Version 1.1.0

sync 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/dependabot.yml

@@ -1,7 +1,13 @@
 version: 2
 updates:
+
 - package-ecosystem: pip
   directory: "/"
   schedule:
     interval: daily
   open-pull-requests-limit: 10
+
+- package-ecosystem: "github-actions"
+  directory: "/"
+  schedule:
+    interval: "weekly"

.github/workflows/auto_close_default_issues.yml

@@ -0,0 +1,42 @@
+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@v8
+        with:
+          script: |
+            const issue = context.payload.issue;
+            const body = issue.body || '';
+            const title = issue.title || '';
+            const textToCheck = (title + ' ' + body).toLowerCase();
+            
+            // Check for specific fields from your custom form
+            const hasCustomFields = body.includes('### Describe bug') || 
+                                   body.includes('### Simple code that reproduces');
+            
+            // Check for bug-related keywords
+            const bugKeywords = ['bug', 'problem', 'broken'];
+            const looksBugReport = bugKeywords.some(keyword => textToCheck.includes(keyword));
+            
+            // Only close if it looks like a bug report but doesn't use the template
+            if (!hasCustomFields && looksBugReport) {
+              await github.rest.issues.createComment({
+                owner: context.repo.owner,
+                repo: context.repo.repo,
+                issue_number: issue.number,
+                body: 'This issue appears to be a bug report but doesn\'t use our bug report template. Resubmit with 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@v6
+
+    - name: Set up Python
+      uses: actions/setup-python@v6
+      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/pyright.yml

@@ -13,10 +13,10 @@ jobs:
 
     steps:
     - name: Checkout code
-      uses: actions/checkout@v2
+      uses: actions/checkout@v6
 
     - name: Set up Python
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v6
 
     - name: Install dependencies
       run: |

.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/python-publish.yml

@@ -13,9 +13,9 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v6
     - name: Set up Python
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v6
       with:
         python-version: '3.x'
     - name: Install dependencies

.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@v6
+      - uses: astral-sh/ruff-action@v3
+        with:
+          args: check --ignore E702 . --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 +1,189 @@
 Change Log
 ===========
 
+1.1.0
+-----
+Features:
+- New price repair: capital gains double-counting #2667
+Fixes:
+- Fix Saudi Arabia MIC Code #2665 @salsugair
+- Add config to __all__ #2673 @kbluck
+- Fix Python 3.9 compatibility regression in calendars.py #2674 @orionnelson
+- Improve stock-split repair false-positives #2668
+- Docs for capital-gains repair; Fix warnings in price-repair 27cb8aa
+Already in main:
+- Upgrade to Pandas 3.0 (Fixes #2679) #2683
+
+1.0
+---
+yfinance been stable a long time now, time to grow up
+
+No breaking changes, but some deprecation warnings.
+
+Features:
+- New config class yf.config / Improve exception handling #2524
+- Feature: Earning Calendar (& other calendars) #2615 @ianmihura
+- Add optional retry mechanism for transient network errors #2627 @axisrow
+Fixes:
+- 'Industry' column names #2613 @danchev
+- Correct 30m interval alignment and filtering for NSE/early-open markets #2642 @biplavbarua
+- Screener's sector industry mapping #2648 @ericpien
+- Set period default to None in multi #2650 @evanreynolds9
+- price-div-repair dropping NaN rows #2651
+- Block curl_cffi version 0.14 #2653
+
+
+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

@@ -1,367 +1,70 @@
+<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.](https://github.com/ranaroussi/yfinance/blob/main/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)
 
 ---
 
 ### Legal Stuff
 
 **yfinance** is distributed under the **Apache Software License**. See
-the [LICENSE.txt](./LICENSE.txt) file in the release for details.
-
+the [LICENSE.txt](https://github.com/ranaroussi/yfinance/blob/main/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
@@ -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 +1,56 @@
+******
+Config
+******
+
+`yfinance` has a new global config for sharing common values:
+
+.. code-block:: python
+
+  >>> import yfinance as yf
+  >>> yf.config
+  {
+    "network": {
+      "proxy": null,
+      "retries": 0
+    },
+    "debug": {
+      "hide_exceptions": true,
+      "logging": false
+    }
+  }
+  >>> yf.config.network
+  {
+    "proxy": null,
+    "retries": 0
+  }
+
+
+Network
+-------
+
+* **proxy** - Set proxy for all yfinance data fetches.
+
+  .. code-block:: python
+
+     yf.config.network.proxy = "PROXY_SERVER"
+
+* **retries** - Configure automatic retry for transient network errors. The retry mechanism uses exponential backoff (1s, 2s, 4s...).
+
+  .. code-block:: python
+
+     yf.config.network.retries = 2
+
+Debug
+-----
+
+* **hide_exceptions** - Set to `False` to stop yfinance hiding exceptions.
+
+  .. code-block:: python
+
+     yf.config.debug.hide_exceptions = False
+
+* **logging** - Set to `True` to enable verbose debug logging.
+
+  .. code-block:: python
+
+     yf.config.debug.logging = True

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 +1,302 @@
+************
+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)
+5. **NEW: capital gains double-counted**
+
+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
+
+
+Capital-gains double-counted
+----------------------------
+
+Clue: price drop matches dividend better than dividend+capital gains.
+
+DODFX
+
+.. code-block:: text
+
+   # ORIGINAL:
+                                  Close  Adj Close  Dividends  Capital Gains
+   Date                                                                     
+   2025-12-18 00:00:00-05:00  16.219999  16.219999      0.837          0.417
+   2025-12-17 00:00:00-05:00  16.920000  15.665999      0.000          0.000
+
+.. code-block:: text
+
+   # REPAIRED:
+                                  Close  Adj Close  Dividends  Capital Gains
+   Date                                                                     
+   2025-12-18 00:00:00-05:00  16.219999  16.219999       0.42          0.417
+   2025-12-17 00:00:00-05:00  16.920000  16.083000       0.00          0.000

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/calendars.py

@@ -0,0 +1,38 @@
+import yfinance as yf
+from datetime import datetime, timedelta
+
+# Default init (today + 7 days)
+calendar = yf.Calendars()
+
+# Today's events: calendar of 1 day
+tomorrow = datetime.now() + timedelta(days=1)
+calendar = yf.Calendars(end=tomorrow)
+
+# Default calendar queries - accessing the properties will fetch the data from YF
+calendar.earnings_calendar
+calendar.ipo_info_calendar
+calendar.splits_calendar
+calendar.economic_events_calendar
+
+# Manual queries
+calendar.get_earnings_calendar()
+calendar.get_ipo_info_calendar()
+calendar.get_splits_calendar()
+calendar.get_economic_events_calendar()
+
+# Earnings calendar custom filters
+calendar.get_earnings_calendar(
+    market_cap=100_000_000,  # filter out small-cap 
+    filter_most_active=True,  # show only actively traded. Uses: `screen(query="MOST_ACTIVES")`
+)
+
+# Example of real use case:
+# Get inminent unreported earnings events
+today = datetime.now()
+is_friday = today.weekday() == 4
+day_after_tomorrow = today + timedelta(days=4 if is_friday else 2)
+
+calendar = yf.Calendars(today, day_after_tomorrow)
+df = calendar.get_earnings_calendar(limit=100)
+
+unreported_df = df[df["Reported EPS"].isnull()]

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 +1,52 @@
+=============
+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:`Calendars <yfinance.Calendars>`: Class for accessing calendar events data.
+- :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.calendars
+   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.calendars.rst

@@ -0,0 +1,21 @@
+=====================
+Calendars
+=====================
+
+.. currentmodule:: yfinance
+
+
+Class
+------------
+The `Calendars` class allows you to get information about upcoming events, for example, earning events.
+
+.. autosummary::
+   :toctree: api/
+
+   Calendars
+
+Sample Code
+------------------
+
+.. literalinclude:: examples/calendars.py
+   :language: python

