Introduction to Python Environments
Understand interpreters, virtual environments, packages, and notebook kernels before choosing a workflow.
Setting Up Anaconda
Install Anaconda or Miniconda and create reproducible Conda environments for data-science work.
Using venv for Virtual Environments
Create, activate, verify, and recreate isolated Python environments with the standard-library venv module.
Creating and Managing Requirements Files
Declare pip installation inputs clearly and distinguish direct requirements from environment snapshots.
Understanding pip
Use pip through the selected Python interpreter to install and inspect distribution packages.
Best Practices for Using pip
Install Python packages predictably and safely with pip and isolated environments.
Introduction to Jupyter Notebooks
Install Jupyter Notebook in an isolated environment and work safely with cells, kernels, and reproducible execution.
Other Python IDEs and Environments
Compare editors, IDEs, and hosted notebooks without confusing them with Python environment managers.
Best Practices for Managing Python Environments
Keep Python environments isolated, reproducible, inspectable, and disposable.