Version 0.2.66

dev -> main

.github/ISSUE_TEMPLATE/bug_report.yaml

@@ -18,7 +18,15 @@ body:
 
         Are you spelling symbol *exactly* same as Yahoo?
 
-        Then visit `finance.yahoo.com` and confirm they have the data you want. Maybe your symbol was delisted, or your expectations of `yfinance` are wrong.
+        Then visit `finance.yahoo.com` and confirm they have the data you want. Maybe your symbol was delisted.
+
+        ### Data is wrong
+
+        **yfinance is not affiliated with Yahoo**. If Yahoo Finance website data is bad, tell Yahoo: https://help.yahoo.com/kb/finance-for-web/report-problems-feedback-ideas-yahoo-finance-sln28397.html.
+
+        But if yfinance is creating error during processing, then finish this form.
+
+        For price errors, try price repair: https://ranaroussi.github.io/yfinance/advanced/price_repair.html
 
         ### Are you spamming Yahoo?
 
@@ -54,7 +62,7 @@ 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 +71,7 @@ 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 on Yahoo Finance website here."
     validations:
       required: false
 

.github/workflows/auto_close_default_issues.yml

@@ -0,0 +1,36 @@
+name: Auto-close issues using default template
+on:
+  issues:
+    types: [opened]
+
+jobs:
+  check-template:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check if issue uses custom template
+        uses: actions/github-script@v7
+        with:
+          script: |
+            const issue = context.payload.issue;
+            const body = issue.body || '';
+            
+            // Check for specific fields from your custom form
+            // Adjust these patterns based on your form structure
+            const hasCustomFields = body.includes('### Describe bug') || 
+                                   body.includes('### Simple code that reproduces');
+            
+            if (!hasCustomFields) {
+              await github.rest.issues.createComment({
+                owner: context.repo.owner,
+                repo: context.repo.repo,
+                issue_number: issue.number,
+                body: 'This issue appears to use the default template. Stop that. Use our custom bug report form.'
+              });
+              
+              await github.rest.issues.update({
+                owner: context.repo.owner,
+                repo: context.repo.repo,
+                issue_number: issue.number,
+                state: 'closed'
+              });
+            }

.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

.github/workflows/deploy_doc.yml

@@ -0,0 +1,44 @@
+name: Build and Deploy Sphinx Docs
+
+on:
+  push:
+    branches:
+      - main
+      # - dev-documented
+  workflow_dispatch:
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Check out the repository
+      uses: actions/checkout@v4
+
+    - name: Set up Python
+      uses: actions/setup-python@v5
+      with:
+        python-version: '3.x'
+
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        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
+
+    - name: Build Sphinx documentation
+      run: |
+        sphinx-build -b html doc/source doc/_build/html -v
+
+    - name: List generated HTML files
+      run: |
+        ls -l -R doc/_build/html
+
+    - name: Deploy to GitHub Pages
+      uses: peaceiris/actions-gh-pages@v4
+      with:
+        github_token: ${{ secrets.GITHUB_TOKEN }}
+        publish_branch: documentation
+        publish_dir: doc/_build/html
+        destination_dir: docs
+        enable_jekyll: false

.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

.github/workflows/ruff.yml

@@ -9,5 +9,7 @@ jobs:
   ruff:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v3
-      - uses: chartboost/ruff-action@v1
+      - uses: actions/checkout@v4
+      - uses: astral-sh/ruff-action@v3
+        with:
+          args: check . --exclude yfinance/pricing_pb2.py

.gitignore

@@ -9,7 +9,6 @@ yfinance.egg-info
 build/
 *.html
 *.css
-*.png
 test.ipynb
 
 # Environments
@@ -18,3 +17,10 @@ test.ipynb
 env/
 venv/
 ENV/
+
+# Documentation
+/doc/build/
+/doc/_build/
+/doc/source/reference/api
+!yfinance.css
+!/doc/source/development/assets/branches.png

CHANGELOG.rst

@@ -1,6 +1,157 @@
 Change Log
 ===========
 
+0.2.66
+------
+Screener: add Swiss exchange and industry field
+Support MIC #2579
+Fixes:
+- parse epoch dt #2573
+- earnings_dates #2591
+- merge intraday prices with divs/splits #2595
+- exceptions missing detail #2599
+
+0.2.65
+------
+Financials: ensure dtype float #2563
+Prices: fix handling arguments start/end/period #2561 #2562
+Price repair: when changing FX, update metadata #2558
+
+0.2.64
+------
+Prices:
+- handle dividends with FX, convert if repair=True  #2549
+- fix 'period' arg when start or end set  #2550
+earnings_dates: handle 'Event Type' properly  #2555
+
+0.2.63
+------
+Fix download(ISIN)  # 2531
+
+0.2.62
+------
+Fix prices 'period=max' sometimes failing  # 2509
+ISIN cache  #2516
+Proxy:
+- fix false 'proxy deprecated' messages
+- fix ISIN + proxy  #2514
+- replace print_once with warnings  #2523
+Error handling:
+- detect rate-limit during crumb fetch  #2491
+- replace requests.HTTPError with curl_cffi
+
+0.2.61
+------
+Fix ALL type hints in websocket #2493
+
+0.2.60
+------
+Fix cookie reuse, and handle DNS blocking fc.yahoo.com #2483
+Fixes for websocket:
+- relax protobuf version #2485
+- increase websockets version #2485
+- fix type hints #2488
+Fix predefined screen offset #2440
+
+0.2.59
+------
+Fix the fix for rate-limit #2452
+Feature: live price data websocket #2201
+
+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:
+- price repair #2111 #2139
+- download() appearance 2109
+- isin() error #2099
+- growth_estimates #2127
+Also new docs #2132
+
+0.2.49
+------
+Fix prices-clean rarely discarding good data #2122
+
+0.2.47 and 0.2.48
+-----------------
+Add yf.download(multi_level_index)
+
 0.2.46
 ------
 Fix regression in 0.2.45 #2094

CONTRIBUTING.md

@@ -0,0 +1,60 @@
+# Contributing
+
+yfinance relies on the community to investigate bugs and contribute code.
+
+This is a quick short guide, full guide at https://ranaroussi.github.io/yfinance/development/index.html
+
+## Branches
+
+YFinance uses a two-layer branch model:
+
+* **dev**: new features & most bug-fixes merged here, tested together, conflicts fixed, etc.
+* **main**: stable branch where PIP releases are created.
+
+## Running a branch
+
+```bash
+pip install git+ranaroussi/yfinance.git@dev  # <- dev branch
+```
+
+https://ranaroussi.github.io/yfinance/development/running.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](https://github.com/ranaroussi/yfinance/pulls), from your fork to this project. If addressing an Issue, link to it
+
+https://ranaroussi.github.io/yfinance/development/code.html
+
+## Documentation website
+
+The new docs website is generated automatically from code. https://ranaroussi.github.io/yfinance/index.html
+
+Remember to updates docs when you change code, and check docs locally.
+
+https://ranaroussi.github.io/yfinance/development/documentation.html
+
+## Git tricks
+
+Help keep the Git commit history and [network graph](https://github.com/ranaroussi/yfinance/network) compact:
+
+* got a long descriptive commit message? `git commit -m "short sentence summary" -m "full commit message"`
+
+* combine multiple commits into 1 with `git squash`
+
+* `git rebase` is your friend: change base branch, or "merge in" updates
+
+https://ranaroussi.github.io/yfinance/development/code.html#git-stuff
+
+## Unit tests
+
+Tests have been written using the built-in Python module `unittest`. Examples:
+
+* Run all tests: `python -m unittest discover -s tests`
+
+https://ranaroussi.github.io/yfinance/development/testing.html
+
+> See the [Developer Guide](https://ranaroussi.github.io/yfinance/development/contributing.html#GIT-STUFF) for more information.

README.md

@@ -1,359 +1,63 @@
+<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://pypi.python.org/pypi/yfinance"><img border=0 src="https://img.shields.io/pypi/dm/yfinance.svg?maxAge=86400&label=installs&color=%2327B1FF" alt="PyPi downloads"></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>
 
+<a href="https://trendshift.io/repositories/4578" target="_blank"><img src="https://trendshift.io/api/badge/repositories/4578" alt="ranaroussi%2Fyfinance | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
 
-**yfinance** offers a threaded and Pythonic way to download market data from [Yahoo!Ⓡ finance](https://finance.yahoo.com).
-
-→ Check out this [Blog post](https://aroussi.com/#post/python-yahoo-finance) for a detailed tutorial with code examples.
-
-[Changelog »](https://github.com/ranaroussi/yfinance/blob/main/CHANGELOG.rst)
+**yfinance** offers a Pythonic way to fetch financial & market data from [Yahoo!Ⓡ finance](https://finance.yahoo.com).
 
 ---
 
-- [Installation](#installation)
-- [Quick start](#quick-start)
-- [Advanced](#logging)
-- [Wiki](https://github.com/ranaroussi/yfinance/wiki)
-- [Contribute](#developers-want-to-contribute)
+> [!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
+
 ## Installation
 
-Install `yfinance` using `pip`:
+Install `yfinance` from PYPI using `pip`:
 
 ``` {.sourceCode .bash}
-$ pip install yfinance --upgrade --no-cache-dir
+$ pip install yfinance
 ```
 
-[With Conda](https://anaconda.org/ranaroussi/yfinance).
-
-To install with optional dependencies, replace `optional` with: `nospam` for [caching-requests](#smarter-scraping), `repair` for [price repair](https://github.com/ranaroussi/yfinance/wiki/Price-repair), or `nospam,repair` for both:
-
-``` {.sourceCode .bash}
-$ pip install "yfinance[optional]"
-```
-
-[Required dependencies](./requirements.txt) , [all dependencies](./setup.py#L62).
+### [yfinance relies on the community to investigate bugs and contribute code. Here's how you can help.](CONTRIBUTING.md)
 
 ---
 
-## Quick Start
-
-### The Ticker module
-
-The `Ticker` module, which allows you to access ticker data in a more Pythonic way:
-
-```python
-import yfinance as yf
-
-msft = yf.Ticker("MSFT")
-
-# get all stock info
-msft.info
-
-# get historical market data
-hist = msft.history(period="1mo")
-
-# show meta information about the history (requires history() to be called first)
-msft.history_metadata
-
-# show actions (dividends, splits, capital gains)
-msft.actions
-msft.dividends
-msft.splits
-msft.capital_gains  # only for mutual funds & etfs
-
-# show share count
-msft.get_shares_full(start="2022-01-01", end=None)
-
-# show financials:
-msft.calendar
-msft.sec_filings
-# - income statement
-msft.income_stmt
-msft.quarterly_income_stmt
-# - balance sheet
-msft.balance_sheet
-msft.quarterly_balance_sheet
-# - cash flow statement
-msft.cashflow
-msft.quarterly_cashflow
-# see `Ticker.get_income_stmt()` for more options
-
-# show holders
-msft.major_holders
-msft.institutional_holders
-msft.mutualfund_holders
-msft.insider_transactions
-msft.insider_purchases
-msft.insider_roster_holders
-
-msft.sustainability
-
-# show recommendations
-msft.recommendations
-msft.recommendations_summary
-msft.upgrades_downgrades
-
-# show analysts data
-msft.analyst_price_targets
-msft.earnings_estimate
-msft.revenue_estimate
-msft.earnings_history
-msft.eps_trend
-msft.eps_revisions
-msft.growth_estimates
-
-# Show future and historic earnings dates, returns at most next 4 quarters and last 8 quarters by default.
-# Note: If more are needed use msft.get_earnings_dates(limit=XX) with increased limit argument.
-msft.earnings_dates
-
-# show ISIN code - *experimental*
-# ISIN = International Securities Identification Number
-msft.isin
-
-# show options expirations
-msft.options
-
-# show news
-msft.news
-
-# get option chain for specific expiration
-opt = msft.option_chain('YYYY-MM-DD')
-# data available via: opt.calls, opt.puts
-```
-
-For tickers that are ETFs/Mutual Funds, `Ticker.funds_data` provides access to fund related data. 
-
-Funds' Top Holdings and other data with category average is returned as `pd.DataFrame`.
-
-```python
-import yfinance as yf
-spy = yf.Ticker('SPY')
-data = spy.funds_data
-
-# show fund description
-data.description
-
-# show operational information
-data.fund_overview
-data.fund_operations
-
-# show holdings related information
-data.asset_classes
-data.top_holdings
-data.equity_holdings
-data.bond_holdings
-data.bond_ratings
-data.sector_weightings
-```
-
-If you want to use a proxy server for downloading data, use:
-
-```python
-import yfinance as yf
-
-msft = yf.Ticker("MSFT")
-
-msft.history(..., proxy="PROXY_SERVER")
-msft.get_actions(proxy="PROXY_SERVER")
-msft.get_dividends(proxy="PROXY_SERVER")
-msft.get_splits(proxy="PROXY_SERVER")
-msft.get_capital_gains(proxy="PROXY_SERVER")
-msft.get_balance_sheet(proxy="PROXY_SERVER")
-msft.get_cashflow(proxy="PROXY_SERVER")
-msft.option_chain(..., proxy="PROXY_SERVER")
-...
-```
-
-### Multiple tickers
-
-To initialize multiple `Ticker` objects, use
-
-```python
-import yfinance as yf
-
-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
-```
-
-To download price history into one table:
-
-```python
-import yfinance as yf
-data = yf.download("SPY AAPL", period="1mo")
-```
-
-#### `yf.download()` and `Ticker.history()` have many options for configuring fetching and processing. [Review the Wiki](https://github.com/ranaroussi/yfinance/wiki) for more options and detail.
-
-### Sector and Industry
-
-The `Sector` and `Industry` modules allow you to access the US market information.
-
-To initialize, use the relevant sector or industry key as below. (Complete mapping of the keys is available in `const.py`.)
-
-```python
-import yfinance as yf
-
-tech = yf.Sector('technology')
-software = yf.Industry('software-infrastructure')
-
-# Common information
-tech.key
-tech.name
-tech.symbol
-tech.ticker
-tech.overview
-tech.top_companies
-tech.research_reports
-
-# Sector information
-tech.top_etfs
-tech.top_mutual_funds
-tech.industries
-
-# Industry information
-software.sector_key
-software.sector_name
-software.top_performing_companies
-software.top_growth_companies
-```
-
-The modules can be chained with Ticker as below.
-```python
-import yfinance as yf
-
-# Ticker to Sector and Industry
-msft = yf.Ticker('MSFT')
-tech = yf.Sector(msft.info.get('sectorKey'))
-software = yf.Industry(msft.info.get('industryKey'))
-
-# Sector and Industry to Ticker
-tech_ticker = tech.ticker
-tech_ticker.info
-software_ticker = software.ticker
-software_ticker.history()
-```
-
-### Market Screener
-The `Screener` module allows you to screen the market based on specified queries.
-
-#### Query Construction
-To create a query, you can use the `EquityQuery` class to construct your filters step by step. The queries support operators: `GT` (greater than), `LT` (less than), `BTWN` (between), `EQ` (equals), and logical operators `AND` and `OR` for combining multiple conditions.
-
-#### Screener
-The `Screener` class is used to execute the queries and return the filtered results. You can set a custom body for the screener or use predefined configurations.
-
-<!-- TODO: link to Github Pages for more including list of predefined bodies, supported fields, operands, and sample code -->
-
-### Logging
-
-`yfinance` now uses the `logging` module to handle messages, default behaviour is only print errors. If debugging, use `yf.enable_debug_mode()` to switch logging to debug with custom formatting.
-
-### Smarter scraping
-
-Install the `nospam` packages for smarter scraping using `pip` (see [Installation](#installation)). These packages help cache calls such that Yahoo is not spammed with requests.
-
-To use a custom `requests` session, pass a `session=` argument to
-the Ticker constructor. This allows for caching calls to the API as well as a custom way to modify requests via  the `User-agent` header.
-
-```python
-import requests_cache
-session = requests_cache.CachedSession('yfinance.cache')
-session.headers['User-agent'] = 'my-program/1.0'
-ticker = yf.Ticker('msft', session=session)
-# The scraped response will be stored in the cache
-ticker.actions
-```
-
-Combine `requests_cache` with rate-limiting to avoid triggering Yahoo's rate-limiter/blocker that can corrupt data.
-```python
-from requests import Session
-from requests_cache import CacheMixin, SQLiteCache
-from requests_ratelimiter import LimiterMixin, MemoryQueueBucket
-from pyrate_limiter import Duration, RequestRate, Limiter
-class CachedLimiterSession(CacheMixin, LimiterMixin, Session):
-    pass
-
-session = CachedLimiterSession(
-    limiter=Limiter(RequestRate(2, Duration.SECOND*5)),  # max 2 requests per 5 seconds
-    bucket_class=MemoryQueueBucket,
-    backend=SQLiteCache("yfinance.cache"),
-)
-```
-
-### Managing Multi-Level Columns
-
-The following answer on Stack Overflow is for [How to deal with
-multi-level column names downloaded with
-yfinance?](https://stackoverflow.com/questions/63107801)
-
--   `yfinance` returns a `pandas.DataFrame` with multi-level column
-    names, with a level for the ticker and a level for the stock price
-    data
-    -   The answer discusses:
-        -   How to correctly read the the multi-level columns after
-            saving the dataframe to a csv with `pandas.DataFrame.to_csv`
-        -   How to download single or multiple tickers into a single
-            dataframe with single level column names and a ticker column
-
-### Persistent cache store
-
-To reduce Yahoo, yfinance store some data locally: timezones to localize dates, and cookie. Cache location is:
-
-- Windows = C:/Users/\<USER\>/AppData/Local/py-yfinance
-- Linux = /home/\<USER\>/.cache/py-yfinance
-- MacOS = /Users/\<USER\>/Library/Caches/py-yfinance
-
-You can direct cache to use a different location with `set_tz_cache_location()`:
-
-```python
-import yfinance as yf
-yf.set_tz_cache_location("custom/cache/location")
-...
-```
-
----
-
-## Developers: want to contribute?
-
-`yfinance` relies on community to investigate bugs and contribute code. Developer guide: https://github.com/ranaroussi/yfinance/discussions/1084
+![Star History Chart](https://api.star-history.com/svg?repos=ranaroussi/yfinance)
 
 ---
 
@@ -362,7 +66,6 @@ yf.set_tz_cache_location("custom/cache/location")
 **yfinance** is distributed under the **Apache Software License**. See
 the [LICENSE.txt](./LICENSE.txt) file in the release for details.
 
-
 AGAIN - 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
@@ -378,3 +81,4 @@ details on your rights to use the actual data downloaded.
 Please drop me a note with any feedback you have.
 
 **Ran Aroussi**
+

doc/Makefile

@@ -0,0 +1,20 @@
+# Minimal makefile for Sphinx documentation
+#
+
+# You can set these variables from the command line, and also
+# from the environment for the first two.
+SPHINXOPTS    ?=
+SPHINXBUILD   ?= sphinx-build
+SOURCEDIR     = source
+BUILDDIR      = build
+
+# Put it first so that "make" without argument is like "make help".
+help:
+	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+
+.PHONY: help Makefile
+
+# Catch-all target: route all unknown targets to Sphinx using the new
+# "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
+%: Makefile
+	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

doc/make.bat

@@ -0,0 +1,35 @@
+@ECHO OFF
+
+pushd %~dp0
+
+REM Command file for Sphinx documentation
+
+if "%SPHINXBUILD%" == "" (
+	set SPHINXBUILD=sphinx-build
+)
+set SOURCEDIR=source
+set BUILDDIR=build
+
+%SPHINXBUILD% >NUL 2>NUL
+if errorlevel 9009 (
+	echo.
+	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
+	echo.installed, then set the SPHINXBUILD environment variable to point
+	echo.to the full path of the 'sphinx-build' executable. Alternatively you
+	echo.may add the Sphinx directory to PATH.
+	echo.
+	echo.If you don't have Sphinx installed, grab it from
+	echo.https://www.sphinx-doc.org/
+	exit /b 1
+)
+
+if "%1" == "" goto help
+
+%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+goto end
+
+:help
+%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+
+:end
+popd

doc/source/_static/yfinance.css

@@ -0,0 +1,4 @@
+/* Hide the "Section Navigation" title */
+p.bd-links__title {
+    display: none;
+}

doc/source/_templates/autosummary/class.rst

@@ -0,0 +1,30 @@
+:orphan:
+
+{{ objname | escape | underline }}
+
+.. currentmodule:: {{ module }}
+
+.. autoclass:: {{ objname }}
+   :exclude-members: {% for item in attributes %}{{ item }}{% if not loop.last %}, {% endif %}{% endfor %}
+
+   {% block attributes %}
+   {% if attributes %}
+   .. rubric:: Attributes
+   
+   {% for item in attributes %}
+   .. autoattribute:: {{ item }}
+      :noindex:
+   {%- endfor %}
+   {% endif %}
+   {% endblock attributes %}
+
+   {% block methods %}
+   {% if methods %}
+   .. rubric:: Methods
+
+   {% for item in methods %}
+   .. automethod:: {{ item }}
+      :noindex:
+   {%- endfor %}
+   {% endif %}
+   {% endblock methods %}

doc/source/advanced/caching.rst

@@ -0,0 +1,18 @@
+Caching
+=======
+
+Persistent Cache
+----------------
+
+To reduce Yahoo, yfinance store some data locally: timezones to localize dates, and cookie. Cache location is:
+
+- Windows = C:/Users/\<USER\>/AppData/Local/py-yfinance
+- Linux = /home/\<USER\>/.cache/py-yfinance
+- MacOS = /Users/\<USER\>/Library/Caches/py-yfinance
+
+You can direct cache to use a different location with :attr:`set_tz_cache_location <yfinance.set_tz_cache_location>`:
+
+.. code-block:: python
+
+    import yfinance as yf
+    yf.set_tz_cache_location("custom/cache/location")

