Models

A few new names for information are introduced in scrapbook:

  • scraps: serializable data values and visualizations such as strings, lists of objects, pandas dataframes, charts, images, or data references.

  • notebook: a wrapped nbformat notebook object with extra methods for interacting with scraps.

  • scrapbook: a collection of notebooks with an interface for asking questions of the collection.

  • encoders: a registered translator of data to/from notebook storage formats.

Scrap

The scrap model houses a few key attributes in a tuple. Namely:

  • name: The name of the scrap

  • data: Any data captured by the scrapbook api call

  • encoder: The name of the encoder used to encode/decode data to/from the notebook

  • display: Any display data used by IPython to display visual content

Notebook

The Notebook object adheres to the nbformat’s json schema, allowing for access to its required fields.

nb = sb.read_notebook('notebook.ipynb')
nb.cells # The cells from the notebook
nb.metadata
nb.nbformat
nb.nbformat_minor

There’s a few additional methods provided, outlined in the API page (read_notebook API)

Scrapbook

A collection of Notebooks is called a Scrapbook. It allows for access the underlying notebooks and to perform data collection from the group as a whole.

# create a scrapbook named `book`
book = sb.read_notebooks('path/to/notebook/collection/')
# get the underlying notebooks as a list
book.notebooks # Or `book.values`

There’s a additional methods provided, outlined in the API page (read_notebooks API)

Encoder

Encoders are accessible by key names to Encoder objects registered against the encoders.registry object. To register new data encoders simply call:

from scrapbook.encoders import registry as encoder_registry
# add encoder to the registry
encoder_registry.register("custom_encoder_name", MyCustomEncoder())

The encode class must implement two methods, encode and decode:

class MyCustomEncoder(object):
    def encode(self, scrap):
        # scrap.data is any type, usually specific to the encoder name
        pass  # Return a `Scrap` with `data` type one of [None, list, dict, *six.integer_types, *six.string_types]

    def decode(self, scrap):
        # scrap.data is one of [None, list, dict, *six.integer_types, *six.string_types]
        pass  # Return a `Scrap` with `data` type as any type, usually specific to the encoder name

This can read transform scraps into a json object representing their contents or location and load those strings back into the original data objects.

For example, here is the code for a custom encoder that can save Altair charts by converting the chart to a dictionary as a part of the encoding process.

from scrapbook.encoders import registry as encoder_registry
import altair as alt

class AltairEncoder(object):
    def encode(self, scrap):
        # Here we assume the input to `sb.glue` is an Altair chart.
        scrap = scrap._replace(data=scrap.data.to_dict())
        return scrap

    def decode(self, scrap):
        scrap = scrap._replace(data=alt.Chart.from_dict(scrap.data))
        return scrap

# Register the encoder so that scrapbook can use it
encoder_registry.register("altair", AltairEncoder())
# Now we can use this encoder with `glue`
sb.glue('my_altair_chart', chart, 'altair')

text

A basic string storage format that saves data as python strings.

sb.glue("hello", "world", "text")

json

sb.glue("foo_json", {"foo": "bar", "baz": 1}, "json")

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Implementation Pending!