Spinn Code
Loading Please Wait
  • Home
  • My Profile

Share something

Explore Qt Development Topics

  • Installation and Setup
  • Core GUI Components
  • Qt Quick and QML
  • Event Handling and Signals/Slots
  • Model-View-Controller (MVC) Architecture
  • File Handling and Data Persistence
  • Multimedia and Graphics
  • Threading and Concurrency
  • Networking
  • Database and Data Management
  • Design Patterns and Architecture
  • Packaging and Deployment
  • Cross-Platform Development
  • Custom Widgets and Components
  • Qt for Mobile Development
  • Integrating Third-Party Libraries
  • Animation and Modern App Design
  • Localization and Internationalization
  • Testing and Debugging
  • Integration with Web Technologies
  • Advanced Topics

About Developer

Khamisi Kibet

Khamisi Kibet

Software Developer

I am a computer scientist, software developer, and YouTuber, as well as the developer of this website, spinncode.com. I create content to help others learn and grow in the field of software development.

If you enjoy my work, please consider supporting me on platforms like Patreon or subscribing to my YouTube channel. I am also open to job opportunities and collaborations in software development. Let's build something amazing together!

  • Email

    infor@spinncode.com
  • Location

    Nairobi, Kenya
cover picture
profile picture Bot SpinnCode

7 Months ago | 52 views

**Course Title:** Modern Python Programming: Best Practices and Trends **Section Title:** Web Development with Python **Topic:** Create a RESTful API with Flask/Django and interact with it using Python.(Lab topic) **Introduction** In this lab topic, we will build a RESTful API using Flask and Django, two popular Python web frameworks. We will learn how to design and implement a simple API, interact with it using Python, and understand the concepts of RESTful APIs. **RESTful API Basics** A RESTful API (Representational State of Resource) is an architectural style for designing networked applications. It is based on the idea of resources, which are identified by URIs, and can be manipulated using a fixed set of operations. Here are the basic principles of RESTful APIs: 1. **Resources**: Everything in REST is a resource. 2. **Client-Server Architecture**: The client and server are separate, with the client making requests to the server to access or modify resources. 3. **Stateless**: The server does not maintain any information about the client state. 4. **Cacheable**: Responses from the server are cacheable, which can reduce the number of requests made to the server. **Flask RESTful API** We will use Flask, a micro web framework written in Python, to build a simple RESTful API. First, let's install Flask using pip: ```bash pip install flask ``` Next, let's create a simple API that can store and retrieve books: **app.py** ```python from flask import Flask, jsonify, request app = Flask(__name__) # Sample data books = [ {"id": 1, "title": "Book 1", "author": "Author 1"}, {"id": 2, "title": "Book 2", "author": "Author 2"}, {"id": 3, "title": "Book 3", "author": "Author 3"} ] # GET /books @app.route('/books', methods=['GET']) def get_books(): return jsonify({"books": books}) # GET /books/:id @app.route('/books/:id', methods=['GET']) @app.route('/books/<int:id>', methods=['GET']) def get_book(id): book = [book for book in books if book['id'] == id] if book: return jsonify({"book": book}) else: return jsonify({"error": "Book not found"}), 404 # POST /books @app.route('/books', methods=['POST']) def create_book(): new_book = { 'id': len(books) + 1, 'title': request.json['title'], 'author': request.json['author'] } books.append(new_book) return jsonify({"book": new_book}), 201 # PUT /books/:id @app.route('/books/<int:id>', methods=['PUT']) def update_book(id): book = [book for book in books if book['id'] == id] if book: book[0]['title'] = request.json.get('title', book[0]['title']) book[0]['author'] = request.json.get('author', book[0]['author']) return jsonify({"book": book[0]}) else: return jsonify({"error": "Book not found"}), 404 # DELETE /books/:id @app.route('/books/<int:id>', methods=['DELETE']) def delete_book(id): book = [book for book in books if book['id'] == id] if book: books.remove(book[0]) return jsonify({"message": "Book deleted"}) else: return jsonify({"error": "Book not found"}), 404 if __name__ == '__main__': app.run() ``` Run the application using Python: ```bash python app.py ``` Now you can interact with the API using tools like curl or Postman. **Django RESTful API** Django is a high-level Python web framework that encourages rapid development and clean, pragmatic design. We will use Django to build a simple RESTful API. First, let's install Django: ```bash pip install django ``` Next, let's create a new Django project and a Django app: ```bash django-admin startproject bookstore cd bookstore python manage.py startapp books ``` Now, let's define a model for books: **books/models.py** ```python from django.db import models class Book(models.Model): title = models.CharField(max_length=100) author = models.CharField(max_length=100) ``` Next, let's create and apply migrations: ```bash python manage.py makemigrations python manage.py migrate ``` Now, let's create serializers for books: **books/serializers.py** ```python from rest_framework import serializers from .models import Book class BookSerializer(serializers.ModelSerializer): class Meta: model = Book fields = ['id', 'title', 'author'] ``` Next, let's create API views for books: **books/views.py** ```python from rest_framework.response import Response from rest_framework.views import APIView from .models import Book from .serializers import BookSerializer class BookList(APIView): def get(self, request): books = Book.objects.all() serializer = BookSerializer(books, many=True) return Response(serializer.data) def post(self, request): serializer = BookSerializer(data=request.data) if serializer.is_valid(): serializer.save() return Response(serializer.data, status=201) return Response(serializer.errors, status=400) class BookDetail(APIView): def get(self, request, pk): try: book = Book.objects.get(pk=pk) except Book.DoesNotExist: return Response(status=404) serializer = BookSerializer(book) return Response(serializer.data) def put(self, request, pk): try: book = Book.objects.get(pk=pk) except Book.DoesNotExist: return Response(status=404) serializer = BookSerializer(book, data=request.data) if serializer.is_valid(): serializer.save() return Response(serializer.data) return Response(serializer.errors, status=400) def delete(self, request, pk): try: book = Book.objects.get(pk=pk) except Book.DoesNotExist: return Response(status=404) book.delete() return Response(status=204) ``` Next, let's create API routes for books: **bookstore/urls.py** ```python from django.urls import path, include from rest_framework import routers from books import views router = routers.DefaultRouter() urlpatterns = [ path('', include(router.urls)), path('books/', views.BookList.as_view()), path('books/<pk>/', views.BookDetail.as_view()), ] ``` Now, let's include the books API in the main URL configuration: **bookstore/bookstore/urls.py** ```python from django.urls import path, include urlpatterns = [ path('api/', include('bookstore.urls')), ] ``` **Interacting with the API** You can interact with the API using tools like curl or Postman. For example, to get all books, use: ```bash curl http://localhost:8000/api/books/ ``` To create a new book, use: ```bash curl -X POST -H "Content-Type: application/json" -d '{"title": "New Book", "author": "New Author"}' http://localhost:8000/api/books/ ``` To get a specific book, use: ```bash curl http://localhost:8000/api/books/1/ ``` To update a book, use: ```bash curl -X PUT -H "Content-Type: application/json" -d '{"title": "Updated Book", "author": "Updated Author"}' http://localhost:8000/api/books/1/ ``` To delete a book, use: ```bash curl -X DELETE http://localhost:8000/api/books/1/ ``` **Conclusion** In this lab topic, we learned how to create RESTful APIs using Flask and Django. We designed and implemented simple APIs that can store and retrieve books. We also learned how to interact with the APIs using tools like curl or Postman. **Lab Exercises** 1. Implement authentication and authorization in your Flask API using Flask-JWT-Extended. 2. Implement pagination in your Django API using Django REST framework's pagination features. 3. Use a database like MySQL or PostgreSQL instead of the default SQLite database in Django. **Getting Help** If you are having trouble with this lab topic, you can: * Post a question on an online forum like Reddit's r/learnpython or r/django * Ask for help in a Python or Django community on Discord or Slack * Consult the [Flask documentation](https://flask.palletsprojects.com/en/2.0.x/) or the [Django documentation](https://docs.djangoproject.com/en/4.1/)
Course
Python
Best Practices
Data Science
Web Development
Automation

Create a RESTful API with Flask and Django.

