Getting Started

Python is a high-level, interpreted programming language that has become the dominant language for data engineering. Known for its clear syntax, extensive standard library, and rich ecosystem of data-focused packages. Essential foundation for all Python data engineering work.

Powerful, free code editor with excellent Python support through extensions. Features IntelliSense, debugging, Git integration, and a vast marketplace of extensions. The most popular IDE for Python data engineering with powerful features for managing virtual environments and running code.

The standard package installer for Python. Used to install and manage Python packages from the Python Package Index (PyPI) and other repositories. Essential tool for managing dependencies in any Python project, comes bundled with Python installations.

Tools for creating isolated Python environments, allowing you to manage project-specific dependencies without conflicts. venv comes built into Python 3, while virtualenv offers additional features. Critical for professional Python development and maintaining clean, reproducible environments.

Industry-standard platform for developing, shipping, and running applications in containers. Essential for data engineering to run databases, Kafka, and other services in isolated, reproducible environments. Docker Desktop provides an easy-to-use interface for managing containers across all operating systems.

Tool for defining and running multi-container Docker applications using YAML configuration files. Perfect for data engineering workflows that require multiple services like databases, message queues, and processing engines running together. Simplifies complex container setups into simple, version-controlled configurations.