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 = "1.1.0" %}
 
 package:
   name: "{{ name|lower }}"
@@ -15,6 +15,7 @@ build:
   script: "{{ PYTHON }} -m pip install . --no-deps --ignore-installed -vv "
 
 requirements:
+  # curl_cffi 0.14 has major problems, see their Github
   host:
     - pandas >=1.3.0
     - numpy >=1.16.5
@@ -26,8 +27,8 @@ requirements:
     - frozendict >=2.3.4
     - beautifulsoup4 >=4.11.1
     - html5lib >=1.1
+    - curl_cffi >=0.7,<0.14
     - peewee >=3.16.2
-    # - pycryptodome >=3.6.6
     - pip
     - python
 
@@ -42,8 +43,8 @@ requirements:
     - frozendict >=2.3.4
     - beautifulsoup4 >=4.11.1
     - html5lib >=1.1
+    - curl_cffi >=0.7,<0.14
     - 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 +2,15 @@ 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 0.14 has major problems, see their Github
+curl_cffi>=0.7,<0.14
+protobuf>=3.19.0
+websockets>=13.0

setup.py

@@ -59,15 +59,22 @@ setup(
     platforms=['any'],
     keywords='pandas, yahoo finance, pandas datareader',
     packages=find_packages(exclude=['contrib', 'docs', 'tests', 'examples']),
+    # curl_cffi 0.14 has major problems, see their Github
     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,<0.14',
+                      '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/AET-L-1wk-100x-error-fixed.csv

@@ -1,37 +0,0 @@
-Date,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits
-2022-05-30 00:00:00+01:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-05-23 00:00:00+01:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-05-16 00:00:00+01:00,14.5500,14.5500,14.5500,14.5500,14.5500,532454,0,0
-2022-05-09 00:00:00+01:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-05-02 00:00:00+01:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-04-25 00:00:00+01:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-04-18 00:00:00+01:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-04-11 00:00:00+01:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-04-04 00:00:00+01:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-03-28 00:00:00+01:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-03-21 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-03-14 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-03-07 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-02-28 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-02-21 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-02-14 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-02-07 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-01-31 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-01-24 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-01-17 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-01-10 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2022-01-03 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2021-12-27 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2021-12-20 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2021-12-13 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2021-12-06 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2021-11-29 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2021-11-22 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2021-11-15 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2021-11-08 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2021-11-01 00:00:00+00:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2021-10-25 00:00:00+01:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2021-10-18 00:00:00+01:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2021-10-11 00:00:00+01:00,14.5500,14.5500,14.5500,14.5500,14.5500,0,0,0
-2021-10-04 00:00:00+01:00,14.8000,15.3400,14.4000,14.5500,14.5500,2171373,0,0
-2021-09-27 00:00:00+01:00,15.6000,16.0000,14.9000,15.0500,15.0500,3860549,0,0

tests/data/AET-L-1wk-100x-error.csv

@@ -1,37 +0,0 @@
-Date,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits
-2022-05-30 00:00:00+01:00,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0,0.0,0.0
-2022-05-23 00:00:00+01:00,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0,0.0,0.0
-2022-05-16 00:00:00+01:00,14.550000190734863,14.550000190734863,0.14550000429153442,0.14550000429153442,0.14550000429153442,532454,0.0,0.0
-2022-05-09 00:00:00+01:00,14.550000190734863,14.550000190734863,14.550000190734863,14.550000190734863,14.550000190734863,0,0.0,0.0
-2022-05-02 00:00:00+01:00,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0,0.0,0.0
-2022-04-25 00:00:00+01:00,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0,0.0,0.0
-2022-04-18 00:00:00+01:00,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0,0.0,0.0
-2022-04-11 00:00:00+01:00,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0,0.0,0.0
-2022-04-04 00:00:00+01:00,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0,0.0,0.0
-2022-03-28 00:00:00+01:00,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0,0.0,0.0
-2022-03-21 00:00:00+00:00,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0,0.0,0.0
-2022-03-14 00:00:00+00:00,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0.14550000429153442,0,0.0,0.0
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tests/data/DODFX-1d-cg-double-count-fixed.csv

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tests/data/DODFX-1d-cg-double-count.csv

@@ -0,0 +1,503 @@
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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?
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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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 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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@@ -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

