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Split up ipynb serializer file
This commit is contained in:
Rob Lourens
42
extensions/ipynb/src/common.ts
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42
extensions/ipynb/src/common.ts
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@@ -0,0 +1,42 @@
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/*---------------------------------------------------------------------------------------------
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* Copyright (c) Microsoft Corporation. All rights reserved.
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* Licensed under the MIT License. See License.txt in the project root for license information.
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*--------------------------------------------------------------------------------------------*/
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import { nbformat } from '@jupyterlab/coreutils';
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/**
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* Metadata we store in VS Code cell output items.
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* This contains the original metadata from the Jupyter outputs.
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*/
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export interface CellOutputMetadata {
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/**
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* Cell output metadata.
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*/
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metadata?: any;
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/**
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* Transient data from Jupyter.
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*/
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transient?: {
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/**
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* This is used for updating the output in other cells.
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* We don't know of other properties, but this is definitely used.
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*/
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display_id?: string;
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} & any;
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/**
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* Original cell output type
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*/
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outputType: nbformat.OutputType | string;
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executionCount?: nbformat.IExecuteResult['ExecutionCount'];
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/**
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* Whether the original Mime data is JSON or not.
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* This properly only exists in metadata for NotebookCellOutputItems
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* (this is something we have added)
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*/
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__isJson?: boolean;
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}
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347
extensions/ipynb/src/deserializers.ts
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347
extensions/ipynb/src/deserializers.ts
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@@ -0,0 +1,347 @@
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/*---------------------------------------------------------------------------------------------
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* Copyright (c) Microsoft Corporation. All rights reserved.
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* Licensed under the MIT License. See License.txt in the project root for license information.
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*--------------------------------------------------------------------------------------------*/
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import { nbformat } from '@jupyterlab/coreutils';
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import { extensions, NotebookCellData, NotebookCellExecutionSummary, NotebookCellKind, NotebookCellOutput, NotebookCellOutputItem, NotebookData } from 'vscode';
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import { CellOutputMetadata } from './common';
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const jupyterLanguageToMonacoLanguageMapping = new Map([
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['c#', 'csharp'],
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['f#', 'fsharp'],
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['q#', 'qsharp'],
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['c++11', 'c++'],
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['c++12', 'c++'],
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['c++14', 'c++']
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]);
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export function getPreferredLanguage(metadata?: nbformat.INotebookMetadata) {
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const jupyterLanguage =
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metadata?.language_info?.name ||
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(metadata?.kernelspec as any)?.language;
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// Default to python language only if the Python extension is installed.
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const defaultLanguage = extensions.getExtension('ms-python.python') ? 'python' : 'plaintext';
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// Note, whatever language is returned here, when the user selects a kernel, the cells (of blank documents) get updated based on that kernel selection.
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return translateKernelLanguageToMonaco(jupyterLanguage || defaultLanguage);
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}
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function translateKernelLanguageToMonaco(language: string): string {
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language = language.toLowerCase();
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if (language.length === 2 && language.endsWith('#')) {
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return `${language.substring(0, 1)}sharp`;
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}
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return jupyterLanguageToMonacoLanguageMapping.get(language) || language;
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}
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const orderOfMimeTypes = [
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'application/vnd.*',
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'application/vdom.*',
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'application/geo+json',
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'application/x-nteract-model-debug+json',
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'text/html',
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'application/javascript',
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'image/gif',
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'text/latex',
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'text/markdown',
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'image/png',
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'image/svg+xml',
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'image/jpeg',
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'application/json',
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'text/plain'
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];
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function sortOutputItemsBasedOnDisplayOrder(outputItems: NotebookCellOutputItem[]): NotebookCellOutputItem[] {
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return outputItems.sort((outputItemA, outputItemB) => {
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const isMimeTypeMatch = (value: string, compareWith: string) => {
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if (value.endsWith('.*')) {
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value = value.substr(0, value.indexOf('.*'));
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}
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return compareWith.startsWith(value);
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};
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const indexOfMimeTypeA = orderOfMimeTypes.findIndex(mime => isMimeTypeMatch(outputItemA.mime, mime));
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const indexOfMimeTypeB = orderOfMimeTypes.findIndex(mime => isMimeTypeMatch(outputItemB.mime, mime));
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return indexOfMimeTypeA - indexOfMimeTypeB;
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});
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}
