025-01-18 16:28:23 +00:00
ValueRaider	4ec93d90f1	Version 0.2.52	2025-01-18 16:14:36 +00:00
ValueRaider	1081f1e809	Merge pull request #2226 from ranaroussi/dev sync dev -> main	2025-01-18 16:09:49 +00:00
ValueRaider	94327906df	Merge pull request #2228 from ranaroussi/dev sync dev -> Sphinx docs #2	2025-01-18 16:09:40 +00:00
ValueRaider	fed35b175f	Fix typo in screener RST doc file	2025-01-18 16:08:48 +00:00
ValueRaider	07474123a2	Merge pull request #2227 from ranaroussi/dev sync dev -> Sphinx docs	2025-01-18 16:01:19 +00:00
ValueRaider	3f6a46d77d	Merge pull request #2207 from ranaroussi/feature/improve-screener-docs Improve Screener docs	2025-01-18 11:02:35 +00:00
ValueRaider	dee9a55e43	Simplify Screener & improve its docs - screener now just a function, not a class - add 'FundQuery' query class - add 'IS-IN' operator - fix 'GTE' & 'LTE' operators - more exchanges Predefined tweaks: - convert predefined query strings to use EquityQuery (better docs) - send predefined queries to Yahoo's predefined endpoint - expose PREDEFINED_SCREENER_QUERIES via __init__.py - screen() argument defaults don't apply to predefineds	2025-01-17 22:15:18 +00:00
ValueRaider	20b3b438e2	Merge pull request #2211 from dhruvan2006/fix/custom-period Fix: Restore dev branch regression with Ticker.history()	2025-01-11 20:57:26 +00:00
ocp1006	0be2ce1fd5	Add pre- / post-stock prices (and other useful information)	2025-01-08 20:11:26 +02:00
Dhruvan Gnanadhandayuthapani	2d60f9ad2a	Fix custom periods	2025-01-07 13:54:50 +01:00
Dhruvan Gnanadhandayuthapani	2919ccb732	Add utils method for validating period	2025-01-07 13:52:40 +01:00
ValueRaider	ffa697cea1	Merge pull request #2202 from dhruvan2006/fix/search-quotes Fix: Extra key in Search quotes	2025-01-05 15:09:31 +00:00
Dhruvan Gnanadhandayuthapani	e3aae8a8ba	Expand Search test suite	2025-01-03 00:35:53 +01:00
Dhruvan Gnanadhandayuthapani	4ded15740e	Fix extra row in search quotes	2025-01-03 00:33:50 +01:00
ValueRaider	506f792772	Merge pull request #2199 from dhruvan2006/fix/requirements Added missing extra dependencies to requirements.txt	2025-01-02 21:23:27 +00:00
Dhruvan Gnanadhandayuthapani	5a342cf8b0	Add missing dependencies to requirements.txt	2025-01-02 15:06:22 +01:00
ValueRaider	52f6462d20	Merge pull request #2194 from dhruvan2006/fix/eps-revisions Fix: Remove hardcoded keys in Analysis	2025-01-01 21:00:33 +00:00
ValueRaider	508afcae23	Analysis: refactor some fetchers, fix tests Refactor some fetch functions (duplicate logic). Fix failing unit tests.	2025-01-01 20:57:55 +00:00
Dhruvan Gnanadhandayuthapani	a9859e2f9f	Remove hardcoded keys in Analysis	2024-12-31 17:42:03 +01:00
ValueRaider	d0e59203cc	Merge pull request #2191 from R5dan/Update-Search Update Search class to allow more options	2024-12-30 15:09:08 +00:00
R5dan	b94173bddf	Update Search class to allow more options	2024-12-30 15:08:19 +00:00
ValueRaider	a928eb45fd	Merge pull request #2192 from R5dan/custom-period Custom period	2024-12-30 15:03:54 +00:00
R5dan	60c7477a03	Custom period	2024-12-30 15:02:37 +00:00
ValueRaider	42d946cee1	Fix TZ-fetch hiding 429 rate-limit error	2024-12-29 18:34:41 +00:00
ValueRaider	24958d5442	Merge pull request #2175 from R5dan/market-summary-v2 Add market Summary	2024-12-29 17:49:05 +00:00
R5dan	966473f7c7	Add Market summary & status	2024-12-29 17:33:51 +00:00
ValueRaider	ae7f371ada	Merge pull request #2180 from dhruvan2006/rate-limit-exception Raise Exception if Rate Limited	2024-12-22 13:12:11 +00:00
Dhruvan Gnanadhandayuthapani	af7806640f	Raise error if rate limited	2024-12-22 11:12:19 +01:00
ValueRaider	64b4726c4e	Merge pull request #2184 from ranaroussi/main sync main -> dev	2024-12-20 21:39:14 +00:00
ValueRaider	5adddf3e88	Version 0.2.51	2024-12-19 22:46:16 +00:00
ValueRaider	5bbe358ad7	Merge pull request #2182 from ranaroussi/dev dev -> main	2024-12-19 22:42:48 +00:00
ValueRaider	38c1323313	Merge pull request #2169 from hjlgood/main Fix get_earnings_dates method	2024-12-19 22:42:36 +00:00
ValueRaider	70243657a7	Earnings dates: fix time-shift, remove 'add_cokies'	2024-12-18 21:07:30 +00:00
jeong	e242617237	Fix Ticker.earnings_dates	2024-12-18 21:04:21 +00:00
ValueRaider	59d0974773	Merge pull request #2173 from dhruvan2006/feature/full-news Feature: Fetch upto 200 news articles	2024-12-14 22:05:59 +00:00
Dhruvan Gnanadhandayuthapani	5bc3ec01d0	Refactor get_news() to fetch more articles	2024-12-14 18:21:15 +01:00
ValueRaider	3f911745c4	Merge pull request #2171 from R5dan/remove-mkdocs Remove mkdocs	2024-12-08 18:23:22 +00:00
R5dan	f95eef6489	Remove mkdocs	2024-12-08 17:28:41 +00:00
ValueRaider	2fc0907217	Merge pull request #2170 from ranaroussi/dev trigger doc update	2024-12-08 11:13:28 +00:00
ValueRaider	3ac85397cb	Merge pull request #2160 from dhruvan2006/feature/search Feature: Add search feature	2024-12-06 19:44:02 +00:00
Dhruvan Gnanadhandayuthapani	873ab0f574	Added new search feature Refactor Search Added unittest for Search Documentation for Search Fix unused import	2024-12-05 23:53:33 +01:00
ValueRaider	f5264649b9	Merge pull request #2168 from ericpien/screener_return_self Update Screener	2024-12-05 22:36:20 +00:00
Eric Pien	90731511ed	Update Screener - Setting Body to Screener returns the Screener Object to enable method chaining. (i.e. `r = yf.Screener().set_predefined_body("day_gainers").response`) - Limit query size to 250 and raise error if larger. This also avoids unnecessary network calls and makes the issue clearer.	2024-12-04 12:45:14 -08:00
ValueRaider	a8f0998ab8	Merge pull request #2147 from dhruvan2006/fix/price-auto-adjust Default yf.download() to auto adjust prices	2024-11-23 19:57:22 +00:00
Dhruvan Gnanadhandayuthapani	02785d61a1	Default yf.download() to auto adjust prices	2024-11-23 19:50:51 +01:00