**Course Title:** Modern Python Programming: Best Practices and Trends **Section Title:** Web Development with Python **Topic:** Create a RESTful API with Flask/Django and interact with it using Python.(Lab topic) **Introduction** In this lab topic, we will build a RESTful API using Flask and Django, two popular Python web frameworks. We will learn how to design and implement a simple API, interact with it using Python, and understand the concepts of RESTful APIs. **RESTful API Basics** A RESTful API (Representational State of Resource) is an architectural style for designing networked applications. It is based on the idea of resources, which are identified by URIs, and can be manipulated using a fixed set of operations. Here are the basic principles of RESTful APIs: 1. **Resources**: Everything in REST is a resource. 2. **Client-Server Architecture**: The client and server are separate, with the client making requests to the server to access or modify resources. 3. **Stateless**: The server does not maintain any information about the client state. 4. **Cacheable**: Responses from the server are cacheable, which can reduce the number of requests made to the server. **Flask RESTful API** We will use Flask, a micro web framework written in Python, to build a simple RESTful API. First, let's install Flask using pip: ```bash pip install flask ``` Next, let's create a simple API that can store and retrieve books: **app.py** ```python from flask import Flask, jsonify, request app = Flask(__name__) # Sample data books = [ {"id": 1, "title": "Book 1", "author": "Author 1"}, {"id": 2, "title": "Book 2", "author": "Author 2"}, {"id": 3, "title": "Book 3", "author": "Author 3"} ] # GET /books @app.route('/books', methods=['GET']) def get_books(): return jsonify({"books": books}) # GET /books/:id @app.route('/books/:id', methods=['GET']) @app.route('/books/<int:id>', methods=['GET']) def get_book(id): book = [book for book in books if book['id'] == id] if book: return jsonify({"book": book}) else: return jsonify({"error": "Book not found"}), 404 # POST /books @app.route('/books', methods=['POST']) def create_book(): new_book = { 'id': len(books) + 1, 'title': request.json['title'], 'author': request.json['author'] } books.append(new_book) return jsonify({"book": new_book}), 201 # PUT /books/:id @app.route('/books/<int:id>', methods=['PUT']) def update_book(id): book = [book for book in books if book['id'] == id] if book: book[0]['title'] = request.json.get('title', book[0]['title']) book[0]['author'] = request.json.get('author', book[0]['author']) return jsonify({"book": book[0]}) else: return jsonify({"error": "Book not found"}), 404 # DELETE /books/:id @app.route('/books/<int:id>', methods=['DELETE']) def delete_book(id): book = [book for book in books if book['id'] == id] if book: books.remove(book[0]) return jsonify({"message": "Book deleted"}) else: return jsonify({"error": "Book not found"}), 404 if __name__ == '__main__': app.run() ``` Run the application using Python: ```bash python app.py ``` Now you can interact with the API using tools like curl or Postman. **Django RESTful API** Django is a high-level Python web framework that encourages rapid development and clean, pragmatic design. We will use Django to build a simple RESTful API. First, let's install Django: ```bash pip install django ``` Next, let's create a new Django project and a Django app: ```bash django-admin startproject bookstore cd bookstore python manage.py startapp books ``` Now, let's define a model for books: **books/models.py** ```python from django.db import models class Book(models.Model): title = models.CharField(max_length=100) author = models.CharField(max_length=100) ``` Next, let's create and apply migrations: ```bash python manage.py makemigrations python manage.py migrate ``` Now, let's create serializers for books: **books/serializers.py** ```python from rest_framework import serializers from .models import Book class BookSerializer(serializers.ModelSerializer): class Meta: model = Book fields = ['id', 'title', 'author'] ``` Next, let's create API views for books: **books/views.py** ```python from rest_framework.response import Response from rest_framework.views import APIView from .models import Book from .serializers import BookSerializer class BookList(APIView): def get(self, request): books = Book.objects.all() serializer = BookSerializer(books, many=True) return Response(serializer.data) def post(self, request): serializer = BookSerializer(data=request.data) if serializer.is_valid(): serializer.save() return Response(serializer.data, status=201) return Response(serializer.errors, status=400) class BookDetail(APIView): def get(self, request, pk): try: book = Book.objects.get(pk=pk) except Book.DoesNotExist: return Response(status=404) serializer = BookSerializer(book) return Response(serializer.data) def put(self, request, pk): try: book = Book.objects.get(pk=pk) except Book.DoesNotExist: return Response(status=404) serializer = BookSerializer(book, data=request.data) if serializer.is_valid(): serializer.save() return Response(serializer.data) return Response(serializer.errors, status=400) def delete(self, request, pk): try: book = Book.objects.get(pk=pk) except Book.DoesNotExist: return Response(status=404) book.delete() return Response(status=204) ``` Next, let's create API routes for books: **bookstore/urls.py** ```python from django.urls import path, include from rest_framework import routers from books import views router = routers.DefaultRouter() urlpatterns = [ path('', include(router.urls)), path('books/', views.BookList.as_view()), path('books/<pk>/', views.BookDetail.as_view()), ] ``` Now, let's include the books API in the main URL configuration: **bookstore/bookstore/urls.py** ```python from django.urls import path, include urlpatterns = [ path('api/', include('bookstore.urls')), ] ``` **Interacting with the API** You can interact with the API using tools like curl or Postman. For example, to get all books, use: ```bash curl http://localhost:8000/api/books/ ``` To create a new book, use: ```bash curl -X POST -H "Content-Type: application/json" -d '{"title": "New Book", "author": "New Author"}' http://localhost:8000/api/books/ ``` To get a specific book, use: ```bash curl http://localhost:8000/api/books/1/ ``` To update a book, use: ```bash curl -X PUT -H "Content-Type: application/json" -d '{"title": "Updated Book", "author": "Updated Author"}' http://localhost:8000/api/books/1/ ``` To delete a book, use: ```bash curl -X DELETE http://localhost:8000/api/books/1/ ``` **Conclusion** In this lab topic, we learned how to create RESTful APIs using Flask and Django. We designed and implemented simple APIs that can store and retrieve books. We also learned how to interact with the APIs using tools like curl or Postman. **Lab Exercises** 1. Implement authentication and authorization in your Flask API using Flask-JWT-Extended. 2. Implement pagination in your Django API using Django REST framework's pagination features. 3. Use a database like MySQL or PostgreSQL instead of the default SQLite database in Django. **Getting Help** If you are having trouble with this lab topic, you can: * Post a question on an online forum like Reddit's r/learnpython or r/django * Ask for help in a Python or Django community on Discord or Slack * Consult the [Flask documentation](https://flask.palletsprojects.com/en/2.0.x/) or the [Django documentation](https://docs.djangoproject.com/en/4.1/)

