One of the things I love about Python is the abundance of handy libraries to cobble together small but useful tools. At work we had a large pylint report, and I wanted to understand it better. In particular, I wanted to trace back to which commit had introduced the violations. I wrote pylintdb.py to do the work.

Since we had a lot of violations (>5000!) I figured it would take some time to use git blame to find the commit for each line. I wanted a way to persist the progress through the lines. SQLite seemed like a good choice. It also would give me ad-hoc queryability, though to be honest, I didn’t even consider that at the time.

SQLite is part of the Python standard library, but there’s a third-party library that makes it super-convenient to use. Dataset lets you use a database without creating a schema or even model first. You just open a database, choose a table name, and then start writing dictionaries to it. It handles all the schema creation (or modification!) behind the scenes. Awesome.

These days, click is the tool of choice for command-line parsing, and other chores needed in the terminal. I used the progress bar functions. They aren’t perfect, but in only a few lines I had a workable indicator.

Other useful things from the Python standard library:

• concurrent.futures for parallelizing the git blame work. It’s got a high-level “map” interface that did exactly what I needed without having to think about queues, threads, and so on.
• subprocess.check_output does the subprocess thing people usually want: just run the command and give me the output.

pylintdb isn’t earth-shattering, it just does exactly what I needed in 120 lines with a minimum of fuss, thanks to dataset, click, and Python.