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 2022-02-11 00:00:00+00:00,0.6875,0.6875,0.6875,0.6875,0.6084982681274415,0,0.0,0.0,0.0
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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
 2022-12-05 00:00:00+00:00,0.6,0.6,0.59,0.6,0.5482531356811523,67809,0.0,0.0,0.0
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@@ -362,9 +362,9 @@ Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits,Capital Gai
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@@ -376,16 +376,16 @@ Datetime,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits,Capital Gai
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 2023-07-20 00:00:00+01:00,0.5700000000000001,0.5700000000000001,0.5700000000000001,0.5700000000000001,0.5389831924438476,0,0.0002,0.0,0.0
 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
 2023-07-24 00:00:00+01:00,0.5700000000000001,0.5700000000000001,0.5700000000000001,0.5700000000000001,0.5389831924438476,0,0.0,0.0,0.0
@@ -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
 2023-08-01 00:00:00+01:00,0.5650000000000001,0.5720000076293945,0.5720000076293945,0.5650000000000001,0.534255256652832,600,0.0,0.0,0.0
 2023-08-02 00:00:00+01:00,0.5650000000000001,0.5650000000000001,0.5650000000000001,0.5650000000000001,0.534255256652832,0,0.0,0.0,0.0
-2023-08-03 00:00:00+01:00,0.5650000000000001,0.54,0.54,0.54,0.5106156539916993,1731,0.0,0.0,0.0
+2023-08-03 00:00:00+01:00,0.5650000000000001,0.54,0.54,0.54,0.5106156921386719,1731,0.0,0.0,0.0
 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
 2023-08-07 00:00:00+01:00,0.5650000000000001,0.5720000076293945,0.5720000076293945,0.5650000000000001,0.534255256652832,8612,0.0,0.0,0.0
 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 @@
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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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 2022-07-25 00:00:00-04:00,3.6500000953674316,3.890000104904175,3.609999895095825,3.8399999141693115,2.1603708267211914,617400,0.0,0.0
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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
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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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 2022-08-30 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
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 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
-2022-10-04 00:00:00-04:00,3.9800000190734863,4.119999885559082,3.9800000190734863,4.010000228881836,2.256012439727783,638800,0.0,0.0
-2022-10-05 00:00:00-04:00,4.019999980926514,4.269999980926514,3.990000009536743,4.170000076293945,2.3460276126861572,615400,0.0,0.0
+2022-10-04 00:00:00-04:00,3.9800000190734863,4.119999885559082,3.9800000190734863,4.010000228881836,2.256012201309204,638800,0.0,0.0
+2022-10-05 00:00:00-04:00,4.019999980926514,4.269999980926514,3.990000009536743,4.170000076293945,2.3460278511047363,615400,0.0,0.0
 2022-10-06 00:00:00-04:00,4.139999866485596,4.409999847412109,4.139999866485596,4.380000114440918,2.4641730785369873,418100,0.0,0.0
-2022-10-07 00:00:00-04:00,4.360000133514404,4.440000057220459,4.21999979019165,4.269999980926514,2.402287483215332,673400,0.0,0.0
+2022-10-07 00:00:00-04:00,4.360000133514404,4.440000057220459,4.21999979019165,4.269999980926514,2.402287244796753,673400,0.0,0.0
 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
-2022-10-13 00:00:00-04:00,3.9100000858306885,4.099999904632568,3.9100000858306885,4.039999961853027,2.272890090942383,625900,0.0,0.0
+2022-10-13 00:00:00-04:00,3.9100000858306885,4.099999904632568,3.9100000858306885,4.039999961853027,2.272890329360962,625900,0.0,0.0
 2022-10-14 00:00:00-04:00,4.010000228881836,4.070000171661377,3.8299999237060547,3.8399999141693115,2.1603708267211914,353500,0.0,0.0
 2022-10-17 00:00:00-04:00,3.890000104904175,3.9700000286102295,3.8499999046325684,3.9000000953674316,2.194126844406128,546400,0.0,0.0
-2022-10-18 00:00:00-04:00,3.930000066757202,3.990000009536743,3.8299999237060547,3.9100000858306885,2.1997525691986084,377200,0.0,0.0
+2022-10-18 00:00:00-04:00,3.930000066757202,3.990000009536743,3.8299999237060547,3.9100000858306885,2.1997528076171875,377200,0.0,0.0
 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
-2022-10-21 00:00:00-04:00,3.9800000190734863,4.039999961853027,3.930000066757202,3.950000047683716,2.2222564220428467,396900,0.0,0.0
+2022-10-21 00:00:00-04:00,3.9800000190734863,4.039999961853027,3.930000066757202,3.950000047683716,2.222256660461426,396900,0.0,0.0
 2022-10-24 00:00:00-04:00,3.9800000190734863,4.059999942779541,3.9100000858306885,4.0,2.2503862380981445,496100,0.0,0.0
-2022-10-25 00:00:00-04:00,3.9700000286102295,4.079999923706055,3.9700000286102295,4.059999942779541,2.284142017364502,532500,0.0,0.0
+2022-10-25 00:00:00-04:00,3.9700000286102295,4.079999923706055,3.9700000286102295,4.059999942779541,2.284141778945923,532500,0.0,0.0
 2022-10-26 00:00:00-04:00,4.050000190734863,4.230000019073486,4.050000190734863,4.210000038146973,2.3685317039489746,877200,0.0,0.0
-2022-10-27 00:00:00-04:00,4.21999979019165,4.300000190734863,4.130000114440918,4.170000076293945,2.3460276126861572,474000,0.0,0.0
-2022-10-28 00:00:00-04:00,4.119999885559082,4.199999809265137,4.03000020980835,4.070000171661377,2.2897682189941406,363900,0.0,0.0
-2022-10-31 00:00:00-04:00,4.010000228881836,4.230000019073486,4.010000228881836,4.110000133514404,2.3122718334198,628500,0.0,0.0
+2022-10-27 00:00:00-04:00,4.21999979019165,4.300000190734863,4.130000114440918,4.170000076293945,2.3460278511047363,474000,0.0,0.0
+2022-10-28 00:00:00-04:00,4.119999885559082,4.199999809265137,4.03000020980835,4.070000171661377,2.2897684574127197,363900,0.0,0.0
+2022-10-31 00:00:00-04:00,4.010000228881836,4.230000019073486,4.010000228881836,4.110000133514404,2.312272071838379,628500,0.0,0.0
 2022-11-01 00:00:00-04:00,4.230000019073486,4.25,4.139999866485596,4.179999828338623,2.351653575897217,319700,0.0,0.0
 2022-11-02 00:00:00-04:00,4.170000076293945,4.340000152587891,4.110000133514404,4.21999979019165,2.374157428741455,481300,0.0,0.0
-2022-11-03 00:00:00-04:00,4.190000057220459,4.340000152587891,4.179999828338623,4.289999961853027,2.413539171218872,279400,0.0,0.0
+2022-11-03 00:00:00-04:00,4.190000057220459,4.340000152587891,4.179999828338623,4.289999961853027,2.413539409637451,279400,0.0,0.0
 2022-11-04 00:00:00-04:00,4.360000133514404,4.590000152587891,4.340000152587891,4.550000190734863,2.559814453125,741800,0.0,0.0
-2022-11-07 00:00:00-05:00,4.559999942779541,4.599999904632568,4.5,4.579999923706055,2.5766923427581787,366700,0.0,0.0
+2022-11-07 00:00:00-05:00,4.559999942779541,4.599999904632568,4.5,4.579999923706055,2.5766921043395996,366700,0.0,0.0
 2022-11-08 00:00:00-05:00,4.590000152587891,4.599999904632568,4.460000038146973,4.510000228881836,2.537310838699341,426500,0.0,0.0
 2022-11-09 00:00:00-05:00,4.099999904632568,4.130000114440918,3.509999990463257,3.5799999237060547,2.0140955448150635,3261400,0.0,0.0