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enum CellOutputMimeTypes {
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error = 'application/vnd.code.notebook.error',
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stderr = 'application/vnd.code.notebook.stderr',
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stdout = 'application/vnd.code.notebook.stdout'
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}
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const textMimeTypes = ['text/plain', 'text/markdown', CellOutputMimeTypes.stderr, CellOutputMimeTypes.stdout];
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function concatMultilineString(str: string | string[], trim?: boolean): string {
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const nonLineFeedWhiteSpaceTrim = /(^[\t\f\v\r ]+|[\t\f\v\r ]+$)/g;
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if (Array.isArray(str)) {
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let result = '';
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for (let i = 0; i < str.length; i += 1) {
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const s = str[i];
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if (i < str.length - 1 && !s.endsWith('\n')) {
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result = result.concat(`${s}\n`);
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} else {
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result = result.concat(s);
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}
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}
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// Just trim whitespace. Leave \n in place
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return trim ? result.replace(nonLineFeedWhiteSpaceTrim, '') : result;
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}
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return trim ? str.toString().replace(nonLineFeedWhiteSpaceTrim, '') : str.toString();
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}
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function convertJupyterOutputToBuffer(mime: string, value: unknown): NotebookCellOutputItem {
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if (!value) {
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return NotebookCellOutputItem.text('', mime);
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}
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try {
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if (
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(mime.startsWith('text/') || textMimeTypes.includes(mime)) &&
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(Array.isArray(value) || typeof value === 'string')
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) {
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const stringValue = Array.isArray(value) ? concatMultilineString(value) : value;
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return NotebookCellOutputItem.text(stringValue, mime);
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} else if (mime.startsWith('image/') && typeof value === 'string' && mime !== 'image/svg+xml') {
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// Images in Jupyter are stored in base64 encoded format.
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// VS Code expects bytes when rendering images.
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if (typeof Buffer !== 'undefined' && typeof Buffer.from === 'function') {
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return new NotebookCellOutputItem(Buffer.from(value, 'base64'), mime);
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} else {
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const data = Uint8Array.from(atob(value), c => c.charCodeAt(0));
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return new NotebookCellOutputItem(data, mime);
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}
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} else if (typeof value === 'object' && value !== null && !Array.isArray(value)) {
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return NotebookCellOutputItem.text(JSON.stringify(value), mime);
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} else {
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// For everything else, treat the data as strings (or multi-line strings).
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value = Array.isArray(value) ? concatMultilineString(value) : value;
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return NotebookCellOutputItem.text(value as string, mime);
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}
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} catch (ex) {
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return NotebookCellOutputItem.error(ex);
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}
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}
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/**
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* Metadata we store in VS Code cells.
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* This contains the original metadata from the Jupyuter cells.
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*/
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interface CellMetadata {
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/**
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* Stores attachments for cells.
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*/
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attachments?: nbformat.IAttachments;
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/**
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* Stores cell metadata.
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*/
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metadata?: Partial<nbformat.ICellMetadata>;
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}
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function getNotebookCellMetadata(cell: nbformat.IBaseCell): CellMetadata {
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// We put this only for VSC to display in diff view.
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// Else we don't use this.
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const propertiesToClone: (keyof CellMetadata)[] = ['metadata', 'attachments'];
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const custom: CellMetadata = {};
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propertiesToClone.forEach((propertyToClone) => {
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if (cell[propertyToClone]) {
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custom[propertyToClone] = JSON.parse(JSON.stringify(cell[propertyToClone]));
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}
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});
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return custom;
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}
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function getOutputMetadata(output: nbformat.IOutput): CellOutputMetadata {
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// Add on transient data if we have any. This should be removed by our save functions elsewhere.
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const metadata: CellOutputMetadata = {
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outputType: output.output_type
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};
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if (output.transient) {
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metadata.transient = output.transient;
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}
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switch (output.output_type as nbformat.OutputType) {
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case 'display_data':
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case 'execute_result':
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case 'update_display_data': {
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metadata.executionCount = output.execution_count;
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metadata.metadata = output.metadata ? JSON.parse(JSON.stringify(output.metadata)) : {};
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break;
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}
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default:
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break;
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}
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return metadata;
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}
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function translateDisplayDataOutput(
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output: nbformat.IDisplayData | nbformat.IDisplayUpdate | nbformat.IExecuteResult
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): NotebookCellOutput {
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// Metadata could be as follows:
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// We'll have metadata specific to each mime type as well as generic metadata.