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")

doc/source/advanced/index.rst

@@ -0,0 +1,12 @@
+========
+Advanced
+========
+
+.. toctree::
+   :maxdepth: 2
+
+   logging
+   config
+   caching
+   multi_level_columns
+   price_repair

doc/source/advanced/logging.rst

@@ -0,0 +1,11 @@
+Logging
+=======
+
+`yfinance` uses the `logging` module to handle messages. By default, only errors are logged.
+
+If debugging, you can switch to debug mode with custom formatting using:
+
+.. code-block:: python
+
+   import yfinance as yf
+   yf.enable_debug_mode()

doc/source/advanced/multi_level_columns.rst

@@ -0,0 +1,13 @@
+************************
+Multi-Level Column Index
+************************
+
+The following answer on Stack Overflow is for `How to deal with
+multi-level column names downloaded with yfinance? <https://stackoverflow.com/questions/63107801>`_
+
+- `yfinance` returns a `pandas.DataFrame` with multi-level column names, with a level for the ticker and a level for the stock price data
+
+The answer discusses:
+
+- How to correctly read the the multi-level columns after saving the dataframe to a csv with `pandas.DataFrame.to_csv`
+- How to download single or multiple tickers into a singledataframe with single level column names and a ticker column

doc/source/advanced/price_repair.rst

@@ -0,0 +1,277 @@
+************
+Price Repair
+************
+
+The new argument ``repair=True`` in ``history()`` and ``download()`` will attempt to fix a variety of price errors caused by Yahoo. Only US market data appears perfect, I guess Yahoo doesn't care much about rest of world?
+
+The returned table will have a new column ``Repaired?`` that specifies if row was repaired.
+
+Price repair
+============
+
+Missing dividend adjustment
+---------------------------
+
+If dividend in data but preceding ``Adj Close`` = ``Close``, then manually apply dividend-adjustment to ``Adj Close``.
+Note: ``Repaired?`` is NOT set to ``True`` because fix only changes ``Adj Close``
+
+.. figure:: /_static/images/repair-prices-missing-div-adjust.png
+   :alt: 8TRA.DE: repair missing dividend adjustment
+   :width: 80%
+   :align: left
+
+   8TRA.DE
+
+.. container:: clearer
+
+   ..
+
+Missing split adjustment
+------------------------
+
+If stock split in data but preceding price data is not adjusted, then manually apply stock split.
+Requires date range include 1 day after stock split for calibration - sometimes Yahoo fails to adjust prices on stock split day.
+
+.. figure:: /_static/images/repair-prices-missing-split-adjust.png
+   :alt: MOB.ST: repair missing split adjustment
+   :width: 80%
+   :align: left
+
+   MOB.ST
+
+.. container:: clearer
+
+   ..
+
+Missing data
+------------
+
+If price data is clearly missing or corrupt, then reconstructed using smaller interval e.g. ``1h`` to fix ``1d`` data.
+
+.. figure:: /_static/images/repair-prices-missing-row.png
+   :alt: 1COV.DE: repair missing row
+   :width: 80%
+   :align: left
+
+   1COV.DE missing row
+
+.. container:: clearer
+
+   ..
+
+.. figure:: /_static/images/repair-prices-missing-volume-intraday.png
+   :alt: 1COV.DE: repair missing Volume, but intraday price changed
+   :width: 80%
+   :align: left
+
+   1COV.DE missing Volume, but intraday price changed
+
+.. container:: clearer
+
+   ..
+
+.. figure:: /_static/images/repair-prices-missing-volume-daily.png
+   :alt: 0316.HK: repair missing Volume, but daily price changed
+   :width: 80%
+   :align: left
+
+   0316.HK missing Volume, but daily price changed
+
+.. container:: clearer
+
+   ..
+
+100x errors
+-----------
+
+Sometimes Yahoo mixes up currencies e.g. $/cents or £/pence. So some prices are 100x wrong.
+Sometimes they are spread randomly through data - these detected with ``scipy`` module.
+Other times they are in a block, because Yahoo decided one day to permanently switch currency.
+
+.. figure:: /_static/images/repair-prices-100x.png
+   :alt: AET.L: repair 100x
+   :width: 80%
+   :align: left
+
+   AET.L
+
+Price reconstruction - algorithm notes
+--------------------------------------
+
+Spam minimised by grouping fetches. Tries to be aware of data limits e.g. ``1h`` cannot be fetched beyond 2 years.
+
+If Yahoo eventually does fix the bad data that required reconstruction, you will see it's slightly different to reconstructed prices and volume often significantly different. Best I can do, and beats missing data.
+
+Dividend repair (new)
+=====================
+
+Fix errors in dividends:
+
+1. adjustment missing or 100x too small/big for the dividend
+2. duplicate dividend (within 7 days)
+3. dividend 100x too big/small for the ex-dividend price drop
+4. ex-div date wrong (price drop is few days/weeks after)
+
+Most errors I've seen are on London stock exchange (£/pence mixup), but no exchange is safe.
+
+IMPORTANT - false positives
+---------------------------
+
+Because fixing (3) relies on price action, there is a chance of a "false positive" (FP) - thinking an error exists when data is good.
+FP rate increases with longer intervals, so only 1d intervals are repaired. If you request repair on multiday intervals (weekly etc), then: 1d is fetched from Yahoo, repaired, then resampled - **this has nice side-effect of solving Yahoo's flawed way of div-adjusting multiday intervals.**
+
+FP rate on 1d is tiny. They tend to happen with tiny dividends e.g. 0.5%, mistaking normal price volatility for an ex-div drop 100x bigger than the dividend, causing repair of the "too small" dividend (repair logic already tries to account for normal volatility by subtracting median). Either accept the risk, or fetch 6-12 months of prices with at least 2 dividends - then can analyse the dividends together to identify false positives.
+
+Adjustment missing
+------------------
+
+1398.HK
+
+.. code-block:: text
+
+   # ORIGINAL:
+                              Close  Adj Close  Dividends
+   2024-07-08 00:00:00+08:00   4.33       4.33   0.335715
+   2024-07-04 00:00:00+08:00   4.83       4.83   0.000000
+
+.. code-block:: text
+
+   # REPAIRED:
+                              Close  Adj Close  Dividends
+   2024-07-08 00:00:00+08:00   4.33   4.330000   0.335715
+   2024-07-04 00:00:00+08:00   4.83   4.494285   0.000000
+
+Adjustment too small
+--------------------
+
+3IN.L
+
+.. code-block:: text
+
+   # ORIGINAL:
+                              Close  Adj Close  Dividends
+   2024-06-13 00:00:00+01:00  3.185   3.185000    0.05950
+   2024-06-12 00:00:00+01:00  3.270   3.269405    0.00000
+
+.. code-block:: text
+
+   # REPAIRED:
+                              Close  Adj Close  Dividends
+   2024-06-13 00:00:00+01:00  3.185   3.185000    0.05950
+   2024-06-12 00:00:00+01:00  3.270   3.210500    0.00000
+
+Duplicate (within 7 days)
+-------------------------
+
+ALC.SW
+
+.. code-block:: text
+
+   # ORIGINAL:
+                                  Close  Adj Close  Dividends
+   2023-05-10 00:00:00+02:00  70.580002  70.352142       0.21
+   2023-05-09 00:00:00+02:00  65.739998  65.318443       0.21
+   2023-05-08 00:00:00+02:00  66.379997  65.745682       0.00
+
+.. code-block:: text
+
+   # REPAIRED:
+                                  Close  Adj Close  Dividends
+   2023-05-10 00:00:00+02:00  70.580002  70.352142       0.00
+   2023-05-09 00:00:00+02:00  65.739998  65.527764       0.21
+   2023-05-08 00:00:00+02:00  66.379997  65.956371       0.00
+
+Dividend too big
+----------------
+
+HLCL.L
+
+.. code-block:: text
+
+   # ORIGINAL:
+                              Close  Adj Close  Dividends
+   2024-06-27 00:00:00+01:00  2.360     2.3600       1.78
+   2024-06-26 00:00:00+01:00  2.375     2.3572       0.00
+
+   # REPAIRED:
+                              Close  Adj Close  Dividends
+   2024-06-27 00:00:00+01:00  2.360     2.3600     0.0178
+   2024-06-26 00:00:00+01:00  2.375     2.3572     0.0000
+
+Dividend & adjust too big
+-------------------------
+
+LTI.L
+
+.. code-block:: text
+
+   # ORIGINAL:
+                              Close  Adj Close     Adj  Dividends
+   2024-08-08 00:00:00+01:00  768.0      768.0  1.0000     5150.0
+   2024-08-07 00:00:00+01:00  819.0    -4331.0 -5.2882        0.0
+                              Close  Adj Close     Adj  Dividends
+   2024-08-08 00:00:00+01:00  768.0      768.0  1.0000       51.5
+   2024-08-07 00:00:00+01:00  819.0      767.5  0.9371        0.0
+
+Dividend too small
+------------------
+
+BVT.L
+
+.. code-block:: text
+
+   # ORIGINAL:
+                               Close  Adj Close     Adj  Dividends
+   2022-02-03 00:00:00+00:00  0.7534   0.675197  0.8962    0.00001
+   2022-02-01 00:00:00+00:00  0.7844   0.702970  0.8962    0.00000
+
+.. code-block:: text
+
+   # REPAIRED:
+                               Close  Adj Close     Adj  Dividends
+   2022-02-03 00:00:00+00:00  0.7534   0.675197  0.8962      0.001
+   2022-02-01 00:00:00+00:00  0.7844   0.702075  0.8950      0.000
+
+Adjusted 2x on day before
+-------------------------
+
+clue: Close < Low
+
+2020.OL
+
+.. code-block:: text
+
+   # ORIGINAL:
+                                     Low       Close   Adj Close  Dividends
+   2023-12-21 00:00:00+01:00  120.199997  121.099998  118.868782       0.18
+   2023-12-20 00:00:00+01:00  122.000000  121.900002  119.477371       0.00
+
+.. code-block:: text
+
+   # REPAIRED:
+                                     Low       Close   Adj Close  Dividends
+   2023-12-21 00:00:00+01:00  120.199997  121.099998  118.868782       0.18
+   2023-12-20 00:00:00+01:00  122.000000  122.080002  119.654045       0.00
+
+ex-div date wrong
+-----------------
+
+TETY.ST
+
+.. code-block:: text
+
+   # ORIGINAL:
+                                  Close  Adj Close  Dividends
+   2022-06-22 00:00:00+02:00  66.699997  60.085415        0.0
+   2022-06-21 00:00:00+02:00  71.599998  64.499489        0.0
+   2022-06-20 00:00:00+02:00  71.800003  64.679657        5.0
+   2022-06-17 00:00:00+02:00  71.000000  59.454838        0.0
+
+.. code-block:: text
+
+   # REPAIRED:
+                                  Close  Adj Close  Dividends
+   2022-06-22 00:00:00+02:00  66.699997  60.085415        5.0
+   2022-06-21 00:00:00+02:00  71.599998  60.007881        0.0
+   2022-06-20 00:00:00+02:00  71.800003  60.175503        0.0
+   2022-06-17 00:00:00+02:00  71.000000  59.505021        0.0

doc/source/conf.py

@@ -0,0 +1,50 @@
+import os
+import sys
+sys.path.insert(0, os.path.abspath('../..')) 
+
+# Configuration file for the Sphinx documentation builder.
+#
+# For the full list of built-in configuration values, see the documentation:
+# https://www.sphinx-doc.org/en/master/usage/configuration.html
+
+# -- Project information -----------------------------------------------------
+# https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information
+
+project = 'yfinance / Pythonic access to market data'
+copyright = '2017-2025 Ran Aroussi'
+author = 'Ran Aroussi'
+
+# -- General configuration ---------------------------------------------------
+# https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration
+
+extensions = ['sphinx.ext.autodoc',
+              'sphinx.ext.napoleon',
+              "sphinx.ext.githubpages",
+              "sphinx.ext.autosectionlabel",
+              "sphinx.ext.autosummary",
+              "sphinx_copybutton"]
+
+templates_path = ['_templates']
+exclude_patterns = []
+autoclass_content = 'both'
+autosummary_generate = True
+autodoc_default_options = {
+    'exclude-members': '__init__',
+    'members': True,
+}
+
+# -- Options for HTML output -------------------------------------------------
+# https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output
+
+html_title = 'yfinance'
+html_theme = 'pydata_sphinx_theme'
+html_theme_options = {
+    "github_url": "https://github.com/ranaroussi/yfinance",
+    "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']

doc/source/development/code.rst

@@ -0,0 +1,90 @@
+****
+Code
+****
+
+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)
+
+Creating your branch
+--------------------
+
+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/{user}/{repo}.git
+
+3. Create a new branch for your feature or bug fix, from appropriate base branch:
+
+   .. code-block:: bash
+
+      git checkout {base e.g. dev}
+      git pull
+      git checkout -b {your 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, give your commits a very short summary then description:
+
+   .. code-block:: bash
+
+      git commit -m "short sentence summary" -m "full commit message"
+      # Long message can be multiple lines (tip: copy-paste)
+
+6. `Open a pull request on Github <https://github.com/ranaroussi/yfinance/pulls>`_.
+
+Running a branch
+----------------
+
+Please see `this page </development/running>`_.
+
+Git stuff
+---------
+
+- You might be asked to move your branch from ``main`` to ``dev``. This is a ``git rebase``. Remember to update **all** branches involved.
+
+  .. code-block:: bash
+
+     # update all branches:
+     git checkout main
+     git pull
+     git checkout dev
+     git pull
+     # rebase from main to dev:
+     git checkout {your branch}
+     git pull
+     git rebase --onto dev main {your branch}
+     git push --force-with-lease origin {your branch}
+
+- ``git rebase`` can also be used to update your branch with new commits from base, but without adding a commit to your branch history like git merge does. This keeps history clean and avoids future merge problems.
+
+  .. code-block:: bash
+
+     git checkout {base branch e.g. dev}
+     git pull
+     git checkout {your branch}
+     git rebase {base}
+     git push --force-with-lease origin {your branch}
+
+- ``git squash`` tiny or negligible commits with meaningful ones, or to combine successive related commits. `git squash guide <https://docs.gitlab.com/ee/topics/git/git_rebase.html#interactive-rebase>`_
+
+  .. code-block:: bash
+
+     git rebase -i HEAD~2
+     git push --force-with-lease origin {your branch}

doc/source/development/documentation.rst

@@ -0,0 +1,54 @@
+*************
+Documentation
+*************
+
+.. contents:: 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.
+
+Building documentation locally
+-------------------------------
+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:: 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:
+
+   .. code-block:: bash
+
+      sphinx-build -b html doc/source doc/_build/html
+
+3. **View Documentation Locally**:
+
+   .. code-block:: bash
+
+      python -m http.server -d ./doc/_build/html
+
+   Then open "localhost:8000" in browser
+
+
+Publishing documentation
+------------------------
+
+Merge into ``main`` branch triggers auto-generating documentation by action ``.github/workflows/deploy_doc.yml``.
+This publishes the generated HTML into branch ``documentation``.
+
+1. Review the changes locally and push to ``dev``.
+
+2. When ``dev`` gets merged to ``main``, GitHub Actions workflow is automated to build documentation.

doc/source/development/index.rst

@@ -0,0 +1,13 @@
+===========
+Development
+===========
+
+yfinance relies on the community to investigate bugs and contribute code. Here's how you can help:
+
+.. toctree::
+   :maxdepth: 1
+
+   code
+   running
+   documentation
+   testing

doc/source/development/running.rst

@@ -0,0 +1,62 @@
+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'>`

doc/source/development/testing.rst

@@ -0,0 +1,50 @@
+Unit Tests
+----------
+
+Tests are written using Python'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.

doc/source/index.rst

@@ -0,0 +1,74 @@
+yfinance documentation
+======================
+
+Download Market Data from Yahoo! Finance's API
+----------------------------------------------
+
+.. admonition:: 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.
+
+Install
+-------
+
+.. code-block:: bash
+
+    $ pip install yfinance
+
+Quick start
+-----------
+
+Showing a small sample of yfinance API, the full API is much bigger and covered in :doc:`reference/index`.
+
+.. code-block:: python
+
+   import yfinance as yf
+   dat = yf.Ticker("MSFT")
+
+
+One ticker symbol
+
+.. code-block:: python
+
+   dat = yf.Ticker("MSFT")
+   dat.info
+   dat.calendar
+   dat.analyst_price_targets
+   dat.quarterly_income_stmt
+   dat.history(period='1mo')
+   dat.option_chain(dat.options[0]).calls
+
+Multiple ticker symbols
+
+.. code-block:: python
+
+   tickers = yf.Tickers('MSFT AAPL GOOG')
+   tickers.tickers['MSFT'].info
+   yf.download(['MSFT', 'AAPL', 'GOOG'], period='1mo')
+
+Funds
+
+.. code-block:: python
+
+   spy = yf.Ticker('SPY').funds_data
+   spy.description
+   spy.top_holdings
+
+.. toctree::
+   :maxdepth: 1
+   :titlesonly:
+
+   advanced/index
+   reference/index
+   development/index

doc/source/reference/examples/download.py

@@ -0,0 +1,2 @@
+import yfinance as yf
+data = yf.download("SPY AAPL", period="1mo")

doc/source/reference/examples/funds_data.py

@@ -0,0 +1,18 @@
+import yfinance as yf
+spy = yf.Ticker('SPY')
+data = spy.funds_data
+
+# show fund description
+data.description
+
+# show operational information
+data.fund_overview
+data.fund_operations
+
+# show holdings related information
+data.asset_classes
+data.top_holdings
+data.equity_holdings
+data.bond_holdings
+data.bond_ratings
+data.sector_weightings

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())

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)

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)

doc/source/reference/examples/market.py

@@ -0,0 +1,6 @@
+import yfinance as yf
+
+EUROPE = yf.Market("EUROPE")
+
+status = EUROPE.status
+summary = EUROPE.summary

doc/source/reference/examples/proxy.py

@@ -0,0 +1,13 @@
+import yfinance as yf
+
+msft = yf.Ticker("MSFT")
+
+msft.history(..., proxy="PROXY_SERVER")
+msft.get_actions(proxy="PROXY_SERVER")
+msft.get_dividends(proxy="PROXY_SERVER")
+msft.get_splits(proxy="PROXY_SERVER")
+msft.get_capital_gains(proxy="PROXY_SERVER")
+msft.get_balance_sheet(proxy="PROXY_SERVER")
+msft.get_cashflow(proxy="PROXY_SERVER")
+msft.option_chain(..., proxy="PROXY_SERVER")
+...

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

doc/source/reference/examples/sector_industry.py

@@ -0,0 +1,25 @@
+import yfinance as yf
+
+tech = yf.Sector('technology')
+software = yf.Industry('software-infrastructure')
+
+# Common information
+tech.key
+tech.name
+tech.symbol
+tech.ticker
+tech.overview
+tech.top_companies
+tech.research_reports
+
+# Sector information
+tech.top_etfs
+tech.top_mutual_funds
+tech.industries
+
+# Industry information
+software.sector_key
+software.sector_name
+software.top_performing_companies
+software.top_growth_companies
+

doc/source/reference/examples/sector_industry_ticker.py

@@ -0,0 +1,11 @@
+import yfinance as yf
+# Ticker to Sector and Industry
+msft = yf.Ticker('MSFT')
+tech = yf.Sector(msft.info.get('sectorKey'))
+software = yf.Industry(msft.info.get('industryKey'))
+
+# Sector and Industry to Ticker
+tech_ticker = tech.ticker
+tech_ticker.info
+software_ticker = software.ticker
+software_ticker.history()

doc/source/reference/examples/ticker.py

@@ -0,0 +1,25 @@
+import yfinance as yf
+
+dat = yf.Ticker("MSFT")
+
+# get historical market data
+dat.history(period='1mo')
+
+# options
+dat.option_chain(dat.options[0]).calls
+
+# get financials
+dat.balance_sheet
+dat.quarterly_income_stmt
+
+# dates
+dat.calendar
+
+# general info
+dat.info
+
+# analysis
+dat.analyst_price_targets
+
+# websocket
+dat.live()

doc/source/reference/examples/tickers.py

@@ -0,0 +1,11 @@
+import yfinance as yf
+
+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
+
+# websocket
+tickers.live()

doc/source/reference/index.rst

@@ -0,0 +1,50 @@
+=============
+API Reference
+=============
+
+Overview
+--------
+
+The `yfinance` package provides easy access to Yahoo! Finance's API to retrieve market data. It includes classes and functions for downloading historical market data, accessing ticker information, managing cache, and more.
+
+
+Public API
+==========
+
+The following are the publicly available classes, and functions exposed by the `yfinance` package:
+
+- :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:`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.
+
+.. toctree::
+   :maxdepth: 1
+   :hidden:
+
+
+   yfinance.ticker_tickers
+   yfinance.stock
+   yfinance.market
+   yfinance.financials
+   yfinance.analysis
+   yfinance.search
+   yfinance.lookup
+   yfinance.websocket
+   yfinance.sector_industry
+   yfinance.screener
+   yfinance.functions
+
+   yfinance.funds_data
+   yfinance.price_history

doc/source/reference/yfinance.analysis.rst

@@ -0,0 +1,81 @@
+===================
+Analysis & Holdings
+===================
+
+.. currentmodule:: yfinance.Ticker
+
+Analysis
+--------
+
+.. autosummary::
+   :toctree: api/
+   :recursive:
+
+   get_recommendations
+   recommendations
+
+   get_recommendations_summary
+   recommendations_summary
+
+   get_upgrades_downgrades
+   upgrades_downgrades
+
+   get_sustainability
+   sustainability
+
+   get_analyst_price_targets
+   analyst_price_targets
+
+   get_earnings_estimate
+   earnings_estimate
+
+   get_revenue_estimate
+   revenue_estimate
+
+   get_earnings_history
+   earnings_history
+
+   get_eps_trend
+   eps_trend
+
+   get_eps_revisions
+   eps_revisions
+
+   get_growth_estimates
+   growth_estimates
+
+
+Holdings
+--------
+
+.. autosummary::
+   :toctree: api/
+   :recursive:
+
+   get_funds_data
+   funds_data
+
+.. seealso::
+   :meth:`yfinance.scrapers.funds.FundsData`
+
+.. autosummary::
+   :toctree: api/
+   :recursive:
+
+   get_insider_purchases
+   insider_purchases
+
+   get_insider_transactions
+   insider_transactions
+
+   get_insider_roster_holders
+   insider_roster_holders
+
+   get_major_holders
+   major_holders
+
+   get_institutional_holders
+   institutional_holders
+
+   get_mutualfund_holders
+   mutualfund_holders

doc/source/reference/yfinance.financials.rst

@@ -0,0 +1,33 @@
+==========
+Financials
+==========
+
+.. currentmodule:: yfinance.Ticker
+
+.. autosummary::
+   :toctree: api/
+   :recursive:
+
+   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
+
+   calendar
+
+   get_earnings_dates
+   earnings_dates
+
+   get_sec_filings
+   sec_filings

doc/source/reference/yfinance.functions.rst

@@ -0,0 +1,32 @@
+=========================
+Functions and Utilities
+=========================
+
+.. currentmodule:: yfinance
+   
+Download Market Data
+~~~~~~~~~~~~~~~~~~~~~
+The `download` function allows you to retrieve market data for multiple tickers at once.
+
+.. autosummary:: 
+   :toctree: api/
+
+   download
+
+Enable Debug Mode
+~~~~~~~~~~~~~~~~~
+Enables logging of debug information for the `yfinance` package.
+
+.. autosummary:: 
+   :toctree: api/
+
+   enable_debug_mode
+
+Set Timezone Cache Location
+~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Sets the cache location for timezone data.
+
+.. autosummary:: 
+   :toctree: api/
+
+   set_tz_cache_location

doc/source/reference/yfinance.funds_data.rst

@@ -0,0 +1,11 @@
+====================
+`FundsData` class
+====================
+
+.. currentmodule:: yfinance.scrapers.funds
+
+.. autosummary::
+   :toctree: api/
+   :recursive:
+
+   FundsData