-2022-11-10 00:00:00-05:00,3.609999895095825,3.609999895095825,3.240000009536743,3.5199999809265137,1.9803398847579956,2489900,0.0,0.0
-2022-11-11 00:00:00-05:00,3.549999952316284,3.549999952316284,3.369999885559082,3.4800000190734863,1.9578360319137573,1531900,0.0,0.0
-2022-11-14 00:00:00-05:00,3.4100000858306885,3.619999885559082,3.380000114440918,3.5199999809265137,1.9803398847579956,1636500,0.0,0.0
-2022-11-15 00:00:00-05:00,3.549999952316284,3.6500000953674316,3.509999990463257,3.619999885559082,2.036599636077881,613200,0.0,0.0
-2022-11-16 00:00:00-05:00,3.619999885559082,3.619999885559082,3.440000057220459,3.450000047683716,1.9409581422805786,1095300,0.0,0.0
-2022-11-17 00:00:00-05:00,3.4200000762939453,3.4200000762939453,3.2200000286102295,3.359999895095825,1.890324592590332,1058500,0.0,0.0
+2022-11-10 00:00:00-05:00,3.609999895095825,3.609999895095825,3.240000009536743,3.5199999809265137,1.9803401231765747,2489900,0.0,0.0
+2022-11-11 00:00:00-05:00,3.549999952316284,3.549999952316284,3.369999885559082,3.4800000190734863,1.9578361511230469,1531900,0.0,0.0
+2022-11-14 00:00:00-05:00,3.4100000858306885,3.619999885559082,3.380000114440918,3.5199999809265137,1.9803401231765747,1636500,0.0,0.0
+2022-11-15 00:00:00-05:00,3.549999952316284,3.6500000953674316,3.509999990463257,3.619999885559082,2.0365993976593018,613200,0.0,0.0
+2022-11-16 00:00:00-05:00,3.619999885559082,3.619999885559082,3.440000057220459,3.450000047683716,1.940958023071289,1095300,0.0,0.0
+2022-11-17 00:00:00-05:00,3.4200000762939453,3.4200000762939453,3.2200000286102295,3.359999895095825,1.890324354171753,1058500,0.0,0.0
 2022-11-18 00:00:00-05:00,3.299999952316284,3.3499999046325684,3.2300000190734863,3.3299999237060547,1.8734464645385742,1005000,0.0,0.0
 2022-11-21 00:00:00-05:00,3.2899999618530273,3.3299999237060547,3.130000114440918,3.2899999618530273,1.8509427309036255,1701700,0.0,0.0
-2022-11-22 00:00:00-05:00,3.309999942779541,3.450000047683716,3.309999942779541,3.4100000858306885,1.9184544086456299,668000,0.0,0.0
-2022-11-23 00:00:00-05:00,3.3399999141693115,3.559999942779541,3.299999952316284,3.4600000381469727,1.9465841054916382,626600,0.0,0.0
+2022-11-22 00:00:00-05:00,3.309999942779541,3.450000047683716,3.309999942779541,3.4100000858306885,1.9184542894363403,668000,0.0,0.0
+2022-11-23 00:00:00-05:00,3.3399999141693115,3.559999942779541,3.299999952316284,3.4600000381469727,1.9465842247009277,626600,0.0,0.0
 2022-11-24 00:00:00-05:00,3.450000047683716,3.4600000381469727,3.380000114440918,3.430000066757202,1.9297062158584595,213400,0.0,0.0
 2022-11-25 00:00:00-05:00,3.450000047683716,3.4800000190734863,3.369999885559082,3.380000114440918,1.9015765190124512,404100,0.0,0.0
-2022-11-28 00:00:00-05:00,3.309999942779541,3.359999895095825,3.259999990463257,3.299999952316284,1.8565688133239746,472800,0.0,0.0
+2022-11-28 00:00:00-05:00,3.309999942779541,3.359999895095825,3.259999990463257,3.299999952316284,1.8565685749053955,472800,0.0,0.0
 2022-11-29 00:00:00-05:00,3.3299999237060547,3.4800000190734863,3.309999942779541,3.4000000953674316,1.9128283262252808,782700,0.0,0.0
 2022-11-30 00:00:00-05:00,3.5899999141693115,3.5899999141693115,3.4000000953674316,3.4000000953674316,1.9128283262252808,1510300,0.0,0.0
 2022-12-01 00:00:00-05:00,3.4600000381469727,3.549999952316284,3.359999895095825,3.369999885559082,1.895950436592102,570700,0.0,0.0
 2022-12-02 00:00:00-05:00,3.369999885559082,3.450000047683716,3.3299999237060547,3.3499999046325684,1.8846986293792725,319600,0.0,0.0
-2022-12-05 00:00:00-05:00,3.4000000953674316,3.4700000286102295,3.259999990463257,3.299999952316284,1.8565688133239746,1100300,0.0,0.0
+2022-12-05 00:00:00-05:00,3.4000000953674316,3.4700000286102295,3.259999990463257,3.299999952316284,1.8565685749053955,1100300,0.0,0.0
 2022-12-06 00:00:00-05:00,3.2899999618530273,3.3499999046325684,3.0799999237060547,3.0799999237060547,1.732797384262085,1268000,0.0,0.0
 2022-12-07 00:00:00-05:00,3.0799999237060547,3.180000066757202,2.9800000190734863,3.0899999141693115,1.738423466682434,769100,0.0,0.0
-2022-12-08 00:00:00-05:00,3.190000057220459,3.190000057220459,2.990000009536743,3.0299999713897705,1.7046674489974976,618300,0.0,0.0
+2022-12-08 00:00:00-05:00,3.190000057220459,3.190000057220459,2.990000009536743,3.0299999713897705,1.7046676874160767,618300,0.0,0.0
 2022-12-09 00:00:00-05:00,3.0199999809265137,3.059999942779541,2.950000047683716,3.059999942779541,1.7215455770492554,779100,0.0,0.0
-2022-12-12 00:00:00-05:00,3.059999942779541,3.0899999141693115,2.950000047683716,2.9700000286102295,1.6709117889404297,1015200,0.0,0.0
-2022-12-13 00:00:00-05:00,3.059999942779541,3.130000114440918,2.930000066757202,3.049999952316284,1.7159194946289062,1585100,0.0,0.0
+2022-12-12 00:00:00-05:00,3.059999942779541,3.0899999141693115,2.950000047683716,2.9700000286102295,1.6709119081497192,1015200,0.0,0.0
+2022-12-13 00:00:00-05:00,3.059999942779541,3.130000114440918,2.930000066757202,3.049999952316284,1.7159196138381958,1585100,0.0,0.0
 2022-12-14 00:00:00-05:00,3.0799999237060547,3.119999885559082,3.009999990463257,3.0999999046325684,1.744049310684204,508600,0.0,0.0
 2022-12-15 00:00:00-05:00,3.049999952316284,3.0799999237060547,2.9700000286102295,3.0799999237060547,1.732797384262085,802900,0.0,0.0
 2022-12-16 00:00:00-05:00,3.009999990463257,3.0299999713897705,2.890000104904175,2.940000057220459,1.6540340185165405,1059300,0.0,0.0
 2022-12-19 00:00:00-05:00,2.9100000858306885,2.930000066757202,2.680000066757202,2.740000009536743,1.5415146350860596,2117800,0.0,0.0
-2022-12-20 00:00:00-05:00,2.740000009536743,2.859999895095825,2.7100000381469727,2.8299999237060547,1.5921483039855957,988400,0.0,0.0
-2022-12-21 00:00:00-05:00,2.8399999141693115,3.059999942779541,2.8399999141693115,3.0299999713897705,1.7046674489974976,796100,0.0,0.0
+2022-12-20 00:00:00-05:00,2.740000009536743,2.859999895095825,2.7100000381469727,2.8299999237060547,1.5921484231948853,988400,0.0,0.0
+2022-12-21 00:00:00-05:00,2.8399999141693115,3.059999942779541,2.8399999141693115,3.0299999713897705,1.7046676874160767,796100,0.0,0.0
 2022-12-22 00:00:00-05:00,3.049999952316284,3.059999942779541,2.890000104904175,2.9200000762939453,1.6427820920944214,1115000,0.0,0.0
 2022-12-23 00:00:00-05:00,2.9700000286102295,3.190000057220459,2.950000047683716,3.1700000762939453,1.7834311723709106,1357700,0.0,0.0
 2022-12-28 00:00:00-05:00,3.109999895095825,3.119999885559082,2.9200000762939453,2.940000057220459,1.6540340185165405,1075500,0.0,0.0
 2022-12-29 00:00:00-05:00,2.9200000762939453,3.009999990463257,2.9200000762939453,2.990000009536743,1.6821637153625488,471300,0.0,0.0
-2022-12-30 00:00:00-05:00,2.9600000381469727,3.0299999713897705,2.9600000381469727,3.0,1.6877896785736084,573100,0.0,0.0
+2022-12-30 00:00:00-05:00,2.9600000381469727,3.0299999713897705,2.9600000381469727,3.0,1.6877899169921875,573100,0.0,0.0
 2023-01-03 00:00:00-05:00,2.9700000286102295,3.0,2.75,2.7699999809265137,1.5583925247192383,766300,0.0,0.0
 2023-01-04 00:00:00-05:00,2.7699999809265137,2.7799999713897705,2.680000066757202,2.7100000381469727,1.5246367454528809,735100,0.0,0.0
