So strukturieren Sie einen Flask-RESTPlus-Webdienst für Produktionsbuilds

In diesem Handbuch zeige ich Ihnen einen schrittweisen Ansatz zum Strukturieren einer Flask RESTPlus-Webanwendung für Test-, Entwicklungs- und Produktionsumgebungen. Ich werde ein Linux-basiertes Betriebssystem (Ubuntu) verwenden, aber die meisten Schritte können unter Windows und Mac repliziert werden.

Bevor Sie mit diesem Handbuch fortfahren, sollten Sie über grundlegende Kenntnisse der Programmiersprache Python und des Flask Micro Frameworks verfügen. Wenn Sie mit diesen nicht vertraut sind, empfehlen wir Ihnen, einen Einführungsartikel zu lesen - So verwenden Sie Python und Flask zum Erstellen einer Web-App.

Wie dieser Leitfaden aufgebaut ist

Diese Anleitung ist in folgende Teile unterteilt:

  • Eigenschaften
  • Was ist Flask-RESTPlus?
  • Einrichtung und Installation
  • Projekteinrichtung und Organisation
  • Konfigurationseinstellungen
  • Flaschenskript
  • Datenbankmodelle und Migration
  • Testen
  • Aufbau
  • Benutzeroperationen
  • Sicherheit und Authentifizierung
  • Routenschutz und Autorisierung
  • Zusätzliche Tipps
  • App & Fazit erweitern

Eigenschaften

Wir werden die folgenden Funktionen und Erweiterungen in unserem Projekt verwenden.

  • Flask-Bcrypt: Eine Flask-Erweiterung, die bcrypt-Hashing-Dienstprogramme für Ihre Anwendung bereitstellt .
  • Flask-Migrate: Eine Erweiterung, die SQLAlchemy-Datenbankmigrationen für Flask-Anwendungen mit Alembic verarbeitet. Die Datenbankoperationen werden über die Flask-Befehlszeilenschnittstelle oder über die Flask-Script-Erweiterung verfügbar gemacht.
  • Flask-SQLAlchemy: Eine Erweiterung für Flask, die Ihrer Anwendung Unterstützung für SQLAlchemy hinzufügt.
  • PyJWT: Eine Python-Bibliothek, mit der Sie JSON-Web-Tokens (JWT) codieren und decodieren können. JWT ist ein offener Industriestandard (RFC 7519) zur sicheren Darstellung von Ansprüchen zwischen zwei Parteien.
  • Flask-Script: Eine Erweiterung, die das Schreiben externer Skripte in Flask und andere Befehlszeilenaufgaben unterstützt, die außerhalb der Webanwendung selbst liegen.
  • Namespaces (Blaupausen)
  • Kolben-Restplus
  • Gerätetest

Was ist Flask-RESTPlus?

Flask-RESTPlus ist eine Erweiterung für Flask, die Unterstützung für das schnelle Erstellen von REST-APIs bietet. Flask-RESTPlus empfiehlt Best Practices mit minimalem Setup. Es bietet eine zusammenhängende Sammlung von Dekoratoren und Tools, mit denen Sie Ihre API beschreiben und die Dokumentation ordnungsgemäß verfügbar machen können (mithilfe von Swagger).

Einrichtung und Installation

Überprüfen Sie, ob Pip installiert ist, indem Sie den Befehl pip --versionin das Terminal eingeben und die Eingabetaste drücken.

pip --version

Wenn das Terminal mit der Versionsnummer antwortet, bedeutet dies, dass pip installiert ist. Fahren Sie mit dem nächsten Schritt fort. Andernfalls installieren Sie pip oder verwenden Sie den Linux-Paketmanager. Führen Sie den folgenden Befehl auf dem Terminal aus und drücken Sie die Eingabetaste. Wählen Sie entweder die Python 2.x- oder die 3.x-Version.

  • Python 2.x.
sudo apt-get install python-pip
  • Python 3.x.
sudo apt-get install python3-pip

Richten Sie den Wrapper für die virtuelle Umgebung und die virtuelle Umgebung ein (abhängig von der oben installierten Version benötigen Sie nur einen davon):

sudo pip install virtualenv sudo pip3 install virtualenvwrapper

Folgen Sie diesem Link, um eine vollständige Einrichtung des Wrappers für die virtuelle Umgebung zu erhalten.