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

doc/source/reference/yfinance.price_history.rst

@@ -0,0 +1,9 @@
+====================
+`PriceHistory` class
+====================
+
+.. currentmodule:: yfinance.scrapers.history
+
+.. autoclass:: PriceHistory
+   :members:
+   :undoc-members:

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`
+   

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

doc/source/reference/yfinance.sector_industry.rst

@@ -0,0 +1,32 @@
+=======================
+Sector and Industry
+=======================
+
+.. currentmodule:: yfinance
+
+Sector class
+--------------
+The `Sector` and `Industry` modules provide access to the Sector and Industry information.
+
+.. autosummary::
+   :toctree: api/
+   :recursive:
+
+   Sector
+   Industry
+
+.. seealso::
+   :attr:`Sector.industries <yfinance.Sector.industries>`
+      Map of sector and industry
+
+Sample Code
+---------------------
+To initialize, use the relevant sector or industry key as below.
+
+.. literalinclude:: examples/sector_industry.py
+   :language: python
+
+The modules can be chained with Ticker as below.
+
+.. literalinclude:: examples/sector_industry_ticker.py
+   :language: python

doc/source/reference/yfinance.stock.rst

@@ -0,0 +1,53 @@
+=====
+Stock
+=====
+
+.. currentmodule:: yfinance.Ticker
+
+Ticker stock methods
+--------------------
+
+.. autosummary::
+   :toctree: api/
+   :recursive:
+
+   get_isin
+   isin
+
+   history
+
+.. seealso::
+   :meth:`yfinance.scrapers.history.PriceHistory.history`
+      Documentation for history
+
+   :doc:`../advanced/price_repair`
+      Documentation for price repair
+
+.. autosummary::
+   :toctree: api/
+   :recursive:
+
+   get_history_metadata
+
+   get_dividends
+   dividends
+
+   get_splits
+   splits
+
+   get_actions
+   actions
+
+   get_capital_gains
+   capital_gains
+
+   get_shares_full
+
+   get_info
+   info
+
+   get_fast_info
+   fast_info
+
+   get_news
+   news

doc/source/reference/yfinance.ticker_tickers.rst

@@ -0,0 +1,46 @@
+=====================
+Ticker and Tickers
+=====================
+
+.. currentmodule:: yfinance
+
+
+Class
+------------
+The `Ticker` module, allows you to access ticker data in a Pythonic way.
+
+.. autosummary::
+   :toctree: api/
+
+   Ticker
+   Tickers
+
+
+Ticker Sample Code
+------------------
+The `Ticker` module, allows you to access ticker data in a Pythonic way.
+
+.. literalinclude:: examples/ticker.py
+   :language: python
+
+To initialize multiple `Ticker` objects, use
+
+.. literalinclude:: examples/tickers.py
+   :language: python
+
+For tickers that are ETFs/Mutual Funds, `Ticker.funds_data` provides access to fund related data. 
+
+Funds' Top Holdings and other data with category average is returned as `pd.DataFrame`.
+
+.. literalinclude:: examples/funds_data.py
+   :language: python
+
+If you want to use a proxy server for downloading data, use:
+
+.. literalinclude:: examples/proxy.py
+   :language: python
+
+To initialize multiple `Ticker` objects, use `Tickers` module
+
+.. literalinclude:: examples/tickers.py
+   :language: python

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()

meta.yaml

@@ -1,5 +1,5 @@
 {% set name = "yfinance" %}
-{% set version = "0.2.46" %}
+{% set version = "0.2.66" %}
 
 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:

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'

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
+requests_cache>=1.0
+requests_ratelimiter>=0.3.1
+scipy>=1.6.3
+curl_cffi>=0.7
+protobuf>=3.19.0
+websockets>=13.0

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>=3.19.0', 'websockets>=13.0'],
     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': [

tests/context.py

@@ -5,10 +5,8 @@ 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 pyrate_limiter import Duration, RequestRate, Limiter
+# from requests_ratelimiter import LimiterSession
+# from pyrate_limiter import Duration, RequestRate, Limiter
 
 _parent_dp = os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))
 _src_dp = _parent_dp
@@ -27,19 +25,24 @@ if os.path.isdir(testing_cache_dirpath):
         import shutil
         shutil.rmtree(testing_cache_dirpath)
 
+# Since switching to curl_cffi, the requests_ratelimiter|cache won't work.
+session_gbl = None
 
-# Setup a session to rate-limit and cache persistently:
-class CachedLimiterSession(CacheMixin, LimiterMixin, Session):
-    pass
-history_rate = RequestRate(1, Duration.SECOND*2)
-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
+# # Setup a session to only rate-limit
+# history_rate = RequestRate(1, Duration.SECOND)
+# limiter = Limiter(history_rate)
 # 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)),
+# )

tests/data/KWS-L-1d-bad-div-fixed.csv

@@ -1,666 +0,0 @@
-Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits,Repaired?
-2022-01-04 00:00:00+00:00,29.46,29.98,28.52,28.66,28.567705078125,169521,0.0,0.0,False
-2022-01-05 00:00:00+00:00,30.0,30.0,28.46,28.900000000000002,28.80693115234375,128698,0.0,0.0,False
-2022-01-06 00:00:00+00:00,28.2,28.560000000000002,27.5,27.82,27.730410156250002,374659,0.0,0.0,False
-2022-01-07 00:00:00+00:00,28.3,28.3,27.400000000000002,27.46,27.3715673828125,80410,0.0,0.0,False
-2022-01-10 00:00:00+00:00,28.16,28.240000000000002,26.2,26.580000000000002,26.49440185546875,135881,0.0,0.0,False
-2022-01-11 00:00:00+00:00,25.92,27.060000000000002,25.92,26.72,26.6339501953125,71414,0.0,0.0,False
-2022-01-12 00:00:00+00:00,26.72,26.96,26.060000000000002,26.8,26.7136962890625,68611,0.0,0.0,False
-2022-01-13 00:00:00+00:00,26.72,27.3239990234375,26.6,27.2,27.1124072265625,155917,0.0,0.0,False
-2022-01-14 00:00:00+00:00,27.52,27.52,26.36,26.560000000000002,26.4744677734375,66402,0.0,0.0,False
-2022-01-17 00:00:00+00:00,27.02,27.22,26.28,27.22,27.13234130859375,60092,0.0,0.0,False
-2022-01-18 00:00:00+00:00,27.66,27.66,26.0,26.86,26.773500976562502,128385,0.0,0.0,False
-2022-01-19 00:00:00+00:00,27.0,27.46,26.7,27.2,27.1124072265625,75141,0.0,0.0,False
-2022-01-20 00:00:00+00:00,26.900000000000002,27.7,26.81172119140625,27.54,27.45131103515625,99304,0.0,0.0,False
-2022-01-21 00:00:00+00:00,27.26,27.88,26.214208984375002,26.38,26.295048828125,123570,0.0,0.0,False
-2022-01-24 00:00:00+00:00,26.14,26.261599121093752,24.72,24.88,24.7998779296875,148794,0.0,0.0,False
-2022-01-25 00:00:00+00:00,24.92,25.2,24.580000000000002,24.580000000000002,24.50084228515625,94318,0.0,0.0,False
-2022-01-26 00:00:00+00:00,25.52,25.52,24.400000000000002,24.66,24.58058837890625,265198,0.0,0.0,False
-2022-01-27 00:00:00+00:00,24.66,25.12669921875,24.400000000000002,24.82,24.74007080078125,248811,0.0,0.0,False
-2022-01-28 00:00:00+00:00,24.7,24.88,24.1,24.32,24.241682128906252,146209,0.0,0.0,False
-2022-01-31 00:00:00+00:00,25.3,25.46,24.3,25.2,25.118845214843752,495745,0.0,0.0,False
-2022-02-01 00:00:00+00:00,25.580000000000002,26.78,25.580000000000002,26.7,26.614016113281252,426366,0.0,0.0,False
-2022-02-02 00:00:00+00:00,25.5,27.28,25.5,26.38,26.295048828125,134118,0.0,0.0,False
-2022-02-03 00:00:00+00:00,26.28,26.3639990234375,24.82,24.88,24.7998779296875,168782,0.0,0.0,False
-2022-02-04 00:00:00+00:00,24.6,25.14,24.400000000000002,24.76,24.680263671875,110543,0.0,0.0,False
-2022-02-07 00:00:00+00:00,25.04,25.04,24.54,24.54,24.4609716796875,163853,0.0,0.0,False
-2022-02-08 00:00:00+00:00,24.64,24.64,23.8,24.12,24.04232421875,146007,0.0,0.0,False
-2022-02-09 00:00:00+00:00,24.5,24.98,24.3,24.7,24.62045654296875,130747,0.0,0.0,False
-2022-02-10 00:00:00+00:00,24.52,24.7,24.080000000000002,24.46,24.38123046875,113862,0.0,0.0,False
-2022-02-11 00:00:00+00:00,24.5,24.72,24.1,24.42,24.341357421875,87108,0.0,0.0,False
-2022-02-14 00:00:00+00:00,24.42,24.42,23.34,23.98,23.9027783203125,79188,0.0,0.0,False
-2022-02-15 00:00:00+00:00,23.86,24.560000000000002,23.54,24.22,24.142004394531252,175846,0.0,0.0,False
-2022-02-16 00:00:00+00:00,24.580000000000002,24.580000000000002,23.76,23.98,23.9027783203125,62392,0.0,0.0,False
-2022-02-17 00:00:00+00:00,24.78,24.78,23.86,23.86,23.78316162109375,111791,0.0,0.0,False
-2022-02-18 00:00:00+00:00,23.84,23.94760009765625,23.36,23.48,23.4043896484375,61467,0.0,0.0,False
-2022-02-21 00:00:00+00:00,23.46,23.64919921875,22.82,23.080000000000002,23.005673828125,71820,0.0,0.0,False
-2022-02-22 00:00:00+00:00,24.18,24.18,22.54,23.38,23.30470703125,75721,0.0,0.0,False
-2022-02-23 00:00:00+00:00,23.78,24.04,23.02,23.02,22.945869140625,122317,0.0,0.0,False
-2022-02-24 00:00:00+00:00,23.3,23.3,21.96,22.52,22.44747802734375,241118,0.0,0.0,False
-2022-02-25 00:00:00+00:00,23.0,23.56,22.66,23.32,23.24490234375,147148,0.0,0.0,False
-2022-02-28 00:00:00+00:00,22.36,24.14,22.36,24.14,24.0622607421875,226698,0.0,0.0,False
-2022-03-01 00:00:00+00:00,24.080000000000002,24.22,23.5,23.5,23.4243212890625,218356,0.0,0.0,False
-2022-03-02 00:00:00+00:00,23.7,23.900000000000002,23.26,23.62,23.543935546875,87219,0.0,0.0,False
-2022-03-03 00:00:00+00:00,23.26,23.8,22.14,22.14,22.06870361328125,137377,0.0,0.0,False
-2022-03-04 00:00:00+00:00,22.3,22.92,20.740000000000002,20.740000000000002,20.6732080078125,173972,0.0,0.0,False
-2022-03-07 00:00:00+00:00,20.740000000000002,21.14,19.5,20.3,20.23462646484375,282380,0.0,0.0,False
-2022-03-08 00:00:00+00:00,20.3,20.82,19.52,19.52,19.457138671875,268763,0.0,0.0,False
-2022-03-09 00:00:00+00:00,20.0,21.02,19.73,21.02,20.9523095703125,624876,0.0,0.0,False
-2022-03-10 00:00:00+00:00,21.22,21.22,20.38,20.44,20.374176025390625,266261,0.0,0.0,False
-2022-03-11 00:00:00+00:00,20.66,21.52,20.46,20.900000000000002,20.8326953125,139879,0.0,0.0,False
-2022-03-14 00:00:00+00:00,21.5,21.88,21.1,21.580000000000002,21.51050537109375,87051,0.0,0.0,False
-2022-03-15 00:00:00+00:00,20.72,21.48,20.72,20.96,20.89250244140625,86783,0.0,0.0,False
-2022-03-16 00:00:00+00:00,21.580000000000002,22.72,21.36,22.48,22.40760498046875,118783,0.0,0.0,False
-2022-03-17 00:00:00+00:00,21.68,22.7,21.68,22.46,22.387670898437502,86717,0.0,0.0,False
-2022-03-18 00:00:00+00:00,21.76,23.32,21.76,23.18,23.10535400390625,147084,0.0,0.0,False
-2022-03-21 00:00:00+00:00,23.400000000000002,23.400000000000002,22.26,22.62,22.547155761718752,290436,0.0,0.0,False
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-2022-04-11 00:00:00+01:00,26.560000000000002,26.692480468750002,25.88,26.0,25.916269531250002,106445,0.0,0.0,False
-2022-04-12 00:00:00+01:00,26.0,26.580000000000002,26.0,26.28,26.19536865234375,134222,0.0,0.0,False
-2022-04-13 00:00:00+01:00,26.62,26.62,25.92,26.3,26.215307617187502,151567,0.0,0.0,False
-2022-04-14 00:00:00+01:00,26.240000000000002,26.52,25.79534912109375,26.0,25.916269531250002,203268,0.0,0.0,False
-2022-04-19 00:00:00+01:00,25.8,26.060000000000002,24.96,25.54,25.45775146484375,202763,0.0,0.0,False
-2022-04-20 00:00:00+01:00,25.740000000000002,25.740000000000002,25.12,25.12,25.03910400390625,133972,0.0,0.0,False
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-2022-04-27 00:00:00+01:00,24.0,24.94,23.2,23.46,23.38445068359375,147954,0.0,0.0,False
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-2022-04-29 00:00:00+01:00,23.22,24.16,23.2,24.04,23.9625830078125,139578,0.0,0.0,False
-2022-05-03 00:00:00+01:00,23.6,24.3,23.18,23.48,23.4043896484375,181511,0.0,0.0,False
-2022-05-04 00:00:00+01:00,23.16,23.26,22.24698974609375,22.44,22.36773681640625,199215,0.0,0.0,False
-2022-05-05 00:00:00+01:00,23.52,23.52,22.18,22.26,22.18831298828125,468283,0.0,0.0,False
-2022-05-06 00:00:00+01:00,21.900000000000002,22.06,21.5,22.0,21.92915283203125,119246,0.0,0.0,False
-2022-05-09 00:00:00+01:00,21.88,21.89320068359375,20.8,21.14,21.071923828125,216918,0.0,0.0,False
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tests/data/KWS-L-1d-bad-div.csv

@@ -1,666 +0,0 @@
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tests/data/NVT-L-1d-bad-div-fixed.csv

@@ -1,391 +1,391 @@
 Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits,Capital Gains,Repaired?
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-2022-01-05 00:00:00+00:00,0.6875,0.6751000213623047,0.675,0.6875,0.5880703675715848,15180,0.0,0.0,0.0,True
-2022-01-06 00:00:00+00:00,0.6875,0.6875,0.6875,0.6875,0.5880703675715848,0,0.0,0.0,0.0,True
-2022-01-07 00:00:00+00:00,0.6875,0.6875,0.6875,0.6875,0.5880703675715848,0,0.0,0.0,0.0,True
-2022-01-10 00:00:00+00:00,0.6875,0.6875,0.6875,0.6875,0.5880703675715848,0,0.0,0.0,0.0,True
-2022-01-11 00:00:00+00:00,0.6875,0.6875,0.6875,0.6875,0.5880703675715848,0,0.0,0.0,0.0,True
-2022-01-12 00:00:00+00:00,0.6875,0.6875,0.6875,0.6875,0.5880703675715848,0,0.0,0.0,0.0,True
-2022-01-13 00:00:00+00:00,0.6875,0.6875,0.6875,0.6875,0.5880703675715848,0,0.0,0.0,0.0,True
-2022-01-14 00:00:00+00:00,0.6875,0.6940000152587891,0.675,0.6875,0.5880703675715848,10268,0.0,0.0,0.0,True
-2022-01-17 00:00:00+00:00,0.6875,0.6940000152587891,0.6940000152587891,0.6875,0.5880703675715848,1004,0.0,0.0,0.0,True
-2022-01-18 00:00:00+00:00,0.6875,0.6940000152587891,0.675,0.6875,0.5880703675715848,15202,0.0,0.0,0.0,True
-2022-01-19 00:00:00+00:00,0.6875,0.675,0.67,0.6875,0.5880703675715848,26258,0.0,0.0,0.0,True
-2022-01-20 00:00:00+00:00,0.6875,0.675,0.675,0.6875,0.5880703675715848,11286,0.0,0.0,0.0,True
-2022-01-21 00:00:00+00:00,0.6875,0.6940000152587891,0.6940000152587891,0.6875,0.5880703675715848,653,0.0,0.0,0.0,True
-2022-01-24 00:00:00+00:00,0.6875,0.6940000152587891,0.6940000152587891,0.6875,0.5880703675715848,300,0.0,0.0,0.0,True
-2022-01-25 00:00:00+00:00,0.6875,0.67,0.67,0.6825,0.5837933928330346,18000,0.0,0.0,0.0,True
-2022-01-26 00:00:00+00:00,0.6825,0.6940000152587891,0.6940000152587891,0.6825,0.5837933928330346,1560,0.0,0.0,0.0,True
-2022-01-27 00:00:00+00:00,0.6825,0.67,0.67,0.6825,0.5837933928330346,1000,0.0,0.0,0.0,True
-2022-01-28 00:00:00+00:00,0.6825,0.67,0.67,0.6825,0.5837933928330346,5588,0.0,0.0,0.0,True
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 2023-07-20 00:00:00+01:00,0.5700000000000001,0.5700000000000001,0.5700000000000001,0.5700000000000001,0.5389831924438476,0,0.02,0.0,0.0,False
 2023-07-21 00:00:00+01:00,0.5700000000000001,0.5770000076293945,0.5770000076293945,0.5700000000000001,0.5389831924438476,344,0.0,0.0,0.0,False
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@@ -396,7 +396,7 @@ Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits,Capital Gai
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 2023-08-08 00:00:00+01:00,0.5650000000000001,0.5650000000000001,0.5650000000000001,0.5650000000000001,0.534255256652832,0,0.0,0.0,0.0,False
@@ -684,3 +684,43 @@ Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits,Capital Gai
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tests/data/NVT-L-1d-bad-div.csv

@@ -14,19 +14,19 @@ Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits,Capital Gai
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 2022-02-15 00:00:00+00:00,0.6875,0.68,0.68,0.6875,0.6084982681274415,19756,0.0,0.0,0.0
@@ -52,148 +52,148 @@ Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits,Capital Gai
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@@ -234,91 +234,91 @@ Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits,Capital Gai
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 2023-04-13 00:00:00+01:00,0.5725,0.56,0.56,0.5700000000000001,0.5388005065917969,1459,0.0,0.0,0.0
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@@ -362,9 +362,9 @@ Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits,Capital Gai
 2023-06-13 00:00:00+01:00,0.5650000000000001,0.54,0.54,0.5650000000000001,0.5340741729736328,4006,0.0,0.0,0.0
 2023-06-14 00:00:00+01:00,0.5650000000000001,0.5608000183105469,0.54,0.5650000000000001,0.5340741729736328,3597,0.0,0.0,0.0
 2023-06-15 00:00:00+01:00,0.5650000000000001,0.5650000000000001,0.5650000000000001,0.5650000000000001,0.5340741729736328,0,0.0,0.0,0.0
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-2023-06-20 00:00:00+01:00,0.5975,0.5975,0.5975,0.5975,0.5647952270507812,0,0.0,0.0,0.0
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+2023-06-20 00:00:00+01:00,0.5975,0.5975,0.5975,0.5975,0.5647952651977539,0,0.0,0.0,0.0
 2023-06-21 00:00:00+01:00,0.6,0.6,0.6,0.6,0.5671584320068359,0,0.0,0.0,0.0
 2023-06-22 00:00:00+01:00,0.6,0.6,0.6,0.6,0.5671584320068359,0,0.0,0.0,0.0
 2023-06-23 00:00:00+01:00,0.6,0.585,0.585,0.6,0.5671584320068359,6482,0.0,0.0,0.0
@@ -376,16 +376,16 @@ Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits,Capital Gai
 2023-07-03 00:00:00+01:00,0.6,0.6,0.6,0.6,0.5671584320068359,0,0.0,0.0,0.0
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 2023-07-05 00:00:00+01:00,0.6,0.6,0.6,0.6,0.5671584320068359,0,0.0,0.0,0.0
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@@ -396,7 +396,7 @@ Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits,Capital Gai
 2023-07-31 00:00:00+01:00,0.5650000000000001,0.5650000000000001,0.5650000000000001,0.5650000000000001,0.534255256652832,0,0.0,0.0,0.0
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 2023-08-04 00:00:00+01:00,0.5650000000000001,0.54,0.54,0.5650000000000001,0.534255256652832,1800,0.0,0.0,0.0
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 2023-08-08 00:00:00+01:00,0.5650000000000001,0.5650000000000001,0.5650000000000001,0.5650000000000001,0.534255256652832,0,0.0,0.0,0.0
@@ -684,3 +684,43 @@ Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits,Capital Gai
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tests/data/SCR-TO-1d-bad-div.csv

