# 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>
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**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")
```
### 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")
...
```
---
## 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
- [peewee](https://pypi.org/project/peewee) \>= 3.16.2
#### 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**
Raw data
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"description": "# Download market data from Yahoo! Finance's API\n\n<table border=1 cellpadding=10><tr><td>\n\n#### \\*\\*\\* IMPORTANT LEGAL DISCLAIMER \\*\\*\\*\n\n---\n\n**Yahoo!, Y!Finance, and Yahoo! finance are registered trademarks of\nYahoo, Inc.**\n\nyfinance is **not** affiliated, endorsed, or vetted by Yahoo, Inc. It's\nan open-source tool that uses Yahoo's publicly available APIs, and is\nintended for research and educational purposes.\n\n**You should refer to Yahoo!'s terms of use**\n([here](https://policies.yahoo.com/us/en/yahoo/terms/product-atos/apiforydn/index.htm),\n[here](https://legal.yahoo.com/us/en/yahoo/terms/otos/index.html), and\n[here](https://policies.yahoo.com/us/en/yahoo/terms/index.htm)) **for\ndetails on your rights to use the actual data downloaded. Remember - the\nYahoo! finance API is intended for personal use only.**\n\n</td></tr></table>\n\n---\n\n<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>\n<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>\n<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>\n<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>\n<a target=\"new\" href=\"https://travis-ci.com/github/ranaroussi/yfinance\"><img border=0 src=\"https://img.shields.io/travis/ranaroussi/yfinance/main.svg?maxAge=1\" alt=\"Travis-CI build status\"></a>\n<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>\n<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>\n<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>\n\n\n**yfinance** offers a threaded and Pythonic way to download market data from [Yahoo!\u24c7 finance](https://finance.yahoo.com).\n\n\u2192 Check out this [Blog post](https://aroussi.com/#post/python-yahoo-finance) for a detailed tutorial with code examples.\n\n[Changelog \u00bb](https://github.com/ranaroussi/yfinance/blob/main/CHANGELOG.rst)\n\n---\n\n## Quick Start\n\n### The Ticker module\n\nThe `Ticker` module, which allows you to access ticker data in a more Pythonic way:\n\n```python\nimport yfinance as yf\n\nmsft = yf.Ticker(\"MSFT\")\n\n# get all stock info\nmsft.info\n\n# get historical market data\nhist = msft.history(period=\"1mo\")\n\n# show meta information about the history (requires history() to be called first)\nmsft.history_metadata\n\n# show actions (dividends, splits, capital gains)\nmsft.actions\nmsft.dividends\nmsft.splits\nmsft.capital_gains # only for mutual funds & etfs\n\n# show share count\nmsft.get_shares_full(start=\"2022-01-01\", end=None)\n\n# show financials:\n# - income statement\nmsft.income_stmt\nmsft.quarterly_income_stmt\n# - balance sheet\nmsft.balance_sheet\nmsft.quarterly_balance_sheet\n# - cash flow statement\nmsft.cashflow\nmsft.quarterly_cashflow\n# see `Ticker.get_income_stmt()` for more options\n\n# show holders\nmsft.major_holders\nmsft.institutional_holders\nmsft.mutualfund_holders\n\n# Show future and historic earnings dates, returns at most next 4 quarters and last 8 quarters by default. \n# Note: If more are needed use msft.get_earnings_dates(limit=XX) with increased limit argument.\nmsft.earnings_dates\n\n# show ISIN code - *experimental*\n# ISIN = International Securities Identification Number\nmsft.isin\n\n# show options expirations\nmsft.options\n\n# show news\nmsft.news\n\n# get option chain for specific expiration\nopt = msft.option_chain('YYYY-MM-DD')\n# data available via: opt.calls, opt.puts\n```\n\nIf you want to use a proxy server for downloading data, use:\n\n```python\nimport yfinance as yf\n\nmsft = yf.Ticker(\"MSFT\")\n\nmsft.history(..., proxy=\"PROXY_SERVER\")\nmsft.get_actions(proxy=\"PROXY_SERVER\")\nmsft.get_dividends(proxy=\"PROXY_SERVER\")\nmsft.get_splits(proxy=\"PROXY_SERVER\")\nmsft.get_capital_gains(proxy=\"PROXY_SERVER\")\nmsft.get_balance_sheet(proxy=\"PROXY_SERVER\")\nmsft.get_cashflow(proxy=\"PROXY_SERVER\")\nmsft.option_chain(..., proxy=\"PROXY_SERVER\")\n...\n```\n\n### Multiple tickers\n\nTo initialize multiple `Ticker` objects, use\n\n```python\nimport yfinance as yf\n\ntickers = yf.Tickers('msft aapl goog')\n\n# access each ticker using (example)\ntickers.tickers['MSFT'].info\ntickers.tickers['AAPL'].history(period=\"1mo\")\ntickers.tickers['GOOG'].actions\n```\n\nTo download price history into one table:\n\n```python\nimport yfinance as yf\ndata = yf.download(\"SPY AAPL\", period=\"1mo\")\n```\n\n#### `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.\n\n### Logging\n\n`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.