./devel/py-Pympler, Python memory analysis tool

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Branch: CURRENT, Version: 0.5, Package name: py27-Pympler-0.5, Maintainer: pkgsrc-users

Pympler is a development tool to measure, monitor and analyze the memory
behavior of Python objects in a running Python application.

By pympling a Python application, detailed insight in the size and the
lifetime of Python objects can be obtained. Undesirable or unexpected
runtime behavior like memory bloat and other “pymples” can easily be
identified.

Pympler integrates three previously separate projects into a single,
comprehensive profiling tool. Asizeof provides basic size information for
one or several Python objects, muppy is used for on-line monitoring of a
Python application and the class tracker provides off-line analysis of
the lifetime of selected Python objects. A web profiling frontend exposes
process statistics, garbage visualisation and class tracker statistics.


Required to run:
[lang/python27]

Required to build:
[pkgtools/cwrappers]

Master sites:

SHA1: 227d47d25a3cbd46f08ffb8ed5520fa9566ba43a
RMD160: 1dcfef01c7720a677c4b5692d98c9fa78ee79136
Filesize: 166.402 KB

Version history: (Expand)


CVS history: (Expand)


   2018-03-14 10:00:17 by Adam Ciarcinski | Files touched by this commit (1)
Log message:
Clean-up
   2018-03-02 16:59:04 by Joerg Sonnenberger | Files touched by this commit (4)
Log message:
Add py-Pympler-0.5:

Pympler is a development tool to measure, monitor and analyze the memory
behavior of Python objects in a running Python application.

By pympling a Python application, detailed insight in the size and the
lifetime of Python objects can be obtained. Undesirable or unexpected
runtime behavior like memory bloat and other “pymples” can easily be
identified.

Pympler integrates three previously separate projects into a single,
comprehensive profiling tool. Asizeof provides basic size information for
one or several Python objects, muppy is used for on-line monitoring of a
Python application and the class tracker provides off-line analysis of
the lifetime of selected Python objects. A web profiling frontend exposes
process statistics, garbage visualisation and class tracker statistics.