@@ -1,128 +1,128 @@
 Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits
 2022-01-04 00:00:00-05:00,3.8299999237060547,4.269999980926514,3.8299999237060547,4.0,2.2503862380981445,559600,0.0,0.0
 2022-01-05 00:00:00-05:00,4.050000190734863,4.199999809265137,4.039999961853027,4.050000190734863,2.2785160541534424,467700,0.0,0.0
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 2022-01-10 00:00:00-05:00,4.199999809265137,4.199999809265137,4.119999885559082,4.199999809265137,2.362905502319336,281900,0.0,0.0
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 2022-01-17 00:00:00-05:00,4.570000171661377,4.760000228881836,4.519999980926514,4.679999828338623,2.6329519748687744,317900,0.0,0.0
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 2022-01-24 00:00:00-05:00,4.309999942779541,4.400000095367432,4.070000171661377,4.380000114440918,2.4641730785369873,391900,0.0,0.0
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 2022-01-26 00:00:00-05:00,4.699999809265137,4.75,4.550000190734863,4.570000171661377,2.571066379547119,229400,0.0,0.0
 2022-01-27 00:00:00-05:00,4.590000152587891,4.699999809265137,4.429999828338623,4.480000019073486,2.520432710647583,1782700,0.0,0.0
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 2022-02-01 00:00:00-05:00,4.900000095367432,4.900000095367432,4.75,4.809999942779541,2.706089496612549,245000,0.0,0.0
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 2022-02-03 00:00:00-05:00,4.71999979019165,4.800000190734863,4.579999923706055,4.730000019073486,2.6610817909240723,567100,0.0,0.0
 2022-02-04 00:00:00-05:00,4.760000228881836,4.980000019073486,4.760000228881836,4.880000114440918,2.745471239089966,728600,0.0,0.0
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 2022-02-08 00:00:00-05:00,4.650000095367432,4.650000095367432,4.360000133514404,4.460000038146973,2.509180784225464,520500,0.0,0.0
 2022-02-09 00:00:00-05:00,4.46999979019165,4.619999885559082,4.449999809265137,4.550000190734863,2.559814453125,225400,0.0,0.0
 2022-02-10 00:00:00-05:00,4.519999980926514,4.610000133514404,4.449999809265137,4.510000228881836,2.537310838699341,225300,0.0,0.0
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 2022-02-14 00:00:00-05:00,4.5,4.550000190734863,4.400000095367432,4.510000228881836,2.537310838699341,507600,0.0,0.0
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 2022-02-17 00:00:00-05:00,4.599999904632568,4.659999847412109,4.519999980926514,4.570000171661377,2.571066379547119,309900,0.0,0.0
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 2022-02-22 00:00:00-05:00,4.460000038146973,4.599999904632568,4.429999828338623,4.53000020980835,2.548562526702881,1063700,0.0,0.0
 2022-02-23 00:00:00-05:00,4.590000152587891,4.739999771118164,4.559999942779541,4.679999828338623,2.6329519748687744,256600,0.0,0.0
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 2022-02-28 00:00:00-05:00,4.880000114440918,5.099999904632568,4.869999885559082,5.079999923706055,2.8579905033111572,543200,0.0,0.0
 2022-03-01 00:00:00-05:00,5.159999847412109,5.28000020980835,5.03000020980835,5.179999828338623,2.914250135421753,481700,0.0,0.0
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 2022-05-11 00:00:00-04:00,4.670000076293945,4.670000076293945,4.21999979019165,4.329999923706055,2.4360432624816895,709200,0.0,0.0
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 2022-05-13 00:00:00-04:00,4.429999828338623,4.840000152587891,4.429999828338623,4.769999980926514,2.6835856437683105,800600,0.0,0.0
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 2022-06-24 00:00:00-04:00,3.9100000858306885,4.170000076293945,3.880000114440918,3.9700000286102295,2.233508348464966,708700,0.0,0.0
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 2022-06-28 00:00:00-04:00,4.199999809265137,4.400000095367432,4.179999828338623,4.309999942779541,2.424791097640991,998100,0.0,0.0
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 2022-06-30 00:00:00-04:00,4.0,4.110000133514404,3.8499999046325684,3.9800000190734863,2.2391343116760254,788400,0.0,0.0
 2022-07-04 00:00:00-04:00,4.019999980926514,4.050000190734863,3.890000104904175,4.03000020980835,2.2672643661499023,501500,0.0,0.0
 2022-07-05 00:00:00-04:00,3.9000000953674316,3.930000066757202,3.680000066757202,3.799999952316284,2.137866973876953,1068800,0.0,0.0
@@ -130,57 +130,57 @@ Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits
 2022-07-07 00:00:00-04:00,3.640000104904175,3.7899999618530273,3.640000104904175,3.7300000190734863,2.098485231399536,537500,0.0,0.0
 2022-07-08 00:00:00-04:00,3.75,3.880000114440918,3.640000104904175,3.799999952316284,2.137866973876953,380000,0.0,0.0
 2022-07-11 00:00:00-04:00,3.740000009536743,3.890000104904175,3.640000104904175,3.8299999237060547,2.154744863510132,1113200,0.0,0.0
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 2022-07-13 00:00:00-04:00,3.4600000381469727,3.5799999237060547,3.440000057220459,3.509999990463257,1.974713921546936,537100,0.0,0.0
 2022-07-14 00:00:00-04:00,3.380000114440918,3.4600000381469727,3.259999990463257,3.440000057220459,1.9353322982788086,877700,0.0,0.0
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 2022-07-18 00:00:00-04:00,3.5799999237060547,3.809999942779541,3.559999942779541,3.7699999809265137,2.1209890842437744,1215000,0.0,0.0
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 2022-07-20 00:00:00-04:00,3.819999933242798,3.890000104904175,3.7300000190734863,3.859999895095825,2.1716225147247314,397100,0.0,0.0
 2022-07-21 00:00:00-04:00,3.740000009536743,3.799999952316284,3.619999885559082,3.7100000381469727,2.087233304977417,481600,0.0,0.0
 2022-07-22 00:00:00-04:00,3.740000009536743,3.7899999618530273,3.630000114440918,3.630000114440918,2.0422255992889404,547400,0.0,0.0
 2022-07-25 00:00:00-04:00,3.6500000953674316,3.890000104904175,3.609999895095825,3.8399999141693115,2.1603708267211914,617400,0.0,0.0
 2022-07-26 00:00:00-04:00,3.9000000953674316,3.9800000190734863,3.7899999618530273,3.869999885559082,2.17724871635437,538400,0.0,0.0
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 2022-08-04 00:00:00-04:00,3.859999895095825,3.880000114440918,3.680000066757202,3.680000066757202,2.0703554153442383,809500,0.0,0.0
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 2022-08-08 00:00:00-04:00,3.799999952316284,3.940000057220459,3.759999990463257,3.940000057220459,2.216630458831787,429300,0.0,0.0
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 2022-08-10 00:00:00-04:00,4.039999961853027,4.039999961853027,3.9000000953674316,3.990000009536743,2.244760513305664,848100,0.0,0.0
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 2022-08-12 00:00:00-04:00,4.150000095367432,4.420000076293945,4.110000133514404,4.300000190734863,2.4191653728485107,1629200,0.0,0.0
 2022-08-15 00:00:00-04:00,4.110000133514404,4.369999885559082,4.03000020980835,4.300000190734863,2.4191653728485107,712300,0.0,0.0
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 2022-08-18 00:00:00-04:00,4.349999904632568,4.639999866485596,4.349999904632568,4.550000190734863,2.559814453125,1213700,0.0,0.0
 2022-08-19 00:00:00-04:00,4.610000133514404,4.650000095367432,4.489999771118164,4.5,2.531684637069702,348900,0.0,0.0
 2022-08-22 00:00:00-04:00,4.460000038146973,4.519999980926514,4.349999904632568,4.510000228881836,2.537310838699341,589300,0.0,0.0
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 2022-08-26 00:00:00-04:00,5.059999942779541,5.170000076293945,5.010000228881836,5.010000228881836,2.8186089992523193,342300,0.0,0.0
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 2022-08-30 00:00:00-04:00,5.070000171661377,5.070000171661377,4.900000095367432,4.940000057220459,2.7792270183563232,335300,0.0,0.0
 2022-08-31 00:00:00-04:00,4.849999904632568,5.050000190734863,4.78000020980835,4.880000114440918,2.745471239089966,517200,0.0,0.0
 2022-09-01 00:00:00-04:00,4.880000114440918,4.880000114440918,4.570000171661377,4.619999885559082,2.599195957183838,587000,0.0,0.0
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 2022-09-08 00:00:00-04:00,4.449999809265137,4.539999961853027,4.409999847412109,4.480000019073486,2.520432710647583,369200,0.0,0.0
 2022-09-09 00:00:00-04:00,4.559999942779541,4.809999942779541,4.559999942779541,4.78000020980835,2.689211845397949,513000,0.0,0.0
 2022-09-12 00:00:00-04:00,4.789999961853027,4.880000114440918,4.739999771118164,4.829999923706055,2.717341423034668,285000,0.0,0.0
 2022-09-13 00:00:00-04:00,4.800000190734863,4.849999904632568,4.71999979019165,4.760000228881836,2.67795991897583,225800,0.0,0.0
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 2022-09-19 00:00:00-04:00,4.5,4.659999847412109,4.389999866485596,4.639999866485596,2.610448122024536,537500,0.0,0.0
 2022-09-20 00:00:00-04:00,4.639999866485596,4.639999866485596,4.429999828338623,4.480000019073486,2.520432710647583,400900,0.0,0.0
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 2022-09-23 00:00:00-04:00,4.0,4.0,3.5999999046325684,3.700000047683716,2.0816073417663574,960400,0.0,0.0
 2022-09-26 00:00:00-04:00,3.690000057220459,3.75,3.3299999237060547,3.369999885559082,1.895950436592102,683500,0.0,0.0
 2022-09-27 00:00:00-04:00,3.440000057220459,3.4700000286102295,3.3399999141693115,3.380000114440918,1.9015765190124512,931200,0.0,0.0
@@ -188,243 +188,243 @@ Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits
 2022-09-29 00:00:00-04:00,3.5899999141693115,3.75,3.4800000190734863,3.740000009536743,2.1041111946105957,640300,0.0,0.0
 2022-09-30 00:00:00-04:00,3.6700000762939453,3.7699999809265137,3.569999933242798,3.700000047683716,2.0816073417663574,536300,0.0,0.0
 2022-10-03 00:00:00-04:00,3.809999942779541,3.940000057220459,3.7699999809265137,3.9000000953674316,2.194126844406128,656400,0.0,0.0
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 2022-10-06 00:00:00-04:00,4.139999866485596,4.409999847412109,4.139999866485596,4.380000114440918,2.4641730785369873,418100,0.0,0.0
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 2022-10-11 00:00:00-04:00,4.090000152587891,4.099999904632568,3.859999895095825,3.990000009536743,2.244760513305664,307800,0.0,0.0
 2022-10-12 00:00:00-04:00,3.940000057220459,3.9800000190734863,3.8399999141693115,3.9700000286102295,2.233508348464966,371100,0.0,0.0
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 2022-10-19 00:00:00-04:00,3.9000000953674316,4.0,3.869999885559082,3.990000009536743,2.244760513305664,379500,0.0,0.0
 2022-10-20 00:00:00-04:00,4.0,4.130000114440918,3.9600000381469727,3.990000009536743,2.244760513305664,453900,0.0,0.0
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 2022-10-26 00:00:00-04:00,4.050000190734863,4.230000019073486,4.050000190734863,4.210000038146973,2.3685317039489746,877200,0.0,0.0
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 2022-11-01 00:00:00-04:00,4.230000019073486,4.25,4.139999866485596,4.179999828338623,2.351653575897217,319700,0.0,0.0
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 2022-11-18 00:00:00-05:00,3.299999952316284,3.3499999046325684,3.2300000190734863,3.3299999237060547,1.8734464645385742,1005000,0.0,0.0
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 2022-12-02 00:00:00-05:00,3.369999885559082,3.450000047683716,3.3299999237060547,3.3499999046325684,1.8846986293792725,319600,0.0,0.0
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 2022-12-06 00:00:00-05:00,3.2899999618530273,3.3499999046325684,3.0799999237060547,3.0799999237060547,1.732797384262085,1268000,0.0,0.0
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 2022-12-09 00:00:00-05:00,3.0199999809265137,3.059999942779541,2.950000047683716,3.059999942779541,1.7215455770492554,779100,0.0,0.0
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 2023-01-04 00:00:00-05:00,2.7699999809265137,2.7799999713897705,2.680000066757202,2.7100000381469727,1.5246367454528809,735100,0.0,0.0
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 2023-01-09 00:00:00-05:00,2.859999895095825,2.950000047683716,2.819999933242798,2.880000114440918,1.620278239250183,491400,0.0,0.0
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 2023-01-12 00:00:00-05:00,2.9700000286102295,3.0799999237060547,2.950000047683716,3.0399999618530273,1.7102934122085571,900700,0.0,0.0
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 2023-01-18 00:00:00-05:00,3.190000057220459,3.2899999618530273,3.130000114440918,3.130000114440918,1.760927438735962,707500,0.0,0.0
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 2023-05-26 00:00:00-04:00,2.4000000953674316,2.4700000286102295,2.369999885559082,2.4000000953674316,1.5923840999603271,150100,0.0,0.0
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 2023-08-29 00:00:00-04:00,2.1600000858306885,2.200000047683716,2.1500000953674316,2.190000057220459,1.7768479585647583,245600,0.0,0.0
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 2023-09-05 00:00:00-04:00,2.4200000762939453,2.4200000762939453,2.2699999809265137,2.390000104904175,1.939117193222046,1434000,0.0,0.0
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 2023-09-07 00:00:00-04:00,2.359999895095825,2.390000104904175,2.319999933242798,2.3499999046325684,1.906663179397583,501700,0.0,0.0
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 2023-09-11 00:00:00-04:00,2.390000104904175,2.4200000762939453,2.3299999237060547,2.3499999046325684,1.906663179397583,740800,0.0,0.0
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-2023-09-13 00:00:00-04:00,2.440000057220459,2.4600000381469727,2.4000000953674316,2.430000066757202,1.9715710878372192,328600,0.0,0.0
+2023-09-12 00:00:00-04:00,2.3499999046325684,2.440000057220459,2.3499999046325684,2.430000066757202,1.9715709686279297,696100,0.0,0.0
+2023-09-13 00:00:00-04:00,2.440000057220459,2.4600000381469727,2.4000000953674316,2.430000066757202,1.9715709686279297,328600,0.0,0.0
 2023-09-14 00:00:00-04:00,2.450000047683716,2.5199999809265137,2.430000066757202,2.5199999809265137,2.497917890548706,553500,0.441,0.0
 2023-09-15 00:00:00-04:00,2.5,2.640000104904175,2.4800000190734863,2.569999933242798,2.5474798679351807,770400,0.0,0.0
 2023-09-18 00:00:00-04:00,2.569999933242798,2.640000104904175,2.5299999713897705,2.559999942779541,2.537567377090454,753200,0.0,0.0
@@ -687,3 +687,37 @@ Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits
 2024-09-25 00:00:00-04:00,27.8700008392334,27.8700008392334,27.0,27.489999771118164,27.489999771118164,30200,0.0,0.0
 2024-09-26 00:00:00-04:00,27.299999237060547,27.479999542236328,26.559999465942383,26.610000610351562,26.610000610351562,51800,0.0,0.0
 2024-09-27 00:00:00-04:00,26.989999771118164,26.989999771118164,26.25,26.579999923706055,26.579999923706055,20600,0.0,0.0
+2024-09-30 00:00:00-04:00,26.610000610351562,27.0,26.5,26.950000762939453,26.950000762939453,25200,0.0,0.0
+2024-10-01 00:00:00-04:00,26.969999313354492,27.690000534057617,26.93000030517578,27.3799991607666,27.3799991607666,42600,0.0,0.0
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tests/data/SOLB-BR-1d-bad-div-fixed.csv

@@ -1,678 +0,0 @@
-Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits,Repaired?
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tests/data/SOLB-BR-1d-bad-div.csv

