line_profiler
prometeo
line_profiler | prometeo | |
---|---|---|
17 | 11 | |
2,481 | 610 | |
1.3% | - | |
8.2 | 0.0 | |
6 days ago | almost 2 years ago | |
Python | Python | |
GNU General Public License v3.0 or later | BSD 2-clause "Simplified" License |
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line_profiler
- Ask HN: C/C++ developer wanting to learn efficient Python
- New version of line_profiler: 4.1.0
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Making Python 100x faster with less than 100 lines of Rust
LineProfiler is the best tool to learn how to write performant Python and code optimization.
https://github.com/pyutils/line_profiler
You can literally see the hot spot of your code, then you can grind different algorithms or change the whole architecture to make it faster.
For example replace short for loops to list comprehensions, vectorize all numpy operations (only vectorize partially do not help the issue), using 'not any()' instead or 'all()' for boolean, etc.
Doing this for like 2 weeks, basically you can automatically recognized most bad code patterns in a glance.
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Why is my Pubmed plant search app so slow?
You may want to try using a package like line_profiler to narrow down where the time is spent.
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How to make nested for loops run faster
When tuning for performance, always measure. Never assume you know where the slow parts are. Run a line profiler and see where all the time is actually going.
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I'm working on a world map generator, but I have one function in particular that is very slow and keeping me from being able to scale my maps to as large as I'd like... is there a way that I can optimize this depth first search function, or another way of grouping contiguous cells based on criteria?
Either way I would highly recommend running a profiler on your code to see where the program is spending most of its time. line_profiler is a very nice one, as it shows you execution time for each line.
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Is it possible to make a function to check how many lines of code have been executed in the program so far (including said function’s lines)?
There are dedicated tools like line_profiler for python - if this doesn't do exactly what you need it can be easily modified.
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Why does sklearn.Pipeline with regex outperform spacy for text preprocessing?
It's surprising to me that an sklearn pipeline and a spacy pipeline both doing simple regexing are vastly different in performance. I would go one layer deeper with measurement with something like line_profiler, which I've used to great effect to get line-by-line perf stats. This should illuminate why.
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Hot profiling for Python
This looks really nice! Does it use line_profiler or is it a different implementation for the profiling? Either way the interface is fantastic!
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Profiling and Analyzing Performance of Python Programs
# https://github.com/pyutils/line_profiler pip install line_profiler kernprof -l -v some-code.py # This might take a while... Wrote profile results to some-code.py.lprof Timer unit: 1e-06 s Total time: 13.0418 s File: some-code.py Function: exp at line 3 Line # Hits Time Per Hit % Time Line Contents ============================================================== 3 @profile 4 def exp(x): 5 1 4.0 4.0 0.0 getcontext().prec += 2 6 1 0.0 0.0 0.0 i, lasts, s, fact, num = 0, 0, 1, 1, 1 7 5818 4017.0 0.7 0.0 while s != lasts: 8 5817 1569.0 0.3 0.0 lasts = s 9 5817 1837.0 0.3 0.0 i += 1 10 5817 6902.0 1.2 0.1 fact *= i 11 5817 2604.0 0.4 0.0 num *= x 12 5817 13024902.0 2239.1 99.9 s += num / fact 13 1 5.0 5.0 0.0 getcontext().prec -= 2 14 1 2.0 2.0 0.0 return +s
prometeo
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Borgo is a statically typed language that compiles to Go
Not impossible but I guess you might end up with an extra runtime layer and some more dynamic operations will not be very fast. Or you restrict it to a subset of Python like this project does: https://github.com/zanellia/prometeo
You could of course write a bytecode VM in Golang but I guess that defeats the purpose.
- Are there any libraries that can easily convert Python to C/C#/or C++? Ones where a person doesn't have to "calibrate" it, just, pip install library and then they can have their Python code in C,C#,or C++?
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I made a Python compiler, that can compile Python source down to fast, standalone executables.
Honest question: How does pycom compare to similar tools like Nuitka, prometeo, or mypyc?
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Profiling and Analyzing Performance of Python Programs
If you don't mind switching to a little different syntax of Python, then you also might want to take a look at prometeo - an embedded domain specific language based on Python, specifically aimed at scientific computing. Prometeo programs transpile to pure C code and its performance can be comparable with hand-written C code.
- GitHub - zanellia/prometeo: An experimental Python-to-C transpiler and domain specific language for embedded high-performance computing
- Show HN: Prometeo – a Python-to-C transpiler for high-performance computing
- An experimental Python-to-C transpiler and domain specific language for embedded high-performance computing
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Show HN: prometeo – a Python-to-C transpiler for high-performance computing
This is awesome! The direction of using a subset of python, while leveraging the user base and static typing to accomplish some other everyday task in a different language is very legit IMO.
I took a cursory look at:
https://github.com/zanellia/prometeo/blob/master/prometeo/cg...
It seems quite similar in spirit to
https://github.com/adsharma/py2many/blob/main/pyrs/transpile...
I'm not spending much time on py2many last few months (started a new job). Let me know if any of it sounds useful - especially the ability to transpile to 7-8 languages including Julia, C++ and Rust.
What are some alternatives?
SnakeViz - An in-browser Python profile viewer
Octavian.jl - Multi-threaded BLAS-like library that provides pure Julia matrix multiplication
memory_profiler - Monitor Memory usage of Python code
llvm-cbe - resurrected LLVM "C Backend", with improvements
reloadium - Hot Reloading and Profiling for Python
StaticCompiler.jl - Compiles Julia code to a standalone library (experimental)
pprofile - Line-granularity, thread-aware deterministic and statistic pure-python profiler
acados - Fast and embedded solvers for nonlinear optimal control
psutil - Cross-platform lib for process and system monitoring in Python
textX - Domain-Specific Languages and parsers in Python made easy http://textx.github.io/textX/
austin - Python frame stack sampler for CPython
MatrixEquations.jl - Solution of Lyapunov, Sylvester and Riccati matrix equations using Julia