Dive into Python, clean code practices, and real-world development tips.
By Jeferson Peter • Apr 14, 2026 — Python
Concurrency and parallelism are often confused, but they solve different problems. Understanding the distinction helps you choose the right model in Python: async, threads, or processes.
By Jeferson Peter • Apr 7, 2026 — Python
Many Python projects start with files in the root directory. The `src/` layout may feel unnecessary at first, but it prevents subtle import bugs and prepares your project for packaging and testing.
By Jeferson Peter • Mar 31, 2026 — Python
Handling errors well is about more than catching exceptions. These patterns help keep your Python code robust, readable, and easier to debug in real-world systems.
By Jeferson Peter • Mar 24, 2026 — Python
Python’s built-in `logging` module is powerful but often verbose. `Loguru` simplifies configuration while providing structured, production-ready logging with minimal setup.
By Jeferson Peter • Mar 17, 2026 — Python
Python’s `pathlib` introduces a cleaner, object-oriented approach to file system paths. Compared to `os.path`, it improves readability, safety, and cross-platform consistency.
By Jeferson Peter • Mar 10, 2026 — Python
Context managers simplify setup and cleanup logic in Python. With `contextlib`, you can create your own reusable context managers for performance tracking, resource handling, and more.
By Jeferson Peter • Mar 3, 2026 — Python
Generators let you handle large data streams with minimal memory usage. The `yield` keyword transforms ordinary functions into lazy iterators that produce values on demand.
By Jeferson Peter • Feb 24, 2026 — Python
Introduced in Python 3.8, the walrus operator (`:=`) allows assignment inside expressions. Used carefully, it reduces duplication and keeps related logic together without harming readability.
By Jeferson Peter • Feb 17, 2026 — Python
Comparing `venv` and `uv` for managing Python virtual environments. Learn the differences, trade-offs, and when to choose each tool for your workflow.
By Jeferson Peter • Dec 18, 2025 — Polars & Pandas
A personal look at the moment my data workflows outgrew Pandas — and how moving to Polars made my pipelines faster, clearer, and more predictable.