Erstellen Sie eine neue Umgebung und aktivieren Sie sie, indem Sie den folgenden Befehl auf dem Terminal ausführen:

mkproject name_of_your_project

Projekteinrichtung und Organisation

Ich werde eine funktionale Struktur verwenden, um die Dateien des Projekts nach ihren Aufgaben zu organisieren. In einer funktionalen Struktur sind Vorlagen in einem Verzeichnis zusammengefasst, statische Dateien in einem anderen und Ansichten in einem dritten.

Erstellen Sie im Projektverzeichnis ein neues Paket mit dem Namen app. appErstellen Sie im Inneren zwei Pakete main und test. Ihre Verzeichnisstruktur sollte ähnlich wie die folgende aussehen.

. ├── app │ ├── __init__.py │ ├── main │ │ └── __init__.py │ └── test │ └── __init__.py └── requirements.txt

Wir werden eine funktionale Struktur verwenden, um unsere Anwendung zu modularisieren.

Im Inneren der mainVerpackung, erstellen Sie drei weitere Pakete nämlich: controller, serviceund model. Das modelPaket enthält alle unsere Datenbankmodelle, während das servicePaket die gesamte Geschäftslogik unserer Anwendung enthält und schließlich das controllerPaket alle unsere Anwendungsendpunkte enthält. Die Baumstruktur sollte nun wie folgt aussehen:

. ├── app │ ├── __init__.py │ ├── main │ │ ├── controller │ │ │ └── __init__.py │ │ ├── __init__.py │ │ ├── model │ │ │ └── __init__.py │ │ └── service │ │ └── __init__.py │ └── test │ └── __init__.py └── requirements.txt

Jetzt können wir die erforderlichen Pakete installieren. Stellen Sie sicher, dass die von Ihnen erstellte virtuelle Umgebung aktiviert ist, und führen Sie die folgenden Befehle auf dem Terminal aus:

pip install flask-bcrypt pip install flask-restplus pip install Flask-Migrate pip install pyjwt pip install Flask-Script pip install flask_testing

Erstellen oder aktualisieren Sie die requirements.txtDatei, indem Sie den folgenden Befehl ausführen:

pip freeze > requirements.txt

Die generierte requirements.txtDatei sollte ähnlich wie die folgende aussehen:

alembic==0.9.8 aniso8601==3.0.0 bcrypt==3.1.4 cffi==1.11.5 click==6.7 Flask==0.12.2 Flask-Bcrypt==0.7.1 Flask-Migrate==2.1.1 flask-restplus==0.10.1 Flask-Script==2.0.6 Flask-SQLAlchemy==2.3.2 Flask-Testing==0.7.1 itsdangerous==0.24 Jinja2==2.10 jsonschema==2.6.0 Mako==1.0.7 MarkupSafe==1.0 pycparser==2.18 PyJWT==1.6.0 python-dateutil==2.7.0 python-editor==1.0.3 pytz==2018.3 six==1.11.0 SQLAlchemy==1.2.5 Werkzeug==0.14.1

Konfigurationseinstellungen

mainErstellen Sie im Paket eine Datei config.pymit dem folgenden Inhalt:

import os # uncomment the line below for postgres database url from environment variable # postgres_local_base = os.environ['DATABASE_URL'] basedir = os.path.abspath(os.path.dirname(__file__)) class Config: SECRET_KEY = os.getenv('SECRET_KEY', 'my_precious_secret_key') DEBUG = False class DevelopmentConfig(Config): # uncomment the line below to use postgres # SQLALCHEMY_DATABASE_URI = postgres_local_base DEBUG = True SQLALCHEMY_DATABASE_URI = 'sqlite:///' + os.path.join(basedir, 'flask_boilerplate_main.db') SQLALCHEMY_TRACK_MODIFICATIONS = False class TestingConfig(Config): DEBUG = True TESTING = True SQLALCHEMY_DATABASE_URI = 'sqlite:///' + os.path.join(basedir, 'flask_boilerplate_test.db') PRESERVE_CONTEXT_ON_EXCEPTION = False SQLALCHEMY_TRACK_MODIFICATIONS = False class ProductionConfig(Config): DEBUG = False # uncomment the line below to use postgres # SQLALCHEMY_DATABASE_URI = postgres_local_base config_by_name = dict( dev=DevelopmentConfig, test=TestingConfig, prod=ProductionConfig ) key = Config.SECRET_KEY

The configuration file contains three environment setup classes which includes testing, development, and production.

