convtools
typer
convtools | typer | |
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3 | 88 | |
38 | 14,398 | |
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7.2 | 8.7 | |
2 months ago | 5 days ago | |
Python | Python | |
MIT License | MIT License |
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convtools
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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
convtools - I built this to generate ad-hoc data converters, but now what I like the most about it is the functional approach.
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convtools models: yet another Pydantic, but faster; validation first; explicit & safe type casting
Sources: https://github.com/westandskif/convtools
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convtools - Table: a helper for stream processing of table-like data
I released a helper for stream processing of table-like data (including CSVs), which works on top of convtools python library - https://github.com/westandskif/convtools
typer
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Github Sponsor Sebastián RamÃrez Python programmer
He is probably most well know for creating FastAPI that I taught to some of my clients and Typer that I've never used.
- 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/
What are some alternatives?
prosto - Prosto is a data processing toolkit radically changing how data is processed by heavily relying on functions and operations with functions - an alternative to map-reduce and join-groupby
click - Python composable command line interface toolkit
Skytrax-Data-Warehouse - A full data warehouse infrastructure with ETL pipelines running inside docker on Apache Airflow for data orchestration, AWS Redshift for cloud data warehouse and Metabase to serve the needs of data visualizations such as analytical dashboards.
Python Fire - Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.
convtools-ita - convtools is a python library to declaratively define conversions for processing collections, doing complex aggregations and joins.
Gooey - Turn (almost) any Python command line program into a full GUI application with one line
protogen-python - The protogen package makes it easy to write protoc plugins in Python
rich - Rich is a Python library for rich text and beautiful formatting in the terminal.
TinyBaker - Composable, first-order file-to-file transformations in Python
python-prompt-toolkit - Library for building powerful interactive command line applications in Python
better-exceptions - Pretty and useful exceptions in Python, automatically.
cement - Application Framework for Python