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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, here, and here) for details on your rights to use the actual data downloaded. Remember - the Yahoo! finance API is intended for personal use only. |
yfinance offers a threaded and Pythonic way to download market data from Yahoo!Ⓡ finance.
→ Check out this Blog post for a detailed tutorial with code examples.
Install yfinance using pip:
$ pip install yfinance --upgrade --no-cache-dir
To install yfinance using conda, see
this.
Test new features by installing betas, provide feedback in corresponding Discussion:
$ pip install yfinance --upgrade --no-cache-dir --pre
To install with extra dependencies, replace extra with nospam for custom requests or repair for price repairing functionality:
$ pip install yfinance[extra]
To view the full list of required dependencies and extra packages, see this.
The Ticker module, which allows you to access ticker data in a more Pythonic way:
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.putsIf you want to use a proxy server for downloading data, use:
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")
...To initialize multiple Ticker objects, use
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'].actionsTo download price history into one table:
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 for more options and detail.
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.
Install the nospam packages for smarter scraping using pip (see 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.
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.actionsCombine requests_cache with rate-limiting to avoid triggering Yahoo's rate-limiter/blocker that can corrupt data.
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"),
)The following answer on Stack Overflow is for How to deal with multi-level column names downloaded with yfinance?
yfinancereturns apandas.DataFramewith 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
- How to correctly read the the multi-level columns after
saving the dataframe to a csv with
- The answer discusses:
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().
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")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():
import yfinance as yf
yf.set_tz_cache_location("custom/cache/location")
...yfinance relies on community to investigate bugs and contribute code. Developer guide: ranaroussi#1084
yfinance is distributed under the Apache Software License. See the 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, here, and here) for detailes on your rights to use the actual data downloaded.
Please drop me an note with any feedback you have.
Ran Aroussi