 2023-01-05 00:00:00-05:00,2.690000057220459,2.7699999809265137,2.680000066757202,2.7100000381469727,1.5246367454528809,716200,0.0,0.0
-2023-01-06 00:00:00-05:00,2.7300000190734863,2.809999942779541,2.7300000190734863,2.799999952316284,1.5752702951431274,333100,0.0,0.0
+2023-01-06 00:00:00-05:00,2.7300000190734863,2.809999942779541,2.7300000190734863,2.799999952316284,1.575270414352417,333100,0.0,0.0
 2023-01-09 00:00:00-05:00,2.859999895095825,2.950000047683716,2.819999933242798,2.880000114440918,1.620278239250183,491400,0.0,0.0
-2023-01-10 00:00:00-05:00,2.859999895095825,2.9100000858306885,2.809999942779541,2.890000104904175,1.6259040832519531,418900,0.0,0.0
+2023-01-10 00:00:00-05:00,2.859999895095825,2.9100000858306885,2.809999942779541,2.890000104904175,1.6259039640426636,418900,0.0,0.0
 2023-01-11 00:00:00-05:00,2.890000104904175,2.990000009536743,2.890000104904175,2.9200000762939453,1.6427820920944214,808900,0.0,0.0
 2023-01-12 00:00:00-05:00,2.9700000286102295,3.0799999237060547,2.950000047683716,3.0399999618530273,1.7102934122085571,900700,0.0,0.0
-2023-01-13 00:00:00-05:00,3.0399999618530273,3.0999999046325684,2.9800000190734863,3.0299999713897705,1.7046674489974976,625000,0.0,0.0
-2023-01-16 00:00:00-05:00,3.0299999713897705,3.0399999618530273,3.0,3.009999990463257,1.6934157609939575,360400,0.0,0.0
+2023-01-13 00:00:00-05:00,3.0399999618530273,3.0999999046325684,2.9800000190734863,3.0299999713897705,1.7046676874160767,625000,0.0,0.0
+2023-01-16 00:00:00-05:00,3.0299999713897705,3.0399999618530273,3.0,3.009999990463257,1.693415641784668,360400,0.0,0.0
 2023-01-17 00:00:00-05:00,3.059999942779541,3.1700000762939453,3.0,3.1500000953674316,1.7721792459487915,699200,0.0,0.0
 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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 2023-05-25 00:00:00-04:00,2.5,2.5,2.380000114440918,2.4000000953674316,1.5923840999603271,287100,0.0,0.0
 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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+2023-08-03 00:00:00-04:00,2.359999895095825,2.450000047683716,2.359999895095825,2.440000057220459,1.9796843528747559,814300,0.0,0.0
 2023-08-04 00:00:00-04:00,2.4700000286102295,2.5399999618530273,2.4200000762939453,2.5399999618530273,2.060818910598755,1363900,0.0,0.0
 2023-08-08 00:00:00-04:00,2.509999990463257,2.549999952316284,2.4700000286102295,2.5299999713897705,2.0527055263519287,776900,0.0,0.0
 2023-08-09 00:00:00-04:00,2.549999952316284,2.559999942779541,2.5,2.5199999809265137,2.0445921421051025,932100,0.0,0.0
 2023-08-10 00:00:00-04:00,2.5199999809265137,2.5299999713897705,2.4700000286102295,2.490000009536743,2.020251750946045,389700,0.0,0.0
 2023-08-11 00:00:00-04:00,2.4800000190734863,2.509999990463257,2.4800000190734863,2.509999990463257,2.0364787578582764,280800,0.0,0.0
-2023-08-14 00:00:00-04:00,2.509999990463257,2.509999990463257,2.4000000953674316,2.430000066757202,1.9715710878372192,361600,0.0,0.0
-2023-08-15 00:00:00-04:00,2.4200000762939453,2.440000057220459,2.2699999809265137,2.319999933242798,1.8823227882385254,1139100,0.0,0.0
+2023-08-14 00:00:00-04:00,2.509999990463257,2.509999990463257,2.4000000953674316,2.430000066757202,1.9715709686279297,361600,0.0,0.0
+2023-08-15 00:00:00-04:00,2.4200000762939453,2.440000057220459,2.2699999809265137,2.319999933242798,1.882322907447815,1139100,0.0,0.0
 2023-08-16 00:00:00-04:00,2.2899999618530273,2.359999895095825,2.2300000190734863,2.259999990463257,1.8336421251296997,474700,0.0,0.0
-2023-08-17 00:00:00-04:00,2.259999990463257,2.309999942779541,2.25,2.309999942779541,1.8742094039916992,1188900,0.0,0.0
-2023-08-18 00:00:00-04:00,2.2699999809265137,2.390000104904175,2.240000009536743,2.359999895095825,1.9147765636444092,554900,0.0,0.0
-2023-08-21 00:00:00-04:00,2.380000114440918,2.4000000953674316,2.3299999237060547,2.3299999237060547,1.8904362916946411,211200,0.0,0.0
-2023-08-22 00:00:00-04:00,2.3499999046325684,2.369999885559082,2.25,2.2699999809265137,1.8417555093765259,336200,0.0,0.0
-2023-08-23 00:00:00-04:00,2.240000009536743,2.259999990463257,2.200000047683716,2.2200000286102295,1.801188349723816,368100,0.0,0.0
-2023-08-24 00:00:00-04:00,2.2100000381469727,2.2100000381469727,2.130000114440918,2.1600000858306885,1.7525076866149902,270700,0.0,0.0
-2023-08-25 00:00:00-04:00,2.1600000858306885,2.190000057220459,2.0,2.109999895095825,1.7119401693344116,706100,0.0,0.0
-2023-08-28 00:00:00-04:00,2.1500000953674316,2.190000057220459,2.130000114440918,2.1500000953674316,1.744394063949585,655500,0.0,0.0
+2023-08-17 00:00:00-04:00,2.259999990463257,2.309999942779541,2.25,2.309999942779541,1.8742092847824097,1188900,0.0,0.0
+2023-08-18 00:00:00-04:00,2.2699999809265137,2.390000104904175,2.240000009536743,2.359999895095825,1.9147766828536987,554900,0.0,0.0
+2023-08-21 00:00:00-04:00,2.380000114440918,2.4000000953674316,2.3299999237060547,2.3299999237060547,1.8904361724853516,211200,0.0,0.0
+2023-08-22 00:00:00-04:00,2.3499999046325684,2.369999885559082,2.25,2.2699999809265137,1.8417556285858154,336200,0.0,0.0
+2023-08-23 00:00:00-04:00,2.240000009536743,2.259999990463257,2.200000047683716,2.2200000286102295,1.8011882305145264,368100,0.0,0.0
+2023-08-24 00:00:00-04:00,2.2100000381469727,2.2100000381469727,2.130000114440918,2.1600000858306885,1.7525074481964111,270700,0.0,0.0
+2023-08-25 00:00:00-04:00,2.1600000858306885,2.190000057220459,2.0,2.109999895095825,1.711940050125122,706100,0.0,0.0
+2023-08-28 00:00:00-04:00,2.1500000953674316,2.190000057220459,2.130000114440918,2.1500000953674316,1.7443941831588745,655500,0.0,0.0
 2023-08-29 00:00:00-04:00,2.1600000858306885,2.200000047683716,2.1500000953674316,2.190000057220459,1.7768479585647583,245600,0.0,0.0
 2023-08-30 00:00:00-04:00,2.180000066757202,2.2200000286102295,2.1700000762939453,2.180000066757202,1.7687344551086426,211200,0.0,0.0
 2023-08-31 00:00:00-04:00,2.190000057220459,2.299999952316284,2.190000057220459,2.2799999713897705,1.8498690128326416,1133800,0.0,0.0
-2023-09-01 00:00:00-04:00,2.299999952316284,2.369999885559082,2.299999952316284,2.359999895095825,1.9147765636444092,761300,0.0,0.0
+2023-09-01 00:00:00-04:00,2.299999952316284,2.369999885559082,2.299999952316284,2.359999895095825,1.9147766828536987,761300,0.0,0.0
 2023-09-05 00:00:00-04:00,2.4200000762939453,2.4200000762939453,2.2699999809265137,2.390000104904175,1.939117193222046,1434000,0.0,0.0
 2023-09-06 00:00:00-04:00,2.380000114440918,2.4000000953674316,2.3299999237060547,2.4000000953674316,1.9472306966781616,352700,0.0,0.0
 2023-09-07 00:00:00-04:00,2.359999895095825,2.390000104904175,2.319999933242798,2.3499999046325684,1.906663179397583,501700,0.0,0.0
-2023-09-08 00:00:00-04:00,2.3499999046325684,2.359999895095825,2.3299999237060547,2.359999895095825,1.9147765636444092,405100,0.0,0.0
+2023-09-08 00:00:00-04:00,2.3499999046325684,2.359999895095825,2.3299999237060547,2.359999895095825,1.9147766828536987,405100,0.0,0.0
 2023-09-11 00:00:00-04:00,2.390000104904175,2.4200000762939453,2.3299999237060547,2.3499999046325684,1.906663179397583,740800,0.0,0.0
