Python Fundamentals for LangChain

Welcome! This repository contains Jupyter notebooks covering the essential Python fundamentals you need to start working with LangChain.

🎯 Purpose

Before diving into LangChain, you need to understand the Python basics that will actually be used in AI development. You don't need to master everything in Python - just the concepts and tools you'll encounter when building LangChain applications.

This course is designed to be:

• Focused: Only what you need for LangChain
• Practical: Real concepts you'll use daily
• Quick: Won't take much of your time
• Foundation: A solid base for AI development with LangChain

Why This Matters

LangChain is a powerful Python framework for building AI applications. To use it effectively, you need to understand:

• Basic Python syntax
• Data structures (lists, dictionaries, sets)
• Control flow (loops, conditionals)
• Functions and decorators
• Object-oriented programming basics
• Modules and imports
• Context managers
• Environment variables
• Type hints

💡 Pro Tip: Use ChatGPT, Claude, or your favorite AI model to expand on any topic covered in the notebooks. These assistants are excellent for clarifying concepts and providing additional examples!

📚 Course Content

The notebooks are structured progressively to build your knowledge step by step:

1. 01_syntax_basics.ipynb - Python syntax fundamentals
2. 02_data_structures_core.ipynb - Lists, dictionaries, tuples, and sets
3. 03_control_flow.ipynb - Conditionals, loops, and flow control
4. 04_functions_and_decorators.ipynb - Function definitions and decorators
5. 05_classes_objects_oop_light.ipynb - Object-oriented programming essentials
6. 06_modules_imports_debugging.ipynb - Working with modules and debugging
7. 07_context_managers.ipynb - Understanding context managers (with statements)
8. 08_env_and_secrets.ipynb - Environment variables and secrets management
9. 09_typing_pydantic_vs_typedict.ipynb - Type hints and validation

🚀 Setup

Prerequisites

You'll need two tools to work with these notebooks:

1. UV - Modern Python Package Manager

What is UV? UV is a fast, modern package and project manager for Python. It's significantly faster than pip and handles virtual environments seamlessly.

Installation:

# On macOS and Linux:
curl -LsSf https://astral.sh/uv/install.sh | sh

# On Windows:
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

2. JupyterLab - Interactive Development Environment

What is JupyterLab? JupyterLab is a web-based interactive development environment for notebooks, code, and data. It allows you to write and execute code in an interactive way, perfect for learning and experimentation.

📖 How to Use This Repository

1. Clone the repository:

   git clone <repository-url>
   cd 01-python-fundamentals

2. Install dependencies:

   uv sync

3. Launch JupyterLab:

   uv run jupyter

4. Work through the notebooks in order (01 through 09)

5. Experiment! Modify the code, try new examples, and use AI assistants to deepen your understanding

🎓 Learning Tips

• Don't rush: Take your time with each concept
• Practice: Modify the examples and create your own
• Ask questions: Use ChatGPT/Claude to clarify any doubts
• Focus on understanding: You don't need to memorize everything
• Keep it practical: Think about how each concept applies to LangChain

🔗 What's Next?

After completing these fundamentals, you'll be ready to dive into LangChain development! You'll have the Python knowledge needed to:

• Build AI-powered applications
• Understand LangChain's architecture
• Work with language models
• Create custom chains and agents
• Manage prompts and memory

🔗 Next Repository → LangChain Beginners

Once you finish these fundamentals, continue with the next step in your learning path:

👉 02-langchain-beginners

That repository will guide you through: • LangChain Expression Language (LCEL) • Prompt templates and chain composition • RAG (Retrieval-Augmented Generation) fundamentals • Vector stores (Chroma / FAISS) • LangGraph memory and modern AI app structure

🧠 You’ll move from learning Python for AI to building actual LLM applications.

📝 License

See the LICENSE file for details.

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Ready to start your LangChain journey? Begin with notebook 01! 🐍✨