chatnoir-resiliparse
Cython
chatnoir-resiliparse | Cython | |
---|---|---|
2 | 79 | |
42 | 8,935 | |
- | 1.3% | |
7.5 | 9.8 | |
6 days ago | 3 days ago | |
Cython | Python | |
Apache License 2.0 | Apache License 2.0 |
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chatnoir-resiliparse
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Selenium over scrapy
bs4 is a little slow, try https://github.com/chatnoir-eu/chatnoir-resiliparse, it's faster for working with the dom written in cython and based on lexbor (written in C and very fast)
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Would I ever need anything besides Python (not pro)
I've been working on this for the last several days, and learning a lot. I'm actually moving away from dask to python multiprocessing, the overhead for extremely fast functions written in cython seems to slow it down when added to a dask task graph sometimes more than running sequentially. At least that's what experiments are showing, https://github.com/chatnoir-eu/chatnoir-resiliparse/issues/23
Cython
- Ask HN: C/C++ developer wanting to learn efficient Python
- Ask HN: Is there a way to use Python statically typed or with any type-checking?
- Cython 3.0
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How to make a c++ python extension?
The approach that I favour is to use Cython. The nice thing with this approach is that your code is still written as (almost) Python, but so long as you define all required types correctly it will automatically create the C extension for you. Early versions of Cython required using Cython specific typing (Python didn't have type hints when Cython was created), but it can now use Python's type hints.
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Never again
and again, everything that was released after using an older version of cython.
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Codon: Python Compiler
Just for reference,
* Nuitka[0] "is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11."
* Pypy[1] "is a replacement for CPython" with builtin optimizations such as on the fly JIT compiles.
* Cython[2] "is an optimising static compiler for both the Python programming language and the extended Cython programming language... makes writing C extensions for Python as easy as Python itself."
* Numba[3] "is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code."
* Pyston[4] "is a performance-optimizing JIT for Python, and is drop-in compatible with ... CPython 3.8.12"
[0] https://github.com/Nuitka/Nuitka
[1] https://www.pypy.org/
[2] https://cython.org/
[3] https://numba.pydata.org/
[4] https://github.com/pyston/pyston
- Slow Rust Compiler is a Feature, not a Bug.
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Any faster Python alternatives?
Profile and optimize the hotspots with cython (or whatever the cool kids are using these days... It's been a while.)
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What exactly is 'JIT'?
JIT essentially means generating machine code for the language on the fly, either during loading of the interpreter (method JIT), or by profiling and optimizing hotspots (tracing JIT). The language itself can be statically or dynamically typed. You could also compile a dynamic language ahead of time, for example, cython.
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Python executable makers
Cython - - embed demo