\n\n### Smarter scraping\n\nTo use a custom `requests` session (for example to cache calls to the\nAPI or customize the `User-agent` header), pass a `session=` argument to\nthe Ticker constructor.\n\n```python\nimport requests_cache\nsession = requests_cache.CachedSession('yfinance.cache')\nsession.headers['User-agent'] = 'my-program/1.0'\nticker = yf.Ticker('msft', session=session)\n# The scraped response will be stored in the cache\nticker.actions\n```\n\nCombine a `requests_cache` with rate-limiting to avoid triggering Yahoo's rate-limiter/blocker that can corrupt data.\n```python\nfrom requests import Session\nfrom requests_cache import CacheMixin, SQLiteCache\nfrom requests_ratelimiter import LimiterMixin, MemoryQueueBucket\nfrom pyrate_limiter import Duration, RequestRate, Limiter\nclass CachedLimiterSession(CacheMixin, LimiterMixin, Session):\n pass\n\nsession = CachedLimiterSession(\n limiter=Limiter(RequestRate(2, Duration.SECOND*5)), # max 2 requests per 5 seconds\n bucket_class=MemoryQueueBucket,\n backend=SQLiteCache(\"yfinance.cache\"),\n)\n```\n\n### Managing Multi-Level Columns\n\nThe following answer on Stack Overflow is for [How to deal with\nmulti-level column names downloaded with\nyfinance?](https://stackoverflow.com/questions/63107801)\n\n- `yfinance` returns a `pandas.DataFrame` with multi-level column\n names, with a level for the ticker and a level for the stock price\n data\n - The answer discusses:\n - How to correctly read the the multi-level columns after\n saving the dataframe to a csv with `pandas.DataFrame.to_csv`\n - How to download single or multiple tickers into a single\n dataframe with single level column names and a ticker column\n\n### `pandas_datareader` override\n\nIf your code uses `pandas_datareader` and you want to download data\nfaster, you can \"hijack\" `pandas_datareader.data.get_data_yahoo()`\nmethod to use **yfinance** while making sure the returned data is in the\nsame format as **pandas\\_datareader**'s `get_data_yahoo()`.\n\n```python\nfrom pandas_datareader import data as pdr\n\nimport yfinance as yf\nyf.pdr_override() # <== that's all it takes :-)\n\n# download dataframe\ndata = pdr.get_data_yahoo(\"SPY\", start=\"2017-01-01\", end=\"2017-04-30\")\n```\n\n### Persistent cache store\n\nTo reduce Yahoo, yfinance store some data locally: timezones to localize dates, and cookie. Cache location is:\n- Windows = C:/Users/\\<USER\\>/AppData/Local/py-yfinance\n- Linux = /home/\\<USER\\>/.cache/py-yfinance\n- MacOS = /Users/\\<USER\\>/Library/Caches/py-yfinance\n\nYou can direct cache to use a different location with `set_tz_cache_location()`:\n```python\nimport yfinance as yf\nyf.set_tz_cache_location(\"custom/cache/location\")\n...\n```\n\n---\n\n## Installation\n\nInstall `yfinance` using `pip`:\n\n``` {.sourceCode .bash}\n$ pip install yfinance --upgrade --no-cache-dir\n```\n\nTest new features by installing betas, provide feedback in [corresponding Discussion](https://github.com/ranaroussi/yfinance/discussions):\n``` {.sourceCode .bash}\n$ pip install yfinance --upgrade --no-cache-dir --pre\n```\n\nTo install `yfinance` using `conda`, see\n[this](https://anaconda.org/ranaroussi/yfinance).\n\n### Requirements\n\n- [Python](https://www.python.org) \\>= 2.7, 3.4+\n- [Pandas](https://github.com/pydata/pandas) \\>= 1.3.0\n- [Numpy](http://www.numpy.org) \\>= 1.16.5\n- [requests](http://docs.python-requests.org/en/master) \\>= 2.31\n- [lxml](https://pypi.org/project/lxml) \\>= 4.9.1\n- [appdirs](https://pypi.org/project/appdirs) \\>= 1.4.4\n- [pytz](https://pypi.org/project/pytz) \\>=2022.5\n- [frozendict](https://pypi.org/project/frozendict) \\>= 2.3.4\n- [beautifulsoup4](https://pypi.org/project/beautifulsoup4) \\>= 4.11.1\n- [html5lib](https://pypi.org/project/html5lib) \\>= 1.1\n- [peewee](https://pypi.org/project/peewee) \\>= 3.16.2\n\n#### Optional (if you want to use `pandas_datareader`)\n\n- [pandas\\_datareader](https://github.com/pydata/pandas-datareader)\n \\>= 0.4.0\n\n## Developers: want to contribute?\n\n`yfinance` relies on community to investigate bugs and contribute code. Developer guide: https://github.com/ranaroussi/yfinance/discussions/1084\n\n---\n\n### Legal Stuff\n\n**yfinance** is distributed under the **Apache Software License**. See\nthe [LICENSE.txt](./LICENSE.txt) file in the release for details.\n\n\nAGAIN - yfinance is **not** affiliated, endorsed, or vetted by Yahoo, Inc. It's\nan open-source tool that uses Yahoo's publicly available APIs, and is\nintended for research and educational purposes. You should refer to Yahoo!'s terms of use\n([here](https://policies.yahoo.com/us/en/yahoo/terms/product-atos/apiforydn/index.htm),\n[here](https://legal.yahoo.com/us/en/yahoo/terms/otos/index.html), and\n[here](https://policies.yahoo.com/us/en/yahoo/terms/index.htm)) for\ndetailes on your rights to use the actual data downloaded.\n\n---\n\n### P.S.\n\nPlease drop me an note with any feedback you have.\n\n**Ran Aroussi**\n",
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