taskipy
typer
taskipy | typer | |
---|---|---|
9 | 87 | |
423 | 14,398 | |
1.4% | - | |
4.9 | 8.7 | |
6 days ago | 3 days ago | |
Python | Python | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
taskipy
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Useful Python Modules for us
pdbpp: Improved pdb boltons: assorted python addtions twisted: event driven networking framework sorcery: Dark magic in python, things know where+how they are being called, helps reducing boilerplate sh: Better alternative for subprocess module, much more pythonic taskipy: npm run scipt_name like functionality snoop: pdb lite, record+replay function steps birdseye: graphical debugger remote-pdb: easy pdb from inside containers typer: wrapper around click for simpler code for CLIs arrow: Always TZ aware datetimes, plus more features more-itertools: more functions for iterators pydantic: data validation + dataclasses loguru: better logging notifiers: sending notifications from python
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What is your favorite ,most underrated 3rd party python module that made your programming 10 times more easier and less code ? so we can also try that out :-) .as a beginner , mine is pyinputplus
Taskipy
- GitHub - illBeRoy/taskipy: the complementary task runner for python
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This Week In Python
taskipy – complementary task runner for python
- Taskipy: The Complementary Task Runner for Python
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Which not so well known Python packages do you like to use on a regular basis and why?
I always use Taskipy https://github.com/illBeRoy/taskipy to run tasks in my applications, works really well with Poetry so when I am running my dev Flask/FastAPI server and Celery or running my tests or format my code it's all there.
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No-op statements syntactically valid only since Python X.Y
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In legacy (don't break anything) mode, there's still no reason to not switch. I export `requirements.txt` with poetry just for pip legacy reasons and it works great. If I just update some scripts, I could avoid it. It's running all the time in CI, it's exercised quite a bit.
What's wrong with just using pip and requirements.txt? There's no dev section. In addition, bumping deps is not the same. I have [a blog post](https://squarism.com/2021/09/10/sciencing-out-updates/) explaining semver updates to a python dev.
_my strong assertion:_ Python and Go missed it from the start. That's why it is so confusing. There's no other choice in Rust but Cargo. Rust devs are never confused on how to add a package, semver it. The answer is always Cargo. It's in the tutorial. It's in the book. It's in the culture.
I think I've heard that pip might support the pyproject spec, poetry already does. If you want scripts like npm, you can have that too with [taskipy](https://github.com/illBeRoy/taskipy). You don't have to.
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Top python libraries/ frameworks that you suggest every one
taskipy
- Writing Makefiles for Python Projects
typer
- Typer: Python library for building CLI applications
- Copilot for your GitHub stars
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Things I've learned about building CLI tools in Python
I have been using Typer on every one of my CLI projects which uses Click under the hood. The documentation is fantastic, the CLI app it produces looks great and lets you create things quickly. I high recommend it.
https://typer.tiangolo.com/
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Things to do with standalone script
Adding CLI capabilities. My preferred library here is typer.
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Where to start for managing a Python code base for public distribution
I just heard about this but it seems to be pretty much the type of thing you want and want fast.
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Help on Docstrings
Docstrings are for documenting how a function/ class/ method/ module works. Often you don't need to add a docstring to your main function because no one will be importing it to use elsewhere. And if you want it to run as a CLI, then there are better ways to document the available options. For example, typer does most of it for you, or in click you add the help text to the decorator.
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Which best practices do you follow to build robust & extensible ETL jobs?
Most computing tasks in airflow DAGs are KubernetesPodOperator containing a CLI (Python Typer). It allows us to pass arguments easily to run DAG manually if needed (the new UI to pass arguments to DAG in airflow 2.6 is really nice). Arguments allow us to replay DAG easily (change start / end dates for instance).
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Devs on teams that deploy anytime you want, what does your SDLC workflow look like?
So it's basically the main .gitlab-ci.yml file plus a separate Python CI app using Typer for the AWS instrumentation.
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The different uses of Python type hints
Similarly for Typer, which is literally "the FastAPI of CLIs"[1]. Handy to type your `main` parameters and have CLI argument parsing. For more complicated cases, it's a wrapper around Click.
[1] https://typer.tiangolo.com/
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Command line parser library, which one do you like the most, regardless of language?
interesting that you hate python, but love Click. Did you try Typer which uses Click underneath?
What are some alternatives?
Toolz - A functional standard library for Python.
click - Python composable command line interface toolkit
wheezy.template - A lightweight template library.
Python Fire - Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.
yamlpath - YAML/JSON/EYAML/Compatible get/set/merge/validate/scan/convert/diff processors using powerful, intuitive, command-line friendly syntax.
Gooey - Turn (almost) any Python command line program into a full GUI application with one line
plumbum - Plumbum: Shell Combinators
rich - Rich is a Python library for rich text and beautiful formatting in the terminal.
zpy - Zsh helpers for Python venvs, with uv or pip-tools
python-prompt-toolkit - Library for building powerful interactive command line applications in Python
requests-html - Pythonic HTML Parsing for Humans™
cement - Application Framework for Python