@@ -1,678 +0,0 @@
-Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits
-2022-01-03 00:00:00+01:00,20.400468826293945,20.80828094482422,20.400468826293945,20.629241943359375,11.042257308959961,559352,0.0,0.0
-2022-01-04 00:00:00+01:00,20.649133682250977,20.897798538208008,20.5098819732666,20.848066329956055,11.15938663482666,930594,0.0,0.0
-2022-01-05 00:00:00+01:00,20.897798538208008,21.126571655273438,20.838119506835938,21.126571655273438,11.308463096618652,572100,0.0,0.0
-2022-01-06 00:00:00+01:00,20.887853622436523,21.126571655273438,20.599401473999023,20.967424392700195,11.223275184631348,532086,0.0,0.0
-2022-01-07 00:00:00+01:00,21.007211685180664,21.186250686645508,20.867958068847656,21.126571655273438,11.308463096618652,698666,0.0,0.0
-2022-01-10 00:00:00+01:00,21.186250686645508,21.245929718017578,20.997264862060547,21.05694580078125,11.271193504333496,972438,0.0,0.0
-2022-01-11 00:00:00+01:00,21.226036071777344,21.514488220214844,21.226036071777344,21.37523651123047,11.441567420959473,894602,0.0,0.0
-2022-01-12 00:00:00+01:00,21.564220428466797,21.604007720947266,21.0469970703125,21.216089248657227,11.356378555297852,838352,0.0,0.0
-2022-01-13 00:00:00+01:00,20.897798538208008,21.14646339416504,20.897798538208008,21.14646339416504,12.180269241333008,514241,1.5,0.0
-2022-01-14 00:00:00+01:00,20.897798538208008,21.066890716552734,20.80828094482422,21.0271053314209,12.111518859863281,708327,0.0,0.0
-2022-01-17 00:00:00+01:00,21.106678009033203,21.633846282958984,21.0469970703125,21.554275512695312,12.415165901184082,947841,0.0,0.0
-2022-01-18 00:00:00+01:00,21.454809188842773,21.484647750854492,21.156410217285156,21.405075073242188,12.329227447509766,966355,0.0,0.0
-2022-01-19 00:00:00+01:00,21.37523651123047,21.822832107543945,21.295663833618164,21.78304672241211,12.546936988830566,1597827,0.0,0.0
-2022-01-20 00:00:00+01:00,21.802940368652344,22.111284255981445,21.544328689575195,21.981977462768555,12.661520004272461,1563328,0.0,0.0
-2022-01-21 00:00:00+01:00,21.74325942993164,21.94219207763672,21.415021896362305,21.65374183654785,12.47245979309082,1539782,0.0,0.0
-2022-01-24 00:00:00+01:00,21.484647750854492,21.58411407470703,20.887853622436523,20.997264862060547,12.094330787658691,1334240,0.0,0.0
-2022-01-25 00:00:00+01:00,21.156410217285156,21.186250686645508,20.877906799316406,20.917692184448242,12.04849910736084,1198631,0.0,0.0
-2022-01-26 00:00:00+01:00,20.997264862060547,21.72336769104004,20.997264862060547,21.415021896362305,12.33495807647705,913216,0.0,0.0
-2022-01-27 00:00:00+01:00,21.11662483215332,21.862619400024414,21.0469970703125,21.6437931060791,12.466729164123535,765306,0.0,0.0
-2022-01-28 00:00:00+01:00,21.554275512695312,21.65374183654785,21.126571655273438,21.484647750854492,12.37506103515625,1109097,0.0,0.0
-2022-01-31 00:00:00+01:00,21.6239013671875,21.65374183654785,21.066890716552734,21.186250686645508,12.203185081481934,999557,0.0,0.0
-2022-02-01 00:00:00+01:00,21.27577018737793,21.405075073242188,21.05694580078125,21.11662483215332,12.163081169128418,732572,0.0,0.0
-2022-02-02 00:00:00+01:00,21.52443504333496,22.021764755249023,21.454809188842773,21.753206253051758,12.529748916625977,1195479,0.0,0.0
-2022-02-03 00:00:00+01:00,21.773099899291992,21.892459869384766,21.6239013671875,21.773099899291992,12.541210174560547,906159,0.0,0.0
-2022-02-04 00:00:00+01:00,21.87256622314453,21.87256622314453,21.345396041870117,21.424968719482422,12.34068489074707,763864,0.0,0.0
-2022-02-07 00:00:00+01:00,21.574167251586914,21.574167251586914,21.265823364257812,21.415021896362305,12.33495807647705,382854,0.0,0.0
-2022-02-08 00:00:00+01:00,21.36528968811035,21.78304672241211,21.36528968811035,21.713420867919922,12.506834030151367,1006721,0.0,0.0
-2022-02-09 00:00:00+01:00,21.812885284423828,21.991924285888672,21.733312606811523,21.981977462768555,12.661520004272461,893571,0.0,0.0
-2022-02-10 00:00:00+01:00,22.021764755249023,22.210750579833984,21.962085723876953,22.041658401489258,12.69589614868164,851844,0.0,0.0
-2022-02-11 00:00:00+01:00,21.882511138916016,22.06155014038086,21.713420867919922,21.882511138916016,12.604229927062988,893486,0.0,0.0
-2022-02-14 00:00:00+01:00,21.514488220214844,21.514488220214844,20.818225860595703,21.14646339416504,12.180269241333008,1234728,0.0,0.0
-2022-02-15 00:00:00+01:00,21.007211685180664,21.713420867919922,20.967424392700195,21.673633575439453,12.483916282653809,687285,0.0,0.0
-2022-02-16 00:00:00+01:00,21.713420867919922,22.06155014038086,21.713420867919922,22.06155014038086,12.707352638244629,798177,0.0,0.0
-2022-02-17 00:00:00+01:00,22.021764755249023,22.081443786621094,21.763153076171875,21.832778930664062,12.575582504272461,684218,0.0,0.0
-2022-02-18 00:00:00+01:00,21.832778930664062,21.892459869384766,21.385181427001953,21.544328689575195,12.40943717956543,737030,0.0,0.0
-2022-02-21 00:00:00+01:00,21.673633575439453,21.68358039855957,20.92763900756836,21.126571655273438,12.168810844421387,677844,0.0,0.0
-2022-02-22 00:00:00+01:00,20.529775619506836,21.196197509765625,20.32089614868164,20.95747947692871,12.071414947509766,1273455,0.0,0.0
-2022-02-23 00:00:00+01:00,21.415021896362305,21.862619400024414,20.987319946289062,21.216089248657227,12.220373153686523,1732461,0.0,0.0
-2022-02-24 00:00:00+01:00,20.48004150390625,20.877906799316406,19.51124382019043,19.70221710205078,11.348388671875,2560976,0.0,0.0
-2022-02-25 00:00:00+01:00,19.903139114379883,20.291057586669922,19.475435256958008,20.201536178588867,11.635993957519531,1423396,0.0,0.0
-2022-02-28 00:00:00+01:00,19.773834228515625,19.903139114379883,19.308332443237305,19.837491989135742,11.42630672454834,1569727,0.0,0.0
-2022-03-01 00:00:00+01:00,19.77781105041504,19.95287322998047,18.73938751220703,18.73938751220703,10.793804168701172,1308216,0.0,0.0
-2022-03-02 00:00:00+01:00,18.536476135253906,19.12929344177246,18.17840003967285,18.966169357299805,10.924428939819336,1739856,0.0,0.0
-2022-03-03 00:00:00+01:00,19.001977920532227,19.077571868896484,18.297758102416992,18.361417770385742,10.576094627380371,834767,0.0,0.0
-2022-03-04 00:00:00+01:00,18.13463592529297,18.14259147644043,16.893299102783203,17.05642318725586,9.824423789978027,2249030,0.0,0.0
-2022-03-07 00:00:00+01:00,16.384033203125,17.10814666748047,15.516690254211426,16.380054473876953,9.434837341308594,2250820,0.0,0.0
-2022-03-08 00:00:00+01:00,16.21295166015625,16.941043853759766,16.16520881652832,16.805768966674805,9.680047035217285,1388112,0.0,0.0
-2022-03-09 00:00:00+01:00,17.207611083984375,18.22614288330078,17.17976188659668,18.22614288330078,10.498175621032715,1580329,0.0,0.0
-2022-03-10 00:00:00+01:00,18.38926887512207,18.429054260253906,17.44632911682129,17.696983337402344,10.19338321685791,1037018,0.0,0.0
-2022-03-11 00:00:00+01:00,17.88397979736328,18.369373321533203,17.585582733154297,17.943660736083984,10.335468292236328,985960,0.0,0.0
-2022-03-14 00:00:00+01:00,18.285823822021484,18.747344970703125,18.250015258789062,18.52056312561035,10.667760848999023,963701,0.0,0.0
-2022-03-15 00:00:00+01:00,19.79372787475586,19.893192291259766,17.99538230895996,18.15452766418457,10.456925392150879,2685295,0.0,0.0
-2022-03-16 00:00:00+01:00,18.78713035583496,18.9741268157959,18.369373321533203,18.76723861694336,10.809844970703125,1321768,0.0,0.0
-2022-03-17 00:00:00+01:00,18.89853286743164,18.966169357299805,18.433032989501953,18.854768753051758,10.860261917114258,1124314,0.0,0.0
-2022-03-18 00:00:00+01:00,18.894554138183594,18.98606300354004,18.47281837463379,18.7990665435791,10.828178405761719,1809744,0.0,0.0
-2022-03-21 00:00:00+01:00,18.7990665435791,19.15714454650879,18.763259887695312,18.91046905517578,10.892345428466797,703039,0.0,0.0
-2022-03-22 00:00:00+01:00,18.966169357299805,19.184995651245117,18.85079002380371,19.05767822265625,10.977137565612793,715772,0.0,0.0
-2022-03-23 00:00:00+01:00,19.121337890625,19.15714454650879,18.671751022338867,18.671751022338867,10.75484561920166,1351532,0.0,0.0
-2022-03-24 00:00:00+01:00,18.659814834594727,18.731430053710938,18.234100341796875,18.30173683166504,10.541718482971191,1286093,0.0,0.0
-2022-03-25 00:00:00+01:00,18.405181884765625,18.47281837463379,18.170442581176758,18.285823822021484,10.532552719116211,726494,0.0,0.0
-2022-03-28 00:00:00+02:00,18.393245697021484,18.759281158447266,18.329587936401367,18.433032989501953,10.61734390258789,837768,0.0,0.0
-2022-03-29 00:00:00+02:00,18.72745132446289,19.256610870361328,18.687665939331055,19.16908073425293,11.041305541992188,917861,0.0,0.0
-2022-03-30 00:00:00+02:00,19.15714454650879,19.15714454650879,18.46088218688965,18.50862693786621,10.66088581085205,823527,0.0,0.0
-2022-03-31 00:00:00+02:00,18.50862693786621,18.822938919067383,17.768600463867188,17.796449661254883,10.250675201416016,1780930,0.0,0.0
-2022-04-01 00:00:00+02:00,17.895915985107422,18.102806091308594,17.880001068115234,17.880001068115234,10.298800468444824,751206,0.0,0.0
-2022-04-04 00:00:00+02:00,17.92376708984375,17.991403579711914,17.517946243286133,17.79247283935547,10.248384475708008,836607,0.0,0.0
-2022-04-05 00:00:00+02:00,17.77655792236328,17.975488662719727,17.382671356201172,17.617412567138672,10.147551536560059,842142,0.0,0.0
-2022-04-06 00:00:00+02:00,17.577625274658203,17.625368118286133,16.87340545654297,17.016637802124023,9.801506996154785,1380130,0.0,0.0
-2022-04-07 00:00:00+02:00,17.10814666748047,17.382671356201172,16.865449905395508,16.89727783203125,9.732755661010742,857449,0.0,0.0
-2022-04-08 00:00:00+02:00,17.191696166992188,17.382671356201172,16.99674415588379,17.191696166992188,9.902338981628418,913588,0.0,0.0
-2022-04-11 00:00:00+02:00,17.219547271728516,17.549774169921875,17.036529541015625,17.203632354736328,9.909214973449707,1067867,0.0,0.0
-2022-04-12 00:00:00+02:00,17.00868034362793,17.565689086914062,16.833620071411133,17.565689086914062,10.117758750915527,1285128,0.0,0.0
-2022-04-13 00:00:00+02:00,17.438373565673828,17.525903701782227,17.267290115356445,17.506010055541992,10.083383560180664,697328,0.0,0.0
-2022-04-14 00:00:00+02:00,17.58160400390625,17.657197952270508,17.406543731689453,17.513967514038086,10.087967872619629,587256,0.0,0.0
-2022-04-19 00:00:00+02:00,17.54181671142578,17.69300651550293,17.418479919433594,17.517946243286133,10.09025764465332,962344,0.0,0.0
-2022-04-20 00:00:00+02:00,17.633325576782227,17.967531204223633,17.609453201293945,17.768600463867188,10.234634399414062,675733,0.0,0.0
-2022-04-21 00:00:00+02:00,17.860109329223633,18.38926887512207,17.860109329223633,18.28980255126953,10.534844398498535,946132,0.0,0.0
-2022-04-22 00:00:00+02:00,18.063018798828125,18.25399398803711,17.87204360961914,18.031190872192383,10.385885238647461,876938,0.0,0.0
-2022-04-25 00:00:00+02:00,17.71687889099121,17.891937255859375,17.549774169921875,17.629348754882812,10.154426574707031,857539,0.0,0.0
-2022-04-26 00:00:00+02:00,17.868066787719727,17.868066787719727,17.342885971069336,17.342885971069336,9.989424705505371,920938,0.0,0.0
-2022-04-27 00:00:00+02:00,17.42245864868164,17.513967514038086,16.865449905395508,17.430416107177734,10.039841651916504,995898,0.0,0.0
-2022-04-28 00:00:00+02:00,17.633325576782227,17.99538230895996,17.601497650146484,17.736770629882812,10.216300010681152,1172803,0.0,0.0
-2022-04-29 00:00:00+02:00,17.848173141479492,18.10678482055664,17.804407119750977,18.015274047851562,10.376717567443848,988594,0.0,0.0
-2022-05-02 00:00:00+02:00,17.88397979736328,18.05506134033203,16.90921401977539,17.74074935913086,10.218591690063477,1031151,0.0,0.0
-2022-05-03 00:00:00+02:00,17.848173141479492,17.93570327758789,17.506010055541992,17.808385848999023,10.257550239562988,1121197,0.0,0.0
-2022-05-04 00:00:00+02:00,18.747344970703125,19.10542106628418,18.532499313354492,18.846811294555664,10.85567855834961,2131889,0.0,0.0
-2022-05-05 00:00:00+02:00,19.18101692199707,19.37994956970215,18.138612747192383,18.17840003967285,10.47067642211914,1420586,0.0,0.0
-2022-05-06 00:00:00+02:00,18.110763549804688,18.560348510742188,17.97150993347168,18.369373321533203,10.580676078796387,967240,0.0,0.0
-2022-05-09 00:00:00+02:00,18.190336227416992,18.305715560913086,17.844194412231445,17.951616287231445,10.34005069732666,1063615,0.0,0.0
-2022-05-10 00:00:00+02:00,18.063018798828125,18.85079002380371,18.04710578918457,18.341524124145508,10.564635276794434,1106715,0.0,0.0
-2022-05-11 00:00:00+02:00,18.46088218688965,18.659814834594727,18.27786636352539,18.47281837463379,10.640260696411133,916544,0.0,0.0
-2022-05-12 00:00:00+02:00,18.04312515258789,18.261951446533203,17.784513473510742,18.222164154052734,10.495884895324707,899448,0.0,0.0
-2022-05-13 00:00:00+02:00,18.405181884765625,18.55636978149414,18.194313049316406,18.38528823852539,10.58984375,614260,0.0,0.0
-2022-05-16 00:00:00+02:00,18.381309509277344,18.612070083618164,18.24205780029297,18.417118072509766,10.608176231384277,734648,0.0,0.0
-2022-05-17 00:00:00+02:00,18.21420669555664,18.747344970703125,18.21420669555664,18.512605667114258,12.22278881072998,625555,2.35,0.0
-2022-05-18 00:00:00+02:00,18.54443359375,18.592178344726562,18.357437133789062,18.357437133789062,12.120339393615723,676447,0.0,0.0
-2022-05-19 00:00:00+02:00,17.677091598510742,17.903873443603516,17.474180221557617,17.513967514038086,11.563447952270508,1239650,0.0,0.0
-2022-05-20 00:00:00+02:00,17.856130599975586,18.063018798828125,17.60547637939453,17.60547637939453,11.62386417388916,792884,0.0,0.0
-2022-05-23 00:00:00+02:00,17.85215187072754,17.987424850463867,17.633325576782227,17.987424850463867,11.876043319702148,661658,0.0,0.0
-2022-05-24 00:00:00+02:00,17.79247283935547,17.83623695373535,17.414501190185547,17.418479919433594,11.500402450561523,729103,0.0,0.0
-2022-05-25 00:00:00+02:00,17.617412567138672,17.89989471435547,17.394607543945312,17.8402156829834,11.778849601745605,645185,0.0,0.0
-2022-05-26 00:00:00+02:00,17.79247283935547,18.05506134033203,17.720855712890625,18.03516960144043,11.907565116882324,523872,0.0,0.0
-2022-05-27 00:00:00+02:00,18.031190872192383,18.198293685913086,17.94763946533203,18.198293685913086,12.015267372131348,578243,0.0,0.0
-2022-05-30 00:00:00+02:00,18.27786636352539,18.433032989501953,18.10678482055664,18.218185424804688,12.028400421142578,568621,0.0,0.0
-2022-05-31 00:00:00+02:00,18.1823787689209,18.218185424804688,17.97150993347168,18.122699737548828,11.965356826782227,1795488,0.0,0.0
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-2024-06-28 00:00:00+02:00,32.95000076293945,33.060001373291016,32.31999969482422,32.869998931884766,32.869998931884766,277611,0.0,0.0
-2024-07-01 00:00:00+02:00,33.29999923706055,33.4900016784668,32.72999954223633,33.4900016784668,33.4900016784668,206747,0.0,0.0
-2024-07-02 00:00:00+02:00,33.5,34.0,33.13999938964844,34.0,34.0,231379,0.0,0.0
-2024-07-03 00:00:00+02:00,33.95000076293945,34.13999938964844,33.47999954223633,34.13999938964844,34.13999938964844,262502,0.0,0.0
-2024-07-04 00:00:00+02:00,34.0,34.20000076293945,33.540000915527344,34.060001373291016,34.060001373291016,130465,0.0,0.0
-2024-07-05 00:00:00+02:00,34.060001373291016,34.279998779296875,33.5099983215332,33.5099983215332,33.5099983215332,212429,0.0,0.0
-2024-07-08 00:00:00+02:00,33.400001525878906,33.95000076293945,32.81999969482422,33.95000076293945,33.95000076293945,194477,0.0,0.0
-2024-07-09 00:00:00+02:00,33.790000915527344,34.060001373291016,32.290000915527344,32.5099983215332,32.5099983215332,364262,0.0,0.0
-2024-07-10 00:00:00+02:00,32.29999923706055,32.38999938964844,31.75,32.040000915527344,32.040000915527344,207620,0.0,0.0
-2024-07-11 00:00:00+02:00,32.11000061035156,32.599998474121094,32.06999969482422,32.349998474121094,32.349998474121094,159663,0.0,0.0
-2024-07-12 00:00:00+02:00,32.29999923706055,32.93000030517578,32.29999923706055,32.59000015258789,32.59000015258789,116583,0.0,0.0
-2024-07-15 00:00:00+02:00,32.459999084472656,32.689998626708984,31.899999618530273,32.279998779296875,32.279998779296875,123588,0.0,0.0
-2024-07-16 00:00:00+02:00,32.20000076293945,32.65999984741211,31.940000534057617,32.45000076293945,32.45000076293945,88377,0.0,0.0
-2024-07-17 00:00:00+02:00,32.72999954223633,33.939998626708984,32.040000915527344,33.939998626708984,33.939998626708984,222062,0.0,0.0
-2024-07-18 00:00:00+02:00,34.0,34.93000030517578,33.79999923706055,34.63999938964844,34.63999938964844,400707,0.0,0.0
-2024-07-19 00:00:00+02:00,34.290000915527344,34.36000061035156,33.529998779296875,34.0099983215332,34.0099983215332,188494,0.0,0.0
-2024-07-22 00:00:00+02:00,34.349998474121094,34.5,33.66999816894531,34.13999938964844,34.13999938964844,144759,0.0,0.0
-2024-07-23 00:00:00+02:00,33.95000076293945,34.02000045776367,33.5,33.83000183105469,33.83000183105469,99602,0.0,0.0
-2024-07-24 00:00:00+02:00,33.54999923706055,33.97999954223633,33.459999084472656,33.5099983215332,33.5099983215332,118200,0.0,0.0
-2024-07-25 00:00:00+02:00,33.400001525878906,33.75,32.43000030517578,33.41999816894531,33.41999816894531,143724,0.0,0.0
-2024-07-26 00:00:00+02:00,33.09000015258789,33.439998626708984,32.650001525878906,33.2599983215332,33.2599983215332,150065,0.0,0.0
-2024-07-29 00:00:00+02:00,33.25,33.560001373291016,33.06999969482422,33.18000030517578,33.18000030517578,101941,0.0,0.0
-2024-07-30 00:00:00+02:00,33.0,33.619998931884766,32.86000061035156,33.18000030517578,33.18000030517578,142743,0.0,0.0
-2024-07-31 00:00:00+02:00,33.849998474121094,34.0,32.20000076293945,32.52000045776367,32.52000045776367,561976,0.0,0.0
-2024-08-01 00:00:00+02:00,32.13999938964844,32.599998474121094,31.190000534057617,31.469999313354492,31.469999313354492,275048,0.0,0.0
-2024-08-02 00:00:00+02:00,31.229999542236328,31.760000228881836,30.860000610351562,30.860000610351562,30.860000610351562,265760,0.0,0.0
-2024-08-05 00:00:00+02:00,30.100000381469727,30.479999542236328,29.469999313354492,29.940000534057617,29.940000534057617,473460,0.0,0.0
-2024-08-06 00:00:00+02:00,30.5,31.010000228881836,30.040000915527344,30.190000534057617,30.190000534057617,264982,0.0,0.0
-2024-08-07 00:00:00+02:00,30.510000228881836,31.229999542236328,30.3799991607666,30.889999389648438,30.889999389648438,178311,0.0,0.0
-2024-08-08 00:00:00+02:00,30.799999237060547,30.959999084472656,30.40999984741211,30.799999237060547,30.799999237060547,172146,0.0,0.0
-2024-08-09 00:00:00+02:00,30.90999984741211,31.520000457763672,30.90999984741211,31.15999984741211,31.15999984741211,179785,0.0,0.0
-2024-08-12 00:00:00+02:00,31.299999237060547,31.690000534057617,30.59000015258789,30.59000015258789,30.59000015258789,132932,0.0,0.0
-2024-08-13 00:00:00+02:00,30.690000534057617,31.040000915527344,30.360000610351562,30.600000381469727,30.600000381469727,103593,0.0,0.0
-2024-08-14 00:00:00+02:00,30.649999618530273,30.68000030517578,30.059999465942383,30.479999542236328,30.479999542236328,209068,0.0,0.0
-2024-08-15 00:00:00+02:00,30.549999237060547,31.09000015258789,30.450000762939453,30.920000076293945,30.920000076293945,125365,0.0,0.0
-2024-08-16 00:00:00+02:00,30.940000534057617,31.1200008392334,30.729999542236328,30.8799991607666,30.8799991607666,141253,0.0,0.0
-2024-08-19 00:00:00+02:00,31.030000686645508,31.299999237060547,30.670000076293945,31.030000686645508,31.030000686645508,180272,0.0,0.0
-2024-08-20 00:00:00+02:00,31.170000076293945,31.170000076293945,30.469999313354492,30.530000686645508,30.530000686645508,152575,0.0,0.0
-2024-08-21 00:00:00+02:00,30.530000686645508,31.020000457763672,30.530000686645508,30.969999313354492,30.969999313354492,128994,0.0,0.0
-2024-08-22 00:00:00+02:00,30.979999542236328,31.1299991607666,30.780000686645508,31.059999465942383,31.059999465942383,15067,0.0,0.0

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()

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()

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"])

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()

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']
 

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
 
@@ -223,7 +224,7 @@ class TestPriceHistory(unittest.TestCase):
         start_d = _dt.date(2022, 1, 1)
         end_d = _dt.date(2023, 1, 1)
 
-        tkr_div_dates = {'BHP.AX': [_dt.date(2022, 9, 1), _dt.date(2022, 2, 24)],  # Yahoo claims 23-Feb but wrong because DST
+        tkr_div_dates = {'BHP.AX': [_dt.date(2022, 9, 1), _dt.date(2022, 2, 24)],
                          'IMP.JO': [_dt.date(2022, 9, 21), _dt.date(2022, 3, 16)],
                          'BP.L': [_dt.date(2022, 11, 10), _dt.date(2022, 8, 11), _dt.date(2022, 5, 12),
                                   _dt.date(2022, 2, 17)],
@@ -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)

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()

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)

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
@@ -16,9 +18,9 @@ from yfinance.exceptions import YFPricesMissingError, YFInvalidPeriodError, YFNo
 
 
 import unittest
-import requests_cache
+# import requests_cache
 from typing import Union, Any, get_args, _GenericAlias
-from urllib.parse import urlparse, parse_qs, urlencode, urlunparse
+# from urllib.parse import urlparse, parse_qs, urlencode, urlunparse
 
 ticker_attributes = (
     ("major_holders", pd.DataFrame),
@@ -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
@@ -176,15 +225,32 @@ 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:
             assert_attribute_type(self, dat, attribute_name, attribute_type)
 
+    def test_ticker_with_symbol_mic(self):
+        equities = [
+            ("OR", "XPAR"),      # L'Oréal on Euronext Paris
+            ("AAPL", "XNYS"),    # Apple on NYSE
+            ("GOOGL", "XNAS"),   # Alphabet on NASDAQ
+            ("BMW", "XETR"),     # BMW on XETRA
+        ]
+        for eq in  equities:
+            # No exception = pass
+            yf.Ticker(eq)
+            yf.Ticker((eq[0], eq[1].lower()))
+
+    def test_ticker_with_symbol_mic_invalid(self):
+        with self.assertRaises(ValueError) as cm:
+            yf.Ticker(('ABC', 'XXXX'))
+        self.assertIn("Unknown MIC code: 'XXXX'", str(cm.exception))
+
 
 class TestTickerHistory(unittest.TestCase):
     session = None
@@ -216,44 +282,57 @@ class TestTickerHistory(unittest.TestCase):
         self.assertFalse(data.empty, "data is empty")
 
     def test_download(self):
+        tomorrow = pd.Timestamp.now().date() + pd.Timedelta(days=1)  # helps with caching
         for t in [False, True]:
             for i in [False, True]:
-                data = yf.download(self.symbols, threads=t, ignore_tz=i)
-                self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
-                self.assertFalse(data.empty, "data is empty")
+                for m in [False, True]:
+                    for n in [1, 'all']:
+                        symbols = self.symbols[0] if n == 1 else self.symbols
+                        data = yf.download(symbols, end=tomorrow, session=self.session, 
+                                           threads=t, ignore_tz=i, multi_level_index=m)
+                        self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
+                        self.assertFalse(data.empty, "data is empty")
+                        if i:
+                            self.assertIsNone(data.index.tz)
+                        else:
+                            self.assertIsNotNone(data.index.tz)
+                        if (not m) and n == 1:
+                            self.assertFalse(isinstance(data.columns, pd.MultiIndex))
+                        else:
+                            self.assertIsInstance(data.columns, pd.MultiIndex)
 
