Python GitHub API

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.

Prerequisites

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

Objectives

In this article we will go through:

• Using an API call to request data.

• Installation of requests library.

• Keeping track of an API response.

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:

• https://api.github.com/ - 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.

• ?

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

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.

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:

Visit 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:

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().

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

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:

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

Output:

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

• status_code as 200.

• Total number of repos as 7694326.

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:

Output:

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

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:

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:

Conclusion

In this tutorial, we have gone over the following:

• Using an API call to request data.

• Installing requests.

• Processing an API response.

You can check out the full code .