(All tags.)
importlib.metadata.version()Sometimes, it’s useful to branch the behaviour of your code based on the version of a package that you have installed. This may be to support an upgrade in your project, or for your own package to support different versions of a dependency.
BrokenPipeError when piping output to other commandsIf you’ve written a Python script that outputs a lot of data, then piped that output into another command that only reads part of it, you might have encountered a BrokenPipeError. For example, take this script:
A neat testing pattern is writing common tests in a base class and then applying them to multiple objects through subclassing. Doing so can help you test smarter and cover more code with less boilerplate.
Python comes with two built-in profilers for measuring the performance of your code: cProfile and profile. They have the same API, but cProfile is a C extension, while profile is implemented in Python. You nearly always want to use cProfile, as it’s faster and doesn’t skew measurements as much.
pre-commit is my favourite Git-integrated “run things on commit” tool. It acts as a kind of package manager, installing tools as necessary from their Git repositories. This makes it fairly easy to set up: all you need to install is pre-commit itself, and it takes things from there.
In Python, a mixin class is a class that is not intended to be used directly, but instead “mixed in” to other classes through multiple inheritance. Mixins are not really a language feature but more of a conventional pattern allowed by Python’s multiple inheritance rules. Unfortunately, adding type hints to mixin classes can be tricky because they implicitly require subclasses to fit a certain shape.
Some Python packages require native libraries to be installed on your system when you install them. For example, mysqlclient requires libssl and libcrypto. If those libraries are missing at install time, clang, the C compiler, fails with a message like:
unittest.mockA few days ago, I blogged about debugging unraisable exceptions with Rich. Here’s a sequel on testing that some block of code doesn’t trigger any unraisable exceptions.
Take this Python class:
sys.monitoringPython 3.12 introduced sys.monitoring, a new framework for “monitoring” tools like debuggers and profilers to hook into. It provides fine-grained control so tools can listen only to certain events on specific lines of code. The framework came from PEP 669, thanks to Mark Shannon of the Faster CPython team.
Sometimes, tests need temporary files or directories. You can do this in Python’s unittest with the standard library tempfile module. Let’s look at some recipes to do so within individual tests and setUp().
uv is a new, fast Python packaging tool. Since the August 20 update, uv can now manage both versions of Python and Python-powered tools.
tracemalloc is Python’s standard library module for tracking memory allocations. It has many bells and whistles for detailed analysis, allowing you to slice allocations by file and line or compare snapshots. But for simple purposes, displaying the total memory allocated is sufficient, which is what this recipe does:
1/0Here’s a code snippet I often type:
pkgutil.resolve_name()Django and other frameworks often allow you to configure classes, functions, or modules to import using strings. To do the same in your own code, use pkgutil.resolve_name() from the standard library (added in Python 3.9):
Sometimes, you want to test a function that uses an inner import and mock that imported object. For example, say you wanted to mock dig() in this example:
class.__subclasses__() returns a list of the direct subclasses of a given class:
Copy-paste-tweaking library code feels like a dirty but inevitable programming practice. Often driven by deadlines or other constraints, it seems all projects end up with something copy-pasted in and tweaked for one specific use case.
inspectMany terminals and text editors support what I’ll call “line number paths” of the form <filename>:<lineno>. Opening that path, whether by clicking or passing to a CLI, opens the given file at that line.
Earlier this week, I made another podcast appearance on The Python Show, episode 22: Git and Django with Adam Johnson. As fellow authors, Mike and I talked a lot about the writing process, on topics like:
Last week, I made another podcast appearance on the PyBites Podcast, episode 139: Maximizing Your Developer Experience (DX) with Adam Johnson. We talked about various topics, including:
I had the pleasure of returning to The Real Python podcast in last week’s episode 179, Improving Your Git Developer Experience in Python. It was great to catch up with host Christopher Bailey and chat about:
Most projects I work on use Python, good ol’ Pip, and pip-tools. Below is a pattern I’ve used to speed up the GitHub Actions workflow runs on several such projects. On larger projects with many dependencies, it can save tens of seconds per run.
The Python standard library’s logging module is a go-to for adding observability to applications. Many tools also integrated with it or enhance its capabilities, such as structlog and Sentry.
When trying to improve a slow function or module, it’s always a good idea to profile it. Here’s a snippet for quickly profiling a section of code with Python’s cProfile module, in two flavours. It’s adapted from the cProfile documentation’s Profile example. I have used versions of this snippet over the years to narrow in on performance issues.