We will be using the application factory pattern for creating our Flask object. This pattern is most useful for creating multiple instances of our application with different settings. This facilitates the ease at which we switch between our testing, development and production environment by calling the create_app function with the required parameter.

In the __init__.py file inside the main package, enter the following lines of code:

from flask import Flask from flask_sqlalchemy import SQLAlchemy from flask_bcrypt import Bcrypt from .config import config_by_name db = SQLAlchemy() flask_bcrypt = Bcrypt() def create_app(config_name): app = Flask(__name__) app.config.from_object(config_by_name[config_name]) db.init_app(app) flask_bcrypt.init_app(app) return app

Flask Script

Now let’s create our application entry point. In the root directory of the project, create a file called manage.py with the following content:

import os import unittest from flask_migrate import Migrate, MigrateCommand from flask_script import Manager from app.main import create_app, db app = create_app(os.getenv('BOILERPLATE_ENV') or 'dev') app.app_context().push() manager = Manager(app) migrate = Migrate(app, db) manager.add_command('db', MigrateCommand) @manager.command def run(): app.run() @manager.command def test(): """Runs the unit tests.""" tests = unittest.TestLoader().discover('app/test', pattern="test*.py") result = unittest.TextTestRunner(verbosity=2).run(tests) if result.wasSuccessful(): return 0 return 1 if __name__ == '__main__': manager.run()

The above code within manage.py does the following:

  • line 4 and 5 imports the migrate and manager modules respectively (we will be using the migrate command soon).
  • line 9 calls the create_app function we created initially to create the application instance with the required parameter from the environment variable which can be either of the following - dev, prod, test. If none is set in the environment variable, the default dev is used.
  • line 13 and 15 instantiates the manager and migrate classes by passing the app instance to their respective constructors.
  • In line 17,we pass the db and MigrateCommandinstances to the add_command interface of the managerto expose all the database migration commands through Flask-Script.
  • line 20 and 25 marks the two functions as executable from the command line.
Flask-Migrate exposes two classes, Migrate and MigrateCommand. The Migrateclass contains all the functionality of the extension. The MigrateCommand class is only used when it is desired to expose database migration commands through the Flask-Script extension.

At this point, we can test the application by running the command below in the project root directory.

python manage.py run

If everything is okay, you should see something like this:

Database Models and Migration

Now let’s create our models. We will be using the db instance of the sqlalchemy to create our models.

The db instance contains all the functions and helpers from both sqlalchemyand sqlalchemy.ormandit provides a class called Model that is a declarative base which can be used to declare models.

In the model package, create a file called user.py with the following content:

from .. import db, flask_bcrypt class User(db.Model): """ User Model for storing user related details """ __tablename__ = "user" id = db.Column(db.Integer, primary_key=True, autoincrement=True) email = db.Column(db.String(255), unique=True, nullable=False) registered_on = db.Column(db.DateTime, nullable=False) admin = db.Column(db.Boolean, nullable=False, default=False) public_id = db.Column(db.String(100), unique=True) username = db.Column(db.String(50), unique=True) password_hash = db.Column(db.String(100)) @property def password(self): raise AttributeError('password: write-only field') @password.setter def password(self, password): self.password_hash = flask_bcrypt.generate_password_hash(password).decode('utf-8') def check_password(self, password): return flask_bcrypt.check_password_hash(self.password_hash, password) def __repr__(self): return "".format(self.username)

The above code within user.py does the following:

  • line 3: The user class inherits from db.Model class which declares the class as a model for sqlalchemy.
  • line 7 through 13 creates the required columns for the user table.
  • line 21 is a setter for the field password_hash and it uses flask-bcryptto generate a hash using the provided password.
  • line 24 compares a given password with already savedpassword_hash.

Now to generate the database table from the user model we just created, we will use migrateCommand through the manager interface. For managerto detect our models, we will have to import theuser model by adding below code to manage.py file:

... from app.main.model import user ...