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/*
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IDisplayData = {
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output_type: 'display_data',
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data: {
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'image/jpg': '/////'
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'image/png': '/////'
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'text/plain': '/////'
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},
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metadata: {
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'image/png': '/////',
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'background': true,
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'xyz': '///
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}
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}
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*/
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const metadata = getOutputMetadata(output);
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const items: NotebookCellOutputItem[] = [];
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if (output.data) {
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for (const key in output.data) {
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items.push(convertJupyterOutputToBuffer(key, output.data[key]));
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}
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}
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return new NotebookCellOutput(sortOutputItemsBasedOnDisplayOrder(items), metadata);
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}
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function translateErrorOutput(output?: nbformat.IError): NotebookCellOutput {
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output = output || { output_type: 'error', ename: '', evalue: '', traceback: [] };
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return new NotebookCellOutput(
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[
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NotebookCellOutputItem.error({
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name: output?.ename || '',
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message: output?.evalue || '',
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stack: (output?.traceback || []).join('\n')
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})
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],
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{ ...getOutputMetadata(output), originalError: output }
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);
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}
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function translateStreamOutput(output: nbformat.IStream): NotebookCellOutput {
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const value = concatMultilineString(output.text);
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const item = output.name === 'stderr' ? NotebookCellOutputItem.stderr(value) : NotebookCellOutputItem.stdout(value);
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return new NotebookCellOutput([item], getOutputMetadata(output));
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}
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const cellOutputMappers = new Map<nbformat.OutputType, (output: any) => NotebookCellOutput>();
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cellOutputMappers.set('display_data', translateDisplayDataOutput);
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cellOutputMappers.set('execute_result', translateDisplayDataOutput);
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cellOutputMappers.set('update_display_data', translateDisplayDataOutput);
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cellOutputMappers.set('error', translateErrorOutput);
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cellOutputMappers.set('stream', translateStreamOutput);
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function jupyterCellOutputToCellOutput(output: nbformat.IOutput): NotebookCellOutput {
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/**
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* Stream, `application/x.notebook.stream`
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* Error, `application/x.notebook.error-traceback`
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* Rich, { mime: value }
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*
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* outputs: [
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new vscode.NotebookCellOutput([
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new vscode.NotebookCellOutputItem('application/x.notebook.stream', 2),
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new vscode.NotebookCellOutputItem('application/x.notebook.stream', 3),
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]),
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new vscode.NotebookCellOutput([
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new vscode.NotebookCellOutputItem('text/markdown', '## header 2'),
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new vscode.NotebookCellOutputItem('image/svg+xml', [
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"<svg baseProfile=\"full\" height=\"200\" version=\"1.1\" width=\"300\" xmlns=\"http://www.w3.org/2000/svg\">\n",
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" <rect fill=\"blue\" height=\"100%\" width=\"100%\"/>\n",
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" <circle cx=\"150\" cy=\"100\" fill=\"green\" r=\"80\"/>\n",
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" <text fill=\"white\" font-size=\"60\" text-anchor=\"middle\" x=\"150\" y=\"125\">SVG</text>\n",
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"</svg>"
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]),
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]),
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]
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*
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*/
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const fn = cellOutputMappers.get(output.output_type as nbformat.OutputType);
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let result: NotebookCellOutput;
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if (fn) {
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result = fn(output);
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} else {
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result = translateDisplayDataOutput(output as any);
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}
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return result;
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}
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function createNotebookCellDataFromRawCell(cell: nbformat.IRawCell): NotebookCellData {
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const cellData = new NotebookCellData(NotebookCellKind.Code, concatMultilineString(cell.source), 'raw');
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cellData.outputs = [];
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cellData.metadata = { custom: getNotebookCellMetadata(cell) };
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return cellData;
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}
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function createNotebookCellDataFromMarkdownCell(cell: nbformat.IMarkdownCell): NotebookCellData {
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const cellData = new NotebookCellData(
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NotebookCellKind.Markup,
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concatMultilineString(cell.source),
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'markdown'
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);
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cellData.outputs = [];
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cellData.metadata = { custom: getNotebookCellMetadata(cell) };
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return cellData;
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}
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function createNotebookCellDataFromCodeCell(cell: nbformat.ICodeCell, cellLanguage: string): NotebookCellData {
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const cellOutputs = Array.isArray(cell.outputs) ? cell.outputs : [];
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const outputs = cellOutputs.map(jupyterCellOutputToCellOutput);
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const hasExecutionCount = typeof cell.execution_count === 'number' && cell.execution_count > 0;
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const source = concatMultilineString(cell.source);
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const executionSummary: NotebookCellExecutionSummary = hasExecutionCount
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? { executionOrder: cell.execution_count as number }
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: {};
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const cellData = new NotebookCellData(NotebookCellKind.Code, source, cellLanguage);
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cellData.outputs = outputs;
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cellData.metadata = { custom: getNotebookCellMetadata(cell) };
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cellData.executionSummary = executionSummary;
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return cellData;
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}
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function createNotebookCellDataFromJupyterCell(
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cellLanguage: string,
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cell: nbformat.IBaseCell
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): NotebookCellData | undefined {
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switch (cell.cell_type) {
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case 'raw': {
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return createNotebookCellDataFromRawCell(cell as nbformat.IRawCell);
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}
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case 'markdown': {
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return createNotebookCellDataFromMarkdownCell(cell as nbformat.IMarkdownCell);
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}
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case 'code': {
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return createNotebookCellDataFromCodeCell(cell as nbformat.ICodeCell, cellLanguage);
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}
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}
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return;
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}
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/**
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* Converts a NotebookModel into VS Code format.
