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

Using pip:

pip install ipytablewidgets

Development installation

The first step requires the following three commands to be run (requires yarn and jupyterlab>=3):

$ git clone https://github.com/progressivis/ipytablewidgets.git
$ cd ipytablewidgets
$ pip install -e .

The development of extensions for jupyter notebook and jupyter lab requires JavaScript code to be modified in-place. For this reason, lab and notebook extensions need to be configured this way:

• For jupyter notebook:

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

• For jupyter lab:

  $ jupyter labextension develop . --overwrite
  

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