Jetzt können wir mit der Migration fortfahren, indem wir die folgenden Befehle im Projektstammverzeichnis ausführen:

  1. Initiieren Sie einen Migrationsordner mit dem initBefehl für Alembic, um die Migrationen durchzuführen.
python manage.py db init

2. Erstellen Sie mit dem migrateBefehl ein Migrationsskript aus den erkannten Änderungen im Modell . Dies hat noch keine Auswirkungen auf die Datenbank.

python manage.py db migrate --message 'initial database migration'

3. Wenden Sie das Migrationsskript mit dem upgradeBefehl auf die Datenbank an

python manage.py db upgrade

Wenn alles erfolgreich ausgeführt wird, sollten Sie über eine neue sqlLite-Datenbank verfügen

flask_boilerplate_main.db Datei im Hauptpaket generiert.

Wiederholen Sie die Befehle migrateund jedes Mal, wenn sich das Datenbankmodell ändertupgrade

Testen

Aufbau

Um sicherzugehen, dass das Setup für unsere Umgebungskonfiguration funktioniert, schreiben wir ein paar Tests dafür.

Create a file called test_config.py in the test package with the content below:

import os import unittest from flask import current_app from flask_testing import TestCase from manage import app from app.main.config import basedir class TestDevelopmentConfig(TestCase): def create_app(self): app.config.from_object('app.main.config.DevelopmentConfig') return app def test_app_is_development(self): self.assertFalse(app.config['SECRET_KEY'] is 'my_precious') self.assertTrue(app.config['DEBUG'] is True) self.assertFalse(current_app is None) self.assertTrue( app.config['SQLALCHEMY_DATABASE_URI'] == 'sqlite:///' + os.path.join(basedir, 'flask_boilerplate_main.db') ) class TestTestingConfig(TestCase): def create_app(self): app.config.from_object('app.main.config.TestingConfig') return app def test_app_is_testing(self): self.assertFalse(app.config['SECRET_KEY'] is 'my_precious') self.assertTrue(app.config['DEBUG']) self.assertTrue( app.config['SQLALCHEMY_DATABASE_URI'] == 'sqlite:///' + os.path.join(basedir, 'flask_boilerplate_test.db') ) class TestProductionConfig(TestCase): def create_app(self): app.config.from_object('app.main.config.ProductionConfig') return app def test_app_is_production(self): self.assertTrue(app.config['DEBUG'] is False) if __name__ == '__main__': unittest.main()

Run the test using the command below:

python manage.py test

You should get the following output:

User Operations

Now let’s work on the following user related operations:

  • creating a new user
  • getting a registered user with his public_id
  • getting all registered users.

User Service class: This class handles all the logic relating to the user model.

In the service package, create a new file user_service.py with the following content:

import uuid import datetime from app.main import db from app.main.model.user import User def save_new_user(data): user = User.query.filter_by(email=data['email']).first() if not user: new_user = User( public_id=str(uuid.uuid4()), email=data['email'], username=data['username'], password=data['password'], registered_on=datetime.datetime.utcnow() ) save_changes(new_user) response_object = { 'status': 'success', 'message': 'Successfully registered.' } return response_object, 201 else: response_object = { 'status': 'fail', 'message': 'User already exists. Please Log in.', } return response_object, 409 def get_all_users(): return User.query.all() def get_a_user(public_id): return User.query.filter_by(public_id=public_id).first() def save_changes(data): db.session.add(data) db.session.commit() 

The above code within user_service.py does the following:

  • line 8 through 29 creates a new user by first checking if the user already exists; it returns a success response_object if the user doesn’t exist else it returns an error code 409 and a failure response_object.
  • line 33und 37geben Sie eine Liste aller registrierten Benutzer und eines Benutzerobjekts zurück, indem Sie jeweils angeben public_id.
  • line 40um 42die Änderungen an der Datenbank festzuschreiben.
Sie müssen jsonify nicht zum Formatieren eines Objekts in JSON verwenden, Flask-restplus führt dies automatisch aus

mainErstellen Sie im Paket ein neues Paket mit dem Namen util. Dieses Paket enthält alle erforderlichen Dienstprogramme, die wir möglicherweise in unserer Anwendung benötigen.

