My First Pip Package
I finally got around to packaging up pg2cf and I am excited to see it out in the wild on pypi. Python packaging is pretty straightforward and this makes distribution of this tool much easier for us internally.
I could not have done it without this awesome python packaging guide.
Using setuptools also makes a lot of other things easier. For instance running tests is as simple as python setup.py test and installing the package locally can be done with python setup.py install. The main benifit of course is that now pg2cf is an executable so you once it is installed you can just run it.
The only “gotcha” that I ran into was that setuptools does not support markdown. Which makes it kind of weird since Markdown is now the standard for README and other documentation on GitHub.
I worked around this by using pandoc, this way I am able to convert my README.md to README.rst easily with pandoc README.md -o README.rst and then use that for PyPI.
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Check out some more stuff to read down below.
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Recent Favorite Blog Posts
This is a collection of the last 8 posts that I bookmarked.
- The contagion of fear from The Observation Deck
- The revolt of the reader from The Observation Deck
- Deeper dive: Were Touch Bar’s problems software rather than hardware? from Unsung
- Joining Cursor from Fatih Arslan
- Pluralistic: Digital sewer socialism (08 Aug 2026) from Pluralistic: Daily links from Cory Doctorow
- Pluralistic: Enshittification and Reverse Centaurs go global (29 Jul 2026) from Pluralistic: Daily links from Cory Doctorow
- AI Mania Is Eviscerating Global Decision-Making from Ludicity
- The default person from https://popagandhi.com/
Articles from blogs I follow around the net
Time
via Christopher Butler November 3, 2026Internet Archive’s alphabet
I love the Internet Archive, but I don’t love its interface. It’s just… not great all around, homely and confusing. It has some endearing qualities, harking back to the web of the 1990s without endless commerce and incessant growth hacking – Wikipedia feel...
via Unsung November 3, 2026Qwen 3.8 27B on my laptop can interpret model weights, too
Yesterday's hot paper was Sparks of Weight-Space Programming: LLMs can natively read & write neural network weights by Rikiya Takehi, Jayden Teoh, Alex Zhang, and Omar Khattab. The paper (OK, the authors classify is as a "blog post", but it's paper-shaped)...
via Simon Willison's Weblog: Entries November 3, 2026Generated by openring