Extending Python

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Extending Python

Python provides the programming syntax and core features. Libraries and frameworks add specialized functionality. Depending on the libraries you import, the same Python code can be used to:

• Build frontend applications (user interfaces)
• Develop backend web APIs and servers
• Perform data analysis and visualization
• Build AI/ML models
• Create Generative AI applications such as chatbots, RAG systems, and AI assistants.

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What are packages really?

Packages are just Python files containing code - typically combinations of functions (which you’ve learned) and classes (coming later). When you import a package, you’re bringing that functionality into your project. Two types of packages:

• Built-in: Come with Python installation (already in your environment)
• External: Downloaded from the internet into your virtual environment folder

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Python’s ecosystem

Python has packages for everything:

• Build frontend applications (user interfaces) (e.g., streamlit, gradio)
• Develop backend web APIs and servers (e.g., fastapi, flask, django)
• Perform data analysis and visualization (e.g., pandas, matplotlib, seaborn)
• Build AI/ML models (e.g., scikit-learn, pytorch, tensorflow)
• Create Generative AI applications such as chatbots, RAG systems, and AI assistants (e.g., openai, langchain)

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What you’ll learn

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Package examples

Here are packages you’ll likely use:

• requests - Make web requests
• pandas - Work with data tables
• scikit-learn - Build machine learning models
• openai - Use AI models
• python-dotenv - Manage secrets

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Let’s begin!

Start by learning how to work with Python’s built-in standard library modules.