scooby 0.3.0

A Great Dane turned Python environment detective

Scooby

A Great Dane turned Python environment detective

This is a lightweight toolset to easily report your Python environment's package versions and hardware resources.

Install from PyPI:

pip install scooby

Scooby has HTML formatting for Jupyter notebooks and rich text formatting for just about every other environment. We designed this module to be lightweight such that it could easily be added as a dependency to Python projects for environment reporting when debugging. Simply add scooby to your dependencies and implement a function to have scooby report on the aspects of the environment you care most about.

If scooby is unable to detect aspects of an environment that you'd like to know, please share this with us as a feature requests or pull requests.

The scooby reporting is derived from the versioning-scripts created by Dieter Werthmüller for empymod, emg3d, and the SimPEG framework. It was heavily inspired by ipynbtools.py from qutip and watermark.py. This package has been altered to create a lightweight implementation so that it can easily be used as an environment reporting tool in any Python library with minimal impact.

Usage

Solving Mysteries

Are you struggling with the mystery of whether or not code is being executed in IPython, Jupyter, or normal Python? Try using some of Scooby's investigative functions to solve these kinds of mysteries:

import scooby

if scooby.in_ipykernel():
    # Do Jupyter stuff
elif scooby.in_ipython():
    # Do IPython stuff
else:
    # Do normal, boring Python stuff

Generating Reports

Use Scooby's Report objects. These objects have representation methods implemented so that if outputted, they show a nicely formatted report but you could also capture the report as an object itself.

>>> import scooby
>>> scooby.Report()

--------------------------------------------------------------------------------
  Date: Sun Jun 30 12:51:42 2019 MDT

            Darwin : OS
                12 : CPU(s)
            x86_64 : Machine
             64bit : Architecture
           32.0 GB : RAM
            Python : Environment

  Python 3.7.3 | packaged by conda-forge | (default, Mar 27 2019, 15:43:19)
  [Clang 4.0.1 (tags/RELEASE_401/final)]

            1.16.3 : numpy
             1.3.0 : scipy
             7.5.0 : IPython
             3.1.0 : matplotlib
             0.2.2 : scooby

  Intel(R) Math Kernel Library Version 2018.0.3 Product Build 20180406 for
  Intel(R) 64 architecture applications
--------------------------------------------------------------------------------

But you can also add addtional packages too if you'd like via the addtional keyword argument:

>>> scooby.Report(additional='pyvista')

--------------------------------------------------------------------------------
  Date: Sun Jun 30 12:52:14 2019 MDT

            Darwin : OS
                12 : CPU(s)
            x86_64 : Machine
             64bit : Architecture
           32.0 GB : RAM
            Python : Environment

  Python 3.7.3 | packaged by conda-forge | (default, Mar 27 2019, 15:43:19)
  [Clang 4.0.1 (tags/RELEASE_401/final)]

            0.20.4 : pyvista
            1.16.3 : numpy
             1.3.0 : scipy
             7.5.0 : IPython
             3.1.0 : matplotlib
             0.2.2 : scooby

  Intel(R) Math Kernel Library Version 2018.0.3 Product Build 20180406 for
  Intel(R) 64 architecture applications
--------------------------------------------------------------------------------

Or maybe you want a whole bunch of additional packages:

>>> scooby.Report(additional=['pyvista', 'vtk', 'appdirs',])

--------------------------------------------------------------------------------
  Date: Sun Jun 30 12:52:37 2019 MDT

            Darwin : OS
                12 : CPU(s)
            x86_64 : Machine
             64bit : Architecture
           32.0 GB : RAM
            Python : Environment

  Python 3.7.3 | packaged by conda-forge | (default, Mar 27 2019, 15:43:19)
  [Clang 4.0.1 (tags/RELEASE_401/final)]

            0.20.4 : pyvista
             8.2.0 : vtk
             1.4.3 : appdirs
            1.16.3 : numpy
             1.3.0 : scipy
             7.5.0 : IPython
             3.1.0 : matplotlib
             0.2.2 : scooby

  Intel(R) Math Kernel Library Version 2018.0.3 Product Build 20180406 for
  Intel(R) 64 architecture applications
--------------------------------------------------------------------------------

Want to add a package to investigate but aren't sure if it is present, simply define the optional list in the arguments. Note that the default libraries of numpy, scipy, IPython, and matplotlib (and scooby) are defaults for optional argument, so you might want to put those in the core argument if you care about those.

>>> scooby.Report(core=['numpy', 'matplotlib'], optional=['foo', ])

--------------------------------------------------------------------------------
  Date: Sun Jun 30 12:52:58 2019 MDT

            Darwin : OS
                12 : CPU(s)
            x86_64 : Machine
             64bit : Architecture
           32.0 GB : RAM
            Python : Environment

  Python 3.7.3 | packaged by conda-forge | (default, Mar 27 2019, 15:43:19)
  [Clang 4.0.1 (tags/RELEASE_401/final)]

            1.16.3 : numpy
             3.1.0 : matplotlib

  Intel(R) Math Kernel Library Version 2018.0.3 Product Build 20180406 for
  Intel(R) 64 architecture applications
--------------------------------------------------------------------------------

Since the foo package wasn't found and it's optional, nothing is reported. But what if you need some sort of error message that a package wasn't found? Then add your package to the additional list and Scooby will report it, just with a NA:

>>> scooby.Report(additional=['foo',])

--------------------------------------------------------------------------------
  Date: Sun Jun 30 12:53:20 2019 MDT

            Darwin : OS
                12 : CPU(s)
            x86_64 : Machine
             64bit : Architecture
           32.0 GB : RAM
            Python : Environment

  Python 3.7.3 | packaged by conda-forge | (default, Mar 27 2019, 15:43:19)
  [Clang 4.0.1 (tags/RELEASE_401/final)]

  Could not import : foo
            1.16.3 : numpy
             1.3.0 : scipy
             7.5.0 : IPython
             3.1.0 : matplotlib
             0.2.2 : scooby

  Intel(R) Math Kernel Library Version 2018.0.3 Product Build 20180406 for
  Intel(R) 64 architecture applications
--------------------------------------------------------------------------------

And you can also sort the packages alphabetically with the sort argument:

>>> scooby.Report(additional=['pyvista', 'vtk', 'appdirs',], sort=True)

--------------------------------------------------------------------------------
  Date: Sun Jun 30 12:54:31 2019 MDT

            Darwin : OS
                12 : CPU(s)
            x86_64 : Machine
             64bit : Architecture
           32.0 GB : RAM
            Python : Environment

  Python 3.7.3 | packaged by conda-forge | (default, Mar 27 2019, 15:43:19)
  [Clang 4.0.1 (tags/RELEASE_401/final)]

             1.4.3 : appdirs
             7.5.0 : IPython
             3.1.0 : matplotlib
            1.16.3 : numpy
            0.20.4 : pyvista
             1.3.0 : scipy
             0.2.2 : scooby
             8.2.0 : vtk

  Intel(R) Math Kernel Library Version 2018.0.3 Product Build 20180406 for
  Intel(R) 64 architecture applications
--------------------------------------------------------------------------------

Optional Requirements

The following is a list of optional requirements and their purpose:

• psutil: report total RAM in GB
• mkl: report Intel(R) Math Kernel Library version