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Development Tools

Skill Level: All Levels

Overview​

Throughout this guide, you'll primarily use Google Colab because it requires no installation and runs directly in your browser.

There are also other tools commonly used by developers and data scientists. Knowing what each does and when to use it will help you choose the right environment as you progress.

Google Colab​

Google Colab is a cloud-based environment for writing and running Python code.

Advantages​

  • No installation required
  • Free to use
  • Accessible from any device
  • Includes many popular Python libraries
  • Easy to share notebooks

Best For​

  • Learning Python
  • Data analysis and visualization
  • Classroom assignments
  • Collaboration

Jupyter Notebook​

Jupyter Notebook lets you combine code, text, images, and visualizations in a single interactive document. Many researchers and educators use it for reproducible analysis.

Best For​

  • Exploratory analysis
  • Reports and narrative notebooks
  • Teaching and demonstrations
  • Documentation with code and results together

Visual Studio Code (VS Code)​

VS Code is a lightweight, highly customizable code editor developed by Microsoft.

Advantages​

  • Excellent Python support
  • Built-in Git integration
  • Extensions for many languages and tools
  • Integrated terminal
  • Jupyter Notebook support

Best For​

  • Software development
  • Larger Python projects
  • Working with multiple files and folders
  • Professional development workflows

Anaconda​

Anaconda is a Python distribution designed for data science.

It bundles Python with many commonly used libraries, such as:

  • Pandas
  • NumPy
  • Matplotlib
  • Seaborn
  • Jupyter Notebook

Advantages​

  • Simplifies package and environment management
  • Includes many data science tools out of the box
  • Ideal for local development on your own machine

Best For​

  • Data science and machine learning
  • Scientific computing
  • Building local analysis environments

Which Tool Should You Use?​

  • Google Colab: Beginners, coursework, and quick experiments
  • Jupyter Notebook: Interactive analysis and reporting
  • VS Code: Software development and larger projects
  • Anaconda: Local data science environments

Our Recommendation​

For this guide, use Google Colab for all coding exercises.

As you become more comfortable with Python, consider using Jupyter Notebook or VS Code (often installed via Anaconda) for larger local projects, while still keeping Colab for quick experiments and classwork.