113 lines
3.3 KiB
Ruby
113 lines
3.3 KiB
Ruby
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# frozen_string_literal: true
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module IpynbDiff
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require 'oj'
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class InvalidNotebookError < StandardError
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end
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# Returns a markdown version of the Jupyter Notebook
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class Transformer
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require 'json'
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require 'yaml'
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require 'output_transformer'
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require 'symbolized_markdown_helper'
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require 'symbol_map'
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require 'transformed_notebook'
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include SymbolizedMarkdownHelper
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@include_frontmatter = true
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def initialize(include_frontmatter: true, hide_images: false)
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@include_frontmatter = include_frontmatter
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@hide_images = hide_images
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@out_transformer = OutputTransformer.new(hide_images)
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end
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def validate_notebook(notebook)
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notebook_json = Oj::Parser.usual.parse(notebook)
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return notebook_json if notebook_json.key?('cells')
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raise InvalidNotebookError
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rescue EncodingError, Oj::ParseError, JSON::ParserError
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raise InvalidNotebookError
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end
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def transform(notebook)
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return TransformedNotebook.new unless notebook
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notebook_json = validate_notebook(notebook)
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transformed = transform_document(notebook_json)
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symbol_map = SymbolMap.parse(notebook)
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TransformedNotebook.new(transformed, symbol_map)
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end
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def transform_document(notebook)
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symbol = JsonSymbol.new('.cells')
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transformed_blocks = notebook['cells'].map.with_index do |cell, idx|
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decorate_cell(transform_cell(cell, notebook, symbol / idx), cell, symbol / idx)
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end
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transformed_blocks.prepend(transform_metadata(notebook)) if @include_frontmatter
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transformed_blocks.flatten
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end
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def decorate_cell(rows, cell, symbol)
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tags = cell['metadata']&.fetch('tags', [])
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type = cell['cell_type'] || 'raw'
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[
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_(symbol, %(%% Cell type:#{type} id:#{cell['id']} tags:#{tags&.join(',')})),
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_,
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rows,
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_
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]
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end
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def transform_cell(cell, notebook, symbol)
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cell['cell_type'] == 'code' ? transform_code_cell(cell, notebook, symbol) : transform_text_cell(cell, symbol)
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end
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def transform_code_cell(cell, notebook, symbol)
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[
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_(symbol / 'source', %(``` #{notebook.dig('metadata', 'kernelspec', 'language') || ''})),
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symbolize_array(symbol / 'source', cell['source'], &:rstrip),
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_(nil, '```'),
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transform_outputs(cell['outputs'], symbol)
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]
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end
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def transform_outputs(outputs, symbol)
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transformed = outputs.map
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.with_index { |output, i| @out_transformer.transform(output, symbol / ['outputs', i]) }
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.compact
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.map { |el| [_, el] }
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[
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transformed.empty? ? [] : [_, _(symbol / 'outputs', '%% Output')],
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transformed
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]
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end
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def transform_text_cell(cell, symbol)
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symbolize_array(symbol / 'source', cell['source'], &:rstrip)
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end
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def transform_metadata(notebook_json)
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as_yaml = {
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'jupyter' => {
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'kernelspec' => notebook_json['metadata']['kernelspec'],
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'language_info' => notebook_json['metadata']['language_info'],
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'nbformat' => notebook_json['nbformat'],
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'nbformat_minor' => notebook_json['nbformat_minor']
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}
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}.to_yaml
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as_yaml.split("\n").map { |l| _(nil, l) }.append(_(nil, '---'), _)
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end
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end
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end
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