utilErstellen Sie im Paket eine neue Datei dto.py. Wie der Name schon sagt, ist das Datenübertragungsobjekt (DTO) für die Übertragung von Daten zwischen Prozessen verantwortlich. In unserem Fall wird es zum Sammeln von Daten für unsere API-Aufrufe verwendet. Wir werden dies besser verstehen, wenn wir fortfahren.

from flask_restplus import Namespace, fields class UserDto: api = Namespace('user', description="user related operations") user = api.model('user', { 'email': fields.String(required=True, description="user email address"), 'username': fields.String(required=True, description="user username"), 'password': fields.String(required=True, description="user password"), 'public_id': fields.String(description='user Identifier') })

Der obige Code dto.pybewirkt Folgendes:

  • line 5 creates a new namespace for user related operations. Flask-RESTPlus provides a way to use almost the same pattern as Blueprint. The main idea is to split your app into reusable namespaces. A namespace module will contain models and resources declaration.
  • line 6 creates a new user dto through the model interface provided by the api namespace in line 5.

User Controller: The user controller class handles all the incoming HTTP requests relating to the user .

Under the controller package, create a new file called user_controller.py with the following content:

from flask import request from flask_restplus import Resource from ..util.dto import UserDto from ..service.user_service import save_new_user, get_all_users, get_a_user api = UserDto.api _user = UserDto.user @api.route('/') class UserList(Resource): @api.doc('list_of_registered_users') @api.marshal_list_with(_user, envelope="data") def get(self): """List all registered users""" return get_all_users() @api.response(201, 'User successfully created.') @api.doc('create a new user') @api.expect(_user, validate=True) def post(self): """Creates a new User """ data = request.json return save_new_user(data=data) @api.route('/') @api.param('public_id', 'The User identifier') @api.response(404, 'User not found.') class User(Resource): @api.doc('get a user') @api.marshal_with(_user) def get(self, public_id): """get a user given its identifier""" user = get_a_user(public_id) if not user: api.abort(404) else: return user

line 1 through 8 imports all the required resources for the user controller.

We defined two concrete classes in our user controller which are

userList and user. These two classes extends the abstract flask-restplus resource.

Concrete resources should extend from this classand expose methods for each supported HTTP method.If a resource is invoked with an unsupported HTTP method,the API will return a response with status 405 Method Not Allowed.Otherwise the appropriate method is called and passed all argumentsfrom the URL rule used when adding the resource to an API instance.

The api namespace in line 7 above provides the controller with several decorators which includes but is not limited to the following:

  • api.route: A decorator to route resources
  • api.marshal_with: A decorator specifying the fields to use for serialization (This is where we use the userDto we created earlier)
  • api.marshal_list_with: A shortcut decorator for marshal_with above withas_list = True
  • api.doc: A decorator to add some api documentation to the decorated object
  • api.response: A decorator to specify one of the expected responses
  • api.expect: A decorator to Specify the expected input model ( we still use the userDto for the expected input)
  • api.param: A decorator to specify one of the expected parameters

We have now defined our namespace with the user controller. Now its time to add it to the application entry point.

In the __init__.py file of app package, enter the following:

# app/__init__.py from flask_restplus import Api from flask import Blueprint from .main.controller.user_controller import api as user_ns blueprint = Blueprint('api', __name__) api = Api(blueprint,, version="1.0", description="a boilerplate for flask restplus web service" ) api.add_namespace(user_ns, path="/user")

The above code within blueprint.py does the following:

  • In line 8, we create a blueprint instance by passing name and import_name.API is the main entry point for the application resources and hence needs to be initialized with the blueprint in line 10.
  • In line 16 , we add the user namespace user_ns to the list of namespaces in the API instance.

We have now defined our blueprint. It’s time to register it on our Flask app.

Update manage.py by importing blueprint and registering it with the Flask application instance.

from app import blueprint ... app = create_app(os.getenv('BOILERPLATE_ENV') or 'dev') app.register_blueprint(blueprint) app.app_context().push() ...

We can now test our application to see that everything is working fine.

python manage.py run

Now open the URL //127.0.0.1:5000 in your browser. You should see the swagger documentation.

Let’s test the create new user endpoint using the swagger testing functionality.