-    def test_no_expensive_calls_introduced(self):
-        """
-        Make sure calling history to get price data has not introduced more calls to yahoo than absolutely necessary.
-        As doing other type of scraping calls than "query2.finance.yahoo.com/v8/finance/chart" to yahoo website
-        will quickly trigger spam-block when doing bulk download of history data.
-        """
-        symbol = "GOOGL"
-        period = "1y"
-        with requests_cache.CachedSession(backend="memory") as session:
-            ticker = yf.Ticker(symbol, session=session)
-            ticker.history(period=period)
-            actual_urls_called = [r.url for r in session.cache.filter()]
+    # Hopefully one day we find an equivalent "requests_cache" that works with "curl_cffi"
+    # def test_no_expensive_calls_introduced(self):
+    #     """
+    #     Make sure calling history to get price data has not introduced more calls to yahoo than absolutely necessary.
+    #     As doing other type of scraping calls than "query2.finance.yahoo.com/v8/finance/chart" to yahoo website
+    #     will quickly trigger spam-block when doing bulk download of history data.
+    #     """
+    #     symbol = "GOOGL"
+    #     period = "1y"
+    #     with requests_cache.CachedSession(backend="memory") as session:
+    #         ticker = yf.Ticker(symbol, session=session)
+    #         ticker.history(period=period)
+    #         actual_urls_called = [r.url for r in session.cache.filter()]
 
-        # Remove 'crumb' argument
-        for i in range(len(actual_urls_called)):
-            u = actual_urls_called[i]
-            parsed_url = urlparse(u)
-            query_params = parse_qs(parsed_url.query)
-            query_params.pop('crumb', None)
-            query_params.pop('cookie', None)
-            u = urlunparse(parsed_url._replace(query=urlencode(query_params, doseq=True)))
-            actual_urls_called[i] = u
-        actual_urls_called = tuple(actual_urls_called)
+    #     # Remove 'crumb' argument
+    #     for i in range(len(actual_urls_called)):
+    #         u = actual_urls_called[i]
+    #         parsed_url = urlparse(u)
+    #         query_params = parse_qs(parsed_url.query)
+    #         query_params.pop('crumb', None)
+    #         query_params.pop('cookie', None)
+    #         u = urlunparse(parsed_url._replace(query=urlencode(query_params, doseq=True)))
+    #         actual_urls_called[i] = u
+    #     actual_urls_called = tuple(actual_urls_called)
+
+    #     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}")
 
-        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."
-        )
     def test_dividends(self):
         data = self.ticker.dividends
         self.assertIsInstance(data, pd.Series, "data has wrong type")
@@ -269,6 +348,12 @@ 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
@@ -296,7 +381,7 @@ 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")
@@ -493,6 +578,34 @@ 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
@@ -609,6 +722,34 @@ 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
@@ -634,6 +775,18 @@ 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
@@ -668,6 +821,14 @@ 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"))
 
@@ -746,8 +907,6 @@ class TestTickerAnalysts(unittest.TestCase):
         data = self.ticker.upgrades_downgrades
         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.assertIsInstance(data.index, pd.DatetimeIndex, "data has wrong index type")
 
         data_cached = self.ticker.upgrades_downgrades
@@ -757,9 +916,6 @@ 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")
 
@@ -768,12 +924,6 @@ 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")
 
@@ -782,12 +932,6 @@ 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")
 
@@ -796,8 +940,6 @@ 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
@@ -808,12 +950,6 @@ 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")
 
@@ -822,12 +958,6 @@ 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', '+5y', '-5y']
-        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")
 
@@ -870,6 +1000,7 @@ 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" ] # Issues 2343
         self.tickers = [yf.Ticker(s, session=self.session) for s in self.symbols]
 
     def tearDown(self):
@@ -885,7 +1016,6 @@ class TestTickerInfo(unittest.TestCase):
         self.assertIsInstance(data, dict, "data has wrong type")
         expected_keys = ['industry', 'currentPrice', 'exchange', 'floatShares', 'companyOfficers', 'bid']
         for k in expected_keys:
-            print(k)
             self.assertIn("symbol", data.keys(), f"Did not find expected key '{k}' in info dict")
         self.assertEqual(self.symbols[0], data["symbol"], "Wrong symbol value in info dict")
 
@@ -900,6 +1030,28 @@ 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")
+
     # def test_fast_info_matches_info(self):
     #     fast_info_keys = set()
     #     for ticker in self.tickers:

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, _parse_user_dt
 
 
 class TestPandas(unittest.TestCase):
@@ -105,11 +41,155 @@ 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"))
+
+    def test_parse_user_dt(self):
+        exchange_tz = "US/Eastern"
+        dtstr = "2024-01-04"
+        epoch = 1704344400  # output of `pd.Timestamp("2024-01-04", tz="US/Eastern").timestamp()`
+        expected = pd.Timestamp(dtstr, tz=exchange_tz)
+
+        self.assertEqual(_parse_user_dt(epoch, exchange_tz), expected)
+        self.assertEqual(_parse_user_dt(dtstr, exchange_tz), expected)
+        self.assertEqual(_parse_user_dt(datetime(year=2024, month=1, day=4).date(), exchange_tz), expected)
+        self.assertEqual(_parse_user_dt(datetime(year=2024, month=1, day=4), exchange_tz), expected)
+        with self.assertRaises(ValueError):
+            self.assertEqual(_parse_user_dt(float(epoch), exchange_tz), expected)
+
+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
 
 

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"]

yfinance/cache.py

@@ -3,13 +3,15 @@ from threading import Lock
 import os as _os
 import platformdirs as _ad
 import atexit as _atexit
-import datetime as _datetime
+import datetime as _dt
 import pickle as _pkl
 
 from .utils import get_yf_logger
 
 _cache_init_lock = Lock()
 
+
+
 # --------------
 # TimeZone cache
 # --------------
@@ -105,7 +107,7 @@ _atexit.register(_TzDBManager.close_db)
 
 
 tz_db_proxy = _peewee.Proxy()
-class _KV(_peewee.Model):
+class _TZ_KV(_peewee.Model):
     key = _peewee.CharField(primary_key=True)
     value = _peewee.CharField(null=True)
     
@@ -146,11 +148,11 @@ class _TzCache:
         db.connect()
         tz_db_proxy.initialize(db)
         try:
-            db.create_tables([_KV])
+            db.create_tables([_TZ_KV])
         except _peewee.OperationalError as e:
             if 'WITHOUT' in str(e):
-                _KV._meta.without_rowid = False
-                db.create_tables([_KV])
+                _TZ_KV._meta.without_rowid = False
+                db.create_tables([_TZ_KV])
             else:
                 raise
         self.initialised = 1  # success
@@ -166,8 +168,8 @@ class _TzCache:
             return None
 
         try:
-            return _KV.get(_KV.key == key).value
-        except _KV.DoesNotExist:
+            return _TZ_KV.get(_TZ_KV.key == key).value
+        except _TZ_KV.DoesNotExist:
             return None
 
     def store(self, key, value):
@@ -185,18 +187,18 @@ class _TzCache:
             return
         try:
             if value is None:
-                q = _KV.delete().where(_KV.key == key)
+                q = _TZ_KV.delete().where(_TZ_KV.key == key)
                 q.execute()
                 return
             with db.atomic():
-                _KV.insert(key=key, value=value).execute()
+                _TZ_KV.insert(key=key, value=value).execute()
         except _peewee.IntegrityError:
             # Integrity error means the key already exists. Try updating the key.
             old_value = self.lookup(key)
             if old_value != value:
                 get_yf_logger().debug(f"Value for key {key} changed from {old_value} to {value}.")
                 with db.atomic():
-                    q = _KV.update(value=value).where(_KV.key == key)
+                    q = _TZ_KV.update(value=value).where(_TZ_KV.key == key)
                     q.execute()
 
 
@@ -301,16 +303,16 @@ class ISODateTimeField(_peewee.DateTimeField):
     # because user discovered peewee allowed an invalid datetime
     # to get written.
     def db_value(self, value):
-        if value and isinstance(value, _datetime.datetime):
+        if value and isinstance(value, _dt.datetime):
             return value.isoformat()
         return super().db_value(value)
     def python_value(self, value):
         if value and isinstance(value, str) and 'T' in value:
-            return _datetime.datetime.fromisoformat(value)
+            return _dt.datetime.fromisoformat(value)
         return super().python_value(value)
 class _CookieSchema(_peewee.Model):
     strategy = _peewee.CharField(primary_key=True)
-    fetch_date = ISODateTimeField(default=_datetime.datetime.now)
+    fetch_date = ISODateTimeField(default=_dt.datetime.now)
     
     # Which cookie type depends on strategy
     cookie_bytes = _peewee.BlobField()
@@ -374,7 +376,7 @@ class _CookieCache:
         try:
             data =  _CookieSchema.get(_CookieSchema.strategy == strategy)
             cookie = _pkl.loads(data.cookie_bytes)
-            return {'cookie':cookie, 'age':_datetime.datetime.now()-data.fetch_date}
+            return {'cookie':cookie, 'age':_dt.datetime.now()-data.fetch_date}
         except _CookieSchema.DoesNotExist:
             return None
 
@@ -415,6 +417,211 @@ def get_cookie_cache():
 
 
 
+# --------------
+# ISIN cache
+# --------------
+
+class _ISINCacheException(Exception):
+    pass
+
+
+class _ISINCacheDummy:
+    """Dummy cache to use if isin cache is disabled"""
+
+    def lookup(self, isin):
+        return None
+
+    def store(self, isin, tkr):
+        pass
+
+    @property
+    def tz_db(self):
+        return None
+
+
+class _ISINCacheManager:
+    _isin_cache = None
+
+    @classmethod
+    def get_isin_cache(cls):
+        if cls._isin_cache is None:
+            with _cache_init_lock:
+                cls._initialise()
+        return cls._isin_cache
+
+    @classmethod
+    def _initialise(cls, cache_dir=None):
+        cls._isin_cache = _ISINCache()
+
+
+class _ISINDBManager:
+    _db = None
+    _cache_dir = _os.path.join(_ad.user_cache_dir(), "py-yfinance")
+
+    @classmethod
+    def get_database(cls):
+        if cls._db is None:
+            cls._initialise()
+        return cls._db
+
+    @classmethod
+    def close_db(cls):
+        if cls._db is not None:
+            try:
+                cls._db.close()
+            except Exception:
+                # Must discard exceptions because Python trying to quit.
+                pass
+
+
+    @classmethod
+    def _initialise(cls, cache_dir=None):
+        if cache_dir is not None:
+            cls._cache_dir = cache_dir
+
+        if not _os.path.isdir(cls._cache_dir):
+            try:
+                _os.makedirs(cls._cache_dir)
+            except OSError as err:
+                raise _ISINCacheException(f"Error creating ISINCache folder: '{cls._cache_dir}' reason: {err}")
+        elif not (_os.access(cls._cache_dir, _os.R_OK) and _os.access(cls._cache_dir, _os.W_OK)):
+            raise _ISINCacheException(f"Cannot read and write in ISINCache folder: '{cls._cache_dir}'")
+
+        cls._db = _peewee.SqliteDatabase(
+            _os.path.join(cls._cache_dir, 'isin-tkr.db'),
+            pragmas={'journal_mode': 'wal', 'cache_size': -64}
+        )
+
+    @classmethod
+    def set_location(cls, new_cache_dir):
+        if cls._db is not None:
+            cls._db.close()
+            cls._db = None
+        cls._cache_dir = new_cache_dir
+
+    @classmethod
+    def get_location(cls):
+        return cls._cache_dir
+
+# close DB when Python exists
+_atexit.register(_ISINDBManager.close_db)
+
+
+isin_db_proxy = _peewee.Proxy()
+class _ISIN_KV(_peewee.Model):
+    key = _peewee.CharField(primary_key=True)
+    value = _peewee.CharField(null=True)
+    created_at = _peewee.DateTimeField(default=_dt.datetime.now)
+    
+    class Meta:
+        database = isin_db_proxy
+        without_rowid = True
+
+
+class _ISINCache:
+    def __init__(self):
+        self.initialised = -1
+        self.db = None
+        self.dummy = False
+
+    def get_db(self):
+        if self.db is not None:
+            return self.db
+
+        try:
+            self.db = _ISINDBManager.get_database()
+        except _ISINCacheException as err:
+            get_yf_logger().info(f"Failed to create ISINCache, reason: {err}. "
+                                 "ISINCache will not be used. "
+                                 "Tip: You can direct cache to use a different location with 'set_isin_cache_location(mylocation)'")
+            self.dummy = True
+            return None
+        return self.db
+
+    def initialise(self):
+        if self.initialised != -1:
+            return
+
+        db = self.get_db()
+        if db is None:
+            self.initialised = 0  # failure
+            return
+
+        db.connect()
+        isin_db_proxy.initialize(db)
+        try:
+            db.create_tables([_ISIN_KV])
+        except _peewee.OperationalError as e:
+            if 'WITHOUT' in str(e):
+                _ISIN_KV._meta.without_rowid = False
+                db.create_tables([_ISIN_KV])
+            else:
+                raise
+        self.initialised = 1  # success
+
+    def lookup(self, key):
+        if self.dummy:
+            return None
+
+        if self.initialised == -1:
+            self.initialise()
+
+        if self.initialised == 0:  # failure
+            return None
+
+        try:
+            return _ISIN_KV.get(_ISIN_KV.key == key).value
+        except _ISIN_KV.DoesNotExist:
+            return None
+
+    def store(self, key, value):
+        if self.dummy:
+            return
+
+        if self.initialised == -1:
+            self.initialise()
+
+        if self.initialised == 0:  # failure
+            return
+
+        db = self.get_db()
+        if db is None:
+            return
+        try:
+            if value is None:
+                q = _ISIN_KV.delete().where(_ISIN_KV.key == key)
+                q.execute()
+                return
+
+            # Remove existing rows with same value that are older than 1 week
+            one_week_ago = _dt.datetime.now() - _dt.timedelta(weeks=1)
+            old_rows_query = _ISIN_KV.delete().where(
+                (_ISIN_KV.value == value) & 
+                (_ISIN_KV.created_at < one_week_ago)
+            )
+            old_rows_query.execute()
+
+            with db.atomic():
+                _ISIN_KV.insert(key=key, value=value).execute()
+
+        except _peewee.IntegrityError:
+            # Integrity error means the key already exists. Try updating the key.
+            old_value = self.lookup(key)
+            if old_value != value:
+                get_yf_logger().debug(f"Value for key {key} changed from {old_value} to {value}.")
+                with db.atomic():
+                    q = _ISIN_KV.update(value=value, created_at=_dt.datetime.now()).where(_ISIN_KV.key == key)
+                    q.execute()
+
+
+def get_isin_cache():
+    return _ISINCacheManager.get_isin_cache()
+
+
+# --------------
+# Utils
+# --------------
+
 def set_cache_location(cache_dir: str):
     """
     Sets the path to create the "py-yfinance" cache folder in.
@@ -425,6 +632,7 @@ def set_cache_location(cache_dir: str):
     """
     _TzDBManager.set_location(cache_dir)
     _CookieDBManager.set_location(cache_dir)
+    _ISINDBManager.set_location(cache_dir)
 
 def set_tz_cache_location(cache_dir: str):
     set_cache_location(cache_dir)

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",
@@ -159,167 +161,310 @@ quote_summary_valid_modules = (
 
