Metadata-Version: 2.1
Name: NAG-PyPOP
Version: 0.3.5
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
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
License-File: LICENSE.md

# 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.