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*/
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export function jupyterNotebookModelToNotebookData(
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notebookContent: Partial<nbformat.INotebookContent>,
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||||
preferredLanguage: string
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): NotebookData {
|
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const notebookContentWithoutCells = { ...notebookContent, cells: [] };
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if (!notebookContent.cells || notebookContent.cells.length === 0) {
|
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throw new Error('Notebook content is missing cells');
|
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}
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const cells = notebookContent.cells
|
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.map(cell => createNotebookCellDataFromJupyterCell(preferredLanguage, cell))
|
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.filter((item): item is NotebookCellData => !!item);
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||||
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||||
const notebookData = new NotebookData(cells);
|
||||
notebookData.metadata = { custom: notebookContentWithoutCells };
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||||
return notebookData;
|
||||
}
|
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@@ -4,7 +4,7 @@
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*--------------------------------------------------------------------------------------------*/
|
||||
|
||||
import * as vscode from 'vscode';
|
||||
import { NotebookSerializer } from './serializer';
|
||||
import { NotebookSerializer } from './notebookSerializer';
|
||||
|
||||
export function activate(context: vscode.ExtensionContext) {
|
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context.subscriptions.push(vscode.workspace.registerNotebookSerializer('jupyter-notebook', new NotebookSerializer(context), {
|
||||
|
||||
@@ -7,7 +7,8 @@ import type { nbformat } from '@jupyterlab/coreutils';
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import * as detectIndent from 'detect-indent';
|
||||
import * as vscode from 'vscode';
|
||||
import { defaultNotebookFormat } from './constants';
|
||||
import { createJupyterCellFromNotebookCell, getPreferredLanguage, jupyterNotebookModelToNotebookData, pruneCell } from './helpers';
|
||||
import { getPreferredLanguage, jupyterNotebookModelToNotebookData } from './deserializers';
|
||||
import { createJupyterCellFromNotebookCell, pruneCell } from './serializers';
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import * as fnv from '@enonic/fnv-plus';
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||||
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||||
export class NotebookSerializer implements vscode.NotebookSerializer {
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||||
@@ -4,69 +4,10 @@
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||||
*--------------------------------------------------------------------------------------------*/
|
||||
|
||||
import { nbformat } from '@jupyterlab/coreutils';
|
||||
import { extensions, NotebookCellData, NotebookCellExecutionSummary, NotebookCellKind, NotebookCellOutput, NotebookCellOutputItem, NotebookData } from 'vscode';
|
||||
|
||||
const jupyterLanguageToMonacoLanguageMapping = new Map([
|
||||
['c#', 'csharp'],
|
||||
['f#', 'fsharp'],
|
||||
['q#', 'qsharp'],
|
||||
['c++11', 'c++'],
|
||||
['c++12', 'c++'],
|
||||
['c++14', 'c++']
|
||||
]);
|
||||
|
||||
export function getPreferredLanguage(metadata?: nbformat.INotebookMetadata) {
|
||||
const jupyterLanguage =
|
||||
metadata?.language_info?.name ||
|
||||
(metadata?.kernelspec as any)?.language;
|
||||
|
||||
// Default to python language only if the Python extension is installed.