You should get the following response

Security and Authentication

Let’s create a model blacklistToken for storing blacklisted tokens. In the models package, create a blacklist.py file with the following content:

from .. import db import datetime class BlacklistToken(db.Model): """ Token Model for storing JWT tokens """ __tablename__ = 'blacklist_tokens' id = db.Column(db.Integer, primary_key=True, autoincrement=True) token = db.Column(db.String(500), unique=True, nullable=False) blacklisted_on = db.Column(db.DateTime, nullable=False) def __init__(self, token): self.token = token self.blacklisted_on = datetime.datetime.now() def __repr__(self): return '

Lets not forget to migrate the changes to take effect on our database.

Import the blacklist class in manage.py.

from app.main.model import blacklist

Run the migrate and upgrade commands

python manage.py db migrate --message 'add blacklist table' python manage.py db upgrade

Next create blacklist_service.py in the service package with the following content for blacklisting a token:

from app.main import db from app.main.model.blacklist import BlacklistToken def save_token(token): blacklist_token = BlacklistToken(token=token) try: # insert the token db.session.add(blacklist_token) db.session.commit() response_object = { 'status': 'success', 'message': 'Successfully logged out.' } return response_object, 200 except Exception as e: response_object = { 'status': 'fail', 'message': e } return response_object, 200

Update the user model with two static methods for encoding and decoding tokens. Add the following imports:

import datetime import jwt from app.main.model.blacklist import BlacklistToken from ..config import key
  • Encoding
def encode_auth_token(self, user_id): """ Generates the Auth Token :return: string """ try: payload = { 'exp': datetime.datetime.utcnow() + datetime.timedelta(days=1, seconds=5), 'iat': datetime.datetime.utcnow(), 'sub': user_id } return jwt.encode( payload, key, algorithm="HS256" ) except Exception as e: return e
  • Decoding: Blacklisted token, expired token and invalid token are taken into consideration while decoding the authentication token.
 @staticmethod def decode_auth_token(auth_token): """ Decodes the auth token :param auth_token: :return: integer|string """ try: payload = jwt.decode(auth_token, key) is_blacklisted_token = BlacklistToken.check_blacklist(auth_token) if is_blacklisted_token: return 'Token blacklisted. Please log in again.' else: return payload['sub'] except jwt.ExpiredSignatureError: return 'Signature expired. Please log in again.' except jwt.InvalidTokenError: return 'Invalid token. Please log in again.'

Now let’s write a test for the user model to ensure that our encode and decode functions are working properly.

In the test package, create base.py file with the following content:

from flask_testing import TestCase from app.main import db from manage import app class BaseTestCase(TestCase): """ Base Tests """ def create_app(self): app.config.from_object('app.main.config.TestingConfig') return app def setUp(self): db.create_all() db.session.commit() def tearDown(self): db.session.remove() db.drop_all()

The BaseTestCase sets up our test environment ready before and after every test case that extends it.

Create test_user_medol.py with the following test cases:

import unittest import datetime from app.main import db from app.main.model.user import User from app.test.base import BaseTestCase class TestUserModel(BaseTestCase): def test_encode_auth_token(self): user = User( email="[email protected]", password="test", registered_on=datetime.datetime.utcnow() ) db.session.add(user) db.session.commit() auth_token = user.encode_auth_token(user.id) self.assertTrue(isinstance(auth_token, bytes)) def test_decode_auth_token(self): user = User( email="[email protected]", password="test", registered_on=datetime.datetime.utcnow() ) db.session.add(user) db.session.commit() auth_token = user.encode_auth_token(user.id) self.assertTrue(isinstance(auth_token, bytes)) self.assertTrue(User.decode_auth_token(auth_token.decode("utf-8") ) == 1) if __name__ == '__main__': unittest.main() 

Run the test with python manage.py test. All the tests should pass.

Let’s create the authentication endpoints for login and logout.

