Metadata-Version: 1.1
Name: darshan
Version: 3.3.0.3
Summary: Python tools to interact with darshan log records of HPC applications.
Home-page: https://www.mcs.anl.gov/research/projects/darshan/
Author: UNKNOWN
Author-email: UNKNOWN
License: UNKNOWN
Description: =======================
        PyDarshan Documentation
        =======================
        
        Python utilities to interact with Darshan log records of HPC applications.
        PyDarshan requires darshan-utils version 3.3 or higher to be installed.
        
        Features
        --------
        
        * Darshan Report Object for common interactive analysis tasks
        * Low-level CFFI bindings for efficient access to darshan log files
        * Plots typically found in the darshan reports (matplotlib)
        * Bundled with darshan-utils while allowing site's darshan-utils to take precedence
        
        
        Usage
        -----
        
        For examples and Jupyter notebooks to get started with pydarshan make sure
        to check out the `examples` subdirectory.
        
        A brief examples showing some of the basic functionality is the following::
        
            import darshan
        
            # Open darshan log
            report = darshan.DarshanReport('example.darshan', read_all=False)
        
            # Load some report data
            report.mod_read_all_records('POSIX')
            report.mod_read_all_records('MPI-IO')
            # or fetch all
            report.read_all_generic_records()
        
            # ...    
            # Generate summaries for currently loaded data
            # Note: aggregations are still experimental and have to be activated:
            darshan.enable_experimental()
            report.summarize()
        
        
        
        Installation
        ------------
        
        To install in most cases the following will work::
        
            pip install --user darshan
        
        For alternative installation instructions and installation from source refer to <docs/install.rst>
        
        
        Testing
        -------
        
        Targets for various tests are included in the makefile. To run the normal 
        test suite use::
        
            make test
        
        Or to test against different version of Python using Tox::
        
            make test-all
        
        Coverage tests can be performed using::
        
            make coverage
        
        Conformance to PEPs can be tested using flake8 via::
        
            make lint
        
        
        Documentation
        -------------
        
        Documentation for the python bindings is generated seperatedly from the 
        darshan-utils C library in the interest of using Sphinx. After installing the
        developement requirements using `pip install -r requirements_dev.txt` the
        documentation can be build using make as follows::
        
            pip install -r requirements_dev.txt
            make docs
        
        File List
        ---------
        
        * darshan::
            core darshan python module code
        * devel::
            scripts for building python wheel
        * docs::
            markdown documentation used by sphinx to auto-generate HTML RTD style doc
        * examples::
            Jupyter notebooks showing pydarshan usage with log files
        * tests::
            pydarshan specific test cases
        * requirements.txt::
            pip requirement file for minimum set of depednencies
        * requirements_dev.txt::
            pip requirement file for depednencies needed to run development tools
        * setup.py::
            python file for building/generating pydarshan package
        * setup.cfg::
            input for setup.py
        * MANIFEST.in::
            input files for setup.py package
        * tox.ini::
            input for tox which runs the automated testing
        
Keywords: darshan
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
