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Data Profiler

Project description

The data_profiler module extends the standard CPython profiler by recording the functions’ signatures. For NumPy array types this includes the dtype attribute and the array’s shape.

It also adds functionality to visualise the augmented profile table in snakeviz.

This module is a direct port of Accelerate.profiler available in Anaconda Accelerate.

Documentation is located here

Installing

The easiest way to install data_profiler and get updates is by using the Anaconda Distribution

#> conda install data_profiler

To compile, test and run from source, it is recommended to create a conda environment containing the following:

  • numpy
  • numba >=0.26.0
  • snakeviz
  • jupyter
  • pytest

for instructions on how to do this see the conda documentation, specifically the section on managing environments.

Once a suitable environment is activated, installation achieved simply by running:

#> python setup.py install

and the installation can be tested with:

#> pytest

Documentation

Documentation is located here.

Building Documentation

It is also possible to build a local copy of the documentation from source. This requires GNU Make and sphinx (available via conda).

Documentation is stored in the doc folder, and should be built with:

#> make SPHINXOPTS=-Wn clean html

This ensures that the documentation renders without errors. If errors occur, they can all be seen at once by building with:

#> make SPHINXOPTS=-n clean html

However, these errors should all be fixed so that building with -Wn is possible prior to merging any documentation changes or updates.

Continuous Integration

Continuous integration is provided by Travis CI, the current build state is available here.

Project details


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