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Getting Started

How to use this repository, set up your environment, and run examples.

Prerequisites

  • Python 3.10+ (for match/case and modern type syntax)
  • pip (comes with Python)
  • git

Check your version: 

python3 --version  # Should be 3.10+
pip --version

Setup

1. Clone the repository

git clone https://github.com/GauravAgarwalGarg/GiggleWithPython.git
cd GiggleWithPython

2. Create a virtual environment

# Quick setup (automated)
bash scripts/setup_venv.sh

# Or manually:
python3 -m venv .venv
source .venv/bin/activate  # Linux/Mac
# .venv\Scripts\activate   # Windows
pip install --upgrade pip

3. Install dependencies

Each section has its own requirements.txt:

# Fundamentals no deps needed (stdlib only)

# Data analytics
pip install -r data-analytics/requirements.txt

# Frameworks (pick one)
pip install -r frameworks/flask/requirements.txt
pip install -r frameworks/fastapi/requirements.txt

# Automation
pip install -r automation/requirements.txt

# Testing
pip install -r testing/requirements.txt

Running Examples

Every Python file has a if __name__ == "__main__": block with runnable demos:

# Run any file directly
python fundamentals/data_types.py
python fundamentals/functions.py
python snippets/regex_patterns.py
python data-analytics/numpy_basics.py

# Run Flask app
python frameworks/flask/app.py
# Visit http://localhost:5000

# Run FastAPI app
python frameworks/fastapi/main.py
# Visit http://localhost:8000/docs

# Run tests
pytest testing/ -v

Project Structure

GiggleWithPython/
├── fundamentals/      # Python language fundamentals (stdlib only)
├── frameworks/        # Web frameworks (Django, Flask, FastAPI)
├── data-analytics/    # Data science (Pandas, NumPy, Matplotlib, SciPy)
├── snippets/          # Reusable utility code
├── automation/        # DevOps helpers (Docker, AWS, SSH)
├── testing/           # Pytest patterns and examples
├── scripts/           # Shell scripts and one-liners
└── docs/              # Documentation

Development Tools

Linting and Formatting

# Run all checks
bash scripts/lint.sh

# Or individually:
ruff check .               # Lint
ruff format .              # Format (replaces black)
mypy fundamentals/ --ignore-missing-imports  # Type check
  • Python (Microsoft)
  • Pylance (type checking)
  • Ruff (linting + formatting)
  • Python Test Explorer
{
    "python.defaultInterpreterPath": ".venv/bin/python",
    "python.testing.pytestEnabled": true,
    "editor.formatOnSave": true,
    "[python]": {
        "editor.defaultFormatter": "charliermarsh.ruff"
    }
}

Tips

  1. Start with fundamentals/ if you're learning Python, work through these files in order
  2. Copy snippets the snippets/ directory is designed to be copy-pasted into your projects
  3. Run everything every file is designed to produce output when run directly
  4. Read the docstrings each function explains WHY, not just WHAT
  5. Use the type hints run mypy to catch bugs before runtime