psrecord | Record the CPU and memory activity of a process

by astrofrog Python Version: 1.4 License: BSD-2-Clause

X-Ray Key Features Code Snippets(3)Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | psrecord Summary

psrecord is a Python library typically used in Utilities applications. psrecord has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install psrecord' or download it from GitHub, PyPI.

Record the CPU and memory activity of a process :chart_with_upwards_trend:

Support

Quality

Security

License

Reuse

Support

psrecord has a low active ecosystem.

It has 485 star(s) with 69 fork(s). There are 12 watchers for this library.

There were 3 major release(s) in the last 6 months.

There are 25 open issues and 13 have been closed. On average issues are closed in 149 days. There are 11 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of psrecord is 1.4

Quality

psrecord has 0 bugs and 0 code smells.

Security

psrecord has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

psrecord code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

psrecord is licensed under the BSD-2-Clause License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

psrecord releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

psrecord saves you 82 person hours of effort in developing the same functionality from scratch.

It has 211 lines of code, 15 functions and 5 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

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psrecord Key Features

No Key Features are available at this moment for psrecord.

psrecord Examples and Code Snippets

Key: value store in Python for possibly 100 GB of data, without client/server

Python

Lines of Code : 33

License : Strong Copyleft (CC BY-SA 4.0)

Copy

from sqlitedict import SqliteDict

mydict = SqliteDict('./my_db.sqlite', autocommit=True)
mydict['some_key'] = any_picklable_object
print(mydict['some_key'])
for key, value in mydict.items():
    print(key, value)
print(len(mydict))
mydict

Running multiple bash commands with individual output files in a single subprocess calls

Python

Lines of Code : 2

License : Strong Copyleft (CC BY-SA 4.0)

Copy

cmd1 | tee /path/to/cmd1file.log | cmd2 > /path/to/cmd2file.log

Running multiple bash commands with individual output files in a single subprocess calls

Python

Lines of Code : 29

License : Strong Copyleft (CC BY-SA 4.0)

Copy

import shlex, pipes
if hasattr(shlex, 'quote'):
    quote = shlex.quote # Python 3
else:
    quote = pipes.quote # Python 2

inner_cmds = [
  [
    'program',
    '--arg1', 'foo',
    '--arg2', 'bar',
    '--output', 'out1.txt'
  ], [

Community Discussions

Trending Discussions on psrecord

Allocating a large multidimensional vector causes memory "overshoot"

OpenCL clCreateContextFromType function results in memory leaks

QUESTION

Allocating a large multidimensional vector causes memory "overshoot"

Asked 2021-Aug-19 at 17:56

I observed an unexpected behavior when using a large multidmensional std::vector variable. In particular, when I allocate a 4-dimensional vector of large size, it can be seen, using a memory profiler, that my task shortly uses more memory than it would require for the variable.

An MWE to reproduce this behavior is the following:

...

ANSWER

Answered 2021-Aug-19 at 17:56

This could be caused for different reasons, like returning without using smart-pointer (which could cause a copy).

But in your particular case, you pass something to F variable's constructor (no matter what), which takes additional memory till constructor returns.

Oh! yet another possible cause, an (un)intelligent vector implementation should reserve more than required (just in case, to speed up later appending).

Example:

Below is what fixed OP's issue:

Source https://stackoverflow.com/questions/68850660

QUESTION

OpenCL clCreateContextFromType function results in memory leaks

Asked 2020-Apr-11 at 20:11

I ran valgrind to one of my open-source OpenCL codes (https://github.com/fangq/mmc), and it detected a lot of memory leaks in the OpenCL host code. Most of those pointed back to the line where I created the context object using clCreateContextFromType.

I double checked all my OpenCL variables, command queues, kernels and programs, and made sure that they are all properly released, but still, when testing on sample programs, every call to the mmc_run_cl() function bumps up memory by 300MB-400MB and won't release at return.

you can reproduce the valgrind report by running the below commands in a terminal:

...

ANSWER

Answered 2020-Apr-11 at 17:20

I double checked all my OpenCL variables, command queues, kernels and programs, and made sure that they are all properly released...

Well I still found one (tiny) memory leak in mmc code:

Source https://stackoverflow.com/questions/61091039

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install psrecord

You can install using 'pip install psrecord' or download it from GitHub, PyPI.
You can use psrecord like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: