Here’s a write-up of an optimization I made in my client Silvr’s project. I ended up disabling a PostgreSQL feature called the JIT (Just-In-Time) compiler which was taking a long time for little benefit.
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 clipboard is an easy way to transfer data from the command line to other tools. Use your system’s “copy to clipboard” command to store a command’s output for pasting into other applications.
You worked on a sizeable feature branch some time ago but left it to focus on other things. Now you’re ready to pick it up, so you want to rebase it onto your updated main branch. But when you try that, you’re presented with an overwhelming number of merge conflicts.
I released Boost Your Git DX nearly two weeks ago. It’s the second in my “Boost Your DX” series, following last year’s Boost Your Django DX. Both books aim to improve your development experience with their respective tool.
I’ve once more had the pleasure of joining Carlton and Will on the Django Chat podcast, in Episode #146. We spoke on Tuesday, just hours after Django 5.0 alpha 1 was released, on several topics:
Git only tracks files, not directories. It will only create a directory if it contains a tracked file. But sometimes you need to “track” a directory, to ensure it exists for fresh clones of a repository. For example, you might need an output directory called build.
Django’s template engine has an underappreciated builtins option that selects libraries to preload in every template. Making a library a builtin avoids the need for an explicit {% load %} tag whenever you use its tags or filters. Putting key libraries in builtins can shorten your templates and make development a little bit faster.
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.
Every object you commit in Git is copied into its object store, within the .git directory. If you undo a commit, the commit object and associated file objects remain in Git’s object store, at least for a while. The normal garbage collection process will clean them out, by default in 30 days.
Docker keeps all objects (images, containers, volumes, etc.), with no automatic cleanup. It thus consumes disk space without bound, which can eventually fill up your development machine.
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.
When you create a function to match an interface, it often needs to accept parameters that it doesn’t use. Once you introduce type hints, testing such functions can become a little irksome as Mypy will require all arguments to have the correct types. Your tests can end up creating unused objects only to match the tested function’s signature. Here’s a technique to avoid that work.
As projects evolve, old functionality gets removed. Often such deletions are incomplete, leaving in their wake unused functions, classes, and other code objects. Unused code is clutter that brings no joy: it hinders comprehension, taxes codebase-wide quality improvements, and can sometimes lead to errors if later used.
Sometimes code depends on the order of a QuerySet whilst not specifying an order. This can lead to random, flaky test failures because databases can return rows in any order when none is specified. The problem is made worse by some databases, notably PostgreSQL, which nearly always return rows in insert order, but occasionally use a different order when a table has had recent deletions.
Mypy 1.4.0 was released last week (2023-06-20). I’m happy to see it includes three improvements that modernize error messages with newer type hint syntax: