psutil
line_profiler
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psutil | line_profiler | |
---|---|---|
7 | 17 | |
9,922 | 2,475 | |
- | 3.9% | |
8.9 | 8.2 | |
7 days ago | 15 days ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | 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.
psutil
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Single Window Mode when Firefox is already launched with -profile "my_profile" parameter
fyi: python + https://github.com/giampaolo/psutil is pretty portable
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Why new Macs break your Docker build, and how to fix it
FYI, you probably already know this, but just in case: https://github.com/giampaolo/psutil/pull/2070
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Steam like timer
Check out https://github.com/giampaolo/psutil
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tiptop, a command-line system monitor
No, not yet, though I'd love to have that in, too. The problem here is fetching the corresponding data since there's no standard interface this yet. (At least none that I know of.) Follow this bug to get updated.
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Tracking CPU usage of computer's individual processes (real time update)
here is a good module to start with: https://github.com/giampaolo/psutil
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Help with a installing a program with wine [WinError 127]
This post thing (idk what it is called) was hard for me to understand, but it looked like they were saying that it may have been an issue with python and wine. They suggested using wine-develop (which i assume is "development" because "apt install wine-develop" cant find it, but it can find development). So I did:
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Profiling Python code with memory_profiler
It uses the psutil library (or can use tracemalloc or posix) to access process information in a cross platform way, so it works on Windows, Mac, and Linux.
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
What are some alternatives?
Ansible - Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy and maintain. Automate everything from code deployment to network configuration to cloud management, in a language that approaches plain English, using SSH, with no agents to install on remote systems. https://docs.ansible.com.
SnakeViz - An in-browser Python profile viewer
pexpect - A Python module for controlling interactive programs in a pseudo-terminal
memory_profiler - Monitor Memory usage of Python code
Fabric - Simple, Pythonic remote execution and deployment.
reloadium - Hot Reloading and Profiling for Python
supervisor - Supervisor process control system for Unix (supervisord)
pprofile - Line-granularity, thread-aware deterministic and statistic pure-python profiler
pyinfra - pyinfra automates infrastructure using Python. It’s fast and scales from one server to thousands. Great for ad-hoc command execution, service deployment, configuration management and more.
prometeo - An experimental Python-to-C transpiler and domain specific language for embedded high-performance computing
Docker Compose - Define and run multi-container applications with Docker
austin - Python frame stack sampler for CPython