Build a small Flask API by mapping URLs and HTTP methods to Python functions, returning JSON with meaningful status codes, and testing the routes with Flask’s test client. The example below implements GET /items, GET /items/<id>, and POST /items using an in-memory collection; it is suitable for learning and local development, not persistent production storage.
What you will build
A REST API exposes resources through HTTP endpoints. In this example, an item is a resource represented as JSON. A client can list items, retrieve one by ID, or submit JSON to create one. The route’s URL and accepted HTTP method together determine which view function handles a request.
Flask routes accept GET by default, so API routes should declare other methods explicitly. Flask also supports method-specific decorators such as @app.get and @app.post. See the Flask Quickstart for routing and request/response behavior.
Install Flask in a virtual environment
The Flask installation documentation currently states that Flask supports Python 3.9 and newer; check the linked documentation if you are working with a newer or unusual Python environment. A virtual environment keeps this project’s dependencies separate from other Python projects.
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Create a project directory and move into it:
mkdir flask-api cd flask-api -
Create and activate a virtual environment. On macOS or Linux:
python3 -m venv .venv source .venv/bin/activateOn Windows PowerShell:
py -m venv .venv .venvScriptsActivate.ps1 -
Install Flask:
python -m pip install Flask
Using python -m pip helps ensure that installation uses the Python interpreter associated with the active environment. Flask documents the virtual-environment workflow and installation command in its installation guide.
Create the API
Save this as app.py. The data is deliberately stored in a Python list so the route and JSON behavior are easy to see. The records disappear when the process stops; use a database or other persistent store for an application that must retain data.
from flask import Flask, abort, request, url_for
app = Flask(__name__)
items = [
{"id": 1, "name": "Notebook"},
{"id": 2, "name": "Pen"},
]
next_item_id = 3
@app.get("/items")
def list_items():
return {"items": items}
@app.get("/items/<int:item_id>")
def get_item(item_id):
item = next((item for item in items if item["id"] == item_id), None)
if item is None:
abort(404, description="Item not found")
return item
@app.post("/items")
def create_item():
global next_item_id
if not request.is_json:
return {"error": "Content-Type must be application/json"}, 415
data = request.get_json()
if not isinstance(data, dict):
return {"error": "JSON body must be an object"}, 400
name = data.get("name")
if not isinstance(name, str) or not name.strip():
return {"error": "'name' must be a non-empty string"}, 400
item = {"id": next_item_id, "name": name.strip()}
next_item_id += 1
items.append(item)
response = app.response_class(
response=app.json.dumps(item),
status=201,
mimetype="application/json",
)
response.headers["Location"] = url_for("get_item", item_id=item["id"])
return response
@app.errorhandler(404)
def handle_not_found(error):
return {"error": error.description or "Not found"}, 404
if __name__ == "__main__":
app.run(debug=True)Why the routes use these methods and responses
-
GET /itemsreads the collection, whileGET /items/<int:item_id>reads one item. The integer path converter rejects non-integer IDs as unmatched routes.Recommended Free Tools
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POST /itemscreates an item. The example requires a JSON object with a non-empty stringname, trims surrounding whitespace, and responds with201 Created. TheLocationheader points to the new item’s retrieval URL. -
A request with a non-JSON content type receives
415 Unsupported Media Type; a JSON body with invalid shape or a missing/blank name receives400 Bad Request. A request for an item ID that is not present receives404 Not Found.Rank #2
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The not-found handler returns a JSON error body while retaining the 404 status. Flask also has default handling for errors such as 405 Method Not Allowed and 500 Internal Server Error; an API can add handlers when it needs a consistent JSON format for those cases too. See Flask’s error handling guidance.
Flask can convert a returned dictionary or list into a JSON response automatically. This example uses that behavior for ordinary results and errors, and constructs a response explicitly for the create route because it needs to set both a status and a header. jsonify() is another supported way to make a JSON response. Returned values must be JSON-serializable; convert database models or other complex objects to plain dictionaries or lists first. Details are in the Flask API reference.
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Flask also allows one route function to handle multiple methods with @app.route("/items", methods=["GET", "POST"]), then branch on request.method. That can be compact when behavior is closely shared. Separate @app.get and @app.post functions make different operations, validation, and return behavior easier to read and maintain, which is why this tutorial uses them.
