Attrs – the Python library everyone needs (2016)
glyph.twistedmatrix.com
Attrs – the Python library everyone needs (2016)
1–10 of 115 posts
Re: Attrs – the Python library everyone needs (2016)
#2see also "dataclasses" since python 3.7
Re: Attrs – the Python library everyone needs (2016)
#3my_point3d = (1.0, 2.5, 7.2)
Voila!
Re: Attrs – the Python library everyone needs (2016)
#4IMO Pydantic is way more ergonomic, has great defaults, and easier to bend to your will when you want to use it a little differently.
Lots of love to Attrs, which is a great library and is a component of a lot of great software. It was my go-to library for years before Pydantic matured, but I think a lot of people have rightly started to move on to Pydantic, particularly with the popularity of FastAPI
Re: Attrs – the Python library everyone needs (2016)
#5see also "dataclasses" since python 3.7
Came here to say this, dataclasses have been super helpful for a big part of the pain point highlighted by the author. More often than not, that is enough for me.
Re: Attrs – the Python library everyone needs (2016)
#6my_point3d = (1.0, 2.5, 7.2) Voila!
This is explicitly called out in the article.
What does your code do when I try my_point3d.x ?
Re: Attrs – the Python library everyone needs (2016)
#7see also "dataclasses" since python 3.7
Not a python guy, so confused as to why a thing called namedtuple behaves like dataclasses, what are their different usecases?
Re: Attrs – the Python library everyone needs (2016)
#8IMO Pydantic is way more ergonomic, has great defaults, and easier to bend to your will when you want to use it a little differently. Lots of love to Attrs, which is a great library and is a component of a lot of great software. It was my go-to library for years before Pydantic matured, but I think a lot of people have rightly started to move on to Pydantic, particularly with the popularity of FastAPI
Pydantic is dataclasses, except types are validated at runtime? It's nice and looks just like a normal dataclass looking at https://pydantic-docs.helpmanual.io/
For any larger program, pervasive type annotations and "compile" time checking with mypy is a really good idea though, which somewhat lessens the need for runtime checking.
Re: Attrs – the Python library everyone needs (2016)
#9IMO Pydantic is way more ergonomic, has great defaults, and easier to bend to your will when you want to use it a little differently. Lots of love to Attrs, which is a great library and is a component of a lot of great software. It was my go-to library for years before Pydantic matured, but I think a lot of people have rightly started to move on to Pydantic, particularly with the popularity of FastAPI
Pydantic is dataclasses, except types are validated at runtime? It's nice and looks just like a normal dataclass looking at https://pydantic-docs.helpmanual.io/ For any larger program, pervasive type annotations and "compile" time checking with mypy is a really good idea though, which somewhat lessens the need for runtime checking.
Pydantic types will be checked by mypy or any other static type analysis tool as well.
I don’t expect any type-related thing to be remotely safe in Python without applying at least mypy and pylint, potentially pyright as well, plus, as always with an interpreted language, unit tests for typing issues that would be caught by a compiler in another language
Re: Attrs – the Python library everyone needs (2016)
#10IMO Pydantic is way more ergonomic, has great defaults, and easier to bend to your will when you want to use it a little differently. Lots of love to Attrs, which is a great library and is a component of a lot of great software. It was my go-to library for years before Pydantic matured, but I think a lot of people have rightly started to move on to Pydantic, particularly with the popularity of FastAPI
Pydantic is dataclasses, except types are validated at runtime? It's nice and looks just like a normal dataclass looking at https://pydantic-docs.helpmanual.io/ For any larger program, pervasive type annotations and "compile" time checking with mypy is a really good idea though, which somewhat lessens the need for runtime checking.
Pydantic works with mypy, so you have validation at build-time and parsing at runtime.