prometeo
memory_profiler
| prometeo | memory_profiler | |
|---|---|---|
| 11 | 6 | |
| 610 | 4,222 | |
| - | 0.8% | |
| 0.0 | 3.7 | |
| almost 2 years ago | 9 days ago | |
| Python | Python | |
| BSD 2-clause "Simplified" License | BSD 3-clause "New" or "Revised" License |
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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.
memory_profiler
- Ask HN: C/C++ developer wanting to learn efficient Python
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8 Most Popular Python HTML Web Scraping Packages with Benchmarks
memory_profiler
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Check Python Memory Usage
pythonprofilers/memory_profiler: Monitor Memory usage of Python code
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Profiling and Analyzing Performance of Python Programs
# https://github.com/pythonprofilers/memory_profiler pip install memory_profiler psutil # psutil is needed for better memory_profiler performance python -m memory_profiler some-code.py Filename: some-code.py Line # Mem usage Increment Occurrences Line Contents ============================================================ 15 39.113 MiB 39.113 MiB 1 @profile 16 def memory_intensive(): 17 46.539 MiB 7.426 MiB 1 small_list = [None] * 1000000 18 122.852 MiB 76.312 MiB 1 big_list = [None] * 10000000 19 46.766 MiB -76.086 MiB 1 del big_list 20 46.766 MiB 0.000 MiB 1 return small_list
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Profiling Python code with memory_profiler
What do you do when your Python program is using too much memory? How do you find the spots in your code with memory allocation, especially in large chunks? It turns out that there is not usually an easy answer to these question, but a number of tools exist that can help you figure out where your code is allocating memory. In this article, I’m going to focus on one of them, memory_profiler.
- What Is Your Favorite Profilerperformance Tool
What are some alternatives?
Octavian.jl - Multi-threaded BLAS-like library that provides pure Julia matrix multiplication
py-spy - Sampling profiler for Python programs
llvm-cbe - resurrected LLVM "C Backend", with improvements
line_profiler
StaticCompiler.jl - Compiles Julia code to a standalone library (experimental)
profiling
acados - Fast and embedded solvers for nonlinear optimal control
pyflame
textX - Domain-Specific Languages and parsers in Python made easy http://textx.github.io/textX/
Laboratory - Achieving confident refactoring through experimentation with Python 2.7 & 3.3+
MatrixEquations.jl - Solution of Lyapunov, Sylvester and Riccati matrix equations using Julia
filprofiler - A Python memory profiler for data processing and scientific computing applications