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.