Python Virtual Environments and Pip

Overview

• Python virtual environments and pip are tools to manage dependencies and package installations.
• Pip is a package manager for Python to install and manage software packages.
• Virtual environments allow for the creation of isolated environments for Python projects.

Pip

• Pip is included with Python installations.
• Installation: pip install <package_name> installs packages globally.
• Version Specific Installation: pip install <package_name>==<version> installs a specific version.
• Update Packages: pip install --upgrade <package_name> updates packages.
• Uninstall Packages: pip uninstall <package_name> removes packages.
• List Installed Packages: pip list shows all globally installed packages.
• Pip Freeze: pip freeze > requirements.txt lists all packages and versions into a requirements file.

Virtual Environments

• Virtual environments are isolated spaces to manage project dependencies without affecting the global Python environment.
• Create a Virtual Environment: python -m venv <environment_name> creates a new virtual environment.
• Activate a Virtual Environment:
  • Windows: source <environment_name>\Scripts\activate
  • Mac/Linux: source <environment_name>/bin/activate
• Deactivate a Virtual Environment: deactivate exits the virtual environment.
• Advantages:
  • Keep project dependencies contained.
  • Avoid conflicts between project requirements.
• Using Pip in a Virtual Environment: Once activated, pip commands apply only to the virtual environment.

Creating a Small Project

• Setup:
  • Initialize a virtual environment.
  • Activate the virtual environment.
  • Use pip to install necessary packages (requests, python-dotenv).
  • Use pip freeze to generate a requirements.txt file.

OpenWeatherMap API

• Used to retrieve current weather data for cities.
• Requires signing up for an API key on openweathermap.org.
• Store the API key in a .env file to manage secrets.

Implementation in Python

• Requests Library: Used to send HTTP requests to external services.
• Python-dotenv Library: Loads environment variables from a .env file.
• Handling API Calls:
  • Construct request URLs with API key and city query.
  • Manage units (e.g., Imperial, Metric) through API parameters.

Project Structure

• Use virtual environments to manage dependencies.
• Use .gitignore to exclude venv and .env from version control.
• Store API keys and secrets outside the codebase to keep them secure.

Conclusion

• Understanding pip and virtual environments is crucial for managing project dependencies and avoiding conflicts.
• Using APIs like OpenWeatherMap allows for dynamic data retrieval and enhances project functionality.
• Proper handling of sensitive data and dependencies is essential for robust and maintainable projects.