Multithreaded download of yahoo stock history with Python – yfinance

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

Python3

import yfinance as yf

Step 2: Getting stocks history data

Python

# 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)

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

Python3

# 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)

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.

Python3

# 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')

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

Python

# 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.')