-2023-09-12 00:00:00-04:00,2.3499999046325684,2.440000057220459,2.3499999046325684,2.430000066757202,1.9715710878372192,696100,0.0,0.0
-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
+2024-10-02 00:00:00-04:00,27.790000915527344,27.799999237060547,26.290000915527344,26.610000610351562,26.610000610351562,78000,0.0,0.0
+2024-10-03 00:00:00-04:00,26.84000015258789,28.489999771118164,26.84000015258789,28.15999984741211,28.15999984741211,84200,0.0,0.0
+2024-10-04 00:00:00-04:00,28.190000534057617,28.549999237060547,27.790000915527344,28.049999237060547,28.049999237060547,65200,0.0,0.0
+2024-10-07 00:00:00-04:00,28.079999923706055,29.15999984741211,27.760000228881836,28.010000228881836,28.010000228881836,44900,0.0,0.0
+2024-10-08 00:00:00-04:00,27.989999771118164,28.110000610351562,26.850000381469727,27.709999084472656,27.709999084472656,26300,0.0,0.0
+2024-10-09 00:00:00-04:00,27.030000686645508,28.360000610351562,27.030000686645508,28.360000610351562,28.360000610351562,23000,0.0,0.0
+2024-10-10 00:00:00-04:00,28.020000457763672,28.799999237060547,27.969999313354492,28.360000610351562,28.360000610351562,24300,0.0,0.0
+2024-10-11 00:00:00-04:00,28.780000686645508,28.780000686645508,28.06999969482422,28.520000457763672,28.520000457763672,12100,0.0,0.0
+2024-10-15 00:00:00-04:00,28.350000381469727,28.350000381469727,26.540000915527344,26.690000534057617,26.690000534057617,77300,0.0,0.0
+2024-10-16 00:00:00-04:00,26.81999969482422,27.110000610351562,26.700000762939453,26.8700008392334,26.8700008392334,12500,0.0,0.0
+2024-10-17 00:00:00-04:00,26.81999969482422,27.18000030517578,26.770000457763672,27.149999618530273,27.149999618530273,21700,0.0,0.0
+2024-10-18 00:00:00-04:00,27.0,27.09000015258789,26.799999237060547,27.040000915527344,27.040000915527344,24400,0.0,0.0
+2024-10-21 00:00:00-04:00,27.059999465942383,27.739999771118164,27.0,27.739999771118164,27.739999771118164,32400,0.0,0.0
+2024-10-22 00:00:00-04:00,27.8799991607666,28.350000381469727,27.639999389648438,28.290000915527344,28.290000915527344,23900,0.0,0.0
+2024-10-23 00:00:00-04:00,28.1200008392334,28.1200008392334,27.450000762939453,27.81999969482422,27.81999969482422,7200,0.0,0.0
+2024-10-24 00:00:00-04:00,27.719999313354492,27.979999542236328,27.469999313354492,27.979999542236328,27.979999542236328,9100,0.0,0.0
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+2024-10-28 00:00:00-04:00,27.950000762939453,28.06999969482422,27.299999237060547,27.739999771118164,27.739999771118164,75500,0.0,0.0
+2024-10-29 00:00:00-04:00,27.479999542236328,27.899999618530273,27.3799991607666,27.6299991607666,27.6299991607666,23100,0.0,0.0
+2024-10-30 00:00:00-04:00,27.290000915527344,28.06999969482422,27.290000915527344,28.06999969482422,28.06999969482422,11500,0.0,0.0
+2024-10-31 00:00:00-04:00,27.75,27.809999465942383,27.190000534057617,27.520000457763672,27.520000457763672,14500,0.0,0.0
+2024-11-01 00:00:00-04:00,27.75,28.229999542236328,27.079999923706055,27.219999313354492,27.219999313354492,20300,0.0,0.0
+2024-11-04 00:00:00-05:00,27.81999969482422,28.510000228881836,27.59000015258789,28.219999313354492,28.219999313354492,21300,0.0,0.0
+2024-11-05 00:00:00-05:00,28.440000534057617,28.440000534057617,28.09000015258789,28.290000915527344,28.290000915527344,7100,0.0,0.0
+2024-11-06 00:00:00-05:00,27.329999923706055,28.479999542236328,27.329999923706055,28.15999984741211,28.15999984741211,35200,0.0,0.0
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+2024-11-11 00:00:00-05:00,27.940000534057617,29.190000534057617,27.940000534057617,28.969999313354492,28.969999313354492,20600,0.0,0.0
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+2024-11-14 00:00:00-05:00,31.489999771118164,32.540000915527344,30.0,32.5,32.5,150800,0.0,0.0
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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?
-2022-01-03 00:00:00+01:00,20.400468826293945,20.80828094482422,20.400468826293945,20.629241943359375,12.511417295076441,559352,0.0,0.0,True
-2022-01-04 00:00:00+01:00,20.649133682250977,20.897798538208008,20.5098819732666,20.848066329956055,12.644130546760964,930594,0.0,0.0,True
-2022-01-05 00:00:00+01:00,20.897798538208008,21.126571655273438,20.838119506835938,21.126571655273438,12.813041465078337,572100,0.0,0.0,True
-2022-01-06 00:00:00+01:00,20.887853622436523,21.126571655273438,20.599401473999023,20.967424392700195,12.716519396668955,532086,0.0,0.0,True
-2022-01-07 00:00:00+01:00,21.007211685180664,21.186250686645508,20.867958068847656,21.126571655273438,12.813041465078337,698666,0.0,0.0,True
-2022-01-10 00:00:00+01:00,21.186250686645508,21.245929718017578,20.997264862060547,21.05694580078125,12.770813195219185,972438,0.0,0.0,True
-2022-01-11 00:00:00+01:00,21.226036071777344,21.514488220214844,21.226036071777344,21.37523651123047,12.96385517091871,894602,0.0,0.0,True
-2022-01-12 00:00:00+01:00,21.564220428466797,21.604007720947266,21.0469970703125,21.216089248657227,12.867332021949712,838352,0.0,0.0,True
-2022-01-13 00:00:00+01:00,20.897798538208008,21.14646339416504,20.897798538208008,21.14646339416504,13.800840442383679,514241,1.5,0.0,True
-2022-01-14 00:00:00+01:00,20.897798538208008,21.066890716552734,20.80828094482422,21.0271053314209,13.722942899544728,708327,0.0,0.0,True
-2022-01-17 00:00:00+01:00,21.106678009033203,21.633846282958984,21.0469970703125,21.554275512695312,14.066989840136957,947841,0.0,0.0,True
-2022-01-18 00:00:00+01:00,21.454809188842773,21.484647750854492,21.156410217285156,21.405075073242188,13.969617371308459,966355,0.0,0.0,True
-2022-01-19 00:00:00+01:00,21.37523651123047,21.822832107543945,21.295663833618164,21.78304672241211,14.216292923631807,1597827,0.0,0.0,True
-2022-01-20 00:00:00+01:00,21.802940368652344,22.111284255981445,21.544328689575195,21.981977462768555,14.34612108113711,1563328,0.0,0.0,True
-2022-01-21 00:00:00+01:00,21.74325942993164,21.94219207763672,21.415021896362305,21.65374183654785,14.131906620288653,1539782,0.0,0.0,True
-2022-01-24 00:00:00+01:00,21.484647750854492,21.58411407470703,20.887853622436523,20.997264862060547,13.703467973555181,1334240,0.0,0.0,True
-2022-01-25 00:00:00+01:00,21.156410217285156,21.186250686645508,20.877906799316406,20.917692184448242,13.651538439448448,1198631,0.0,0.0,True
-2022-01-26 00:00:00+01:00,20.997264862060547,21.72336769104004,20.997264862060547,21.415021896362305,13.976110454051131,913216,0.0,0.0,True
-2022-01-27 00:00:00+01:00,21.11662483215332,21.862619400024414,21.0469970703125,21.6437931060791,14.12541353754598,765306,0.0,0.0,True
-2022-01-28 00:00:00+01:00,21.554275512695312,21.65374183654785,21.126571655273438,21.484647750854492,14.021549066534426,1109097,0.0,0.0,True
-2022-01-31 00:00:00+01:00,21.6239013671875,21.65374183654785,21.066890716552734,21.186250686645508,13.826805209437046,999557,0.0,0.0,True
-2022-02-01 00:00:00+01:00,21.27577018737793,21.405075073242188,21.05694580078125,21.11662483215332,13.781365516394134,732572,0.0,0.0,True
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tests/data/SOLB-BR-1d-bad-div.csv

