How Can I Optimize My Python Flask API for Better Performance?

[Soham1087]

I'm presently working on a backend development project to build a RESTful API using Python and Flask. Although I've had assistance with this site, I've seen a drop in performance as the amount of API queries rises. Especially during times of high usage, the response times are slower than I would want them to be.

Here's a simplified version of my Flask API code:

from flask import Flask, jsonify

app = Flask(__name__)

# Sample data
data = [
    {"id": 1, "name": "Product A", "price": 10.99},
    {"id": 2, "name": "Product B", "price": 15.99},
    # More data entries...
]

@app.route('/api/products', methods=['GET'])
def get_all_products():
    return jsonify(data)

if __name__ == '__main__':
    app.run(debug=True)

I believe there are optimizations I can make to improve the performance of my Flask API, but I'm not sure where to start. Could someone please review my code and suggest best practices or modifications that can help me achieve better response times, especially as the number of API requests increases? Thank you!

 

[Kurenai_ryu]

how are you deploying your application? or do you intend to keep serving the built-in development server of flask?

is your API completely stateless? that's very important for replication, either by WSGI for flask or any other replation method.
maybe you can disable the debug mode, and start a threaded run, but as those answers suggest, it's better to deploy your application with other tools.


If you don't want that maybe consider another option like Tornado or even better FastAPI