typedload
peps
| typedload | peps | |
|---|---|---|
| 5 | 36 | |
| 254 | 4,140 | |
| - | 0.7% | |
| 8.1 | 9.8 | |
| 7 days ago | about 24 hours ago | |
| Python | reStructuredText | |
| GNU General Public License v3.0 or later | - |
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.
typedload
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Show HN: Up to 100x Faster FastAPI with simdjson and io_uring on Linux 5.19
Author of typedload here!
FastAPI relies on (not so fast) pydantic, which is one of the slowest libraries in that category.
Don't expect to find such benchmarks on the pydantic documentation itself, but the competing libraries will have them.
[0] https://ltworf.github.io/typedload/
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Pydantic vs Protobuf vs Namedtuples vs Dataclasses
I wrote typedload, which is significantly faster than pydantic. Just uses normal dataclasses/attrs/NamedTuple, has a better API and is pure Python!
- Informatica serve a qualcosa?
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Show HN: Python framework is faster than Golang Fiber
I read all the perftests in the repo. I think they nearly all parse a structure that contains a repetition of the same or similar thing a couple hundred thousand times times and the timing function returns the min and max of 5 attempts. I just picked one example for posting.
Not a Python expert, but could the Pydantic tests be possibly not realistic and/or misleading because they are using kwargs in __init__ [1] to parse the object instead of calling the parse_obj class method [2]? According to some PEPs [3], isn't Python creating a new dictionary for that parameter which would be included in the timing? That would be unfortunate if that accounted for the difference.
Something else I think about is if a performance test doesn't produce a side effect that is checked, a smart compiler or runtime could optimize the whole benchmark away. Or too easy for the CPU to do branch prediction, etc. I think I recall that happening to me in Java in the past, but probably not happened here in Python.
[1] https://github.com/ltworf/typedload/blob/37c72837e0a8fd5f350...
[2] https://docs.pydantic.dev/usage/models/#helper-functions
[3] https://peps.python.org/pep-0692/
peps
- PEP 722: Python dependencies for single-file scripts
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Getting started with the Mojo programming language
If you have suggestions that could improve the Python experience, consider proposing these through the Python Enhancement Proposal (PEP) process. The Mojo team actively encourages this, as it views Mojo as a new member of the Python family.
- PEP 684 was accepted – Per-interpreter GIL in Python 3.12
- Disallow import * for your Python package
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Ask HN: Just Finished Stroustrup's 'Practice and Principles'. What Next?
after 1-6, should have a good idea of what type of documentation / coding standards / tools / levels of abstraction want to have/see for a projects source code/deliverable. :-)
[1] : http://github.com/Blackgu/ebooks/blob/master/ebooks/2012-2-1...
[2] : http://peps.python.org
[3] http://medium.com/codex/say-goodbye-to-loops-in-python-and-w...
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Don't carelessly rely on fixed-size unsigned integers overflow
Yet development is carried via consensus between developers and users, there are places where users come to discuss thinks and ask questsion, there are place where resolutions are described in a POSITA-understandable terms and so on.
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Show HN: Python framework is faster than Golang Fiber
Oh, I have a pretty fresh news for you.
https://github.com/python/peps/pull/2955
- PEP703 Making the Global Interpreter Lock Optional in CPython
- PEP 703: Making the Global Interpreter Lock Optional in CPython
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Are there any published articles about Python that I can reference?
You mean like PEPs? https://peps.python.org
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