Python Basics

This repository is a notebook-based learning path for building a solid foundation in Python. The notebooks begin with the VS Code Jupyter Notebook workflow and readable code conventions, then progress through variables, strings, control flow, data structures, comprehensions, and reusable functions.

Follow the notebooks in numerical order. Each notebook is self-contained, but the concepts build from basic expressions to a final functions challenge.

Learning Objectives

By the end of this repository, you should be able to:

• Work productively with Jupyter notebooks in VS Code.
• Write readable Python code using clear naming and formatting conventions.
• Use variables, numeric operators, strings, conditional statements, and loops.
• Choose and manipulate lists, tuples, dictionaries, and sets.
• Build concise collection transformations with comprehensions.
• Define, call, test, and explain reusable Python functions.

Learning Path

The modules build on each other in order.

1 - Getting Started

VS Code notebooks and readable-code conventions.

File	Description
1 - Intro To Jupyter Notebook	Open notebooks in VS Code, select a kernel, execute cells, work with Markdown, and use notebook tooling
2 - Coding Best Practices	Apply readable naming, whitespace, and formatting practices based on PEP 8

2 - Python Basics

Variables, strings, conditions, and loops.

File	Description
1 - Numeric Variable Types	Work with variables, numeric data types, operators, and type conversion
2 - Strings	Create, combine, index, slice, format, and iterate through text values
3 - If Statements	Express conditional logic with if, elif, else, and boolean operators
4 - Loops	Repeat operations with while and for loops and control execution with continue and break

3 - Data Structures

Collections, mutability, and concise transformations.

File	Description
1 - Lists	Store, modify, index, slice, and iterate through ordered collections
2 - Tuples	Understand immutable sequences and compare them with mutable lists
3 - Dictionaries	Map keys to values, update dictionaries, and loop through keys, values, and items
4 - Sets	Store unique values and use set operations for membership and comparison
5 - Comprehension	Build lists, dictionaries, and tuples concisely from iterables

4 - Functions And Challenge

Reusable code, arguments, and final practice.

File	Description
1 - Introduction To Functions	Understand why functions are useful and define simple reusable operations
2 - Function Definitions	Work with parameters, annotations, defaults, and multiple arguments
3 - Calling Functions	Use positional and keyword arguments correctly
4 - Challenge	Apply the unit's concepts in progressive practice tasks

Additional Folders and Files

File / Folder	Description
Solution	Complete solution versions of the notebooks with worked code and explanations
Assets	Local screenshots used in the VS Code Jupyter notebook introduction
pyproject.toml	Project configuration and dependency declarations
uv.lock	Reproducible dependency lock file

Setup

Note

Throughout these steps, text in angle brackets like <repo-name> is a placeholder. Replace it including the < > brackets with your own value. For example, cd <repo-name> becomes cd my-python-basics-project.

1. Create the Repository from the Template

Click Use this template on GitHub.

When creating the repository:

• Set yourself as the Owner
• Choose a repository name
• Disable Include all branches
• Click Create repository

Important

If you are working in pairs or groups, only one person should complete this step.

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2. Add Collaborators (Pairs/Groups Only)

If you are working with teammates:

1. Open the repository on GitHub
2. Go to Settings → Collaborators
3. Add your teammates as collaborators
4. Share the repository link with your team

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3. Clone the Repository

Copy the SSH URL from the Code button on GitHub, then run:

git clone <copied-ssh-url>

The copied SSH URL will look like: git@github.com:<your-username>/<repo-name>.git.

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4. Move into the Project Folder and Install Dependencies

This installs all dependencies and creates a virtual environment in .venv/.

cd <repo-name>
uv sync

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5. Open the Notebooks

Note

Open VS Code from the project root so it detects the environment created by uv sync.

Launch VS Code in the project root:

code .

Then open a notebook and select the Python environment created by uv sync as the kernel.

References & Further Reading

• The Python Tutorial: Official Python introduction covering syntax, data structures, control flow, and functions.
• Built-in Functions: Official reference for functions such as len, range, type, print, input, zip, and sorted.
• Jupyter Notebooks in VS Code: Official VS Code guide for notebook editing, kernels, variables, and cell execution.
• PEP 8 - Style Guide for Python Code: Widely used conventions for readable Python code.
• uv Documentation: Official documentation for dependency management and reproducible Python environments.