  • First we need a dto for the login payload. We will use the auth dto for the @expect annotation in login endpoint. Add the code below to the dto.py
class AuthDto: api = Namespace('auth', description="authentication related operations") user_auth = api.model('auth_details', { 'email': fields.String(required=True, description="The email address"), 'password': fields.String(required=True, description="The user password"), })
  • Next, we create an authentication helper class for handling all authentication related operations. This auth_helper.py will be in the service package and will contain two static methods which are login_user and logout_user

Original text


When a user is logged out, the user’s token is blacklisted ie the user can’t log in again with that same token.
from app.main.model.user import User from ..service.blacklist_service import save_token class Auth: @staticmethod def login_user(data): try: # fetch the user data user = User.query.filter_by(email=data.get('email')).first() if user and user.check_password(data.get('password')): auth_token = user.encode_auth_token(user.id) if auth_token: response_object = { 'status': 'success', 'message': 'Successfully logged in.', 'Authorization': auth_token.decode() } return response_object, 200 else: response_object = { 'status': 'fail', 'message': 'email or password does not match.' } return response_object, 401 except Exception as e: print(e) response_object = { 'status': 'fail', 'message': 'Try again' } return response_object, 500 @staticmethod def logout_user(data): if data: auth_token = data.split(" ")[1] else: auth_token = '' if auth_token: resp = User.decode_auth_token(auth_token) if not isinstance(resp, str): # mark the token as blacklisted return save_token(token=auth_token) else: response_object = { 'status': 'fail', 'message': resp } return response_object, 401 else: response_object = { 'status': 'fail', 'message': 'Provide a valid auth token.' } return response_object, 403
  • Let us now create endpoints for login and logout operations.

    In the controller package, create

    auth_controller.py with the following contents:

from flask import request from flask_restplus import Resource from app.main.service.auth_helper import Auth from ..util.dto import AuthDto api = AuthDto.api user_auth = AuthDto.user_auth @api.route('/login') class UserLogin(Resource): """ User Login Resource """ @api.doc('user login') @api.expect(user_auth, validate=True) def post(self): # get the post data post_data = request.json return Auth.login_user(data=post_data) @api.route('/logout') class LogoutAPI(Resource): """ Logout Resource """ @api.doc('logout a user') def post(self): # get auth token auth_header = request.headers.get('Authorization') return Auth.logout_user(data=auth_header)
  • At this point the only thing left is to register the auth api namespace with the application Blueprint

Update __init__.py file of app package with the following

# app/__init__.py from flask_restplus import Api from flask import Blueprint from .main.controller.user_controller import api as user_ns from .main.controller.auth_controller import api as auth_ns blueprint = Blueprint('api', __name__) api = Api(blueprint,, version="1.0", description="a boilerplate for flask restplus web service" ) api.add_namespace(user_ns, path="/user") api.add_namespace(auth_ns)

Run the application with python manage.py run and open the url //127.0.0.1:5000 in your browser.

The swagger documentation should now reflect the newly created auth namespace with the login and logout endpoints.

Before we write some tests to ensure our authentication is working as expected, let’s modify our registration endpoint to automatically login a user once the registration is successful.

Add the method generate_token below to user_service.py:

def generate_token(user): try: # generate the auth token auth_token = user.encode_auth_token(user.id) response_object = { 'status': 'success', 'message': 'Successfully registered.', 'Authorization': auth_token.decode() } return response_object, 201 except Exception as e: response_object = { 'status': 'fail', 'message': 'Some error occurred. Please try again.' } return response_object, 401

The generate_token method generates an authentication token by encoding the user id. This token isthe returned as a response.

Next, replace the return block in save_new_user method below

response_object = { 'status': 'success', 'message': 'Successfully registered.' } return response_object, 201

with

return generate_token(new_user)

Now its time to test the login and logout functionalities. Create a new test file test_auth.py in the test package with the following content:

