#dunder-methods

#dunder-methods

subprocess module relies on busy-loop polling to determine whether a process has completed yet. Modern operating systems have callback mechanisms to do this, and Python 3.15 will now take advantage of these.

Ever since writing about them, the generator in JavaScript has become my favorite hammer. I'll wield it nearly any chance I can get it. Usually, that looks like rolling through a finite batch of items over time. For example, doing something with a bunch of leap years: ...or lazily processing some files: In both examples, the pool of items is exhausted once and never replenished. The for loop stops, and the final item returned by the iterator contains done: true. C'est fini.

Readable failures. When something breaks, I want to understand why in seconds, not minutes. Predictable setup. I want to know exactly what state my tests are running against. Minimal magic. The less indirection between my test code and what's actually happening, the better. Easy onboarding. New team members should be able to write tests on day one without learning a new paradigm.

LBYL came more naturally to me in my early years of programming. It seemed to have fewer obstacles in those early stages, fewer tricky concepts. And in my 10+ years of teaching Python, I also preferred teaching LBYL to beginners and delaying EAFP until later. But over the years, as I came to understand Python's psyche better, I gradually shifted my programming style-and then, my teaching style, too.

For a long time I wanted to document something I have done many times in production systems but never explained clearly: using Django ORM as a standalone module to connect to an existing database. In my work I have often dealt with legacy systems where the only reliable source of truth was the database itself. In those situations, Django ORM became my Swiss army knife.

By working through this quiz, you'll revisit the descriptor protocol, how .__get__() and .__set__() control attribute access, and how to implement read only descriptors. You'll also explore data vs. non-data descriptors, attribute lookup order, and the .__set_name__() method.

We also patched two potential denial-of-service vulnerabilities when handling large, malformed inputs. One exploits inefficient string concatenation in header parsing under ASGI ( CVE 2025-14550). Concatenating strings in a loop is known to be slow, and we've done fixes in public where the impact is low. The other one ( CVE 2026-1285) exploits deeply nested entities. December's vulnerability in the XML serializer ( CVE 2025-64460) was about those very two themes.

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.

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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.

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.