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52 results for “pawamoy”
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Ignoring a <4 constraint makes sense, but the fact that a single maximum constraint means it refuses to resolve dependencies that lack a maximum makes no sense in the first place. 🤷
I've been playing with #PDM a bit as a possible replacement for poetry (with this project, even) but haven't been ready to move to it yet. It seems to be missing some convenience features that I rely heavily on - having the `shell` command launch an activated subshell that you can just exit to return to the unactivated venv state is muscle-memory for me, so I constantly end up closing my terminal. And I haven't found a way to make pdm install actual scripts/symlinks for declared entrypoints - you have to always do `pdm run entrypoint [...]` rather than just running `entrypoint [...]` after activating the shell.
I'll have to see if poetry v2 actually fixes all of the things that made me want to switch away from poetry. Maybe it won't be necessary.
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Hmmm, how come #uv manages to install #cffi==1.16.0 in GitHub Actions on ubuntu-latest and #Python 3.13.0b1 while it fails locally on (Arch)Linux and Python 3.13.0b1 🤔
There is no wheel of 1.16.0 for CPython 3.13 🤔 And sources fail to compile (not compatible with 3.13). I'm confused 🤔 🤔 🤔
https://github.com/pawamoy/duty/actions/runs/9147683333/job/25149389495
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Hmmm, how come #uv manages to install #cffi==1.16.0 in GitHub Actions on ubuntu-latest and #Python 3.13.0b1 while it fails locally on (Arch)Linux and Python 3.13.0b1 🤔
There is no wheel of 1.16.0 for CPython 3.13 🤔 And sources fail to compile (not compatible with 3.13). I'm confused 🤔 🤔 🤔
https://github.com/pawamoy/duty/actions/runs/9147683333/job/25149389495
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Hmmm, how come #uv manages to install #cffi==1.16.0 in GitHub Actions on ubuntu-latest and #Python 3.13.0b1 while it fails locally on (Arch)Linux and Python 3.13.0b1 🤔
There is no wheel of 1.16.0 for CPython 3.13 🤔 And sources fail to compile (not compatible with 3.13). I'm confused 🤔 🤔 🤔
https://github.com/pawamoy/duty/actions/runs/9147683333/job/25149389495
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Hmmm, how come #uv manages to install #cffi==1.16.0 in GitHub Actions on ubuntu-latest and #Python 3.13.0b1 while it fails locally on (Arch)Linux and Python 3.13.0b1 🤔
There is no wheel of 1.16.0 for CPython 3.13 🤔 And sources fail to compile (not compatible with 3.13). I'm confused 🤔 🤔 🤔
https://github.com/pawamoy/duty/actions/runs/9147683333/job/25149389495
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Hmmm, how come #uv manages to install #cffi==1.16.0 in GitHub Actions on ubuntu-latest and #Python 3.13.0b1 while it fails locally on (Arch)Linux and Python 3.13.0b1 🤔
There is no wheel of 1.16.0 for CPython 3.13 🤔 And sources fail to compile (not compatible with 3.13). I'm confused 🤔 🤔 🤔
https://github.com/pawamoy/duty/actions/runs/9147683333/job/25149389495
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I created a small #Python #Markdown extension that parses `pycon` syntax code blocks *without indentation and without fences*, and renders them using #pymdownx's Highlight extension 🙂
It will be useful in Python docstrings, to add examples anywhere just how #doctest expects them!
It's immediately available to my sponsors and has been added to the GraviFridge goal (https://pawamoy.github.io/insiders/#1000-gravifridge-user-manual) 😊
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When installing dependencies, formatting code, linting it, type-checking it, and building docs with #Poetry or #PDM, #Black, #Flake8, #Mypy and #MkDocs would previously take from 2min to several more, it now takes less than 15 seconds for the whole thing, thanks to #uv, #Ruff, #ty and #Zensical.
This is for 5 #Python versions (3.10 to 3.15).
