ipytablewidgets 0.1.0

A set of widgets to help facilitate reuse of large tables across widgets

ipytablewidgets

NB: End to end tests use Galata framework.

Traitlets and widgets to efficiently data tables (e.g. Pandas DataFrame) using the jupyter notebook

ipytablewidgets is a set of widgets and traitlets to reuse of large tables such as Pandas DataFrames across different widgets, and different packages.

Installation

NB: Currently only the development mode installation is available.

Installation with miniconda/anaconda (recommended):

For now, the easiest way to install ipytablewidgets is as follows:

1. Clone this repository then cd into it

2. Install the latest version of miniconda (if not yet done)

3. Create a conda environment with the following command:

conda env create -f environment.yml # [-n customized-env-name]

NB: by default it will create an environment called ipytablewidgets. If you want, you can change this name in the file environment.yml before runninng the command or by using the option-n customized-env-name. Remember to reflect this change in the following commands.

4. Activate this environment:

conda activate ipytablewidgets

5. Execute the following commands (this step is not necessary if you don't need TableWidget but only the traitlet TableType, see the Tables section for more details):

jupyter nbextension install --py --symlink --sys-prefix ipytablewidgets
jupyter nbextension enable --py --sys-prefix ipytablewidgets

Or, if you use jupyterlab:

jupyter labextension install @jupyter-widgets/jupyterlab-manager
jupyter labextension install .

Tables

The main widget for tables is the TableWidget class. It has a main trait: A table. This table's main purpose is simply to be a standardized way of transmitting table data from the kernel to the frontend, and to allow the data to be reused across any number of other widgets, but with only a single sync across the network.

import pandas as pd
from ipytableidgets import TableWidget, PandasAdapter, serialization

@widgets.register
class MyWidget(DOMWidget):
    """
    My widget needing a table
    """
    _view_name = Unicode('MyWidgetView').tag(sync=True)
    _model_name = Unicode('MyWidgetModel').tag(sync=True)
    ...
    data = Instance(TableWidget).tag(sync=True, **serialization)
    def __init__(self, wg, **kwargs):
        self.data = wg
        super().__init__(**kwargs)

df = pd.DataFrame({'a': [1,2], 'b': [3.5, 4.5], 'c': ['foo','bar'])
table_widget = TableWidget(PandasAdapter(df))
my_widget = MyWidget(table_widget)

You can see EchoTableWidget which is a more realistic example, currently used for end to end testing and demo.

Or, if you prefer to use the TableType traitlet directly:

from ipytablewidgets import serialization, TableType

@widgets.register
class MyWidget(DOMWidget):
    """
    My widget needing a table
    """
    ...
    data = TableType(None).tag(sync=True, **serialization)

Developers

Developers should consider using ipytablewidgets because:

• It gives readily accessible syncing of table data using the binary transfer protocol of ipywidgets.
• It gives compression methods speifically suited for columnar data.
• It avoids duplication of common code among different extensions, ensuring that bugs discovered for one extension gets fixed in all.

Overview

The major parts of ipyablewidgets are:

• Traits/Widgets definitions
• Adapters to convert tables to those traits
• Serializers/deserializers to send the data across the network
• Apropriate javascript handling and representation of the data