|
||||
const defaultLanguage = extensions.getExtension('ms-python.python') ? 'python' : 'plaintext';
|
||||
|
||||
// Note, whatever language is returned here, when the user selects a kernel, the cells (of blank documents) get updated based on that kernel selection.
|
||||
return translateKernelLanguageToMonaco(jupyterLanguage || defaultLanguage);
|
||||
}
|
||||
import { NotebookCellData, NotebookCellKind, NotebookCellOutput } from 'vscode';
|
||||
import { CellOutputMetadata } from './common';
|
||||
|
||||
const textDecoder = new TextDecoder();
|
||||
function translateKernelLanguageToMonaco(language: string): string {
|
||||
language = language.toLowerCase();
|
||||
if (language.length === 2 && language.endsWith('#')) {
|
||||
return `${language.substring(0, 1)}sharp`;
|
||||
}
|
||||
return jupyterLanguageToMonacoLanguageMapping.get(language) || language;
|
||||
}
|
||||
|
||||
const orderOfMimeTypes = [
|
||||
'application/vnd.*',
|
||||
'application/vdom.*',
|
||||
'application/geo+json',
|
||||
'application/x-nteract-model-debug+json',
|
||||
'text/html',
|
||||
'application/javascript',
|
||||
'image/gif',
|
||||
'text/latex',
|
||||
'text/markdown',
|
||||
'image/png',
|
||||
'image/svg+xml',
|
||||
'image/jpeg',
|
||||
'application/json',
|
||||
'text/plain'
|
||||
];
|
||||
|
||||
function sortOutputItemsBasedOnDisplayOrder(outputItems: NotebookCellOutputItem[]): NotebookCellOutputItem[] {
|
||||
return outputItems.sort((outputItemA, outputItemB) => {
|
||||
const isMimeTypeMatch = (value: string, compareWith: string) => {
|
||||
if (value.endsWith('.*')) {
|
||||
value = value.substr(0, value.indexOf('.*'));
|
||||
}
|
||||
return compareWith.startsWith(value);
|
||||
};
|
||||
const indexOfMimeTypeA = orderOfMimeTypes.findIndex(mime => isMimeTypeMatch(outputItemA.mime, mime));
|
||||
const indexOfMimeTypeB = orderOfMimeTypes.findIndex(mime => isMimeTypeMatch(outputItemB.mime, mime));
|
||||
return indexOfMimeTypeA - indexOfMimeTypeB;
|
||||
});
|
||||
}
|
||||
|
||||
|
||||
enum CellOutputMimeTypes {
|
||||
error = 'application/vnd.code.notebook.error',
|
||||
@@ -76,57 +17,6 @@ enum CellOutputMimeTypes {
|
||||
|
||||
const textMimeTypes = ['text/plain', 'text/markdown', CellOutputMimeTypes.stderr, CellOutputMimeTypes.stdout];
|
||||
|
||||
function concatMultilineString(str: string | string[], trim?: boolean): string {
|
||||
const nonLineFeedWhiteSpaceTrim = /(^[\t\f\v\r ]+|[\t\f\v\r ]+$)/g;
|
||||
if (Array.isArray(str)) {
|
||||
let result = '';
|
||||
for (let i = 0; i < str.length; i += 1) {
|
||||
const s = str[i];
|
||||
if (i < str.length - 1 && !s.endsWith('\n')) {
|
||||
result = result.concat(`${s}\n`);
|
||||
} else {
|
||||
result = result.concat(s);
|
||||
}
|
||||
}
|
||||
|
||||
// Just trim whitespace. Leave \n in place
|
||||
return trim ? result.replace(nonLineFeedWhiteSpaceTrim, '') : result;
|
||||
}
|
||||
return trim ? str.toString().replace(nonLineFeedWhiteSpaceTrim, '') : str.toString();
|
||||
}
|
||||
|
||||
function convertJupyterOutputToBuffer(mime: string, value: unknown): NotebookCellOutputItem {
|
||||
if (!value) {
|
||||
return NotebookCellOutputItem.text('', mime);
|
||||
}
|
||||
try {
|
||||
if (
|
||||
(mime.startsWith('text/') || textMimeTypes.includes(mime)) &&
|
||||
(Array.isArray(value) || typeof value === 'string')
|
||||
) {
|
||||
const stringValue = Array.isArray(value) ? concatMultilineString(value) : value;
|
||||
return NotebookCellOutputItem.text(stringValue, mime);
|
||||
} else if (mime.startsWith('image/') && typeof value === 'string' && mime !== 'image/svg+xml') {
|
||||
// Images in Jupyter are stored in base64 encoded format.