 # map last updated as of 2024.09.18
 SECTOR_INDUSTY_MAPPING = {
-    'basic-materials': {'specialty-chemicals',
-                        'gold',
-                        'building-materials',
-                        'copper',
-                        'steel',
-                        'agricultural-inputs',
-                        'chemicals',
-                        'other-industrial-metals-mining',
-                        'lumber-wood-production',
-                        'aluminum',
-                        'other-precious-metals-mining',
-                        'coking-coal',
-                        'paper-paper-products',
-                        'silver'},
-    'communication-services': {'internet-content-information',
-                                'telecom-services',
-                                'entertainment',
-                                'electronic-gaming-multimedia',
-                                'advertising-agencies',
-                                'broadcasting',
-                                'publishing'},
-    'consumer-cyclical': {'internet-retail',
-                            'auto-manufacturers',
-                            'restaurants',
-                            'home-improvement-retail',
-                            'travel-services',
-                            'specialty-retail',
-                            'apparel-retail',
-                            'residential-construction',
-                            'footwear-accessories',
-                            'packaging-containers',
-                            'lodging',
-                            'auto-parts',
-                            'auto-truck-dealerships',
-                            'gambling',
-                            'resorts-casinos',
-                            'leisure',
-                            'apparel-manufacturing',
-                            'personal-services',
-                            'furnishings-fixtures-appliances',
-                            'recreational-vehicles',
-                            'luxury-goods',
-                            'department-stores',
-                            'textile-manufacturing'},
-    'consumer-defensive': {'discount-stores',
-                            'beverages-non-alcoholic',
-                            'household-personal-products',
-                            'packaged-foods',
-                            'tobacco',
-                            'confectioners',
-                            'farm-products',
-                            'food-distribution',
-                            'grocery-stores',
-                            'beverages-brewers',
-                            'education-training-services',
-                            'beverages-wineries-distilleries'},
-    'energy': {'oil-gas-integrated',
-                'oil-gas-midstream',
-                'oil-gas-e-p',
-                'oil-gas-equipment-services',
-                'oil-gas-refining-marketing',
-                'uranium',
-                'oil-gas-drilling',
-                'thermal-coal'},
-    'financial-services': {'banks-diversified',
-                            'credit-services',
-                            'asset-management',
-                            'insurance-diversified',
-                            'banks-regional',
-                            'capital-markets',
-                            'financial-data-stock-exchanges',
-                            'insurance-property-casualty',
-                            'insurance-brokers',
-                            'insurance-life',
-                            'insurance-specialty',
-                            'mortgage-finance',
-                            'insurance-reinsurance',
-                            'shell-companies',
-                            'financial-conglomerates'},
-    'healthcare': {'drug-manufacturers-general',
-                    'healthcare-plans',
-                    'biotechnology',
-                    'medical-devices',
-                    'diagnostics-research',
-                    'medical-instruments-supplies',
-                    'medical-care-facilities',
-                    'drug-manufacturers-specialty-generic',
-                    'health-information-services',
-                    'medical-distribution',
-                    'pharmaceutical-retailers'},
-    'industrials': {'aerospace-defense',
-                    'specialty-industrial-machinery',
-                    'railroads',
-                    'building-products-equipment',
-                    'farm-heavy-construction-machinery',
-                    'specialty-business-services',
-                    'integrated-freight-logistics',
-                    'waste-management',
-                    'conglomerates',
-                    'industrial-distribution',
-                    'engineering-construction',
-                    'rental-leasing-services',
-                    'consulting-services',
-                    'trucking',
-                    'electrical-equipment-parts',
-                    'airlines',
-                    'tools-accessories',
-                    'pollution-treatment-controls',
-                    'security-protection-services',
-                    'marine-shipping',
-                    'metal-fabrication',
-                    'infrastructure-operations',
-                    'staffing-employment-services',
-                    'airports-air-services',
-                    'business-equipment-supplies'},
-    'real-estate': {'reit-specialty',
-                    'reit-industrial',
-                    'reit-retail',
-                    'reit-residential',
-                    'reit-healthcare-facilities',
-                    'real-estate-services',
-                    'reit-office',
-                    'reit-diversified',
-                    'reit-mortgage',
-                    'reit-hotel-motel',
-                    'real-estate-development',
-                    'real-estate-diversified'},
-    'technology': {'software-infrastructure',
-                    'semiconductors',
-                    'consumer-electronics',
-                    'software-application',
-                    'information-technology-services',
-                    'semiconductor-equipment-materials',
-                    'communication-equipment',
-                    'computer-hardware',
-                    'electronic-components',
-                    'scientific-technical-instruments',
-                    'solar',
-                    'electronics-computer-distribution'},
-    'utilities': {'utilities-regulated-electric',
-                    'utilities-renewable',
-                    'utilities-diversified',
-                    'utilities-regulated-gas',
-                    'utilities-independent-power-producers',
-                    'utilities-regulated-water'}
+    'Basic Materials': {'Specialty Chemicals',
+                        'Gold',
+                        'Building Materials',
+                        'Copper',
+                        'Steel',
+                        'Agricultural Inputs',
+                        'Chemicals',
+                        'Other Industrial Metals & Mining',
+                        'Lumber & Wood Production',
+                        'Aluminum',
+                        'Other Precious Metals & Mining',
+                        'Coking Coal',
+                        'Paper & Paper Products',
+                        'Silver'},
+    'Communication Services': {'Advertising Agencies',
+                                'Broadcasting',
+                                'Electronic Gaming & Multimedia',
+                                'Entertainment',
+                                'Internet Content & Information',
+                                'Publishing',
+                                'Telecom Services'},
+    'Consumer Cyclical': {'Apparel Manufacturing',
+                            'Apparel Retail',
+                            'Auto & Truck Dealerships',
+                            'Auto Manufacturers',
+                            'Auto Parts',
+                            'Department Stores',
+                            'Footwear & Accessories',
+                            'Furnishings, Fixtures & Appliances',
+                            'Gambling',
+                            'Home Improvement Retail',
+                            'Internet Retail',
+                            'Leisure',
+                            'Lodging',
+                            'Luxury Goods',
+                            'Packaging & Containers',
+                            'Personal Services',
+                            'Recreational Vehicles',
+                            'Residential Construction',
+                            'Resorts & Casinos',
+                            'Restaurants',
+                            'Specialty Retail',
+                            'Textile Manufacturing',
+                            'Travel Services'},
+    'Consumer Defensive': {'Beverages - Brewers',
+                            'Beverages - Non-Alcoholic',
+                            'Beverages - Wineries & Distilleries',
+                            'Confectioners',
+                            'Discount Stores',
+                            'Education & Training Services',
+                            'Farm Products',
+                            'Food Distribution',
+                            'Grocery Stores',
+                            'Household & Personal Products',
+                            'Packaged Foods',
+                            'Tobacco'},
+    'Energy': {'Oil Gas Drilling',
+                'Oil Gas E P',
+                'Oil Gas Equipment Services',
+                'Oil Gas Integrated',
+                'Oil Gas Midstream',
+                'Oil Gas Refining Marketing',
+                'Thermal Coal',
+                'Uranium'},
+    'Financial Services': {'Asset Management',
+                            'Banks Diversified',
+                            'Banks Regional',
+                            'Capital Markets',
+                            'Credit Services',
+                            'Financial Conglomerates',
+                            'Financial Data Stock Exchanges',
+                            'Insurance Brokers',
+                            'Insurance Diversified',
+                            'Insurance Life',
+                            'Insurance Property Casualty',
+                            'Insurance Reinsurance',
+                            'Insurance Specialty',
+                            'Mortgage Finance',
+                            'Shell Companies'},
+    'Healthcare': {'Biotechnology',
+                    'Diagnostics Research',
+                    'Drug Manufacturers General',
+                    'Drug Manufacturers Specialty Generic',
+                    'Health Information Services',
+                    'Healthcare Plans',
+                    'Medical Care Facilities',
+                    'Medical Devices',
+                    'Medical Distribution',
+                    'Medical Instruments Supplies',
+                    'Pharmaceutical Retailers'},
+    'Industrials': {'Aerospace Defense',
+                    'Airlines',
+                    'Airports Air Services',
+                    'Building Products Equipment',
+                    'Business Equipment Supplies',
+                    'Conglomerates',
+                    'Consulting Services',
+                    'Electrical Equipment Parts',
+                    'Engineering Construction',
+                    'Farm Heavy Construction Machinery',
+                    'Industrial Distribution',
+                    'Infrastructure Operations',
+                    'Integrated Freight Logistics',
+                    'Marine Shipping',
+                    'Metal Fabrication',
+                    'Pollution Treatment Controls',
+                    'Railroads',
+                    'Rental Leasing Services',
+                    'Security Protection Services',
+                    'Specialty Business Services',
+                    'Specialty Industrial Machinery',
+                    'Staffing Employment Services',
+                    'Tools Accessories',
+                    'Trucking',
+                    'Waste Management'},
+    'Real Estate': {'Real Estate Development',
+                    'Real Estate Diversified',
+                    'Real Estate Services',
+                    'Reit Diversified',
+                    'Reit Healthcare Facilities',
+                    'Reit Hotel Motel',
+                    'Reit Industrial',
+                    'Reit Mortgage',
+                    'Reit Office',
+                    'Reit Residential',
+                    'Reit Retail',
+                    'Reit Specialty'},
+    'Technology': {'Communication Equipment',
+                    'Computer Hardware',
+                    'Consumer Electronics',
+                    'Electronic Components',
+                    'Electronics Computer Distribution',
+                    'Information Technology Services',
+                    'Scientific Technical Instruments',
+                    'Semiconductor Equipment Materials',
+                    'Semiconductors',
+                    'Software Application',
+                    'Software Infrastructure',
+                    'Solar'},
+    'Utilities': {'Utilities Diversified',
+                    'Utilities Independent Power Producers',
+                    'Utilities Regulated Electric',
+                    'Utilities Regulated Gas',
+                    'Utilities Regulated Water',
+                    'Utilities Renewable'},
 }
+SECTOR_INDUSTY_MAPPING_LC = {}
+for k in SECTOR_INDUSTY_MAPPING.keys():
+    k2 = k.lower().replace('& ', '').replace('- ', '').replace(', ', ' ').replace(' ', '-')
+    SECTOR_INDUSTY_MAPPING_LC[k2] = []
+    for v in SECTOR_INDUSTY_MAPPING[k]:
+        v2 = v.lower().replace('& ', '').replace('- ', '').replace(', ', ' ').replace(' ', '-')
+        SECTOR_INDUSTY_MAPPING_LC[k2].append(v2)
+
+# _MIC_TO_YAHOO_SUFFIX maps Market Identifier Codes (MIC) to Yahoo Finance market suffixes.
+# c.f. :
+# https://help.yahoo.com/kb/finance-for-web/SLN2310.html;_ylt=AwrJKiCZFo9g3Y8AsDWPAwx.;_ylu=Y29sbwMEcG9zAzEEdnRpZAMEc2VjA3Ny?locale=en_US
+# https://www.iso20022.org/market-identifier-codes
+
+_MIC_TO_YAHOO_SUFFIX = {
+    'XCBT': 'CBT', 'XCME': 'CME', 'IFUS': 'NYB', 'CECS': 'CMX', 'XNYM': 'NYM', 'XNYS': '', 'XNAS': '',  # United States
+    'XBUE': 'BA',  # Argentina
+    'XVIE': 'VI',  # Austria
+    'XASX': 'AX', 'XAUS': 'XA',  # Australia
+    'XBRU': 'BR',  # Belgium
+    'BVMF': 'SA',  # Brazil
+    'CNSX': 'CN', 'NEOE': 'NE', 'XTSE': 'TO', 'XTSX': 'V',  # Canada
+    'XSGO': 'SN',  # Chile
+    'XSHG': 'SS', 'XSHE': 'SZ',  # China
+    'XBOG': 'CL',  # Colombia
+    'XPRA': 'PR',  # Czech Republic
+    'XCSE': 'CO',  # Denmark
+    'XCAI': 'CA',  # Egypt
+    'XTAL': 'TL',  # Estonia
+    'CEUX': 'XD', 'XEUR': 'NX',  # Europe (Cboe Europe, Euronext)
+    'XHEL': 'HE',  # Finland
+    'XPAR': 'PA',  # France
+    'XBER': 'BE', 'XBMS': 'BM', 'XDUS': 'DU', 'XFRA': 'F', 'XHAM': 'HM', 'XHAN': 'HA', 'XMUN': 'MU', 'XSTU': 'SG', 'XETR': 'DE',  # Germany
+    'XATH': 'AT',  # Greece
+    'XHKG': 'HK',  # Hong Kong
+    'XBUD': 'BD',  # Hungary
+    'XICE': 'IC',  # Iceland
+    'XBOM': 'BO', 'XNSE': 'NS',  # India
+    'XIDX': 'JK',  # Indonesia
+    'XDUB': 'IR',  # Ireland
+    'XTAE': 'TA',  # Israel
+    'MTAA': 'MI', 'EUTL': 'TI',  # Italy
+    'XTKS': 'T',  # Japan
+    'XKFE': 'KW',  # Kuwait
+    'XRIS': 'RG',  # Latvia
+    'XVIL': 'VS',  # Lithuania
+    'XKLS': 'KL',  # Malaysia
+    'XMEX': 'MX',  # Mexico
+    'XAMS': 'AS',  # Netherlands
+    'XNZE': 'NZ',  # New Zealand
+    'XOSL': 'OL',  # Norway
+    'XPHS': 'PS',  # Philippines
+    'XWAR': 'WA',  # Poland
+    'XLIS': 'LS',  # Portugal
+    'XQAT': 'QA',  # Qatar
+    'XBSE': 'RO',  # Romania
+    'XSES': 'SI',  # Singapore
+    'XJSE': 'JO',  # South Africa
+    'XKRX': 'KS', 'KQKS': 'KQ',  # South Korea
+    'BMEX': 'MC',  # Spain
+    'XTAD': 'SAU',  # Saudi Arabia
+    'XSTO': 'ST',  # Sweden
+    'XSWX': 'SW',  # Switzerland
+    'ROCO': 'TWO', 'XTAI': 'TW',  # Taiwan
+    'XBKK': 'BK',  # Thailand
+    'XIST': 'IS',  # Turkey
+    'XDFM': 'AE',  # UAE
+    'AQXE': 'AQ', 'XCHI': 'XC', 'XLON': 'L', 'ILSE': 'IL',  # United Kingdom
+    'XCAR': 'CR',  # Venezuela
+    'XSTC': 'VN'  # Vietnam
+}
+
+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': {},
+        'sw': {'EBS'},
+        '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"
-    },
+    "industry": SECTOR_INDUSTY_MAPPING,
     "peer_group": {
         "US Fund Equity Energy",
         "US CE Convertibles",
@@ -426,136 +571,149 @@ EQUITY_SCREENER_EQ_MAP = {
         "Banks"
     }
 }
-EQUITY_SCREENER_FIELDS = {
-    # EQ Fields
-    "region",
-    "sector",
-    "peer_group",
-    "exchanges",
-
-    # price
-    "eodprice",
-    "intradaypricechange",
-    "lastclosemarketcap.lasttwelvemonths",
-    "percentchange",
-    "lastclose52weekhigh.lasttwelvemonths",
-    "fiftytwowkpercentchange",
-    "intradayprice",
-    "lastclose52weeklow.lasttwelvemonths",
-    "intradaymarketcap",
-
-    # trading
-    "beta",
-    "avgdailyvol3m",
-    "pctheldinsider",
-    "pctheldinst",
-    "dayvolume",
-    "eodvolume",
-
-    # short interest
-    "short_percentage_of_shares_outstanding.value",
-    "short_interest.value",
-    "short_percentage_of_float.value",
-    "days_to_cover_short.value",
-    "short_interest_percentage_change.value",
-
-    # valuation
-    "bookvalueshare.lasttwelvemonths",
-    "lastclosemarketcaptotalrevenue.lasttwelvemonths",
-    "lastclosetevtotalrevenue.lasttwelvemonths",
-    "pricebookratio.quarterly",
-    "peratio.lasttwelvemonths",
-    "lastclosepricetangiblebookvalue.lasttwelvemonths",
-    "lastclosepriceearnings.lasttwelvemonths",
-    "pegratio_5y",
-
-    # profitability
-    "consecutive_years_of_dividend_growth_count",
-    "returnonassets.lasttwelvemonths",
-    "returnonequity.lasttwelvemonths",
-    "forward_dividend_per_share",
-    "forward_dividend_yield",
-    "returnontotalcapital.lasttwelvemonths",
-
-    # leverage
-    "lastclosetevebit.lasttwelvemonths",
-    "netdebtebitda.lasttwelvemonths",
-    "totaldebtequity.lasttwelvemonths",
-    "ltdebtequity.lasttwelvemonths",
-    "ebitinterestexpense.lasttwelvemonths",
-    "ebitdainterestexpense.lasttwelvemonths",
-    "lastclosetevebitda.lasttwelvemonths",
-    "totaldebtebitda.lasttwelvemonths",
-
-    # liquidity
-    "quickratio.lasttwelvemonths",
-    "altmanzscoreusingtheaveragestockinformationforaperiod.lasttwelvemonths",
-    "currentratio.lasttwelvemonths",
-    "operatingcashflowtocurrentliabilities.lasttwelvemonths",
-
-    # income statement
-    "totalrevenues.lasttwelvemonths",
-    "netincomemargin.lasttwelvemonths",
-    "grossprofit.lasttwelvemonths",
-    "ebitda1yrgrowth.lasttwelvemonths",
-    "dilutedepscontinuingoperations.lasttwelvemonths",
-    "quarterlyrevenuegrowth.quarterly",
-    "epsgrowth.lasttwelvemonths",
-    "netincomeis.lasttwelvemonths",
-    "ebitda.lasttwelvemonths",
-    "dilutedeps1yrgrowth.lasttwelvemonths",
-    "totalrevenues1yrgrowth.lasttwelvemonths",
-    "operatingincome.lasttwelvemonths",
-    "netincome1yrgrowth.lasttwelvemonths",
-    "grossprofitmargin.lasttwelvemonths",
-    "ebitdamargin.lasttwelvemonths",
-    "ebit.lasttwelvemonths",
-    "basicepscontinuingoperations.lasttwelvemonths",
-    "netepsbasic.lasttwelvemonths"
-    "netepsdiluted.lasttwelvemonths",
-
-    # balance sheet
-    "totalassets.lasttwelvemonths",
-    "totalcommonsharesoutstanding.lasttwelvemonths",
-    "totaldebt.lasttwelvemonths",
-    "totalequity.lasttwelvemonths",
-    "totalcurrentassets.lasttwelvemonths",
-    "totalcashandshortterminvestments.lasttwelvemonths",
-    "totalcommonequity.lasttwelvemonths",
-    "totalcurrentliabilities.lasttwelvemonths",
-    "totalsharesoutstanding",
-
-    # cash flow
-    "forward_dividend_yield",
-    "leveredfreecashflow.lasttwelvemonths",
-    "capitalexpenditure.lasttwelvemonths",
-    "cashfromoperations.lasttwelvemonths",
-    "leveredfreecashflow1yrgrowth.lasttwelvemonths",
-    "unleveredfreecashflow.lasttwelvemonths",
-    "cashfromoperations1yrgrowth.lasttwelvemonths",
-
-    # ESG
-    "esg_score",
-    "environmental_score",
-    "governance_score",
-    "social_score",
-    "highest_controversy"
+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",
+        "industry"}, 
+    "price":{
+        "lastclosemarketcap.lasttwelvemonths",
+        "percentchange",
+        "lastclose52weekhigh.lasttwelvemonths",
+        "fiftytwowkpercentchange",
+        "lastclose52weeklow.lasttwelvemonths",
+        "intradaymarketcap"},
+    "trading":{
+        "beta",
+        "avgdailyvol3m",
+        "pctheldinsider",
+        "pctheldinst",
+        "dayvolume",
+        "eodvolume"},
+    "short_interest":{
+        "short_percentage_of_shares_outstanding.value",
+        "short_interest.value",
+        "short_percentage_of_float.value",
+        "days_to_cover_short.value",
+        "short_interest_percentage_change.value"},
+    "valuation":{
+        "bookvalueshare.lasttwelvemonths",
+        "lastclosemarketcaptotalrevenue.lasttwelvemonths",
+        "lastclosetevtotalrevenue.lasttwelvemonths",
+        "pricebookratio.quarterly",
+        "peratio.lasttwelvemonths",
+        "lastclosepricetangiblebookvalue.lasttwelvemonths",
+        "lastclosepriceearnings.lasttwelvemonths",
+        "pegratio_5y"},
+    "profitability":{
+        "consecutive_years_of_dividend_growth_count",
+        "returnonassets.lasttwelvemonths",
+        "returnonequity.lasttwelvemonths",
+        "forward_dividend_per_share",
+        "forward_dividend_yield",
+        "returnontotalcapital.lasttwelvemonths"},
+    "leverage":{
+        "lastclosetevebit.lasttwelvemonths",
+        "netdebtebitda.lasttwelvemonths",
+        "totaldebtequity.lasttwelvemonths",
+        "ltdebtequity.lasttwelvemonths",
+        "ebitinterestexpense.lasttwelvemonths",
+        "ebitdainterestexpense.lasttwelvemonths",
+        "lastclosetevebitda.lasttwelvemonths",
+        "totaldebtebitda.lasttwelvemonths"},
+    "liquidity":{
+        "quickratio.lasttwelvemonths",
+        "altmanzscoreusingtheaveragestockinformationforaperiod.lasttwelvemonths",
+        "currentratio.lasttwelvemonths",
+        "operatingcashflowtocurrentliabilities.lasttwelvemonths"},
+    "income_statement":{
+        "totalrevenues.lasttwelvemonths",
+        "netincomemargin.lasttwelvemonths",
+        "grossprofit.lasttwelvemonths",
+        "ebitda1yrgrowth.lasttwelvemonths",
+        "dilutedepscontinuingoperations.lasttwelvemonths",
+        "quarterlyrevenuegrowth.quarterly",
+        "epsgrowth.lasttwelvemonths",
+        "netincomeis.lasttwelvemonths",
+        "ebitda.lasttwelvemonths",
+        "dilutedeps1yrgrowth.lasttwelvemonths",
+        "totalrevenues1yrgrowth.lasttwelvemonths",
+        "operatingincome.lasttwelvemonths",
+        "netincome1yrgrowth.lasttwelvemonths",
+        "grossprofitmargin.lasttwelvemonths",
+        "ebitdamargin.lasttwelvemonths",
+        "ebit.lasttwelvemonths",
+        "basicepscontinuingoperations.lasttwelvemonths",
+        "netepsbasic.lasttwelvemonths"
+        "netepsdiluted.lasttwelvemonths"},
+    "balance_sheet":{
+        "totalassets.lasttwelvemonths",
+        "totalcommonsharesoutstanding.lasttwelvemonths",
+        "totaldebt.lasttwelvemonths",
+        "totalequity.lasttwelvemonths",
+        "totalcurrentassets.lasttwelvemonths",
+        "totalcashandshortterminvestments.lasttwelvemonths",
+        "totalcommonequity.lasttwelvemonths",
+        "totalcurrentliabilities.lasttwelvemonths",
+        "totalsharesoutstanding"},
+    "cash_flow":{
+        "forward_dividend_yield",
+        "leveredfreecashflow.lasttwelvemonths",
+        "capitalexpenditure.lasttwelvemonths",
+        "cashfromoperations.lasttwelvemonths",
+        "leveredfreecashflow1yrgrowth.lasttwelvemonths",
+        "unleveredfreecashflow.lasttwelvemonths",
+        "cashfromoperations1yrgrowth.lasttwelvemonths"},
+    "esg":{
+        "esg_score",
+        "environmental_score",
+        "governance_score",
+        "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"
+]

yfinance/data.py

@@ -1,7 +1,8 @@
 import functools
 from functools import lru_cache
 
-import requests as requests
+from curl_cffi import requests
+from urllib.parse import urlsplit, urljoin
 from bs4 import BeautifulSoup
 import datetime
 
@@ -10,6 +11,8 @@ from frozendict import frozendict
 from . import utils, cache
 import threading
 
+from .exceptions import YFRateLimitError, YFDataException
+
 cache_maxsize = 64
 
 
@@ -47,7 +50,13 @@ 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 +65,8 @@ 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
 
@@ -70,16 +77,16 @@ 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
 
         try:
-            self._session.cache
+            session.cache
         except AttributeError:
             # Not caching
             self._session_is_caching = False
@@ -88,8 +95,25 @@ class YfData(metaclass=SingletonMeta):
             # Can't simply use a non-caching session to fetch cookie & crumb,
             # because then the caching-session won't have cookie.
             self._session_is_caching = True
-            from requests_cache import DO_NOT_CACHE
-            self._expire_after = DO_NOT_CACHE
+            # But since switch to curl_cffi, can't use requests_cache with it.
+            raise YFDataException("request_cache sessions don't work with curl_cffi, which is necessary now for Yahoo API. Solution: stop setting session, let YF handle.")
+
+        if not isinstance(session, requests.session.Session):
+            raise YFDataException(f"Yahoo API requires curl_cffi session not {type(session)}. Solution: stop setting session, let YF handle.")
+
+        with self._cookie_lock:
+            self._session = session
+            if self._proxy is not None:
+                self._session.proxies = self._proxy
+
+    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:
@@ -114,83 +138,83 @@ class YfData(metaclass=SingletonMeta):
         if not have_lock:
             self._cookie_lock.release()
 
-    def _save_session_cookies(self):
-        try:
-            cache.get_cookie_cache().store('csrf', self._session.cookies)
-        except Exception:
+    @utils.log_indent_decorator
+    def _save_cookie_curlCffi(self):
+        if self._session is None:
             return False
+        cookies = self._session.cookies.jar._cookies
+        if len(cookies) == 0:
+            return False
+        yh_domains = [k for k in cookies.keys() if 'yahoo' in k]
+        if len(yh_domains) > 1:
+            # Possible when cookie fetched with CSRF method. Discard consent cookie.
+            yh_domains = [k for k in yh_domains if 'consent' not in k]
+        if len(yh_domains) > 1:
+            utils.get_yf_logger().debug(f'Multiple Yahoo cookies, not sure which to cache: {yh_domains}')
+            return False
+        if len(yh_domains) == 0:
+            return False
+        yh_domain = yh_domains[0]
+        yh_cookie = {yh_domain: cookies[yh_domain]}
+        cache.get_cookie_cache().store('curlCffi', yh_cookie)
         return True
 
-    def _load_session_cookies(self):
-        cookie_dict = cache.get_cookie_cache().lookup('csrf')
-        if cookie_dict is None:
+    @utils.log_indent_decorator
+    def _load_cookie_curlCffi(self):
+        if self._session is None:
             return False
-        # Periodically refresh, 24 hours seems fair.
-        if cookie_dict['age'] > datetime.timedelta(days=1):
+        cookie_dict = cache.get_cookie_cache().lookup('curlCffi')
+        if cookie_dict is None or len(cookie_dict) == 0:
             return False
-        self._session.cookies.update(cookie_dict['cookie'])
-        utils.get_yf_logger().debug('loaded persistent cookie')
-
-    def _save_cookie_basic(self, cookie):
-        try:
-            cache.get_cookie_cache().store('basic', cookie)
-        except Exception:
+        cookies = cookie_dict['cookie']
+        domain = list(cookies.keys())[0]
+        cookie = cookies[domain]['/']['A3']
+        expiry_ts = cookie.expires
+        if expiry_ts > 2e9:
+            # convert ms to s
+            expiry_ts //= 1e3
+        expiry_dt = datetime.datetime.fromtimestamp(expiry_ts, tz=datetime.timezone.utc)
+        expired = expiry_dt < datetime.datetime.now(datetime.timezone.utc)
+        if expired:
+            utils.get_yf_logger().debug('cached cookie expired')
             return False
+        self._session.cookies.jar._cookies.update(cookies)
+        self._cookie = cookie
         return True
-    def _load_cookie_basic(self):
-        cookie_dict = cache.get_cookie_cache().lookup('basic')
-        if cookie_dict is None:
-            return None
-        # Periodically refresh, 24 hours seems fair.
-        if cookie_dict['age'] > datetime.timedelta(days=1):
-            return None
-        utils.get_yf_logger().debug('loaded persistent cookie')
-        return cookie_dict['cookie']
 
-    def _get_cookie_basic(self, proxy=None, timeout=30):
+    @utils.log_indent_decorator
+    def _get_cookie_basic(self, 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
+            return True
+        elif self._load_cookie_curlCffi():
+            utils.get_yf_logger().debug('reusing persistent cookie')
+            return True
 
