Python
Virtual environments are isolated Python environments that allow you to install packages for specific projects without affecting your system-wide Python installation. Why Use Virtual Environments? * Dependency Isolation: Different projects can use different versions of the same package * Clean Development: Avoid polluting your global Python installation * Reproducibility: Easily share project dependencies
Python
Core Philosophy * Flask: Microframework (minimal core, extensible) * Django: "Batteries-included" full-stack framework Quick Comparison Table Feature Flask Django Template Engine Jinja2 (default) Built-in ORM Extension Built-in Admin Interface None by default Built-in Authentication Extension Built-in Project Structure Flexible Strict MVC Learning Curve Gentle Steeper Default Database None SQLite REST
Python
Modern Python web framework for building APIs with Python 3.7+ that focuses on: * High performance (ASGI support) * Automatic API documentation * Type validation via Python type hints Key Features 1. ASGI Standard - Native async/await support 2. Automatic Docs - Interactive Swagger UI & ReDoc 3. Data Validation -
Python
1. Purpose * Lists all package dependencies for a Python project * Allows easy installation of required packages using pip * Ensures consistent environments across different setups 2. Basic Usage # Generate from currently installed packages (best used in virtualenv) pip freeze > requirements.txt # Install packages from file pip install -r requirements.txt
Python
Short Answer: No, but it depends on: * Python version being used * Package structure requirements * Specific functionality needed Detailed Breakdown: 1. Python Version Considerations * Python < 3.3: Required in every directory to be recognized as a package * Python 3.3+: Not strictly required (namespace packages) but still commonly used 2.
Python
1. What is Web Scraping? * Automated extraction of data from websites * Converts unstructured web data into structured format * Common use cases: Price monitoring, market research, lead generation 2. Core Components 2.1 HTTP Requests * Libraries: * requests (simple HTTP requests) * urllib (built-in library) * Example: import requests response = requests.get('https:
Python
* A special Python file used to mark directories as Python package directories * Required in Python versions prior to 3.3 to make a directory recognized as a package * Can be empty or contain initialization code for the package * Key file in Python's package structure and import system Key
Python
The __pycache__ directory is automatically created by Python to store compiled bytecode files (.pyc files) when you import modules. Here's what you need to know: 1. Purpose: * Speeds up subsequent imports of the same module * Contains pre-compiled bytecode (optimized intermediate format) instead of re-parsing source code every time