django-async-orm
typer
| django-async-orm | typer | |
|---|---|---|
| 6 | 88 | |
| 130 | 14,398 | |
| - | - | |
| 6.1 | 8.7 | |
| 10 months ago | 5 days ago | |
| Python | Python | |
| MIT License | MIT License |
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django-async-orm
- Django 4.0 Released
- Django module that brings async to django ORM.
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Show HN: Django Async ORM
I'm not sure if its official. Would love some more guidance/clarity/docs/funding from the django foundation on what it looks like to migrate legacy code to the new ways.
The rednaks repo works great for just giving the new async stuff a go. If everything else is also using async.
I did some experimentation with this. And its a pain trying to migrate a production application that uses gevent and psycogreen2.
The documentation on the code migration path is pretty sparse.
The main hiccup that I ran into was psycogreen2 not being supported.
https://stackoverflow.com/questions/67735453/django-async-or...
https://github.com/rednaks/django-async-orm/discussions/9
- Django 4.0 release candidate 1 released
- Bringing Async Capabilities to Django ORM
typer
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Github Sponsor Sebastián Ramírez 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?
tortoise-orm - Familiar asyncio ORM for python, built with relations in mind
click - Python composable command line interface toolkit
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
Python Fire - Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.
django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
Gooey - Turn (almost) any Python command line program into a full GUI application with one line
aiosql - Simple SQL in Python
rich - Rich is a Python library for rich text and beautiful formatting in the terminal.
celery - Distributed Task Queue (development branch)
python-prompt-toolkit - Library for building powerful interactive command line applications in Python
docker-django-example - A production ready example Django app that's using Docker and Docker Compose.
cement - Application Framework for Python