         # To avoid infinite recursion, do NOT use self.get()
         # - 'allow_redirects' copied from @psychoz971 solution - does it help USA?
-        response = self._session.get(
-            url='https://fc.yahoo.com',
-            headers=self.user_agent_headers,
-            proxies=proxy,
-            timeout=timeout,
-            allow_redirects=True)
+        try:
+            self._session.get(
+                url='https://fc.yahoo.com',
+                timeout=timeout,
+                allow_redirects=True)
+        except requests.exceptions.DNSError:
+            # Possible because url on some privacy/ad blocklists
+            return False
+        self._save_cookie_curlCffi()
+        return 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):
+    @utils.log_indent_decorator
+    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:
+        if not self._get_cookie_basic():
             return None
-
         # - '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
         }
@@ -200,6 +224,10 @@ class YfData(metaclass=SingletonMeta):
         else:
             crumb_response = self._session.get(**get_args)
         self._crumb = crumb_response.text
+        if crumb_response.status_code == 429 or "Too Many Requests" in self._crumb:
+            utils.get_yf_logger().debug(f"Didn't receive crumb {self._crumb}")
+            raise YFRateLimitError()
+
         if self._crumb is None or '<html>' in self._crumb:
             utils.get_yf_logger().debug("Didn't receive crumb")
             return None
@@ -208,32 +236,36 @@ 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):
+        if not self._get_cookie_basic(timeout):
+            return None
+        return self._get_crumb_basic(timeout)
 
-    def _get_cookie_csrf(self, proxy, timeout):
+    @utils.log_indent_decorator
+    def _get_cookie_csrf(self, timeout):
         if self._cookie is not None:
             utils.get_yf_logger().debug('reusing cookie')
             return True
 
-        elif self._load_session_cookies():
+        elif self._load_cookie_curlCffi():
             utils.get_yf_logger().debug('reusing persistent cookie')
             self._cookie = True
             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 +294,36 @@ 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()
+        self._save_cookie_curlCffi()
         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
@@ -298,6 +332,10 @@ class YfData(metaclass=SingletonMeta):
             r = self._session.get(**get_args)
         self._crumb = r.text
 
+        if r.status_code == 429 or "Too Many Requests" in self._crumb:
+            utils.get_yf_logger().debug(f"Didn't receive crumb {self._crumb}")
+            raise YFRateLimitError()
+
         if self._crumb is None or '<html>' in self._crumb or self._crumb == '':
             utils.get_yf_logger().debug("Didn't receive crumb")
             return None
@@ -306,8 +344,8 @@ 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 +355,37 @@ 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):
+        response = self._make_request(url, request_method = self._session.get, params=params, timeout=timeout)
+
+        # Accept cookie-consent if redirected to consent page
+        if not self._is_this_consent_url(response.url):
+            # "Consent Page not detected"
+            pass
+        else:
+            # "Consent Page detected"
+            response = self._accept_consent_form(response, timeout)
+
+        return response
+
     @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:
@@ -345,36 +393,27 @@ 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:
             request_args['json'] = body
-            
+
         response = request_method(**request_args)
         utils.get_yf_logger().debug(f'response code={response.status_code}')
         if response.status_code >= 400:
@@ -383,30 +422,104 @@ 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()
+        return response.json()
+
+    def _is_this_consent_url(self, response_url: str) -> bool:
+        """
+        Check if given response_url is consent page
+
+        Args:
+            response_url (str) : response.url
+    
+        Returns:
+            True : This is cookie-consent page
+            False : This is not cookie-consent page
+        """
+        try:
+            return urlsplit(response_url).hostname and urlsplit(
+                response_url
+            ).hostname.endswith("consent.yahoo.com")
+        except Exception:
+            return False
+
+    def _accept_consent_form(
+        self, consent_resp: requests.Response, timeout: int
+    ) -> requests.Response:
+        """
+        Click 'Accept all' to cookie-consent form and return response object.
+
+        Args:
+            consent_resp (requests.Response) : Response instance of cookie-consent page
+            timeout (int) : Raise TimeoutError if post doesn't respond
+    
+        Returns:
+            response (requests.Response) : Reponse instance received from the server after accepting cookie-consent post.
+        """
+        soup = BeautifulSoup(consent_resp.text, "html.parser")
+    
+        # Heuristic: pick the first form; Yahoo's CMP tends to have a single form for consent
+        form = soup.find("form")
+        if not form:
+            return consent_resp
+    
+        # action : URL to send "Accept Cookies"
+        action = form.get("action") or consent_resp.url
+        action = urljoin(consent_resp.url, action)
+    
+        # Collect inputs (hidden tokens, etc.)
+        """
+        <input name="csrfToken" type="hidden" value="..."/>
+        <input name="sessionId" type="hidden" value="..."/>
+        <input name="originalDoneUrl" type="hidden" value="..."/>
+        <input name="namespace" type="hidden" value="yahoo"/>
+        """
+        data = {}
+        for inp in form.find_all("input"):
+            name = inp.get("name")
+            if not name:
+                continue
+            typ = (inp.get("type") or "text").lower()
+            val = inp.get("value") or ""
+    
+            if typ in ("checkbox", "radio"):
+                # If it's clearly an "agree"/"accept" field or already checked, include it
+                if (
+                    "agree" in name.lower()
+                    or "accept" in name.lower()
+                    or inp.has_attr("checked")
+                ):
+                    data[name] = val if val != "" else "1"
+            else:
+                data[name] = val
+    
+        # If no explicit agree/accept in inputs, add a best-effort flag
+        lowered = {k.lower() for k in data.keys()}
+        if not any(("agree" in k or "accept" in k) for k in lowered):
+            data["agree"] = "1"
+    
+        # Submit the form with "Referer". Some servers check this header as a simple CSRF protection measure.
+        headers = {"Referer": consent_resp.url}
+        response = self._session.post(
+            action, data=data, headers=headers, timeout=timeout, allow_redirects=True
+        )
+        return response

yfinance/domain/domain.py

@@ -1,65 +1,138 @@
-from ..ticker import Ticker
-from ..const import _QUERY1_URL_
-from ..data import YfData
-from typing import Dict, List, Optional
-
+from abc import ABC, abstractmethod
 import pandas as _pd
+from typing import Dict, List, Optional
+import warnings
+
+from ..const import _QUERY1_URL_, _SENTINEL_
+from ..data import YfData
+from ..ticker import Ticker
 
 _QUERY_URL_ = f'{_QUERY1_URL_}/v1/finance'
 
-class Domain:
-    def __init__(self, key: str, session=None, proxy=None):
+class Domain(ABC):
+    """
+    Abstract base class representing a domain entity in financial data, with key attributes 
+    and methods for fetching and parsing data. Derived classes must implement the `_fetch_and_parse()` method.
+    """
+
+    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.
+        """
         self._key: str = key
-        self.proxy = proxy
         self.session = session
         self._data: YfData = YfData(session=session)
-        
+        if proxy is not _SENTINEL_:
+            warnings.warn("Set proxy via new config function: yf.set_config(proxy=proxy)", DeprecationWarning, stacklevel=2)
+            self._data._set_proxy(proxy)
+
         self._name: Optional[str] = None
         self._symbol: Optional[str] = None
         self._overview: Optional[Dict] = None
         self._top_companies: Optional[_pd.DataFrame] = None
         self._research_reports: Optional[List[Dict[str, str]]] = None
-    
+
     @property
     def key(self) -> str:
+        """
+        Retrieves the key of the domain entity.
+
+        Returns:
+            str: The unique key of the domain entity.
+        """
         return self._key
-    
+
     @property
     def name(self) -> str:
+        """
+        Retrieves the name of the domain entity.
+
+        Returns:
+            str: The name of the domain entity.
+        """
         self._ensure_fetched(self._name)
         return self._name
-    
+
     @property
     def symbol(self) -> str:
+        """
+        Retrieves the symbol of the domain entity.
+
+        Returns:
+            str: The symbol representing the domain entity.
+        """
         self._ensure_fetched(self._symbol)
         return self._symbol
-    
+
     @property
     def ticker(self) -> Ticker:
+        """
+        Retrieves a Ticker object based on the domain entity's symbol.
+
+        Returns:
+            Ticker: A Ticker object associated with the domain entity.
+        """
         self._ensure_fetched(self._symbol)
         return Ticker(self._symbol)
-    
+
     @property
     def overview(self) -> Dict:
+        """
+        Retrieves the overview information of the domain entity.
+
+        Returns:
+            Dict: A dictionary containing an overview of the domain entity.
+        """
         self._ensure_fetched(self._overview)
         return self._overview
-    
+
     @property
     def top_companies(self) -> Optional[_pd.DataFrame]:
+        """
+        Retrieves the top companies within the domain entity.
+
+        Returns:
+            pandas.DataFrame: A DataFrame containing the top companies in the domain.
+        """
         self._ensure_fetched(self._top_companies)
         return self._top_companies 
-    
+
     @property
     def research_reports(self) -> List[Dict[str, str]]:
+        """
+        Retrieves research reports related to the domain entity.
+
+        Returns:
+            List[Dict[str, str]]: A list of research reports, where each report is a dictionary with metadata.
+        """
         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.
+
+        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:
+        """
+        Parses and assigns common data fields such as name, symbol, overview, and top companies.
+
+        Args:
+            data (Dict): The raw data received from the API.
+        """
         self._name = data.get('name')
         self._symbol = data.get('symbol')
         self._overview = self._parse_overview(data.get('overview', {}))
@@ -67,6 +140,15 @@ class Domain:
         self._research_reports = data.get('researchReports')
 
     def _parse_overview(self, overview) -> Dict:
+        """
+        Parses the overview data for the domain entity.
+
+        Args:
+            overview (Dict): The raw overview data.
+
+        Returns:
+            Dict: A dictionary containing parsed overview information.
+        """
         return {
             "companies_count": overview.get('companiesCount', None),
             "market_cap": overview.get('marketCap', {}).get('raw', None),
@@ -78,6 +160,15 @@ class Domain:
         }
 
     def _parse_top_companies(self, top_companies) -> Optional[_pd.DataFrame]:
+        """
+        Parses the top companies data and converts it into a pandas DataFrame.
+
+        Args:
+            top_companies (Dict): The raw top companies data.
+
+        Returns:
+            Optional[pandas.DataFrame]: A DataFrame containing top company data, or None if no data is available.
+        """
         top_companies_column = ['symbol', 'name', 'rating', 'market weight']
         top_companies_values = [(c.get('symbol'), 
                                 c.get('name'), 
@@ -87,11 +178,22 @@ class Domain:
         if not top_companies_values: 
             return None
         
-        return _pd.DataFrame(top_companies_values, columns = top_companies_column).set_index('symbol')
+        return _pd.DataFrame(top_companies_values, columns=top_companies_column).set_index('symbol')
 
+    @abstractmethod
     def _fetch_and_parse(self) -> None:
+        """
+        Abstract method for fetching and parsing domain-specific data. 
+        Must be implemented by derived classes.
+        """
         raise NotImplementedError("_fetch_and_parse() needs to be implemented by children classes")
 
     def _ensure_fetched(self, attribute) -> None:
+        """
+        Ensures that the given attribute is fetched by calling `_fetch_and_parse()` if the attribute is None.
+
+        Args:
+            attribute: The attribute to check and potentially fetch.
+        """
         if attribute is None:
-            self._fetch_and_parse()
+            self._fetch_and_parse()

yfinance/domain/industry.py

@@ -1,14 +1,31 @@
 from __future__ import print_function
-from typing import Dict, Optional
 
 import pandas as _pd
+from typing import Dict, Optional
+import warnings
+
+from .. import utils
+from ..const import _SENTINEL_
+from ..data import YfData
 
 from .domain import Domain, _QUERY_URL_
-from .. import utils
 
 class Industry(Domain):
-    def __init__(self, key, session=None, proxy=None):
-        super(Industry, self).__init__(key, session, proxy)
+    """
+    Represents an industry within a sector.
+    """
+
+    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.
+        """
+        if proxy is not _SENTINEL_:
+            warnings.warn("Set proxy via new config function: yf.set_config(proxy=proxy)", DeprecationWarning, stacklevel=2)
+            YfData(proxy=proxy)
+        YfData(session=session)
+        super(Industry, self).__init__(key, session)
         self._query_url = f'{_QUERY_URL_}/industries/{self._key}'
 
         self._sector_key = None
@@ -17,29 +34,68 @@ class Industry(Domain):
         self._top_growth_companies = None
 
     def __repr__(self):
+        """
+        Returns a string representation of the Industry instance.
+        
+        Returns:
+            str: String representation of the Industry instance.
+        """
         return f'yfinance.Industry object <{self._key}>'
     
     @property
     def sector_key(self) -> str:
+        """
+        Returns the sector key of the industry.
+        
+        Returns:
+            str: The sector key.
+        """
         self._ensure_fetched(self._sector_key)
         return self._sector_key
     
     @property
     def sector_name(self) -> str:
+        """
+        Returns the sector name of the industry.
+        
+        Returns:
+            str: The sector name.
+        """
         self._ensure_fetched(self._sector_name)
         return self._sector_name
     
     @property
     def top_performing_companies(self) -> Optional[_pd.DataFrame]:
+        """
+        Returns the top performing companies in the industry.
+        
+        Returns:
+            Optional[pd.DataFrame]: DataFrame containing top performing companies.
+        """
         self._ensure_fetched(self._top_performing_companies)
         return self._top_performing_companies
     
     @property
     def top_growth_companies(self) -> Optional[_pd.DataFrame]:
+        """
+        Returns the top growth companies in the industry.
+        
+        Returns:
+            Optional[pd.DataFrame]: DataFrame containing top growth companies.
+        """
         self._ensure_fetched(self._top_growth_companies)
         return self._top_growth_companies
     
     def _parse_top_performing_companies(self, top_performing_companies: Dict) -> Optional[_pd.DataFrame]:
+        """
+        Parses the top performing companies data.
+        
+        Args:
+            top_performing_companies (Dict): Dictionary containing top performing companies data.
+        
+        Returns:
+            Optional[pd.DataFrame]: DataFrame containing parsed top performing companies data.
+        """
         compnaies_column = ['symbol','name','ytd return',' last price','target price']
         compnaies_values = [(c.get('symbol', None),
                              c.get('name', None),
@@ -53,6 +109,15 @@ class Industry(Domain):
         return _pd.DataFrame(compnaies_values, columns = compnaies_column).set_index('symbol')
     
     def _parse_top_growth_companies(self, top_growth_companies: Dict) -> Optional[_pd.DataFrame]:
+        """
+        Parses the top growth companies data.
+        
+        Args:
+            top_growth_companies (Dict): Dictionary containing top growth companies data.
+        
+        Returns:
+            Optional[pd.DataFrame]: DataFrame containing parsed top growth companies data.
+        """
         compnaies_column = ['symbol','name','ytd return',' growth estimate']
         compnaies_values = [(c.get('symbol', None),
                              c.get('name', None),
@@ -65,10 +130,13 @@ class Industry(Domain):
         return _pd.DataFrame(compnaies_values, columns = compnaies_column).set_index('symbol')
 
     def _fetch_and_parse(self) -> None:
+        """
+        Fetches and parses the industry data.
+        """
         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)
 
@@ -84,4 +152,4 @@ class Industry(Domain):
             logger.debug("Got response: ")
             logger.debug("-------------")
             logger.debug(f" {result}")
-            logger.debug("-------------")
+            logger.debug("-------------")

yfinance/domain/market.py

@@ -0,0 +1,103 @@
+import datetime as dt
+import json as _json
+import warnings
+
+from ..const import _QUERY1_URL_, _SENTINEL_
+from ..data import utils, YfData
+
+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_:
+            warnings.warn("Set proxy via new config function: yf.set_config(proxy=proxy)", DeprecationWarning, stacklevel=2)
+            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

yfinance/domain/sector.py

@@ -1,58 +1,145 @@
 from __future__ import print_function
-from typing import Dict, Optional
 
 import pandas as _pd
+from typing import Dict, Optional
+import warnings
+
+from ..const import SECTOR_INDUSTY_MAPPING_LC, _SENTINEL_
+from ..data import YfData
+from ..utils import dynamic_docstring, generate_list_table_from_dict, get_yf_logger
 
 from .domain import Domain, _QUERY_URL_
-from .. import utils
 
 class Sector(Domain):
-    def __init__(self, key, session=None, proxy=None):
-        super(Sector, self).__init__(key, session, proxy)
-        self._query_url: str = f'{_QUERY_URL_}/sectors/{self._key}'
+    """
+    Represents a financial market sector and allows retrieval of sector-related data 
+    such as top ETFs, top mutual funds, and industry data.
+    """
+
+    def __init__(self, key, session=None, proxy=_SENTINEL_):
+        """
+        Args:
+            key (str): The key representing the sector.
+            session (requests.Session, optional): A session for making requests. Defaults to None.
+            proxy (dict, optional): A dictionary containing proxy settings for the request. Defaults to None.
         
+        .. seealso::
+   
+            :attr:`Sector.industries <yfinance.Sector.industries>`
+                Map of sector and industry
+        """
+        if proxy is not _SENTINEL_:
+            warnings.warn("Set proxy via new config function: yf.set_config(proxy=proxy)", DeprecationWarning, stacklevel=2)
+            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
         self._industries: Optional[_pd.DataFrame] = None
 
     def __repr__(self):
+        """
+        Returns the string representation of the Sector object.
+
+        Returns:
+            str: A string representation of the object.
+        """
         return f'yfinance.Sector object <{self._key}>'
     
     @property
     def top_etfs(self) -> Dict[str, str]:
+        """
+        Gets the top ETFs for the sector.
+
+        Returns:
+            Dict[str, str]: A dictionary of ETF symbols and names.
+        """
         self._ensure_fetched(self._top_etfs)
         return self._top_etfs
 
     @property
     def top_mutual_funds(self) -> Dict[str, str]:
+        """
+        Gets the top mutual funds for the sector.
+
+        Returns:
+            Dict[str, str]: A dictionary of mutual fund symbols and names.
+        """
         self._ensure_fetched(self._top_mutual_funds)
         return self._top_mutual_funds
 
+    @dynamic_docstring({"sector_industry": generate_list_table_from_dict(SECTOR_INDUSTY_MAPPING_LC,bullets=True)})
     @property
     def industries(self) -> _pd.DataFrame:
+        """
+        Gets the industries within the sector.
+
+        Returns:
+            pandas.DataFrame: A DataFrame with industries' key, name, symbol, and market weight.
+
+        {sector_industry}
+        """
         self._ensure_fetched(self._industries)
         return self._industries
     
     def _parse_top_etfs(self, top_etfs: Dict) -> Dict[str, str]:
+        """
+        Parses top ETF data from the API response.
+
+        Args:
+            top_etfs (Dict): The raw ETF data from the API response.
+
+        Returns:
+            Dict[str, str]: A dictionary of ETF symbols and names.
+        """
         return {e.get('symbol'): e.get('name') for e in top_etfs}
 
     def _parse_top_mutual_funds(self, top_mutual_funds: Dict) -> Dict[str, str]:
+        """
+        Parses top mutual funds data from the API response.
+
+        Args:
+            top_mutual_funds (Dict): The raw mutual fund data from the API response.
+
+        Returns:
+            Dict[str, str]: A dictionary of mutual fund symbols and names.
+        """
         return {e.get('symbol'): e.get('name') for e in top_mutual_funds}
     
     def _parse_industries(self, industries: Dict) -> _pd.DataFrame:
+        """
+        Parses industry data from the API response into a DataFrame.
+
+        Args:
+            industries (Dict): The raw industry data from the API response.
+
+        Returns:
+            pandas.DataFrame: A DataFrame containing industry key, name, symbol, and market weight.
+        """
         industries_column = ['key','name','symbol','market weight']
         industries_values = [(i.get('key'),
                               i.get('name'),
                               i.get('symbol'),
                               i.get('marketWeight',{}).get('raw', None)
                               ) for i in industries if i.get('name') != 'All Industries']
-        return _pd.DataFrame(industries_values, columns = industries_column).set_index('key')
+        return _pd.DataFrame(industries_values, columns=industries_column).set_index('key')
 
     def _fetch_and_parse(self) -> None:
+        """
+        Fetches and parses sector data from the API.
+
+        Fetches data for the sector and parses the top ETFs, top mutual funds, 
+        and industries within the sector. Stores the parsed data in the corresponding
+        attributes `_top_etfs`, `_top_mutual_funds`, and `_industries`.
+
+        Raises:
+            Exception: If fetching or parsing the sector data fails.
+        """
         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)
 
@@ -61,9 +148,9 @@ class Sector(Domain):
             self._industries = self._parse_industries(data.get('industries', {}))
 
         except Exception as e:
-            logger = utils.get_yf_logger()
+            logger = get_yf_logger()
             logger.error(f"Failed to get sector data for '{self._key}' reason: {e}")
             logger.debug("Got response: ")
             logger.debug("-------------")
             logger.debug(f" {result}")
-            logger.debug("-------------")
+            logger.debug("-------------")

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 one of: {valid_ranges}")
+
+
+class YFRateLimitError(YFException):
+    def __init__(self):
+        super().__init__("Too Many Requests. Rate limited. Try after a while.")

yfinance/live.py

@@ -0,0 +1,335 @@
+import asyncio
+import base64
+import json
+from typing import List, Optional, Callable, Union
+
+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: Union[str, List[str]]):
+        """
+        Subscribe to a stock symbol or a list of stock symbols.
+
+        Args:
+            symbols (Union[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: Union[str, List[str]]):
+        """
+        Unsubscribe from a stock symbol or a list of stock symbols.
+
+        Args:
+            symbols (Union[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: Union[str, List[str]]):
+        """
+        Subscribe to a stock symbol or a list of stock symbols.
+
+        Args:
+            symbols (Union[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: Union[str, List[str]]):
+        """
+        Unsubscribe from a stock symbol or a list of stock symbols.
+
+        Args:
+            symbols (Union[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()

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
+import warnings
+
+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=_SENTINEL_, timeout=30, raise_errors=True):
+        self.session = session
+        self._data = YfData(session=self.session)
+
+        if proxy is not _SENTINEL_:
+            warnings.warn("Set proxy via new config function: yf.set_config(proxy=proxy)", DeprecationWarning, stacklevel=2)
+            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")