Run the API locally and make requests
From the directory containing app.py, start Flask’s development server:
flask --app app run --debugThe server prints a local address, usually http://127.0.0.1:5000. Keep it running in that terminal while you send requests from another one.
List items and retrieve one item
Use curl to request the collection:
curl -i http://127.0.0.1:5000/itemsThe response should have a 200 status and JSON similar to:
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{"items":[{"id":1,"name":"Notebook"},{"id":2,"name":"Pen"}]}Retrieve the first item with curl -i http://127.0.0.1:5000/items/1. For an ID that is absent, such as 999, the API returns a 404 response with a JSON error body.
Send a JSON POST request
Specify the JSON content type and provide a JSON object in the request body:
curl -i -X POST http://127.0.0.1:5000/items
-H "Content-Type: application/json"
-d '{"name":"Marker"}'A successful response has status 201, a JSON representation of the created item, and a Location header. Try {} to see the validation error, or send a non-JSON body to see the unsupported-media-type response.
Test routes without starting a server
Flask’s test client makes requests directly to the application, so a live server is not needed. The json argument serializes a request body and sets its JSON content type; JSON responses can be inspected through response.json. These features are documented in Testing Flask Applications.
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Create test_app.py beside app.py:
import unittest
from app import app, items
class ItemApiTests(unittest.TestCase):
def setUp(self):
app.config["TESTING"] = True
self.client = app.test_client()
def test_list_items_returns_json(self):
response = self.client.get("/items")
self.assertEqual(response.status_code, 200)
self.assertIsInstance(response.json["items"], list)
def test_missing_item_returns_json_404(self):
response = self.client.get("/items/999")
self.assertEqual(response.status_code, 404)
self.assertEqual(response.json["error"], "Item not found")
def test_create_item_returns_created_resource(self):
response = self.client.post("/items", json={"name": "Test item"})
self.assertEqual(response.status_code, 201)
self.assertEqual(response.json["name"], "Test item")
self.assertIn("Location", response.headers)
def test_create_item_rejects_blank_name(self):
response = self.client.post("/items", json={"name": " "})
self.assertEqual(response.status_code, 400)
self.assertIn("error", response.json)
if __name__ == "__main__":
unittest.main()Run the tests with:
python -m unittest -vBecause this example mutates module-level in-memory data, a POST test can affect later requests during the same process. For larger suites, use a fixture or application factory to create a fresh app and isolated test data for each test. The current tests check response status, JSON content, and a response header rather than depending on incidental implementation details.
Decide what to improve before production
The tutorial app demonstrates request handling, but the in-memory list is neither durable nor designed for concurrent application workers. A production API typically needs persistent storage, explicit data validation, authentication and authorization where appropriate, and operational monitoring. Those are application design decisions, not features Flask automatically supplies.
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The debug=True setting and Flask’s built-in server are for local development. Flask explicitly warns not to use the development server or interactive debugger in production: the debugger can expose powerful execution capabilities, and the server is not the production deployment mechanism. Flask is a WSGI application; choose a production deployment option described in the Flask deployment documentation. Do not expose the debug server to the public internet.
Troubleshooting common problems
-
ModuleNotFoundError: No module named 'flask': activate the project’s virtual environment, then install Flask withpython -m pip install Flaskusing that same interpreter.The Tool Desk
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Flask cannot find the application: run the command from the directory containing
app.pyand useflask --app app run --debug. The value after--appidentifies the module, not the filename with its.pysuffix. -
POST returns 415: send
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POST returns 400: verify that the body is valid JSON, is an object rather than a string or array, and contains a non-empty string in
name. -
A route returns 404 or 405: check the path spelling, the item ID, and the method. A path that exists for GET does not automatically accept POST; this API only creates through
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Changes vanish after restarting: that is expected because the sample keeps data in memory. Add a persistent datastore and define how records are created, read, and updated there.
-
Tests fail depending on execution order: the shared list and ID counter persist within the Python process. Reset or isolate application data between tests rather than relying on a particular test order.
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Frequently Asked Questions
Does this example implement every REST operation?
No. It demonstrates listing, retrieving, and creating items. Update and delete routes are intentionally omitted so the basic request and response pattern stays focused.
Can a Flask API return database objects directly as JSON?
Not generally: return JSON-serializable values. Convert a model to plain dictionaries or lists, or construct a response with the fields the API should expose.
Quick Recap
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