Metadata-Version: 2.1
Name: NAG-PyPOP
Version: 0.3.2
Summary: Python notebook support for POP metrics and reports
Home-page: https://github.com/numericalalgorithmsgroup/pypop.git
Author: Numerical Algorithms Group
Author-email: phil.tooley@nag.co.uk
License: UNKNOWN
Description: # PyPOP
        
        Documentation: https://numericalalgorithmsgroup.github.io/pypop/doc.html
        
        A python package for calculating POP metrics from application profiles, primarily designed for
        literate programming using Jupyter notebooks.
        
        PyPOP currently consumes Extrae `*.prv` traces, but is designed with a view to adding support for
        additional formats.
        
        ## Requirements
        
          * [Extrae] (for trace capture)
          * [Paraver/Paramedir] (for trace analysis)
          * [Dimemas] *optional* (for ideal network analysis)
          * [Numpy]
          * [Pandas]
        
        [Extrae]: https://tools.bsc.es/extrae
        [Paraver/Paramedir]: https://tools.bsc.es/paraver#batchprocessing
        [Dimemas]: https://tools.bsc.es/dimemas
        [Numpy]: https://numpy.org/
        [Pandas]: https://pandas.pydata.org/
        
        
        ``Paramedir`` and ``Dimemas`` must be available on the system PATH (Linux ``$PATH`` or Windows
        ``%PATH%`` variables) so that they can be found by PyPOP.
        
        ## Installation
        
        PyPOP itself can be installed using the `pip` package manager:
        
        ```bash
        $ pip install [--user] NAG-PyPOP
        ```
        
        The optional `--user` directive instructs pip to install to the users home directory instead of the
        system site package directory.
        
        **N.B: Some linux distributions are still shipping Python2 alongside Python3. PyPOP requires
        Python3 and so you may need to install using the `pip3` command rather than the `pip` command.**
        
        Note that the [Extrae] tool is needed to collect application traces and the [Paraver/Paramedir] and
        [Dimemas] tools must be installed for trace Analysis.
        
        ## Usage
        
        Jupyter notebooks are intended to be the primary interface to PyPOP.  This guide uses several
        example notebooks to demonstrate the core functionality of PyPOP for calculation of the POP Metrics
        as well as advanced analysis of trace files.
        
        PyPOP comes with example notebooks. These are located in the examples directory, which can be
        found using the `pypop.examples` module:
        
        ```bash
        $ python -m pypop.examples
        /home/phil/repos/pypop/pypop/examples
        ```
        
        Copy these to directory where you have read permissions, e.g.
        
        ```bash
          $ cp -vr $(python -m pypop.examples) $HOME/pypop_examples
        ```
        
        These notebooks demonstrate usage of the main elements of the package.
        
        See the [quickstart] guide and [API documentation] for more detail on usage.
        
        [quickstart]: https://numericalalgorithmsgroup.github.io/pypop/quickstart.html
        [API documentation]: https://numericalalgorithmsgroup.github.io/pypop/api/pypop.html
        
        Copyright (c) 2019, Numerical Algorithms Group Ltd.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