|
||||
// VS Code expects bytes when rendering images.
|
||||
if (typeof Buffer !== 'undefined' && typeof Buffer.from === 'function') {
|
||||
return new NotebookCellOutputItem(Buffer.from(value, 'base64'), mime);
|
||||
} else {
|
||||
const data = Uint8Array.from(atob(value), c => c.charCodeAt(0));
|
||||
return new NotebookCellOutputItem(data, mime);
|
||||
}
|
||||
} else if (typeof value === 'object' && value !== null && !Array.isArray(value)) {
|
||||
return NotebookCellOutputItem.text(JSON.stringify(value), mime);
|
||||
} else {
|
||||
// For everything else, treat the data as strings (or multi-line strings).
|
||||
value = Array.isArray(value) ? concatMultilineString(value) : value;
|
||||
return NotebookCellOutputItem.text(value as string, mime);
|
||||
}
|
||||
} catch (ex) {
|
||||
return NotebookCellOutputItem.error(ex);
|
||||
}
|
||||
}
|
||||
|
||||
export function createJupyterCellFromNotebookCell(
|
||||
vscCell: NotebookCellData
|
||||
): nbformat.IRawCell | nbformat.IMarkdownCell | nbformat.ICodeCell {
|
||||
@@ -186,39 +76,6 @@ function splitMultilineString(source: nbformat.MultilineString): string[] {
|
||||
return [];
|
||||
}
|
||||
|
||||
/**
|
||||
* Metadata we store in VS Code cell output items.
|
||||
* This contains the original metadata from the Jupyuter Outputs.
|
||||
*/
|
||||
interface CellOutputMetadata {
|
||||
/**
|
||||
* Cell output metadata.
|
||||
*/
|
||||
metadata?: any;
|
||||
/**
|
||||
* Transient data from Jupyter.
|
||||
*/
|
||||
transient?: {
|
||||
/**
|
||||
* This is used for updating the output in other cells.
|
||||
* We don't know of others properties, but this is definitely used.
|
||||
*/
|
||||
display_id?: string;
|
||||
} & any;
|
||||
/**
|
||||
* Original cell output type
|
||||
*/
|
||||
outputType: nbformat.OutputType | string;
|
||||
executionCount?: nbformat.IExecuteResult['ExecutionCount'];
|
||||
/**
|
||||
* Whether the original Mime data is JSON or not.
|
||||
* This properly only exists in metadata for NotebookCellOutputItems
|
||||
* (this is something we have added)
|
||||
*/
|
||||
__isJson?: boolean;
|
||||
}
|
||||
|
||||
|
||||
function translateCellDisplayOutput(output: NotebookCellOutput): JupyterOutput {
|
||||
const customMetadata = output.metadata as CellOutputMetadata | undefined;
|
||||
let result: JupyterOutput;
|
||||
@@ -512,207 +369,3 @@ function fixupOutput(output: nbformat.IOutput): nbformat.IOutput {
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
function getNotebookCellMetadata(cell: nbformat.IBaseCell): CellMetadata {
|
||||
// We put this only for VSC to display in diff view.
|
||||
// Else we don't use this.
|
||||
const propertiesToClone: (keyof CellMetadata)[] = ['metadata', 'attachments'];
|
||||
const custom: CellMetadata = {};
|
||||
propertiesToClone.forEach((propertyToClone) => {
|
||||
if (cell[propertyToClone]) {
|
||||
custom[propertyToClone] = JSON.parse(JSON.stringify(cell[propertyToClone]));
|
||||
}
|
||||
});
|
||||
return custom;
|
||||
}
|
||||
function getOutputMetadata(output: nbformat.IOutput): CellOutputMetadata {
|
||||
// Add on transient data if we have any. This should be removed by our save functions elsewhere.
