In Python DevOps, exposing a REST API can be accomplished using several frameworks. One of the most popular frameworks for creating REST APIs is Flask. Flask is a lightweight WSGI web application framework that is easy to set up and use to build web services and APIs.
Below is an example of how to create a basic REST API using the Flask framework.
from flask import Flask, jsonify, request
app = Flask(__name__)
@app.route('/api/v1/items', methods=['GET'])
def get_items():
items = [{'id': 1, 'name': 'Item 1'}, {'id': 2, 'name': 'Item 2'}]
return jsonify(items)
@app.route('/api/v1/items', methods=['POST'])
def create_item():
new_item = request.json
# Logic to add the item to the database can be added here
return jsonify(new_item), 201
if __name__ == '__main__':
app.run(debug=True)
How do I avoid rehashing overhead with std::set in multithreaded code?
How do I find elements with custom comparators with std::set for embedded targets?
How do I erase elements while iterating with std::set for embedded targets?
How do I provide stable iteration order with std::unordered_map for large datasets?
How do I reserve capacity ahead of time with std::unordered_map for large datasets?
How do I erase elements while iterating with std::unordered_map in multithreaded code?
How do I provide stable iteration order with std::map for embedded targets?
How do I provide stable iteration order with std::map in multithreaded code?
How do I avoid rehashing overhead with std::map in performance-sensitive code?
How do I merge two containers efficiently with std::map for embedded targets?