Extend jupyterlab-lsp¶
Note: the API is likely to change in the future; your suggestions are welcome!
How to add a new LSP feature?¶
Features (as well as other parts of the frontend) reuse the JupyterLab plugins system. Each plugin is a TypeScript package exporting one or more JupyterFrontEndPlugin
s (see the JupyterLab extesion developer tutorial for an overview). Each feature has to register itself with the
FeatureManager
(which is provided after requesting ILSPFeatureManager
token) using register(options: IFeatureOptions)
method.
Your feature specification should follow the IFeature
interface, which can be divided into three major parts:
editorIntegrationFactory
: constructors for the feature-CodeEditor integrators (implementing theIFeatureEditorIntegration
interface), one for each supported CodeEditor (e.g. CodeMirror or Monaco); for CodeMirror integration you can base your feature integration on the abstractCodeMirrorIntegration
class.labIntegration
: an optional object integrating feature with the JupyterLab interfaceoptional fields for easy integration of some of the common JupyterLab systems, such as:
settings system
commands system (including context menu)
For further integration with the JupyterLab, you can request additional JupyterLab tokens (consult JupyterLab documentation on core tokens).
How to override the default implementation of a feature?¶
You can specify a list of extensions to be disabled the the feature manager passing their plugin identifiers in supersedes
field of IFeatureOptions
.
How to integrate a new code editor implementation?¶
CodeMirrorEditor
code editor is supported by default, but any JupyterLab editor implementing the CodeEditor.IEditor
interface can be adapted for the use with the LSP extension. To add your custom code editor (e.g. Monaco) after implementing a CodeEditor.IEditor
interface wrapper (which you would have anyways for the JupyterLab integration), you need to also implement a virtual editor (IVirtualEditor
interface) for it.
Why virtual editor?¶
The virtual editor takes multiple instances of your editor (e.g. in a notebook) and makes them act like a single editor. For example, when “onKeyPress” event is bound on the VirtualEditor instance, it should be bound onto each actual code editor; this allows the features to be implemented without the knowledge about the number of editor instances on the page.
How to register the implementation?¶
A virtualEditorManager
will be provided if you request ILSPVirtualEditorManager
token; use registerEditorType(options: IVirtualEditorType<IEditor>)
method passing a name that you will also use to identify the code editor, the editor class, and your VirtualEditor constructor.
How to integrate a new DocumentWidget
?¶
JupyterLab editor widgets (such as Notebook or File Editor) implement IDocumentWidget
interface. Each such widget has to adapted by a WidgetAdapter
to enable its use with the LSP extension. The role of the WidgetAdapter
is to extract the document metadata (language, mimetype) and the underlying code editor (e.g. CodeMirror or Monaco) instances so that other parts of the LSP extension can interface with them without knowing about the implementation details of the DocumentWidget
(or even about the existence of a Notebook construct!).
Your custom WidgetAdapter
implementation has to register itself with WidgetAdapterManager
(which can be requested with ILSPAdapterManager
token), calling registerAdapterType(options: IAdapterTypeOptions)
method. Among the options, in addition to the custom WidgetAdapter
, you need to provide a tracker (IWidgetTracker
) which will notify the extension via a signal when a new instance of your document widget is getting created.
How to add a custom magic or foreign extractor?¶
It is now possible to register custom code replacements using ILSPCodeOverridesManager
token and to register custom foreign code extractors using ILSPCodeExtractorsManager
token, however this API is considered provisional and subject to change.
Future plans for transclusions handling¶
We will strive to make it possible for kernels to register their custom syntax/code transformations easily, but the frontend API will remain available for the end-users who write their custom syntax modifications with actionable side-effects (e.g. a custom IPython magic which copies a variable from the host document to the embedded document).
How to add custom icons for the completer?¶
Prepare the icons in the SVG format (we use 16 x 16 pixels, but you should be fine with up to 24 x 24). You can load them for webpack in typescript using imports if you include a
typings.d.ts
file with the following content:
typescript declare module '*.svg' { const script: string; export default script; }
in your src/
. You should probably keep the icons in your style/
directory.
Prepare
CompletionKind
→IconSvgString
mapping for the light (and optionally dark) theme, implementing theICompletionIconSet
interface. We have an additionalKernel
completion kind that is used for completions provided by kernel that had no recognizable type provided.Provide all other metadata required by the
ICompletionTheme
interface and register it onILSPCompletionThemeManager
instance usingregister_theme()
method.Provide any additional CSS styling targeting the JupyterLab completer elements inside of
.lsp-completer-theme-{id}
, e.g..lsp-completer-theme-material .jp-Completer-icon svg
for the material theme. Remember to include the styles by importing the in one of the source files.
For an example of a complete theme see theme-vscode.
Extend jupyter-lsp¶
Language Server Specs¶
Language Server Specs can be configured by Jupyter users, or distributed by third parties as python or JSON files. Since we’d like to see as many Language Servers work out of the box as possible, consider contributing a spec, if it works well for you!
Message Listeners¶
Message listeners may choose to receive LSP messages immediately after being received from the client (e.g. jupyterlab-lsp
) or a language server. All listeners of a message are scheduled concurrently, and the message is passed along once all listeners return (or fail). This allows listeners to, for example, modify files on disk before the language server reads them.
If a listener is going to perform an expensive activity that shouldn’t block delivery of a message, a non-blocking technique like IOLoop.add_callback and/or a queue should be used.
Add a Listener with entry_points
¶
Listeners can be added via entry_points by a package installed in the same environment as notebook
:
## setup.cfg
[options.entry_points]
jupyter_lsp_listener_all_v1 =
some-unique-name = some.module:some_function
jupyter_lsp_listener_client_v1 =
some-other-unique-name = some.module:some_other_function
jupyter_lsp_listener_server_v1 =
yet-another-unique-name = some.module:yet_another_function
At present, the entry point names generally have no impact on functionality aside from logging in the event of an error on import.
Add a Listener with Jupyter Configuration¶
Listeners can be added via traitlets
configuration, e.g.
## jupyter_notebook_config.jsons
{
'LanguageServerManager':
{
'all_listeners': ['some.module.some_function'],
'client_listeners': ['some.module.some_other_function'],
'server_listeners': ['some.module.yet_another_function'],
},
}
Add a listener with the Python API¶
lsp_message_listener
can be used as a decorator, accessed as part of a serverextension
.
This listener receives all messages from the client and server, and prints them out.
from jupyter_lsp import lsp_message_listener
def load_jupyter_server_extension(nbapp):
@lsp_message_listener("all")
async def my_listener(scope, message, language_server, manager):
print("received a {} {} message from {}".format(
scope, message["method"], language_server
))
scope
is one of client
, server
or all
, and is required.
Listener options¶
Fine-grained controls are available as part of the Python API. Pass these as named arguments to lsp_message_listener
.
language_server
: a regular expression of language serversmethod
: a regular expression of LSP JSON-RPC method names