The DX got much better 🥰
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When installing dependencies, formatting code, linting it, type-checking it, and building docs with #Poetry or #PDM, #Black, #Flake8, #Mypy and #MkDocs would previously take from 2min to several more, it now takes less than 15 seconds for the whole thing, thanks to #uv, #Ruff, #ty and #Zensical.
This is for 5 #Python versions (3.10 to 3.15).
The DX got much better 🥰
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When installing dependencies, formatting code, linting it, type-checking it, and building docs with #Poetry or #PDM, #Black, #Flake8, #Mypy and #MkDocs would previously take from 2min to several more, it now takes less than 15 seconds for the whole thing, thanks to #uv, #Ruff, #ty and #Zensical.
This is for 5 #Python versions (3.10 to 3.15).
The DX got much better 🥰
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When installing dependencies, formatting code, linting it, type-checking it, and building docs with #Poetry or #PDM, #Black, #Flake8, #Mypy and #MkDocs would previously take from 2min to several more, it now takes less than 15 seconds for the whole thing, thanks to #uv, #Ruff, #ty and #Zensical.
This is for 5 #Python versions (3.10 to 3.15).
The DX got much better 🥰
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Griffe is now able to compute source links for objects, pointing to GitHub or other Git services online. See the changelog for v1.14: https://mkdocstrings.github.io/griffe/changelog/#1140-2025-09-05.
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Griffe is now able to compute source links for objects, pointing to GitHub or other Git services online. See the changelog for v1.14: https://mkdocstrings.github.io/griffe/changelog/#1140-2025-09-05.
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Griffe is now able to compute source links for objects, pointing to GitHub or other Git services online. See the changelog for v1.14: https://mkdocstrings.github.io/griffe/changelog/#1140-2025-09-05.
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Griffe is now able to compute source links for objects, pointing to GitHub or other Git services online. See the changelog for v1.14: https://mkdocstrings.github.io/griffe/changelog/#1140-2025-09-05.
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Griffe is now able to compute source links for objects, pointing to GitHub or other Git services online. See the changelog for v1.14: https://mkdocstrings.github.io/griffe/changelog/#1140-2025-09-05.
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Kinda crazy to see #Griffe mentioned as inspiration for the design of #OpenAI's Agents SDK 🤯 Cool to see the SDK's API reference being documented with #mkdoctrings, too 🥰
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Kinda crazy to see #Griffe mentioned as inspiration for the design of #OpenAI's Agents SDK 🤯 Cool to see the SDK's API reference being documented with #mkdoctrings, too 🥰
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Kinda crazy to see #Griffe mentioned as inspiration for the design of #OpenAI's Agents SDK 🤯 Cool to see the SDK's API reference being documented with #mkdoctrings, too 🥰
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Kinda crazy to see #Griffe mentioned as inspiration for the design of #OpenAI's Agents SDK 🤯 Cool to see the SDK's API reference being documented with #mkdoctrings, too 🥰
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Kinda crazy to see #Griffe mentioned as inspiration for the design of #OpenAI's Agents SDK 🤯 Cool to see the SDK's API reference being documented with #mkdoctrings, too 🥰
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Also, use #Cappa 😛 Cappa leaves your functions/dataclasses (commands) intact.
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How do you generate JSON schemas of your dataclasses' **inputs**? Any third-party library (something else than stdlib's dataclasses) allowing one to do that?
For example, input type is `int | str`, but final/output type is always `int` (coerced). I want to document the input type, not the output type.
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Rewriting an argparse-based CLI with #Cappa. It's much cleaner:
- less verbose
- better contained (single module instead of using submodules for subcommands)
- better typed (dataclasses!)
- as reusable, or more reusable in other CLIs (classes instead of functions that modify an argparse parser)
- much easier to use programmatically (no need to call `main` or build an `argparse.Namespace` manually)
- better documented
- better output (rich!)