# Download market data from Yahoo! Finance's API
#### \*\*\* 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.**
--- Python version PyPi version PyPi status PyPi downloads Travis-CI build status CodeFactor Star this repo Follow me on twitter **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) --- ## 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: # - 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 # 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 ``` 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. ### 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 To use a custom `requests` session (for example to cache calls to the API or customize the `User-agent` header), pass a `session=` argument to the Ticker constructor. ```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 a `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 ### `pandas_datareader` override If your code uses `pandas_datareader` and you want to download data faster, you can "hijack" `pandas_datareader.data.get_data_yahoo()` method to use **yfinance** while making sure the returned data is in the same format as **pandas\_datareader**'s `get_data_yahoo()`. ```python from pandas_datareader import data as pdr import yfinance as yf yf.pdr_override() # <== that's all it takes :-) # download dataframe data = pdr.get_data_yahoo("SPY", start="2017-01-01", end="2017-04-30") ``` ### Timezone cache store When fetching price data, all dates are localized to stock exchange timezone. But timezone retrieval is relatively slow, so yfinance attemps to cache them in your users cache folder. 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") ... ``` --- ## Installation Install `yfinance` using `pip`: ``` {.sourceCode .bash} $ pip install yfinance --upgrade --no-cache-dir ``` Test new features by installing betas, provide feedback in [corresponding Discussion](https://github.com/ranaroussi/yfinance/discussions): ``` {.sourceCode .bash} $ pip install yfinance --upgrade --no-cache-dir --pre ``` To install `yfinance` using `conda`, see [this](https://anaconda.org/ranaroussi/yfinance). ### Requirements - [Python](https://www.python.org) \>= 2.7, 3.4+ - [Pandas](https://github.com/pydata/pandas) \>= 1.3.0 - [Numpy](http://www.numpy.org) \>= 1.16.5 - [requests](http://docs.python-requests.org/en/master) \>= 2.31 - [lxml](https://pypi.org/project/lxml) \>= 4.9.1 - [appdirs](https://pypi.org/project/appdirs) \>= 1.4.4 - [pytz](https://pypi.org/project/pytz) \>=2022.5 - [frozendict](https://pypi.org/project/frozendict) \>= 2.3.4 - [beautifulsoup4](https://pypi.org/project/beautifulsoup4) \>= 4.11.1 - [html5lib](https://pypi.org/project/html5lib) \>= 1.1 #### Optional (if you want to use `pandas_datareader`) - [pandas\_datareader](https://github.com/pydata/pandas-datareader) \>= 0.4.0 ## Developers: want to contribute? `yfinance` relies on community to investigate bugs and contribute code. Developer guide: https://github.com/ranaroussi/yfinance/discussions/1084 --- ### Legal Stuff **yfinance** is distributed under the **Apache Software License**. See the [LICENSE.txt](./LICENSE.txt) file in the release for details. AGAIN - yfinance is **not** affiliated, endorsed, or vetted by Yahoo, Inc. It's an open-source tool that uses Yahoo's publicly available APIs, and is intended for research and educational purposes. You should refer to Yahoo!'s terms of use ([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 detailes on your rights to use the actual data downloaded. --- ### P.S. Please drop me an note with any feedback you have. **Ran Aroussi**