yfapi

Welcome to YahooFinanceAPI

An unofficial library to capture data from Yahoo Finance API in an easier way. Having access to capture data from some stocks provided by the service. It is possible to configure your capture to select and filter different types of data regarding the stocks provided.

First Steps

initially, install the package through the following command in your terminal:

pip install yfapi

Note: For those more familiarized and who choose to keep the packages in a venv environment, you can use the command python -m venv yfapi.

Warnings

If you are running your code on Windows, it is extremely important that you consider indenting your code as in the following example:

from yfapi import YahooFinance

if __name__ == '__main__':
	# directly run your code that uses the
	# YahooFinance class here, or even functions that use it.

Then we would use it as follows:

from yfapi import YahooFinance

if __name__ == '__main__':
	stock_data = YahooFinance('STOCK_TICKER', '1d', '1d')

Methods

Initially, it is necessary to instantiate our variable that will receive the YahooFinance class, followed by the following attributes:

Attribute	Type
ticker	str or list
interval	str
range	str

• ticker: It is the code referring to the stock, Example: AMZN (Amazon), TSLA (Tesla) and AAPL (Apple).

• interval: It is the time interval of how you want the data referring to the "range" attribute. Examples: 1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo.

• range: It is the scale of capture, which can be days, months or years. Examples: 1d, 2d, 5d, 1mo, 2mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max.

for that, instantiate as in this example code:

from yfapi import YahooFinance

google_data = YahooFinance('GOOG', '1d', '1d')

remember, if you are running the code on Windows you should run such functions like this:

from yfapi import YahooFinance

if __name__ == '__main__':
	google_data = YahooFinance('GOOG', '1d', '1d')

Note: if you instantiate the YahooFinance class using a list of tickers for the "ticker" attribute, a loading bar will be shown referring to the amount of tickers present in the list.

info

Returns a Pandas DataFrame, with the following values referring to stock:

• ticker
• chartPreviousClose
• currency
• currentTradingPeriod
• dataGranularity
• exchangeName
• exchangeTimezoneName
• firstTradeDate
• gmtoffset
• instrumentType
• previousClose
• priceHint
• range
• regularMarketPrice
• regularMarketTime
• scale
• timezone

For that, just use the method like this example code:

from yfapi import YahooFinance


google_data = YahooFinance('GOOG', '1d', '1d')
google_info = google_data.info()

trading_period

Returns a Pandas DataFrame with the following data:

• timezone
• start
• end
• gmtoffset

it is necessary to insert the argument referring to which type of period you are looking for, being possible to capture "pre", "regular" and "post".

Arg	Type
type	str

For that, just use the method like this example code:

from yfapi import YahooFinance


google_data = YahooFinance('GOOG', '1d', '1d')
google_trading_period = google_data.trading_period("regular")

all_values

Returns a Pandas DataFrame with the following data:

• ticker
• time
• close
• open
• high
• low
• volume

For that, just use the method like this example code:

from yfapi import YahooFinance

google_data = YahooFinance('GOOG', '1d', '1d')
google_values = google_data.all_values()

close

Returns a Pandas DataFrame with the following data:

• ticker
• time
• close

For that, just use the method like this example code:

from yfapi import YahooFinance


google_data = YahooFinance('GOOG', '1d', '1d')
google_close = google_data.close()

open

Returns a Pandas DataFrame with the following data:

• ticker
• time
• open

For that, just use the method like this example code:

from yfapi import YahooFinance


google_data = YahooFinance('GOOG', '1d', '1d')
google_open = google_data.open()

high

Returns a Pandas DataFrame with the following data:

• ticker
• time
• high

For that, just use the method like this example code:

from yfapi import YahooFinance

google_data = YahooFinance('GOOG', '1d', '1d')
google_high = google_data.high()

low

Returns a Pandas DataFrame with the following data:

• ticker
• time
• low

For that, just use the method like this example code:

from yfapi import YahooFinance

google_data = YahooFinance('GOOG', '1d', '1d')
google_low = google_data.low()

volume

Returns a Pandas DataFrame with the following data:

• ticker
• time
• volume

For that, just use the method like this example code:

from yfapi import YahooFinance

google_data = YahooFinance('GOOG', '1d', '1d')
google_volume = google_data.volume()

to_csv

If you have already captured some data using the methods mentioned above, you can export it to a .csv spreadsheet.

Arg	Type
dir (optional)	str
sep (optional)	str

• dir: The path where you want your .csv file to be saved, by default is set to the current folder where the script is running and named "database.csv", which is also changeable. Your .csv will be saved in the given path, for example: "my_stock_databases/stock_name.csv". It is recommended to insert the suffix ".csv", however if it does not exist, it will be inserted at the end of the string received by this argument.

• sep: It is the separator/delimiter used in this worksheet .csv, by default it is set to ";", but you can change it to any other. For example a comma (",").

For that, just use the method like this example code:

from yfapi import YahooFinance

google_data = YahooFinance('GOOG', '1d', '1d')
google_data = google_data.all_values()
google_data.to_csv("google_database.csv", sep=",")

Note: If you haven't captured any data, an error will be returned stating this.

to_excel

If you have already captured some data using the methods mentioned above, you can export it to a .xlsx spreadsheet.

Arg	Type
dir (optional)	str

• dir: The path where you want your .xlsx file to be saved, by default is set to the current folder where the script is running and named "database.xlsx", which is also changeable. Your .xlsx will be saved in the given path, for example: "my_stock_databases/stock_name.xlsx". It is recommended to insert the suffix ".xlsx", however if it does not exist, it will be inserted at the end of the string received by this argument.

For that, just use the method like this example code:

from yfapi import YahooFinance

google_data = YahooFinance('GOOG', '1d', '1d')
google_data = google_data.all_values()
google_data.to_excel("google_database.xlsx")

Note: If you haven't captured any data, an error will be returned stating this.