import unittest import json from app.test.base import BaseTestCase def register_user(self): return self.client.post( '/user/', data=json.dumps(dict( email="[email protected]", username="username", password="123456" )), content_type="application/json" ) def login_user(self): return self.client.post( '/auth/login', data=json.dumps(dict( email="[email protected]", password="123456" )), content_type="application/json" ) class TestAuthBlueprint(BaseTestCase): def test_registered_user_login(self): """ Test for login of registered-user login """ with self.client: # user registration user_response = register_user(self) response_data = json.loads(user_response.data.decode()) self.assertTrue(response_data['Authorization']) self.assertEqual(user_response.status_code, 201) # registered user login login_response = login_user(self) data = json.loads(login_response.data.decode()) self.assertTrue(data['Authorization']) self.assertEqual(login_response.status_code, 200) def test_valid_logout(self): """ Test for logout before token expires """ with self.client: # user registration user_response = register_user(self) response_data = json.loads(user_response.data.decode()) self.assertTrue(response_data['Authorization']) self.assertEqual(user_response.status_code, 201) # registered user login login_response = login_user(self) data = json.loads(login_response.data.decode()) self.assertTrue(data['Authorization']) self.assertEqual(login_response.status_code, 200) # valid token logout response = self.client.post( '/auth/logout', headers=dict( Authorization="Bearer" + json.loads( login_response.data.decode() )['Authorization'] ) ) data = json.loads(response.data.decode()) self.assertTrue(data['status'] == 'success') self.assertEqual(response.status_code, 200) if __name__ == '__main__': unittest.main()

Visit the github repo for a more exhaustive test cases.

Route protection and Authorization

So far, we have successfully created our endpoints, implemented login and logout functionalities but our endpoints remains unprotected.

We need a way to define rules that determines which of our endpoint is open or requires authentication or even an admin privilege.

We can achieve this by creating custom decorators for our endpoints.

Before we can protect or authorize any of our endpoints, we need to know the currently logged in user. We can do this by pulling the Authorization token from the header of the current request by using the flask library request.We then decode the user details from the Authorization token.

In the Auth class of auth_helper.py file, add the following static method:

@staticmethod def get_logged_in_user(new_request): # get the auth token auth_token = new_request.headers.get('Authorization') if auth_token: resp = User.decode_auth_token(auth_token) if not isinstance(resp, str): user = User.query.filter_by(id=resp).first() response_object = { 'status': 'success', 'data': { 'user_id': user.id, 'email': user.email, 'admin': user.admin, 'registered_on': str(user.registered_on) } } return response_object, 200 response_object = { 'status': 'fail', 'message': resp } return response_object, 401 else: response_object = { 'status': 'fail', 'message': 'Provide a valid auth token.' } return response_object, 401

Now that we can retrieve the logged in user from the request, let’s go ahead and create the decorators.

Create a file decorator.py in the util package with the following content:

from functools import wraps from flask import request from app.main.service.auth_helper import Auth def token_required(f): @wraps(f) def decorated(*args, **kwargs): data, status = Auth.get_logged_in_user(request) token = data.get('data') if not token: return data, status return f(*args, **kwargs) return decorated def admin_token_required(f): @wraps(f) def decorated(*args, **kwargs): data, status = Auth.get_logged_in_user(request) token = data.get('data') if not token: return data, status admin = token.get('admin') if not admin: response_object = { 'status': 'fail', 'message': 'admin token required' } return response_object, 401 return f(*args, **kwargs) return decorated

For more information about decorators and how to create them, take a look at this link.

Now that we have created the decorators token_required and admin_token_required for valid token and for an admin token respectively, all that is left is to annotate the endpoints which we wish to protect with the freecodecamp orgappropriate decorator.

Extra tips

Currently to perform some tasks in our application, we are required to run different commands for starting the app, running tests, installing dependencies etc. We can automate those processes by arranging all the commands in one file using Makefile.

On the root directory of the application, create a Makefile with no file extension. The file should contain the following:

.PHONY: clean system-packages python-packages install tests run all clean: find . -type f -name '*.pyc' -delete find . -type f -name '*.log' -delete system-packages: sudo apt install python-pip -y python-packages: pip install -r requirements.txt install: system-packages python-packages tests: python manage.py test run: python manage.py run all: clean install tests run

Here are the options of the make file.

  1. make install : installs both system-packages and python-packages
  2. make clean : cleans up the app
  3. make tests : runs the all the tests
  4. make run : starts the application
  5. make all : performs clean-up,installation , run tests , and starts the app.

Extending the App & Conclusion

It’s pretty easy to copy the current application structure and extend it to add more functionalities/endpoints to the App. Just view any of the previous routes that have been implemented.

Feel free to leave a comment have you any question, observations or recommendations. Also, if this post was helpful to you, click on the clap icon so others will see this here and benefit as well.

Visit the github repository for the complete project.

Thanks for reading and good luck!