Metadata-Version: 2.1
Name: nbtutor
Version: 1.0.4
Summary: Visualize Python code execution in Jupyter Notebook cells
Home-page: https://github.com/lgpage/nbtutor
Author: Logan Page
Author-email: page.lg@gmail.com
License: BSD 3-Clause
Keywords: ipython jupyter notebook python tutor visualize code exection
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Framework :: IPython
Classifier: Programming Language :: Python
Classifier: License :: OSI Approved :: BSD License
License-File: LICENCE.rst

Nbtutor
=======

Visualize Python code execution (line-by-line) in `Jupyter Notebook
<http://jupyter.org>`__ cells. Inspired by `Online Python Tutor
<http://pythontutor.com>`__.

.. figure:: usage.gif
   :alt:

   Usage

Install
-------

Note: installing directly off this repo won't work, as we don't ship the built
JavaScript and CSS assets. See more about `developing <#develop>`__ below.

``pip``
~~~~~~~

.. code:: shell

    pip install nbtutor
    jupyter nbextension install --overwrite --py nbtutor
    jupyter nbextension enable --py nbtutor

``conda``
~~~~~~~~~

.. code:: shell

    conda install -c conda-forge nbtutor

Usage (Jupyter Notebook)
------------------------

First load the ``nbtutor`` IPython kernel extension at top of the Notebook by
executing the following magic in a ``CodeCell``:

.. code:: python

    %load_ext nbtutor

Then to visualize the execute of code in a ``CodeCell`` add the
following magic to the top of the ``CodeCell`` and execute it again:

.. code:: python

    %%nbtutor


Optional arguments
~~~~~~~~~~~~~~~~~~

There are also optional arguments that can be used with the cell magic:

-  Reset the IPython user namespace

   .. code:: python

       %%nbtutor -r/--reset

-  Suppress the confirmation message from ``-r/--reset``

   .. code:: python

       %%nbtutor -r/--reset -f/--force

-  Render primitive objects inline

   .. code:: python

       %%nbtutor -i/--inline

-  Specify the maximum frame depth to visualize (default: 1)

   .. code:: python

       %%nbtutor -d/--depth N

-  Specify the number of significant digits for floats (default: 3)

   .. code:: python

       %%nbtutor --digits D

-  Specify the maximum number of elements to visualize for "sequence"
   type objects (default: 5)

   .. code:: python

       %%nbtutor --max_size S

-  Step through all frames (including frames from other cells and other
   global scopes altogether)

   .. code:: python

       %%nbtutor --step_all

-  Expand ``numpy`` arrays to show underlying data

   .. code:: python

       %%nbtutor --expand_arrays

-  No inlined keys, attributes, or primitive objects

   .. code:: python

       %%nbtutor --nolies


Notes
-----

-  Visualizing ``numpy`` arrays is somewhat experimental. Simple
   ``ndarray``\ s and simple slicing should work, but anything beyond
   that is un-tested.
-  If you find a problem please feel free to submit an
   `issue <https://github.com/lgpage/nbtutor/issues>`__


Develop
-------

This assumes you have cloned this repository locally:

.. code:: shell

    git clone https://github.com/lgpage/nbtutor.git
    cd nbtutor


Repo architecture
~~~~~~~~~~~~~~~~~

The ``nbtutor`` nbextension is built from ``./src`` into
``./nbtutor/static/nbtutor`` with: - ``less`` for style - ``es6`` (via
``babel``) for javascript - ``browserify`` for packaging

The ``nbtutor`` ipython kernel extension (magics) is stored in the
``./nbtutor/ipython`` folder

Build tools are stored in the ``./tools`` folder.


Getting started
~~~~~~~~~~~~~~~

You'll need conda installed, either from
`Anaconda <https://www.continuum.io/downloads>`__ or
`miniconda <http://conda.pydata.org/miniconda.html>`__. You can create a
Python development environment named ``nbtutor`` from
``./environment.yml``.

.. code:: shell

    conda create -n nbtutor python=YOUR_FAVORITE_PYTHON
    conda env update
    source activate nbtutor

We use ``npm`` for ``node.js`` dependencies, so then run:

.. code:: shell

    npm install

Finally, you are ready to build the assets with:

.. code:: shell

    npm run build


Installing the nbextension
~~~~~~~~~~~~~~~~~~~~~~~~~~

To ensure that you always get the right assets (for development),
install the nbextension with the ``symlink`` options:

.. code:: shell

    python setup.py develop
    jupyter nbextension install --overwrite --symlink --sys-prefix --py nbtutor
    jupyter nbextension enable --sys-prefix --py nbtutor


