Yfinance is a python package that enables us to fetch historical market data from Yahoo Finance API in a Pythonic way. It becomes so easy for all the Python developers to get data with the help of yfinance.
We can easily download historical stock data from yfinance, but the problem is, it is very time taking. Hence, we use multithreading for covering up the time. Multithreading enables us to download large amounts of data by executing multiple threads concurrently.
Installation
This module does not come built-in with Python. To install it type the below command in the terminal.
pip install yfinance
Let’s see the process step by step which are explained below with the implementation:
Step 1: Get all the required modules
import yfinance as yf
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Step 2: Getting stocks history data
# Get the stocks info import yfinance as yf
# Ticker is a function responsible # for fetching the data MSFT is # representing info about Microsoft # Corporation msft = yf.Ticker( 'MSFT' )
# msft.info will return all information # about microsoft corporation data = msft.history()
# printing the data print (data)
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Output:
This is a recent year’s stock data of Microsoft Corporation. Please note that if we use data = msft.history(period=’max’) it will return all data till now.
Step 3: Downloading the data
# pip install yfinance import yfinance as yf
# Here we use yf.download function data = yf.download(
# tickers has value of company
# shortname
tickers = 'MSFT' ,
) # printing the data print (data)
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Output:
Hence, 1 of 1 download is completed. It is all data from beginning to end till now of only one company.
Step 4: Download the data from several companies
This is a code for downloading the data from companies like IBM, Apple (AAPL), Amazon(AMZN), Microsoft(MSFT), etc.
# pip install yfinance import yfinance as yf
ticker_list = [ 'IBM' , 'MSFT' , 'AAPL' , 'AMZN' ]
# Here we use yf.download function data = yf.download(
# passes the ticker
tickers = ticker_list,
# used for access data[ticker]
group_by = 'ticker' ,
) # used for making transpose data = data.T
for t in ticker_list:
# printing name
print (t)
print ( '\n' )
# used data.loc as it takes only index
# labels and returns dataframe
print (data.loc[t])
print ( '\n' )
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Output:
Step 5: Calculating the time of execution and using multithreading
As yfinance uses its own built-in threading technique for mass downloading. To do this, We need to assign a new parameter in a yf.download.
data = yf.download(
tickers=ticker_list,
threads=True, # Set thread value to true
group_by=’ticker’,
)
Program for calculating time, we use the time module
# pip install yfinance import yfinance as yf
import time
# Time starts from here start = time.time()
ticker_list = [ 'IBM' , 'MSFT' , 'AAPL' , 'AMZN' ]
# Here we use yf.download function data = yf.download(
tickers = ticker_list,
threads = True ,
group_by = 'ticker' ,
) # used for making transpose data = data.T
for t in ticker_list:
print (t)
# used data.loc as it takes only index
# labels and returns dataframe
print (data.loc[t])
# Total time calculated print ( 'The program takes ' , time.time() - start, 'seconds.' )
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Before thread:
After thread: