Python Webhook Integration: 3 Easy Steps

on Automation, Data Driven, Data Integration, Flask, JSON, Python, REST API, SaaS, Tutorials, Web APIs, Webhook • October 26th, 2021 • Write for Hevo

With more and more organizations moving to SaaS (Software-as-a-Service) based products for running their businesses, integration between various services is a common requirement. In a completely on-premise world, these integrations would have happened through shared databases or even API (Application Programming Interface) calls. In the case of SaaS products, getting the data from one service to another in a real-time manner requires additional mechanisms.

For example, you may want to raise a shipping request in your internal application every time an order is created in your cloud CRM (Customer Relationship Management) or you may want to add a message to the group message application every time a comment is left on your issue tracker. To handle such real-time requirements, Webhooks are a great solution.

This article will guide you through the process of setting up Python Webhook Integration using 3 simple steps. It will provide you with a brief overview of Python and Webhook with their key features. You will also explore the key benefits of setting up Python Webhook Integration in further sections. Let’s get started.

Table of Contents

Prerequisites

Setting up Python Webhook Integration will be a lot easier if you’ve gone through the following prerequisites:

  • Working knowledge of Python Programming Language.
  • Working knowledge of Webhooks.
  • Familiarity with Python Environment.

Introduction to Python

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Python is a programming language that is commonly used to create Websites, Web Applications, Automated Operations, and perform Data Analysis. Python is a general-purpose programming language, which means it can be used to develop a wide range of applications and isn’t tailored to any specific problem. Its versatility, combined with its ease of use for beginners, has made it one of the most widely used programming languages today.

Python provides an extensive set of libraries that can be used for Data Analytics, Visualization, Numerical Computation, and Machine Learning. Some of the popular Python libraries that are widely used include Numpy, Pandas, Scipy, Matplotlib, and many more. Additionally, it has a vast and growing global community, with Google, Facebook, Netflix, and IBM relying on it.

Key Features of Python

Python provides a variety of features that make it a popular choice in today’s IT (Information Technology) market. Some of the key features of Python include:

  • Ease of learning: Python is a beginner-friendly language, so most people with a basic understanding of programming can easily adapt to the syntax and begin their coding. Python’s English Script, simple Phrase Structure, and Code Readability make it simple for programmers and non-programmers to learn and understand.
  • Scalability: Python, unlike other programming languages like Java and R, can easily handle large volumes of data with ease. Moreover, it can help you with difficulties that other programming languages can’t solve.
  • Wider Community Support: Python is a free and open-source programming language with a plethora of tools and comprehensive documentation. Moreover, it has one of the largest programming and Data Science communities.
  • Robust and Portable: Python is a robust and portable programming language. This means that Python code created on one computer can be effortlessly transferred to another computer and run without difficulties.

To know more about Python, visit this link.

Introduction to Webhooks

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In a nutshell, Webhooks are simple URLs (Uniform Resource Locator) that accept a POST request with a well-defined data structure. To understand this better, let’s consider a scenario where a message has to be sent to an internal group messaging application when an order request is raised in the internal Order Tracking application. To accomplish this using the Webhook, the Order Tracking application should have an option to call a specific URL when an action happens. This URL must be a Web Service that is hosted by the messaging service to receive information that has to be posted in the group. This URL is generally called the Webhook. 

In the real scenario, the messaging application must be capable of generating such URLs that can be accessed by client applications who want to send messages to the group. Since the Web Service URL is public, it should have an authentication mechanism to prevent any attacks. A username and password-based authentication or a signed request-based one is typically used as authentication methods for Webhooks. 

To know more about Webhooks, visit this link.

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Steps to Set Up Python Webhook Integration

Now that you have a basic grasp of both technologies let’s try to understand the procedure to set up Python Webhook Integration. Integrating Python and Webhook is as simple as creating a Web Service using a Web Framework like Django or Flask.  Below are the steps you can follow to set up Python Webhook Integration:

Step 1: Install Flask to your Python Environment

The first step in setting up Python Webhook Integration is to install Flask to your Python environment. You can install it using the below command.

python -m pip install Flask

Step 2: Create a Web Service

Once you have installed Flask to your Python environment, you need to create a Web Service using Flask. The Web Service can be easily created with the app.route decorator. Open a file named webhook.py and enter the below code.

from flask import Flask, request, Response
app = Flask(__name__)
@app.route('/my_webhook', methods=['POST'])
def return_response():
    print(request.json);
    ## Do something with the request.json data.
    return Response(status=200)
if __name__ == "__main__": app.run()

The above snippet of code initializes a Flask app using the Flask class. It then prints out the request.json which contains the data that is submitted by the client. Usually, this data will be extracted using known keys and will be used to perform some functionality. In our messenger example, the relevant information for publishing a message to the group channel will be parsed from the request.json, and a function to publish the message will be called.

The important bit to understand here is the app.route decorator which abstracts away most of the details about listening to a POST request. The app.route decorator has a path attribute that decides the URL that will be called by the client. In this case, the URL path will be https://domain:port/my_webhook. 

Since Webhooks are meant to receive data from predefined events, the URLs are typically designed to include path names that signify the evident name as well. 

Step 3: Run the Flask Server

After you have successfully created the Web Service, you can now run the Flask server using the below command.

export FLASK_APP=webhook.py
python -m flask run

That’s all there is to know about setting up a Python Webhook Integration. The client applications that support Webhooks for sending data usually have a mechanism to register the URLs. 

For example, applications like Gitlab, Slack, etc. provide a UI (User Interface) for registering the Webhook URLs. The client applications will also have methods to add authentication to the Webhooks. They may send a token or a secret that you can specify while sending data to Webhooks. In such cases, the logic to verify the authentication information also has to be implemented inside the return_response function. 

The other end of the problem, which is to develop code to call this Webhook when specific events take place is much more complex. Fortunately, there are open source Frameworks available in Python that can help with this. Thorn is a well-known Python Framework that can be used with Django Rest Framework to easily implement Webhooks. 

Key Benefits of Setting Up Python Webhook Integration

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Python Webhook Integration provides numerous benefits. Some of the key benefits of setting up Python Webhook Integration include:

  • Python Webhook Integration provides real-time updates with excellent performance. Webhooks are a great option if you need to update server data often and limit the number of unnecessary API requests from the client to the server.
  • Python Webhook Integration provides high availability and can be easily accessed from any mobile or desktop device. Thus, you’ll be able to receive timely notifications on your phone and laptop using your Python Webhook Integration.
  • Python Webhook Integration is a great option for automated messaging that can be tailored to your specific requirements. You may also easily customize your Webhooks’ name and avatar.

These were some of the key benefits of setting up Python Webhook Integration.

Conclusion

Webhooks are an elegant way of integrating applications that exist independently. The only alternative to using webhook is to have the application that needs the data repeatedly poll an API hosted at the source application. This is complicated and prone to failure. Hence Webhooks are the preferred way of real-time data transfer between two independently hosted applications.

In this article, you learned how to set up Python Webhook Integration. It also gave an overview of Python and Webhook with their key features. You also learned about the key benefits of setting up this integration. You can now create your Python Webhook Integration to obtain all of your required data in one place and get the most out of it.

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Share your experience of setting up Python Webhook Integration in the comments section below!

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