|
||||
const metadata: CellOutputMetadata = {
|
||||
outputType: output.output_type
|
||||
};
|
||||
if (output.transient) {
|
||||
metadata.transient = output.transient;
|
||||
}
|
||||
|
||||
switch (output.output_type as nbformat.OutputType) {
|
||||
case 'display_data':
|
||||
case 'execute_result':
|
||||
case 'update_display_data': {
|
||||
metadata.executionCount = output.execution_count;
|
||||
metadata.metadata = output.metadata ? JSON.parse(JSON.stringify(output.metadata)) : {};
|
||||
break;
|
||||
}
|
||||
default:
|
||||
break;
|
||||
}
|
||||
|
||||
return metadata;
|
||||
}
|
||||
|
||||
|
||||
function translateDisplayDataOutput(
|
||||
output: nbformat.IDisplayData | nbformat.IDisplayUpdate | nbformat.IExecuteResult
|
||||
): NotebookCellOutput {
|
||||
// Metadata could be as follows:
|
||||
// We'll have metadata specific to each mime type as well as generic metadata.
|
||||
/*
|
||||
IDisplayData = {
|
||||
output_type: 'display_data',
|
||||
data: {
|
||||
'image/jpg': '/////'
|
||||
'image/png': '/////'
|
||||
'text/plain': '/////'
|
||||
},
|
||||
metadata: {
|
||||
'image/png': '/////',
|
||||
'background': true,
|
||||
'xyz': '///
|
||||
}
|
||||
}
|
||||
*/
|
||||
const metadata = getOutputMetadata(output);
|
||||
const items: NotebookCellOutputItem[] = [];
|
||||
if (output.data) {
|
||||
for (const key in output.data) {
|
||||
items.push(convertJupyterOutputToBuffer(key, output.data[key]));
|
||||
}
|
||||
}
|
||||
|
||||
return new NotebookCellOutput(sortOutputItemsBasedOnDisplayOrder(items), metadata);
|
||||
}
|
||||
|
||||
function translateErrorOutput(output?: nbformat.IError): NotebookCellOutput {
|
||||
output = output || { output_type: 'error', ename: '', evalue: '', traceback: [] };
|
||||
return new NotebookCellOutput(
|
||||
[
|
||||
NotebookCellOutputItem.error({
|
||||
name: output?.ename || '',
|
||||
message: output?.evalue || '',
|
||||
stack: (output?.traceback || []).join('\n')
|
||||
})
|
||||
],
|
||||
{ ...getOutputMetadata(output), originalError: output }
|
||||
);
|
||||
}
|
||||
|
||||
function translateStreamOutput(output: nbformat.IStream): NotebookCellOutput {
|
||||
const value = concatMultilineString(output.text);
|
||||
const item = output.name === 'stderr' ? NotebookCellOutputItem.stderr(value) : NotebookCellOutputItem.stdout(value);
|
||||
return new NotebookCellOutput([item], getOutputMetadata(output));
|
||||
}
|
||||
|
||||
const cellOutputMappers = new Map<nbformat.OutputType, (output: any) => NotebookCellOutput>();
|
||||
cellOutputMappers.set('display_data', translateDisplayDataOutput);
|
||||
cellOutputMappers.set('execute_result', translateDisplayDataOutput);
|
||||
cellOutputMappers.set('update_display_data', translateDisplayDataOutput);
|
||||
cellOutputMappers.set('error', translateErrorOutput);
|
||||
cellOutputMappers.set('stream', translateStreamOutput);
|
||||
|
||||
function jupyterCellOutputToCellOutput(output: nbformat.IOutput): NotebookCellOutput {
|
||||
/**
|
||||
* Stream, `application/x.notebook.stream`
|
||||
* Error, `application/x.notebook.error-traceback`
|
||||
* Rich, { mime: value }
|
||||
*
|
||||
* outputs: [
|
||||
new vscode.NotebookCellOutput([
|
||||
new vscode.NotebookCellOutputItem('application/x.notebook.stream', 2),
|
||||
new vscode.NotebookCellOutputItem('application/x.notebook.stream', 3),
|
||||
]),
|
||||
new vscode.NotebookCellOutput([
|
||||
new vscode.NotebookCellOutputItem('text/markdown', '## header 2'),
|
||||
new vscode.NotebookCellOutputItem('image/svg+xml', [
|
||||
"<svg baseProfile=\"full\" height=\"200\" version=\"1.1\" width=\"300\" xmlns=\"http://www.w3.org/2000/svg\">\n",
|
||||
