Pympler

v1.1

A development tool to measure, monitor and analyze the memory behavior of Python objects. For more information about how to use this package see README

Latest version published 4 months ago

License: Apache-2.0

PyPI

GitHub

Package Health Score

83 / 100

security
No known security issues
popularity
Influential project
maintenance
Healthy
community
Sustainable

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Popularity

Influential project

GitHub Stars: 1.21K
Forks: 89
Contributors: 30

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package Pympler, we found that it has been starred 1,210 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Jun 28, 2024
Direct Vulnerabilities: 0
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0
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0
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0
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Indirect Vulnerabilities: 0
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0
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0
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License Risk: 0
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

Apache-2.0

Security Policy

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Maintenance

Healthy

Commit Frequency

Open Issues: 48
Open PR: 12
Last Release: 4 months ago
Last Commit: 4 months ago

Further analysis of the maintenance status of Pympler based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Healthy.

We found that Pympler demonstrates a positive version release cadence with at least one new version released in the past 12 months.

As a healthy sign for on-going project maintenance, we found that the GitHub repository had at least 1 pull request or issue interacted with by the community.

Community

Sustainable

Readme: Yes
Contributing.md: No
Code of Conduct: No
Contributors: 30
Funding: No

With more than 10 contributors for the Pympler repository, this is possibly a sign for a growing and inviting community.

We found a way for you to contribute to the project! Looks like Pympler is missing a Code of Conduct.

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Package

Python Versions Compatibility: >=3.6

Age: 16 years
Latest Release: 4 months ago
Dependencies: 0 Direct
Versions: 18
Maintainers: 2
Wheels: OS Independent

Not sure how to use Pympler?

To help you get started, we've collected the most common ways that Pympler is being used within popular public projects.

lrq3000 / pyFileFixity / pyFileFixity / lib / profilers / visual / pympler / refgraph.py View on Github

def _get_graphviz_data(self):
        """
        Emit a graph representing the connections between the objects described
        within the metadata list. The text representation can be transformed to
        a graph with graphviz. Returns a string.
        """
        s = []
        header = '// Process this file with graphviz\n'
        s.append( header)
        s.append('digraph G {\n')
        s.append('    node [shape=box];\n')
        for md in self.metadata:
            label = trunc(md.str, 48).replace('"', "'")
            extra = ''
            if md.type == 'instancemethod':
                extra = ', color=red'
            elif md.type == 'frame':
                extra = ', color=orange'
            s.append('    "X%s" [ label = "%s\\n%s" %s ];\n' % \
                (hex(md.id)[1:], label, md.type, extra))
        for e in self.edges:
            extra = ''
            if e.label == '__dict__':
                extra = ',weight=100'
            s.append('    X%s -> X%s [label="%s"%s];\n' % \
                (hex(e.src)[1:], hex(e.dst)[1:], e.label, extra))

        s.append('}\n')
        return "".join(s)

View more ways to use Pympler

README for pympler

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.

Pympler is written entirely in Python, with no dependencies to external libraries on Linux and MacOS. On Windows, pywin32 is required.

Installation from PyPI

To install the latest version of Pympler from the Python package index run:

pip install Pympler

Installation from source

Before installing Pympler, try it with your Python version:

python setup.py try

If any errors are reported, check whether your Python version is supported. Pympler is written entirely in Python, with no dependencies other than standard Python modules and libraries. Pympler works with Python 3.6, 3.7, 3.8, 3.9, 3.10, 3.11 and 3.12.

For a system-wide installation from source run:

pip install .

Test the installed Pympler package:

python setup.py test

Usage

The usage of pympler is described in the documentation. It is available either in this distribution at doc/index.html or you can read it online.

Contributing

You can post wishes, bug reports or patches at our issue tracker or write an email to pympler-dev@googlegroups.com.

FAQs

What is Pympler?

A development tool to measure, monitor and analyze the memory behavior of Python objects. Visit Snyk Advisor to see a full health score report for Pympler, including popularity, security, maintenance & community analysis.

Is Pympler popular?

The python package Pympler receives a total of 419,375 weekly downloads. As such, Pympler popularity was classified as an influential project. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is Pympler well maintained?

We found that Pympler demonstrated a healthy version release cadence and project activity. It has a community of 30 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is Pympler safe to use?

The python package Pympler was scanned for known vulnerabilities and missing license, and no issues were found. Thus the package was deemed as safe to use. See the full health analysis review.

Last updated on 8 November-2024, at 08:38 (UTC).

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