profilehooks | Python decorators | Monitoring library

by mgedmin Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | profilehooks Summary

profilehooks is a Python library typically used in Performance Management, Monitoring applications. profilehooks has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Python decorators for profiling/tracing/timing a single function

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profilehooks has a low active ecosystem.

It has 278 star(s) with 28 fork(s). There are 10 watchers for this library.

It had no major release in the last 6 months.

There are 8 open issues and 9 have been closed. On average issues are closed in 71 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of profilehooks is current.

Quality

profilehooks has 0 bugs and 8 code smells.

Security

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

profilehooks code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

profilehooks is licensed under the MIT License. This license is Permissive.

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

Reuse

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

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

profilehooks saves you 268 person hours of effort in developing the same functionality from scratch.

It has 649 lines of code, 73 functions and 3 files.

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

Top functions reviewed by kandi - BETA

kandi has reviewed profilehooks and discovered the below as its top functions. This is intended to give you an instant insight into profilehooks implemented functionality, and help decide if they suit your requirements.

Print out the traceback
Count the number of blank lines in the source code
Mark the source at a given line number
Identify function name
Find source line number of source lines
Return a set of docstrings from a file
Print out the program exit
Prints profiling statistics
Prints a message to stdout
Read file contents

Get all kandi verified functions for this library.

profilehooks Key Features

No Key Features are available at this moment for profilehooks.

profilehooks Examples and Code Snippets

No Code Snippets are available at this moment for profilehooks.

Community Discussions

Trending Discussions on profilehooks

Python profiling, imports (and specially __init__) is what seems to take the most time

QUESTION

Python profiling, imports (and specially __init__) is what seems to take the most time

Asked 2018-May-27 at 17:27

I have a script that seemed to run slow and that i profiled using cProfile (and visualisation tool KCacheGrind)

It seems that what is taking almost 90% of the runtime is the import sequence, and especially the running of the _ _ init _ _.py files...

Here a screenshot of the KCacheGrind output (sorry for attaching an image...)

I am not very familiar with how the import sequence works in python ,so maybe i got something confused... I also placed _ _ init _ _.py files in everyone of my custom made packages, not sure if that was what i should have done.

Anyway, if anyone has any hint, greatly appreciated!

EDIT: additional picture when function are sorted by self:

EDIT2:

here the code attached, for more clarity for the answerers:

...

ANSWER

Answered 2018-May-27 at 17:27

No. You are conflating cumulative time with time spent in the top-level code of the __init__.py file itself. The top-level code calls other methods, and those together take a lot of time.

Look at the self column instead to find where all that time is being spent. Also see What is the difference between tottime and cumtime in a python script profiled with cProfile?, the incl. column is the cumulative time, self is the total time.

I'd just filter out all the entries; the Python project has already made sure those paths are optimised.

However, your second screenshot does show that in your profiling run, all that your Python code busied itself with was loading bytecode for modules to import (the marshal module provides the Python bytecode serialisation implementation). Either the Python program did nothing but import modules and no other work was done, or it is using some form of dynamic import that is loading a large number of modules or is otherwise ignoring the normal module caches and reloading the same module(s) repeatedly.

You can profile import times using Python 3.7's new -X importtime command-line switch, or you could use a dedicated import-profiler to find out why imports take such a long time.

Source https://stackoverflow.com/questions/50554374

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

Vulnerabilities

No vulnerabilities reported

Install profilehooks

You can download it from GitHub.
You can use profilehooks 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 .

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