Welcome to another lesson in our course on building APIs with Python and Flask. Previously, you learned how to set up a simple Flask application and run it using the built-in Flask server. Now, let's take our Flask application to the next level by introducing Gunicorn, a more robust way to serve our application.
Before we start using Gunicorn, let's quickly recap how to set up a simple Flask application. Here’s a basic app that we covered in the previous lesson:
Python1from flask import Flask 2 3# Initialize a Flask app instance 4app = Flask(__name__) 5 6# Note: We won't need the app.run() block when using Gunicorn
In this code:
- We import the
Flask
class from theflask
module. - We create an instance of the
Flask
class and call itapp
.
When using Gunicorn, there's no need for the if __name__ == "__main__": app.run()
block, which was necessary when using the built-in Flask server.
Gunicorn (Green Unicorn) is a Python WSGI HTTP server that serves your Flask application. WSGI (Web Server Gateway Interface) is a specification that allows different web servers to communicate with web applications written in Python. Essentially, Gunicorn acts as a middleman that helps your Flask application communicate with the web client (such as a browser or a mobile app).
Imagine you have built a web application that needs to handle hundreds of requests per second. The built-in Flask server might struggle with this load, but Gunicorn, with its ability to manage multiple workers, can handle the traffic smoothly. This makes your application reliable and efficient.
Flask’s built-in server is suitable for development and testing but is not designed to handle production-level traffic. Here’s a comparison to help clarify:
-
Flask’s Built-in Server:
- Simple to use and set up.
- Suitable for development and smaller applications.
- Struggles with high traffic and multiple simultaneous requests.
-
Gunicorn:
- Configurable for different performance needs.
- Can manage multiple worker processes to handle high traffic.
- Suitable for production environments where stability and performance are critical.
By deploying your Flask application with Gunicorn, you ensure that it can handle more users and provide a better experience, especially in a real-world, high-traffic scenario.
First, we need to install Gunicorn. If you are working on your local machine, you can install it using pip
with the following command:
Bash1pip install gunicorn
Note: In the CodeSignal environment, Gunicorn is pre-installed, so you don’t need to worry about this step.
Once your Python script with the Flask app instance is ready, open your terminal and navigate to the directory containing the file. Then, run the following command:
Bash1gunicorn filename:app
Breaking down the command:
gunicorn
: This is the command to start Gunicorn.solution:app
: This specifies the module name (solution
) and the application instance (app
) to run.
This command will start the server, and you should see output indicating that Gunicorn is running and listening for requests on 127.0.0.1:8000
by default.
You can also specify the IP address and port number to be used by Gunicorn. For example, to listen on all available IP addresses (0.0.0.0
) and port 8080
, you can add the -b
(bind) option to the command:
Bash1gunicorn -b 0.0.0.0:8080 filename:app
-b 0.0.0.0:8080
: This specifies that Gunicorn should bind to 0.0.0.0
(all available IP addresses) and listen on port 8080
.
Gunicorn offers a range of options to customize the server's behavior, including:
- Worker Processes: Adjust the number of worker processes to handle concurrent requests.
- Timeouts: Set custom timeouts for requests to avoid hanging processes.
- Logging: Configure detailed logging to monitor and debug application behavior.
- Daemon Mode: Run Gunicorn as a background service using daemon mode.
In this lesson, we explored how to enhance our Flask application by deploying it using Gunicorn. You learned:
- What Gunicorn is and why it is beneficial.
- How to set up and run a Flask application with Gunicorn.
- The advantages of using Gunicorn over the built-in Flask server.
Now, you are ready to try this on your own! The practice exercises following this lesson will give you a chance to apply what you've learned and solidify your understanding.