A directory without an __init__.py file becomes a namespace package, which behaves differently from a regular package and may cause slower imports. You can use __init__.py to explicitly define a package's public API by importing specific modules or functions into the package namespace.
Mocking in Python with unittest.mock allows you to simulate complex logic or unpredictable dependencies, such as responses from external services. The Mock class can imitate real objects, and the patch() function lets you temporarily substitute mocks for real objects in your tests.
This quiz sharpens your intuition for Python's asyncio module. You'll decide when async is the right tool, see how the event loop schedules work, and understand how coroutines pause and resume around I/O.
Episode Sponsor: Den is a member of the MCP Steering Committee and a Core Maintainer focusing on auth and security. He explains how MCP acts as a universal bridge, providing AI models with the real-time context they need. He shares insights on working with MCP Apps and moving beyond simple text to render web-based user interfaces directly in your chat window.
Writing clear, consistent docstrings in Python helps others understand your code's purpose, parameters, and outputs. In this video course, you'll learn about best practices, standard formats, and common pitfalls to avoid, ensuring your documentation is accessible to users and tools alike. By the end of this video course, you'll understand that:
In the previous lesson, you learned how to turn text into embeddings - compact, high-dimensional vectors that capture semantic meaning. By computing cosine similarity between these vectors, you could find which sentences or paragraphs were most alike. That worked beautifully for a small handcrafted corpus of 30-40 paragraphs. But what if your dataset grows to millions of documents or billions of image embeddings? Suddenly, your brute-force search breaks down - and that's where Approximate Nearest Neighbor (ANN) methods come to the rescue.
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Join us on March 4th 2026, for an unforgettable, non-stop event, streamed from our studio in Amsterdam. We'll be joined live by 15 well-known and beloved speakers from Python communities around the globe, including Carol Willing, Deb Nicholson, Sheena O'Connell, Paul Everitt, Marlene Mhangami, and Carlton Gibson. They'll be speaking about topics such as core Python, AI, community, web development and data science.
Prerequisites This guide is for all Python users who want to grow their Python knowledge, get involved with the Python community, or explore new professional opportunities. Your level of experience with Python doesn't matter, and neither does whether you use Python professionally or as a hobbyist-regularly or only from time to time. If you use Python, you're a Python developer, and Python conferences are for Python developers!
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Bob and I have spent many years as Python devs, and 6 years coaching with Pybites and we can safely say that being a Senior Developer is only about 1/3 Python knowledge. The other 60% is the ecosystem. It's the tooling. It's all of the tech around Python that makes you stand out from the rest. This is the biggest blind spot keeping developers stuck in Tutorial Hell. You spend hours memorising obscure library features, but you crumble when asked to configure a CI/CD pipeline.
Kacper Borucki blogged about parameterizing exception testing, and linked to pytest docs and a StackOverflow answer with similar approaches. The common way to test exceptions is to use pytest.raises as a context manager, and have separate tests for the cases that succeed and those that fail. Instead, this approach lets you unify them. I tweaked it to this, which I think reads nicely: One parameterized test that covers both good and bad outcomes. Nice.
The PSF is pleased to announce its fourth batch of PSF Fellows for 2025 ! Let us welcome the new PSF Fellows for Q4 ! The following people continue to do amazing things for the Python community: Chris Brousseau Dave Forgac Inessa Pawson Karen Dalton Tatiana Andrea Delgadillo Garzofino Thank you for your continued contributions. We have added you to our Fellows Roster .
Using AI to help download photos so we can consolidate all our images into one place. Over the years, [Audrey](https://audrey.feldroy.com) and I have accumulated photos across a variety of services. Flickr, SmugMug, and others all have chunks of our memories sitting on their servers. Some of these services we haven't touched in years, others we pay for but rarely use. It was time to bring everything home.
port-killer A powerful cross-platform port management tool for developers. Monitor ports, manage Kubernetes port forwards, integrate Cloudflare Tunnels, and kill processes with one click. Features: 🔍 Auto-discovers all listening TCP ports ⚡ One-click process termination (graceful + force kill) 🔄 Auto-refresh with configurable interval 🔎 Search and filter by port number or process name ⭐ Favorites for quick access to important ports 👁️ Watched ports with notifications 📂 Smart categorization (Web Server, Database, Development, System)
To learn how to query, visualize, and export live warehouse data from Streamlit, just keep reading. Now that we've prepared our helper modules and configured Snowflake credentials, it's time to bring everything together into one cohesive Streamlit app. The main driver script, lesson3_main.py, acts as the command center - defining layout, navigation, and page logic. It connects Streamlit's interactive UI to the Snowflake data warehouse and orchestrates how users query, explore, visualize, and export results.
We speak with course instructor Stephen Gruppetta about building a course where the participants start using their knowledge as soon as possible. He describes how he's evolved his teaching techniques over years of working with beginners. We explore the advantages of having a curated collection of written tutorials, video courses, and a forum for asking those nagging questions. We also speak with students Louis and Andrew about their experiences learning
Structural pattern matching excels at... matching the structure of your objects! For the two examples in this article, we'll be using a number of dataclasses that you can use to build abstract Boolean expressions: from dataclasses import dataclass class Expr: pass @dataclass class And(Expr): exprs: list[Expr] @dataclass class Or(Expr): exprs: list[Expr] @dataclass class Not(Expr): expr: Expr @dataclass class Var(Expr): name: str
If you want to learn Python or improve your skills, a detailed plan can help you gauge your current status and navigate toward a target goal. This tutorial will help you craft a personal Python learning roadmap so you can track your progress and stay accountable to your goals and timeline: The steps in this tutorial are useful for Python developers and learners of all experience levels. While you may
