If we dive into Python scripting or need to share a small utility with a colleague, we quickly run into a familiar problem: Incompatible or missing package versions. We can solve that problem with virtual environments, but that brings us right to the next one. Managing multiple environments for small, standalone scripts is tedious and breaks the workflow.
One of the new features in Python 3.14 is the support for version 7 of UUID. This means we can get a built-in support for collision free and sortable unique identifiers without the need for additional packages. Let us see how we can use them.
As I introduced project management with uv in this blog, we skipped the code part of creating our own packages. Let us end the year with closing this gap and see what it takes to make a package for PyPI.org
When we work on larger Python projects, inconsistent formatting and lingering lint errors can break our flow. We may use tools like Black, isort, and Flake8 to keep code clean, but running each in sequence feels slow and an extra burden that we soon will skip. Luckily for us, there is a tool named Ruff by the same team that wrote uv. Let us see how Ruff can help us to get more consistent Python code.
Sometimes all you want to do is a quick update of a Python package and you run into a learning opportunity. I had this experience many times, and while that is frustrating at the time, it usually ends up with me better understanding the tools I use. Let us take a failed update of MkDocs as an example on what to do if we run into an error after updating a package.
The more I use uv, the more I like the great experience this little tool offers. In this post we explore five helpful tricks I learned as I run into some issues along the way.
Last week we explored the uv tool and saw how much of pip we can reuse while profiting from the massive speed boost. In this post we explore the final part of uv and see how it can help us to manage our projects and prepare our package for pypi.org.
If we dive into machine learning, we quickly run into a problem: Incompatible package versions. We can solve that problem with virtual environments, but that brings us right to the next one. Pip is a great tool, but when we need to install the same package multiple times, pip will download the package again and again. That is slow and breaks the flow. Let us explore an alternative solution.
If you try out a Python package in the REPL, the output of print() may not be the most useful one. In Ruby I used for this case the class PrettyPrint and as it turns out, Python has a similar built-in feature. Let's have a look.