@@ -1,678 +0,0 @@
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tests/data/VWILX-1d-cg-double-count-fixed.csv

@@ -0,0 +1,503 @@
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tests/data/VWILX-1d-cg-double-count.csv

@@ -0,0 +1,503 @@
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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_calendars.py

@@ -0,0 +1,55 @@
+from datetime import datetime, timedelta, timezone
+import unittest
+
+import pandas as pd
+
+from tests.context import yfinance as yf, session_gbl
+
+
+class TestCalendars(unittest.TestCase):
+    def setUp(self):
+        self.calendars = yf.Calendars(session=session_gbl)
+
+    def test_get_earnings_calendar(self):
+        result = self.calendars.get_earnings_calendar(limit=1)
+        tickers = self.calendars.earnings_calendar.index.tolist()
+
+        self.assertIsInstance(result, pd.DataFrame)
+        self.assertEqual(len(result), 1)
+        self.assertIsInstance(tickers, list)
+        self.assertEqual(len(tickers), len(result))
+        self.assertEqual(tickers, result.index.tolist())
+        
+        first_ticker = result.index.tolist()[0]
+        result_first_ticker = self.calendars.earnings_calendar.loc[first_ticker].name
+        self.assertEqual(first_ticker, result_first_ticker)
+
+    def test_get_earnings_calendar_init_params(self):
+        result = self.calendars.get_earnings_calendar(limit=5)
+        self.assertGreaterEqual(result['Event Start Date'].iloc[0], pd.to_datetime(datetime.now(tz=timezone.utc)))
+
+        start = datetime.now(tz=timezone.utc) - timedelta(days=7)
+        result = yf.Calendars(start=start).get_earnings_calendar(limit=5)
+        self.assertGreaterEqual(result['Event Start Date'].iloc[0], pd.to_datetime(start))
+
+    def test_get_ipo_info_calendar(self):
+        result = self.calendars.get_ipo_info_calendar(limit=5)
+
+        self.assertIsInstance(result, pd.DataFrame)
+        self.assertEqual(len(result), 5)
+
+    def test_get_economic_events_calendar(self):
+        result = self.calendars.get_economic_events_calendar(limit=5)
+
+        self.assertIsInstance(result, pd.DataFrame)
+        self.assertEqual(len(result), 5)
+
+    def test_get_splits_calendar(self):
+        result = self.calendars.get_splits_calendar(limit=5)
+
+        self.assertIsInstance(result, pd.DataFrame)
+        self.assertEqual(len(result), 5)
+
+
+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

@@ -61,7 +61,7 @@ class TestPriceRepairAssumptions(unittest.TestCase):
                         vol_diff_pct0 = (dfr['Volume'].iloc[0] - df_truth['Volume'].iloc[0])/df_truth['Volume'].iloc[0]
                         vol_diff_pct1 = (dfr['Volume'].iloc[-1] - df_truth['Volume'].iloc[-1])/df_truth['Volume'].iloc[-1]
                         vol_diff_pct = _np.array([vol_diff_pct0, vol_diff_pct1])
-                        vol_match = vol_diff_pct > -0.23
+                        vol_match = vol_diff_pct > -0.32
                         vol_match_nmatch = _np.sum(vol_match)
                         vol_match_ndiff = len(vol_match) - vol_match_nmatch
                         if vol_match.all():
@@ -78,6 +78,8 @@ class TestPriceRepairAssumptions(unittest.TestCase):
 
                     if debug:
                         print("- investigate:")
+                        print(f"  - interval = {interval}")
+                        print(f"  - period = {period}")
                         print("- df_truth:")
                         print(df_truth)#[['Open', 'Close', 'Volume']])
                         df_1d = dat.history(interval='1d', period=period)
@@ -121,7 +123,7 @@ class TestPriceRepair(unittest.TestCase):
 
         tkrs = ["BHP.AX", "IMP.JO", "BP.L", "PNL.L", "INTC"]
 
-        dt_now = _pd.Timestamp.utcnow()
+        dt_now = _pd.Timestamp.now('UTC')
         td_60d = _dt.timedelta(days=60)
 
         # Round time for 'requests_cache' reuse
@@ -301,10 +303,9 @@ class TestPriceRepair(unittest.TestCase):
         # Sometimes Yahoo suddenly shifts from cents->$ from some recent date.
 
         tkrs = ['AET.L', 'SSW.JO']
-        intervals = ['1d', '1wk']
-        # tkrs = ['AET.L']
-        # intervals = ['1wk']
-        # import yfinance as yf ; yf.enable_debug_mode()
+        # intervals = ['1d', '1wk']
+        # Give up repairing 1wk intervals directly. Instead will resample from 1d
+        intervals = ['1d']
 
         for tkr in tkrs:
             for interval in intervals:
@@ -361,27 +362,23 @@ 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 = df_bad.sort_index()
-        df_bad.index.name = "Date"
-        df_bad.index = df_bad.index.tz_localize(tz_exchange)
+        correct_df = dat.history(period='1mo', auto_adjust=False)
+
+        dt_bad = correct_df.index[len(correct_df)//2]
+        df_bad = correct_df.copy()
+        for c in df_bad.columns:
+            df_bad.loc[dt_bad, c] = _np.nan
 
         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
         for c in ["Open", "Low", "High", "Close"]:
-            self.assertTrue(_np.isclose(repaired_df[c], correct_df[c], rtol=1e-8).all())
+            try:
+                self.assertTrue(_np.isclose(repaired_df[c], correct_df[c], rtol=1e-7).all())
+            except Exception:
+                print(f"# column = {c}")
+                print("# correct:") ; print(correct_df[c])
+                print("# repaired:") ; print(repaired_df[c])
+                raise
 
         self.assertTrue("Repaired?" in repaired_df.columns)
         self.assertFalse(repaired_df["Repaired?"].isna().any())
@@ -390,19 +387,21 @@ 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)
@@ -419,7 +418,13 @@ class TestPriceRepair(unittest.TestCase):
 
                 df_slice_bad_repaired = hist._fix_zeroes(df_slice_bad, "1d", tz_exchange, prepost=False)
                 for c in ["Close", "Adj Close"]:
-                    self.assertTrue(_np.isclose(df_slice_bad_repaired[c], df_slice[c], rtol=rtol).all())
+                    try:
+                        self.assertTrue(_np.isclose(df_slice_bad_repaired[c], df_slice[c], rtol=rtol).all())
+                    except Exception:
+                        print(f"# column = {c}")
+                        print("# correct:") ; print(df_slice[c])
+                        print("# repaired:") ; print(df_slice_bad_repaired[c])
+                        raise
                 self.assertTrue("Repaired?" in df_slice_bad_repaired.columns)
                 self.assertFalse(df_slice_bad_repaired["Repaired?"].isna().any())
 
@@ -462,7 +467,7 @@ 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', 'TISI']
         good_tkrs += ['BOL.ST', 'TUI1.DE']
         intervals = ['1d', '1wk', '1mo', '3mo']
         for tkr in good_tkrs:
@@ -488,7 +493,7 @@ 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)
@@ -524,33 +529,36 @@ class TestPriceRepair(unittest.TestCase):
                     # print(repaired_df[c] - correct_df[c])
                     raise
 
