python-uncompyle6
A cross-version Python bytecode decompiler (by rocky)
memory_profiler
Monitor Memory usage of Python code (by pythonprofilers)
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python-uncompyle6 | memory_profiler | |
---|---|---|
8 | 6 | |
3,549 | 4,210 | |
- | 1.3% | |
8.9 | 3.7 | |
about 1 month ago | 13 days ago | |
Python | Python | |
GNU General Public License v3.0 only | BSD 3-clause "New" or "Revised" License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
python-uncompyle6
Posts with mentions or reviews of python-uncompyle6.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-11-20.
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Testing Github Co-Pilot and Trying to Win World Cup Bet
Q: What is RAPID_API_KEY = os.environ.get('RAPID_API_KEY')? A: You should store configuration in environment variables; never in code. See 12 factors app. Python .pyc files can easily be "decompiled" to .py and reveal all secrets in code.
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PSA: Global QR Code bot could have malware...
I was able to figure out that this is a python program which was compiled to an .exe. Using uncompyle6 and pyc2bytecode, I was able to decompile the .exe into the python bytecode...but I'm no expert at reading python bytecode. If you want to do this yourself, note that you will need to use the same version of python as the version used to make the exe (python 3.9). I did easily by changing the python_version in my Pipfile to 3.9 and using pipenv shell.
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Synack Red Team Five CTF Writeup - Rev
It's a Pyinstaller binary.(I have used it once before, so I just knew it by checking the file.) Use https://github.com/extremecoders-re/pyinstxtractor to extract its source code archive in binary (by just running python pyinstxtractor.py ./backdoor or something), now many .pyc files are extracted. Find src.pyc and it's malformed as Python3.9, so https://github.com/rocky/python-uncompyle6/ denies to decompile. But challenge information says it's Python3.8, so I write helloworld python script and execute it with Python3.8. It yields Python3.8 .pyc file. Analyze it and find signature is \x55. Change src.pyc's signature from \x61 to \x55 and decompile by running uncompyle6 backdoor-src.38.pyc > backdoor-src.py
- Help! Decompiling python 3.6 to source code
- De-obfuscating .pyc files?
- Recovering lost python code from .pyc?
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Error: uncompyle6 requires Python 2.6-3.8
If not, you’ll either need to install and use 3.8 to run the program, or you’ll need to help the author continue support beyond 3.8.
memory_profiler
Posts with mentions or reviews of memory_profiler.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-04-10.
- 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?
When comparing python-uncompyle6 and memory_profiler you can also consider the following projects:
python-decompile3 - Python decompiler for 3.7-3.8 Stripped down from uncompyle6 so we can refactor and start to fix up some long-standing problems
py-spy - Sampling profiler for Python programs
line_profiler
remote-pdb - Remote vanilla PDB (over TCP sockets).
profiling
pdb++
pyflame
pyinstxtractor - PyInstaller Extractor
Laboratory - Achieving confident refactoring through experimentation with Python 2.7 & 3.3+
filprofiler - A Python memory profiler for data processing and scientific computing applications
python-uncompyle6 vs python-decompile3
memory_profiler vs py-spy
python-uncompyle6 vs py-spy
memory_profiler vs line_profiler
python-uncompyle6 vs remote-pdb
memory_profiler vs profiling
python-uncompyle6 vs pdb++
memory_profiler vs pyflame
python-uncompyle6 vs pyinstxtractor
memory_profiler vs Laboratory
python-uncompyle6 vs pyflame
memory_profiler vs filprofiler