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[READ ONLY] Refer to gitlab repo for updated version - Total Knowledge of I/O Reference Implementation. Please see wiki for contribution guidelines.

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TOKIO - Total Knowledge of I/O

pytokio is a Python implementation of the TOKIO framework. The full documentation can be found at https://pytokio.readthedocs.io/en/latest/

Installation

pytokio has a single site-specific configuration file:

tokio/site.json

which you may wish to edit and configure to match your site's file system names and the naming conventions. Most of these parameters are only required for the higher-level convenience tools, so editing this is not essential to getting started.

Once you've edited tokio/site.json to your liking, simply do

$ pip install .

or

$ python setup.py install --prefix=/path/to/installdir

Alternatively, pytokio does not technically require a proper installation and it is sufficient to clone the git repo, add it to PYTHONPATH, and import tokio from there. If you wish to use the pytokio CLI tools without properly installing pytokio, also add the git repo's bin/ subdirectory to PATH.

pytokio supports both Python 2.7 and 3.6 and, at minimum, requires h5py, numpy, and pandas. The full requirements are listed in requirements.txt.

Quick Start

pytokio is a Python library that provides the APIs necessary to develop analysis routines that combine data from different I/O monitoring tools that may be available in your data center. However several simple utilities are included to demonstrate how pytokio can be used in the bin/ directory.

Additionally, the pytokio git repository contains several other examples and tests to demonstrate the ways in which pytokio can be used.

  • examples/ contains standalone Jupyter notebooks and scripts that illustrate different aspects of the pytokio API that do useful things. They are designed to run on NERSC systems via https://jupyter.nersc.gov/.
  • tests/ contains unit and integration tests for the pytokio library and the scripts bundled in /bin

Copyright and License

Total Knowledge of I/O Copyright (c) 2017, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved.

If you have questions about your rights to use or distribute this software, please contact Berkeley Lab's Innovation & Partnerships Office at [email protected].

NOTICE. This Software was developed under funding from the U.S. Department of Energy and the U.S. Government consequently retains certain rights. As such, the U.S. Government has been granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, distribute copies to the public, prepare derivative works, and perform publicly and display publicly, and to permit other to do so.

For license terms, please see LICENSE.md included in this repository.

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