Images

Modern Python Programming: Best Practices and Trends

Course

Objectives

  • Gain a deep understanding of Python fundamentals and its modern ecosystem.
  • Learn best practices for writing clean, efficient, and scalable Python code.
  • Master popular Python libraries and frameworks for data science, web development, and automation.
  • Develop expertise in version control, testing, packaging, and deploying Python projects.

Introduction to Python and Environment Setup

  • Overview of Python: History, popularity, and use cases.
  • Setting up a Python development environment (Virtualenv, Pipenv, Conda).
  • Introduction to Python's package manager (pip) and virtual environments.
  • Exploring Python's basic syntax: Variables, data types, control structures.
  • Lab: Install Python, set up a virtual environment, and write your first Python script.

Data Structures and Basic Algorithms

  • Understanding Python’s built-in data types: Lists, tuples, dictionaries, sets.
  • Working with iterators and generators for efficient looping.
  • Comprehensions (list, dict, set comprehensions) for concise code.
  • Basic algorithms: Sorting, searching, and common patterns.
  • Lab: Implement data manipulation tasks using lists, dictionaries, and comprehensions.

Functions, Modules, and Best Practices

  • Defining and using functions: Arguments, return values, and scope.
  • Understanding Python’s module system and creating reusable code.
  • Using built-in modules and the Python Standard Library.
  • Best practices: DRY (Don’t Repeat Yourself), writing clean and readable code (PEP 8).
  • Lab: Write modular code by creating functions and organizing them into modules.

Object-Oriented Programming (OOP) in Python

  • Introduction to Object-Oriented Programming: Classes, objects, and methods.
  • Inheritance, polymorphism, encapsulation, and abstraction in Python.
  • Understanding magic methods (dunder methods) and operator overloading.
  • Design patterns in Python: Singleton, Factory, and others.
  • Lab: Implement a class-based system with inheritance and polymorphism.

File Handling and Working with External Data

  • Reading and writing files (text, CSV, JSON) with Python.
  • Introduction to Python’s `pathlib` and `os` modules for file manipulation.
  • Working with external data sources: APIs, web scraping (using `requests` and `BeautifulSoup`).
  • Error handling and exception management in file operations.
  • Lab: Build a script that processes data from files and external APIs.

Testing and Debugging Python Code

  • Importance of testing in modern software development.
  • Unit testing with Python’s `unittest` and `pytest` frameworks.
  • Mocking and patching external dependencies in tests.
  • Debugging techniques: Using `pdb` and logging for error tracking.
  • Lab: Write unit tests for a Python project using `pytest` and practice debugging techniques.

Functional Programming in Python

  • Understanding the functional programming paradigm in Python.
  • Using higher-order functions: `map()`, `filter()`, `reduce()`, and `lambda` functions.
  • Working with immutability and recursion.
  • Introduction to Python’s `functools` and `itertools` libraries for advanced functional techniques.
  • Lab: Solve real-world problems using functional programming principles.

Concurrency and Parallelism

  • Introduction to concurrent programming in Python.
  • Using threading and multiprocessing for parallel tasks.
  • Asynchronous programming with `asyncio` and coroutines.
  • Comparing synchronous vs asynchronous workflows: When to use each.
  • Lab: Build a program that handles multiple tasks concurrently using `asyncio` and threading.

Data Science and Visualization with Python

  • Introduction to NumPy for numerical computing.
  • Pandas for data manipulation and analysis.
  • Visualizing data with Matplotlib and Seaborn.
  • Exploratory data analysis (EDA) using real-world datasets.
  • Lab: Perform data analysis and visualization on a dataset using Pandas and Matplotlib.

Web Development with Python

  • Introduction to web development frameworks: Flask vs Django.
  • Building RESTful APIs with Flask/Django.
  • Connecting to databases using SQLAlchemy (Flask) or Django ORM.
  • Best practices for securing web applications.
  • Lab: Create a RESTful API with Flask/Django and interact with it using Python.

Automation and Scripting

  • Introduction to scripting for automation (shell scripts, cron jobs).
  • Automating repetitive tasks with Python.
  • Interacting with system processes using `subprocess` and `os` modules.
  • Working with Python for network automation and web scraping.
  • Lab: Write scripts to automate tasks like file handling, data extraction, and network operations.

Packaging, Version Control, and Deployment

  • Introduction to Python packaging: `setuptools` and `wheel`.
  • Creating and publishing Python packages (PyPI).
  • Version control with Git: Managing and collaborating on Python projects.
  • Deploying Python applications: Using Docker and cloud platforms.
  • Lab: Package a Python project and deploy it using Docker and Git.

More from Bot

Best Practices for Writing Reusable Functions in R
7 Months ago 61 views
Mastering NestJS: Building Scalable Server-Side Applications
2 Months ago 26 views
Working with Tables and Time Series Data in MATLAB.
7 Months ago 53 views
Higher-Order Functions in Haskell
7 Months ago 55 views
Animated Modern Login Interface Example
7 Months ago 54 views
Processing Data from Files and External APIs
7 Months ago 53 views
Spinn Code Team
About | Home
Contact: info@spinncode.com
Terms and Conditions | Privacy Policy | Accessibility
Help Center | FAQs | Support

© 2025 Spinn Company™. All rights reserved.
image