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151 lines
6.3 KiB
Python
151 lines
6.3 KiB
Python
"""A preprocessor that extracts all of the outputs from the
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notebook file. The extracted outputs are returned in the 'resources' dictionary.
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"""
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# Copyright (c) IPython Development Team.
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# Distributed under the terms of the Modified BSD License.
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import json
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import os
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import sys
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from binascii import a2b_base64
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from mimetypes import guess_extension
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from textwrap import dedent
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from traitlets import Set, Unicode
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from .base import Preprocessor
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def guess_extension_without_jpe(mimetype):
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"""
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This function fixes a problem with '.jpe' extensions
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of jpeg images which are then not recognised by latex.
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For any other case, the function works in the same way
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as mimetypes.guess_extension
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"""
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ext = guess_extension(mimetype)
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if ext == ".jpe":
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ext = ".jpeg"
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return ext
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def platform_utf_8_encode(data):
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"""Encode data based on platform."""
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if isinstance(data, str):
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if sys.platform == "win32":
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data = data.replace("\n", "\r\n")
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data = data.encode("utf-8")
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return data
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class ExtractOutputPreprocessor(Preprocessor):
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"""
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Extracts all of the outputs from the notebook file. The extracted
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outputs are returned in the 'resources' dictionary.
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"""
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output_filename_template = Unicode("{unique_key}_{cell_index}_{index}{extension}").tag(
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config=True
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)
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extract_output_types = Set({"image/png", "image/jpeg", "image/svg+xml", "application/pdf"}).tag(
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config=True
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)
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def preprocess_cell(self, cell, resources, cell_index):
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"""
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Apply a transformation on each cell,
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Parameters
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----------
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cell : NotebookNode cell
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Notebook cell being processed
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resources : dictionary
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Additional resources used in the conversion process. Allows
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preprocessors to pass variables into the Jinja engine.
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cell_index : int
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Index of the cell being processed (see base.py)
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"""
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# Get the unique key from the resource dict if it exists. If it does not
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# exist, use 'output' as the default. Also, get files directory if it
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# has been specified
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unique_key = resources.get("unique_key", "output")
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output_files_dir = resources.get("output_files_dir", None)
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# Make sure outputs key exists
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if not isinstance(resources["outputs"], dict):
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resources["outputs"] = {}
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# Loop through all of the outputs in the cell
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for index, out in enumerate(cell.get("outputs", [])):
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if out.output_type not in {"display_data", "execute_result"}:
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continue
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if "text/html" in out.data:
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out["data"]["text/html"] = dedent(out["data"]["text/html"])
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# Get the output in data formats that the template needs extracted
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for mime_type in self.extract_output_types:
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if mime_type in out.data:
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data = out.data[mime_type]
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# Binary files are base64-encoded, SVG is already XML
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if mime_type in {"image/png", "image/jpeg", "application/pdf"}:
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# data is b64-encoded as text (str, unicode),
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# we want the original bytes
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data = a2b_base64(data)
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elif mime_type == "application/json" or not isinstance(data, str):
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# Data is either JSON-like and was parsed into a Python
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# object according to the spec, or data is for sure
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# JSON. In the latter case we want to go extra sure that
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# we enclose a scalar string value into extra quotes by
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# serializing it properly.
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if isinstance(data, bytes):
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# We need to guess the encoding in this
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# instance. Some modules that return raw data like
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# svg can leave the data in byte form instead of str
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data = data.decode("utf-8")
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data = platform_utf_8_encode(json.dumps(data))
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else:
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# All other text_type data will fall into this path
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data = platform_utf_8_encode(data)
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ext = guess_extension_without_jpe(mime_type)
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if ext is None:
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ext = "." + mime_type.rsplit("/")[-1]
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if out.metadata.get("filename", ""):
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filename = out.metadata["filename"]
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if not filename.endswith(ext):
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filename += ext
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else:
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filename = self.output_filename_template.format(
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unique_key=unique_key, cell_index=cell_index, index=index, extension=ext
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)
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# On the cell, make the figure available via
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# cell.outputs[i].metadata.filenames['mime/type']
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# where
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# cell.outputs[i].data['mime/type'] contains the data
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if output_files_dir is not None:
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filename = os.path.join(output_files_dir, filename)
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out.metadata.setdefault("filenames", {})
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out.metadata["filenames"][mime_type] = filename
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if filename in resources["outputs"]:
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msg = (
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"Your outputs have filename metadata associated "
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"with them. Nbconvert saves these outputs to "
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"external files using this filename metadata. "
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"Filenames need to be unique across the notebook, "
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f"or images will be overwritten. The filename {filename} is "
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"associated with more than one output. The second "
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"output associated with this filename is in cell "
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f"{cell_index}."
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)
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raise ValueError(msg)
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# In the resources, make the figure available via
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# resources['outputs']['filename'] = data
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resources["outputs"][filename] = data
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return cell, resources
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