Python Field Notes

Personal learning notes, examples, and exercises for Python.

This repository combines:

• notebook-based study materials
• practical code snippets for standard library and third-party packages
• selected assignments from the Coursera course "Diving in Python"
• small experiments and utilities

Quick Start

1. Install with uv

uv sync

This creates and manages a project environment from pyproject.toml.

Run tools with uv run:

uv run jupyter lab
# or
uv run jupyter notebook

2. Launch Jupyter

You can use either Jupyter Notebook or JupyterLab:

uv run jupyter notebook
# or
uv run jupyter lab

Repository Structure

• docs/: repository navigation and learning-path docs
• notes/tutorial/: core Python notes from basics to advanced topics (functions, classes, generators, regex, testing, performance, serialization, concurrency)
• notes/packages/: package-focused examples (numpy, matplotlib, sqlalchemy, logging, itertools, and more)
• notes/tips_and_tricks/: concise practical examples and experiments
• notes/frameworks/: framework-related notes (for example, Django notebook)
• exercises/coursera/: solutions and materials from Coursera Python courses
• exercises/books/python-workout/: chapter-based Python Workout exercises
• exercises/testing/learning-pytest/: chapter-based pytest learning project
• examples/async-and-io/learning-asyncio/: async programming and networking examples
• examples/databases/learning-sqlalchemy/: SQLAlchemy querying and ORM examples
• examples/assets/: supporting scripts, fixtures, and tests for smaller exercises
• examples/packagesample/: a minimal Python package layout example
• tooling/: development environment notes (virtual environments, VS Code, docs)

Using the Repository

Learning path suggestion

1. Start with notes/tutorial/00_intro.ipynb and follow files in order.
2. Explore notes/packages/ when you need targeted package examples.
3. Use notes/tips_and_tricks/ for quick practical patterns.
4. Check exercises/coursera/ for assignment-style practice.
5. Practice book-style tasks in exercises/books/python-workout/.
6. Practice testing-focused tasks in exercises/testing/learning-pytest/.
7. Explore async examples in examples/async-and-io/learning-asyncio/.
8. Explore SQLAlchemy examples in examples/databases/learning-sqlalchemy/.

Working in VS Code REPL

Open the command palette and run:

• Python: Start REPL

Then inspect built-in docs, for example:

>>> help(str)
>>> help(str.upper)

If you use uv, you can also start IPython with:

uv run ipython

References

The history of Python

• Guido van Rossum: The Early Years of Python
• Guido van Rossum: The Modern Era of Python
• Guido van Rossum: BDFL Python 3 retrospective

Selected PEPs

• PEP 257 -- Docstring Conventions
• PEP 440 -- Version Identification and Dependency Specification

License

Copyright (C) 2019-2026 Andrey Krisanov.

Licensed under the MIT License. See LICENSE for details.