Documents#
JupyterLab can be extended in several ways:
Extensions (top level): Application extensions extend the functionality of JupyterLab itself, and we cover them in the Develop Extensions.
Document widget extensions (lower level): Document widget extensions extend the functionality of document widgets added to the application, and we cover them in this section.
For this section, the term ‘document’ refers to any visual thing that is backed by a file stored on disk (i.e. uses Contents API).
Overview of document architecture#
A ‘document’ in JupyterLab is represented by a model instance implementing the
IModel interface.
The model interface is intentionally fairly small, and concentrates on representing
the data in the document and signaling changes to that data. Each model has an
associated IContext
instance as well. The context for a model is the bridge between the internal data
of the document, stored in the model, and the file metadata and operations possible
on the file, such as save and revert. Since many objects will need both the context
and the model, the context contains a reference to the model as its .model attribute.
A single file path can have multiple different models (and hence different contexts) representing the file. For example, a notebook can be opened with a notebook model and with a text model. Different models for the same file path do not directly communicate with each other.
Models contain an instance of ISharedDocument that acts as data storage for the model’s content. As of JupyterLab 4, the default data storage implementation is a YDocument based on Yjs, a high-performance CRDT for building collaborative applications. Both the interface and the implementation are provided by the package @jupyter/ydoc.
DocumentWidget represent
a view of a document model. There can be multiple document widgets associated with
a single document model, and they naturally stay in sync with each other since they
are views on the same underlying data model.
The DocumentRegistry
is where document types and factories are registered. Plugins can
require a document registry instance and register their content types
and providers.
The DocumentManager
uses the Document Registry to create models and widgets for documents.
The Document Manager handles the lifecycle of documents for the application.
Document Registry#
Document widget extensions in the JupyterLab application can register:
file types
model factories for specific file types
widget factories for specific model factories
widget extension factories
Note
We recommend you to look at the document example to help understanding a practical case.
Widget Factories#
Widget Factories (see DocumentRegistry addWidgetFactory method) create a widget for a given file.
If multiple widget factories are associated with the same file type, the user will be able to choose one of them using “Open with” list in the context menu of the file browser.
Added in version 4.4: Widget factories now can accept a contentProviderId parameter allowing the widgets to modify the way the content is provisioned. For example, using a custom provider enables fetching the document content in chunks rather than all at once.
Example
The notebook widget factory that creates NotebookPanel widgets.
Model Factories#
Model Factories (see DocumentRegistry addModelFactory method) create a model for a given file.
Models are generally differentiated by the contents options used to fetch the model (e.g. text, base64, notebook).
Widget Extension Factories#
Widget Extension Factories (see DocumentRegistry addWidgetExtension method) add additional functionality to a widget type. An extension instance is
created for each widget instance, enabling the extension to add
functionality to each widget or observe the widget and/or its context.
Examples
The ipywidgets extension that is created for NotebookPanel widgets.
Adding a button to the toolbar of each NotebookPanel widget.
File Types#
File Types (see DocumentRegistry addFileType method) add a new file type to be understood through a mimetype and file extensions within JupyterLab.
Document Models#
IModel instances are created by the model factories and passed to widget factories and widget
extension factories. Models are the way in which we interact with the
data of a document. For a simple text file, we typically only use the
to/fromString() methods. A more complex document like a Notebook
contains more points of interaction like the Notebook metadata.
Document Contexts#
IContext instances are created by the Document Manager and passed to widget factories and
widget extensions. The context contains the model as one of its
properties so that we can pass a single object around.
They are used to provide an abstracted interface to the session and
Contents API from @jupyterlab/services for the given model. They can
be shared between widgets.
The reason for a separate context and model is so that it is easy to create model factories and the heavy lifting of the context is left to the Document Manager. Contexts are not meant to be subclassed or re-implemented. Instead, the contexts are intended to be the glue between the document model and the wider application.
Document Manager#
The Document Manager handles:
document models
document contexts
The File Browser uses the Document Manager to open documents and manage them.