Introduction to Python Environments
A comprehensive guide to Python environments and their importance for development and data science projects.
Setting Up Anaconda
Step-by-step instructions for installing Anaconda and managing environments and packages.
Using venv for Virtual Environments
An overview of the built-in venv module for creating and managing isolated Python environments.
Best Practices for Managing Python Environments
Guidelines for managing dependencies and handling environment conflicts in Python projects.
Understanding pip
An introduction to pip, the package installer for Python, and how to use it for managing packages.
Best Practices for Using pip
Guidelines and best practices for effectively using pip in Python projects.
Creating and Managing Requirements Files
A guide to creating and managing requirements files in Python projects for effective dependency management.
Introduction to Jupyter Notebooks
A comprehensive guide to installing, using, and leveraging Jupyter Notebooks for data science.
Other Python IDEs and Environments
An overview of popular IDEs and environments for Python programming, including PyCharm, Visual Studio Code, and Google Colab.