-        # Had very high price volatility in Jan-2021 around split date that could
-        # be mistaken for missing stock split adjustment. And old logic did think
-        # column 'High' required fixing - wrong!
-        sketchy_tkrs = ['FIZZ']
-        intervals = ['1wk']
-        for tkr in sketchy_tkrs:
-            for interval in intervals:
-                dat = yf.Ticker(tkr, session=self.session)
-                tz_exchange = dat.fast_info["timezone"]
-                hist = dat._lazy_load_price_history()
+        false_positives = {}
+        # FIZZ had very high price volatility in Jan-2021 around split date:
+        false_positives['FIZZ'] = {'interval': '1d', 'start': '2020-11-30', 'end': '2021-04-01'}
+        # GME has crazy price action in Jan 2021, mistaken for missing 2007 split
+        false_positives['GME'] = {'interval': '1d', 'start': '2007-01-01', 'end': '2023-01-01'}
+        # NVDA has a ~33% price drop on 2004-08-06, confused with earlier 3:2 split
+        false_positives['NVDA'] = {'interval': '1d', 'start': '2001-07-01', 'end': '2007-09-15'}
+        # yf.config.debug.logging = True
+        for tkr, args in false_positives.items():
+            interval = args['interval']
+            dat = yf.Ticker(tkr, session=self.session)
+            tz_exchange = dat.fast_info["timezone"]
+            hist = dat._lazy_load_price_history()
 
-                df_good = hist.history(start='2020-11-30', end='2021-04-01', interval=interval, auto_adjust=False)
+            df_good = hist.history(auto_adjust=False, **args)
 
-                repaired_df = hist._fix_bad_stock_splits(df_good, interval, tz_exchange)
+            repaired_df = hist._fix_bad_stock_splits(df_good, interval, tz_exchange)
 
-                # Expect no change from repair
-                df_good = df_good.sort_index()
-                repaired_df = repaired_df.sort_index()
-                for c in ["Open", "Low", "High", "Close", "Adj Close", "Volume"]:
-                    try:
-                        self.assertTrue((repaired_df[c].to_numpy() == df_good[c].to_numpy()).all())
-                    except AssertionError:
-                        print(f"tkr={tkr} interval={interval} COLUMN={c}")
-                        df_dbg = df_good[[c]].join(repaired_df[[c]], lsuffix='.good', rsuffix='.repaired')
-                        f_diff = repaired_df[c].to_numpy() != df_good[c].to_numpy()
-                        print(df_dbg[f_diff | _np.roll(f_diff, 1) | _np.roll(f_diff, -1)])
-                        raise
+            # Expect no change from repair
+            df_good = df_good.sort_index()
+            repaired_df = repaired_df.sort_index()
+            for c in ["Open", "Low", "High", "Close", "Adj Close", "Volume"]:
+                try:
+                    self.assertTrue((repaired_df[c].to_numpy() == df_good[c].to_numpy()).all())
+                except AssertionError:
+                    print(f"tkr={tkr} interval={interval} COLUMN={c}")
+                    df_dbg = df_good[[c]].join(repaired_df[[c]], lsuffix='.good', rsuffix='.repaired')
+                    f_diff = repaired_df[c].to_numpy() != df_good[c].to_numpy()
+                    print(df_dbg[f_diff | _np.roll(f_diff, 1) | _np.roll(f_diff, -1)])
+                    raise
 
     def test_repair_bad_div_adjusts(self):
         interval = '1d'
@@ -580,7 +588,6 @@ 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
@@ -588,7 +595,6 @@ class TestPriceRepair(unittest.TestCase):
 
         # Div 0.01x
         bad_tkrs += ['NVT.L']
-        bad_tkrs += ['TENT.L']
 
         # Missing div adjusts:
         bad_tkrs += ['1398.HK']
@@ -597,8 +603,6 @@ 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']
 
@@ -692,6 +696,44 @@ class TestPriceRepair(unittest.TestCase):
                 print(repaired_df[c][f_diff] - correct_df[c][f_diff])
                 raise
 
+    def test_repair_capital_gains_double_count(self):
+        bad_tkrs = ['DODFX', 'VWILX', 'JENYX']
+        for tkr in bad_tkrs:
+            dat = yf.Ticker(tkr, session=self.session)
+            hist = dat._lazy_load_price_history()
+
+            interval = '1d'
+            fp = os.path.join(self.dp, "data", tkr.replace('.','-')+'-'+interval+"-cg-double-count.csv")
+
+            df_bad = _pd.read_csv(fp, index_col="Date")
+            df_bad.index = _pd.to_datetime(df_bad.index, utc=True)
+
+            repaired_df = hist._repair_capital_gains(df_bad)
+
+            fp = os.path.join(self.dp, "data", tkr.replace('.','-')+'-'+interval+"-cg-double-count-fixed.csv")
+            correct_df = _pd.read_csv(fp, index_col="Date")
+            correct_df.index = _pd.to_datetime(correct_df.index, utc=True)
+
+            repaired_df = repaired_df.sort_index()
+            correct_df = correct_df.sort_index()
+            for c in ["Open", "Low", "High", "Close", "Adj Close", "Volume"]:
+                try:
+                    self.assertTrue(_np.isclose(repaired_df[c], correct_df[c], rtol=5e-6).all())
+                except AssertionError:
+                    f = (correct_df['Capital Gains']!=0).to_numpy()
+                    f2 = f|_np.roll(f,1)|_np.roll(f,2)|_np.roll(f,-1)|_np.roll(f,-2)
+                    print(f"tkr={tkr} COLUMN={c}")
+                    print("- repaired_df")
+                    print(repaired_df[f2].drop(['Open', 'High', 'Low', 'Volume', 'Capital Gains'], axis=1))
+                    print("- repaired_df[c]")
+                    print(repaired_df[f2][c])
+                    print("- correct_df[c]:")
+                    print(correct_df[f2][c])
+                    print("- diff:")
+                    print(repaired_df[f2][c] - correct_df[f2][c])
+                    raise
+
+
 
 if __name__ == '__main__':
     unittest.main()

tests/test_prices.py

@@ -2,6 +2,7 @@ from tests.context import yfinance as yf
 from tests.context import session_gbl
 
 import unittest
+import socket
 
 import datetime as _dt
 import pytz as _tz
@@ -46,7 +47,7 @@ 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):
@@ -56,18 +57,19 @@ 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_utc = _pd.Timestamp.now('UTC')
             dt = dt_utc.astimezone(_tz.timezone(tz))
             start_d = dt.date() - _dt.timedelta(days=7)
             df = dat.history(start=start_d, interval="1h")
@@ -85,9 +87,9 @@ 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_utc = _pd.Timestamp.now('UTC')
             dt = dt_utc.astimezone(_tz.timezone(tz))
             if dt.time() < _dt.time(17, 0):
                 continue
@@ -111,7 +113,7 @@ 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 +187,7 @@ 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 +214,7 @@ 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 +225,7 @@ 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 +403,7 @@ 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 +418,8 @@ 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 +427,12 @@ 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)
@@ -453,6 +457,21 @@ class TestPriceHistory(unittest.TestCase):
 
         dat.history(start=start, end=end, interval=interval)
 
+    def test_transient_error_detection(self):
+        """Test that _is_transient_error correctly identifies transient vs permanent errors"""
+        from yfinance.data import _is_transient_error
+        from yfinance.exceptions import YFPricesMissingError
+
+        # Transient errors (should retry)
+        self.assertTrue(_is_transient_error(socket.error("Network error")))
+        self.assertTrue(_is_transient_error(TimeoutError("Timeout")))
+        self.assertTrue(_is_transient_error(OSError("OS error")))
+
+        # Permanent errors (should NOT retry)
+        self.assertFalse(_is_transient_error(ValueError("Invalid")))
+        self.assertFalse(_is_transient_error(YFPricesMissingError('INVALID', '')))
+        self.assertFalse(_is_transient_error(KeyError("key")))
+
 
 if __name__ == '__main__':
     unittest.main()

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)