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Introduction to Python

Python IDEs and Editors

PyCharm, VS Code, Jupyter Notebooks

Interview: Development tools knowledge

Last Updated: June 12, 2026 • 6 min read

Choosing the right IDE or editor significantly impacts your Python development productivity. Each tool has different strengths depending on your use case — web development, data science, scripting, or large-scale application development.

VS Code

The most popular editor for Python development. Lightweight, extensible, and free.

  • Essential extensions: Python (Microsoft), Pylance, Python Debugger, Ruff (linter)
  • Features: IntelliSense, debugging, Jupyter support, Git integration, remote development
  • Best for: Web development, scripting, general-purpose Python programming
  • Settings: Configure python.defaultInterpreterPath to point to your virtual environment

PyCharm

Full-featured IDE by JetBrains. Available in free Community Edition and paid Professional Edition.

  • Community Edition: Core Python development, debugging, version control
  • Professional: Web frameworks (Django, Flask, FastAPI), database tools, Docker, remote development
  • Strengths: Superior refactoring, deep code analysis, integrated database tools, test runners
  • Best for: Large-scale Python projects, enterprise development

Jupyter Notebooks

Interactive, cell-based environment. The standard tool for data science, machine learning, and exploratory analysis.

  • Features: Cell-by-cell execution, inline plots, markdown documentation, rich output
  • JupyterLab: Next-generation interface with tabs, file browser, and terminal
  • Google Colab: Free cloud-based Jupyter with GPU access — great for ML projects
  • Best for: Data science, machine learning, teaching, prototyping

Other Notable Tools

  • Sublime Text: Fast, lightweight, good for quick edits with Python packages
  • Vim/Neovim: Terminal-based, highly customizable with plugins like coc.nvim and LSP
  • Spyder: Scientific IDE designed for data analysis with variable explorer and IPython console
  • Thonny: Beginner-friendly IDE with built-in debugger and step-through visualization

Recommended Setup

For most Python developers: VS Code with the Python + Pylance + Ruff extensions for daily coding, and Jupyter (or Google Colab) for data exploration. Use PyCharm Professional if you work on large Django/FastAPI projects and need integrated database tools.

Use Cases

Web development with Django/Flask/FastAPI using VS Code or PyCharm

Data science and machine learning with Jupyter Notebooks

Quick scripting and automation with any editor

Large-scale enterprise Python application development

Common Mistakes

Not configuring the Python interpreter path to point to your virtual environment

Using Jupyter for production code without converting to proper .py modules

Not setting up linting (Ruff/flake8) and formatting (Ruff/black) in your editor

Ignoring IDE debugging tools and relying only on print statements