" <rect fill=\"blue\" height=\"100%\" width=\"100%\"/>\n",
|
||||
" <circle cx=\"150\" cy=\"100\" fill=\"green\" r=\"80\"/>\n",
|
||||
" <text fill=\"white\" font-size=\"60\" text-anchor=\"middle\" x=\"150\" y=\"125\">SVG</text>\n",
|
||||
"</svg>"
|
||||
]),
|
||||
]),
|
||||
]
|
||||
*
|
||||
*/
|
||||
const fn = cellOutputMappers.get(output.output_type as nbformat.OutputType);
|
||||
let result: NotebookCellOutput;
|
||||
if (fn) {
|
||||
result = fn(output);
|
||||
} else {
|
||||
result = translateDisplayDataOutput(output as any);
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
function createNotebookCellDataFromRawCell(cell: nbformat.IRawCell): NotebookCellData {
|
||||
const cellData = new NotebookCellData(NotebookCellKind.Code, concatMultilineString(cell.source), 'raw');
|
||||
cellData.outputs = [];
|
||||
cellData.metadata = { custom: getNotebookCellMetadata(cell) };
|
||||
return cellData;
|
||||
}
|
||||
function createNotebookCellDataFromMarkdownCell(cell: nbformat.IMarkdownCell): NotebookCellData {
|
||||
const cellData = new NotebookCellData(
|
||||
NotebookCellKind.Markup,
|
||||
concatMultilineString(cell.source),
|
||||
'markdown'
|
||||
);
|
||||
cellData.outputs = [];
|
||||
cellData.metadata = { custom: getNotebookCellMetadata(cell) };
|
||||
return cellData;
|
||||
}
|
||||
function createNotebookCellDataFromCodeCell(cell: nbformat.ICodeCell, cellLanguage: string): NotebookCellData {
|
||||
const cellOutputs = Array.isArray(cell.outputs) ? cell.outputs : [];
|
||||
const outputs = cellOutputs.map(jupyterCellOutputToCellOutput);
|
||||
const hasExecutionCount = typeof cell.execution_count === 'number' && cell.execution_count > 0;
|
||||
|
||||
const source = concatMultilineString(cell.source);
|
||||
|
||||
const executionSummary: NotebookCellExecutionSummary = hasExecutionCount
|
||||
? { executionOrder: cell.execution_count as number }
|
||||
: {};
|
||||
|
||||
const cellData = new NotebookCellData(NotebookCellKind.Code, source, cellLanguage);
|
||||
|
||||
cellData.outputs = outputs;
|
||||
cellData.metadata = { custom: getNotebookCellMetadata(cell) };
|
||||
cellData.executionSummary = executionSummary;
|
||||
return cellData;
|
||||
}
|
||||
|
||||
function createNotebookCellDataFromJupyterCell(
|
||||
cellLanguage: string,
|
||||
cell: nbformat.IBaseCell
|
||||
): NotebookCellData | undefined {
|
||||
switch (cell.cell_type) {
|
||||
case 'raw': {
|
||||
return createNotebookCellDataFromRawCell(cell as nbformat.IRawCell);
|
||||
}
|
||||
case 'markdown': {
|
||||
return createNotebookCellDataFromMarkdownCell(cell as nbformat.IMarkdownCell);
|
||||
}
|
||||
case 'code': {
|
||||
return createNotebookCellDataFromCodeCell(cell as nbformat.ICodeCell, cellLanguage);
|
||||
}
|
||||
}
|
||||
|
||||
return;
|
||||
}
|
||||
|
||||
/**
|
||||
* Converts a NotebookModel into VS Code format.
|
||||
*/
|
||||
export function jupyterNotebookModelToNotebookData(
|
||||
notebookContent: Partial<nbformat.INotebookContent>,
|
||||
preferredLanguage: string
|
||||
): NotebookData {
|
||||
const notebookContentWithoutCells = { ...notebookContent, cells: [] };
|
||||
if (!notebookContent.cells || notebookContent.cells.length === 0) {
|
||||
throw new Error('Notebook content is missing cells');
|
||||
}
|
||||
|
||||
const cells = notebookContent.cells
|
||||
.map(cell => createNotebookCellDataFromJupyterCell(preferredLanguage, cell))
|
||||
.filter((item): item is NotebookCellData => !!item);
|
||||
|
||||
const notebookData = new NotebookData(cells);
|
||||
notebookData.metadata = { custom: notebookContentWithoutCells };
|
||||
return notebookData;
|
||||
}
|
||||
Reference in New Issue
Block a user