Arguably – The best Python CLI library, arguably

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I spent the past few weeks working on arguably. It uses your function signatures and docstrings to create a CLI. I built it to have the most common features of other libraries (and a few extra) in a much more concise syntax - no need for @click.option or typer.Option. It succeeds when you barely notice it's there. For most cases, you decorate a function with @arguably.command, and it just does what you'd expect: * Positional args for the function become positional CLI args * Keyword-only args become --options * Type hints set up parsing * Docstrings provide help messages for each command and argument This also means it's good at making a script into a CLI without any integration at all, like Python Fire does. Just run `python3 -m arguably your_script.py` to give your script a CLI. This is my first time making an open-source project with real testing and documentation, definitely a learning experience. mkdocs didn't work for me at first, so I wrote some wild workarounds: https://treykeown.github.io/arguably/contributing/#building-...

Visit product View on Hacker NewsJun 20, 2023

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: open · Missing: mac, agents, macos

57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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