Working with GitHub API in Python

August 24, 2021

When fetching information from the web, we usually request for complete web pages, and extract information by parsing the HTML scripts. Similarly, an Application Programming Interface (API) performs the same operation in a more efficient way.

This tutorial will teach you how to create a self-contained application that generates a summary based on the information it obtains through the API.

GitHub is a website where programmers can contribute to various open-source projects.

In this article, we will request information related to Python projects on GitHub using the Github API. We will also summarize information that we’ve obtained using the API.


As a prerequisite, you must have a little understanding of Python to follow the tutorial along.


In this article we will go through:

  • Using an API call to request data.
  • Installation of requests library.
  • Keeping track of an API response.
  • Using the response dictionary.
  • Summing up the top repositories.

Requesting data using an API call

GitHub’s web API allows you to make API requests for a range of data.

Type the following into your web browser URL bar and press Enter to see how an API call appears like:

Let’s examine the parts of the API call:

  • - sends the request to the GitHub web server that handles API calls.
  • search/repositories - is the endpoint that informs the API to search across all of GitHub repositories.
  • ? - indicates that an argument is about to be passed.
  • q=- the character q stands for query.
  • language:python - that queries repositories that use only Python as their main language.
  • &sort=stars - the projects are sorted by the number of stars they have gotten.

Upon fetching the API data, the response will look like:

  "total_count": 7668509,
  "incomplete_results": false,
  "items": [
      "id": 54346799,
      "node_id": "MDEwOlJlcG9zaXRvcnk1NDM0Njc5OQ==",
      "name": "public-apis",
      "full_name": "public-apis/public-apis",

NOTE: The output above shows only the first few lines of the response.

Let’s examine the output:

  • In the second line of the result, you can see that GitHub has detected a total of 7668509 Python projects.
  • We know the request was successful if the value for incomplete results is false.
  • The key items holds a list of objects that contains information of the Python-based projects on GitHub.

Let’s try to explore more information by parsing the API’s output using Python.

Installing requests

The requests package enables us to request data from the website and evaluate the result easily using a Python program.

Run the following command to install requests:

pip install --user requests

Visit this link, if this is your first time using pip for installing packages.

Processing an API response

To fetch the most starred Python projects on GitHub, we’ll start writing a program that will make an API call and evaluate the data as shown:

import requests

# Create an API request 
url = ''
response = requests.get(url)
print("Status code: ", response.status_code)
# In a variable, save the API response.
response_dict = response.json()
# Evaluate the results.

Let’s understand the code snippet above:

  • We begin by importing the requests module.
  • Then, we use the requests package to make the API call to the particular url using get().
  • The API response is saved by a variable called response.
  • The status_code attribute of the response object indicates if the request was complete.
  • A successful API call returns the status_code 200, while an unsuccessful one returns 500.
  • Then, we use the json() function to convert the information from JSON format to a Python dictionary.
  • We store the converted JSON in response_dict.

Then, we print the keys from response_dict, which are as follows:

Status code: 200
dict_keys(['items', 'total_count', 'incomplete_results'])

Using the response dictionary

Now, let’s make a report that sums up all the information.

Here, we will be calculating the total number of available repositories with language as Python, and fetch all the keys under items as shown:

print("Total repos:", response_dict['total_count'])
# find total number of repositories
repos_dicts = response_dict['items']
print("Repos found:", len(repos_dicts))
# examine the first repository
repo_dict = repos_dicts[0]
print("Keys:", len(repo_dict))
for key in sorted(repo_dict.keys()):

Let’s understand the code snippet above:

  • The value linked with the total_count reflects the count of GitHub Python projects available.
  • The value of items is a list of dictionaries, each providing information about a single Python repository.
  • The list of dictionaries is then saved in repos_dicts.
  • We select the first item from repos_dicts to look more closely at the information given about each repository.
  • Finally, we print the all of keys of an item.


Status code: 200
Total repos: 7694326
Repos found: 30
Keys: 74


The GitHub API gets back a range of data for every repository like:

  • status_code as 200.
  • Total number of repos as 7694326.
  • Total number of repos found as 30.
  • Each repository repo_dict having 74 keys.

You may get a sense of the type of information you can get about a repository by observing these keys.

Let’s have a look at what some of the keys in repos dict entail:

# Find out more about the repositories.
repos_dicts = response_dict['items']
print("Repositories found:", len(repos_dicts))
# Examine the first repository.
repo_dict = repos_dicts[0]
print("\nThe following is some information regarding the first repository:")
print('Name:', repo_dict['name'])  #print the project's name
print('Owner:', repo_dict['owner']['login'])  #use the key owner and the the key login to get the dictionary describing the owner and the owner’s login name respectively.
print('Stars:', repo_dict['stargazers_count'])  #print how many stars the project has earned
print('Repository:', repo_dict['html_url'])  #print URL for the project’s GitHub repoitory
print('Created:', repo_dict['created_at'])  #print when it was created
print('Updated:', repo_dict['updated_at'])  #show when it was last updated
print('Description:', repo_dict['description']) #print the repository’s description


Status-code: 200
Total repos: 7588335
Repositories found: 30

The following is some information regarding the first repository:
Name: public-apis
Owner: public-apis
Stars: 144904
Created: 2016-03-20T23:49:42Z
Updated: 2021-07-31T13:15:51Z
Description: A collective list of free APIs

Examining the output:

  • You can observe that the most popular Python repository on GitHub is public-apis.
  • Owner of the repository is public-apis.
  • It has been starred more than 140,000 times.
  • Project was created on the date of 2016 March.
  • Project description of public-apis is collective collection of open APIs.

Summing up the top repositories

We’ll try to analyze more than one repository.

Let’s create a loop that prints specified information about each of the repositories supplied by the API call:

# Find out more about the repositories.
repos_dicts = respons_dict['items']
print("Repositories found:", len(repos_dicts))
print("\nListed details on each repository:")
for repos_dict in repos_dicts:   #loop through all the dictionaries in repos_dicts.
    print('\nName:', repos_dict['name'])
    print('Owner:', repos_dict['owner']['login'])
    print('Stars:', repos_dict['stargazers_count'])
    print('Repository:', repos_dict['html_url'])
    print('Description:', repos_dict['description'])

We print the name of each project, its owner, the number of stars it has, its GitHub URL, and the project’s description inside the loop:

Name: public-apis
Owner: public-apis
Stars: 144910
Description: A collective list of free APIs

Name: system-design-primer
Owner: donnemartin
Stars: 139818
Description: Learn how to design large-scale systems.

Name: Python
Owner: TheAlgorithms
Stars: 113616
Description: All Algorithms implemented in Python


In this tutorial, we have gone over the following:

  • Using an API call to request data.
  • Installing requests.
  • Processing an API response.
  • Using the response dictionary.
  • Summing up the top repositories.

You can check out the full code here.

Happy coding.

Further reading

Peer Review Contributions by: Srishilesh P S