In Python networking, exposing a REST API can be achieved using various frameworks. One of the most popular frameworks for this purpose is Flask. Below is an example of how to create a simple REST API using Flask that exposes a couple of endpoints.
from flask import Flask, jsonify, request
app = Flask(__name__)
# Sample data
items = [
{'id': 1, 'name': 'Item One'},
{'id': 2, 'name': 'Item Two'},
]
@app.route('/api/items', methods=['GET'])
def get_items():
return jsonify(items)
@app.route('/api/items/', methods=['GET'])
def get_item(item_id):
item = next((item for item in items if item['id'] == item_id), None)
if item:
return jsonify(item)
return jsonify({'message': 'Item not found'}), 404
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?