def write_notebook_output(notebook, output_dir, notebook_name, location=None):
"""Extract output from notebook cells and write to files in output_dir.
This also modifies 'notebook' in-place, adding metadata to each cell that
maps output mime-types to the filenames the output was saved under.
"""
resources = dict(unique_key=os.path.join(output_dir, notebook_name),
outputs={})
# Modifies 'resources' in-place
ExtractOutputPreprocessor().preprocess(notebook, resources)
# Write the cell outputs to files where we can (images and PDFs),
# as well as the notebook file.
FilesWriter(build_directory=output_dir).write(
nbformat.writes(notebook),
resources,
os.path.join(output_dir, notebook_name + ".ipynb"),
)
exporter = nbconvert.exporters.ScriptExporter(
log=LoggerAdapterWrapper(js.logger))
with warnings.catch_warnings():
# See https://github.com/jupyter/nbconvert/issues/1388
warnings.simplefilter('ignore', DeprecationWarning)
contents, resources = exporter.from_notebook_node(notebook)
notebook_file = notebook_name + resources['output_extension']
output_dir = Path(output_dir)
# utf-8 is the de-facto standard encoding for notebooks.
(output_dir / notebook_file).write_text(contents, encoding="utf8")
def write_notebook_output(notebook, output_dir, notebook_name, location=None):
"""Extract output from notebook cells and write to files in output_dir.
This also modifies 'notebook' in-place, adding metadata to each cell that
maps output mime-types to the filenames the output was saved under.
"""
resources = dict(unique_key=os.path.join(output_dir, notebook_name), outputs={})
# Modifies 'resources' in-place
ExtractOutputPreprocessor().preprocess(notebook, resources)
# Write the cell outputs to files where we can (images and PDFs),
# as well as the notebook file.
FilesWriter(build_directory=output_dir).write(
nbformat.writes(notebook),
resources,
os.path.join(output_dir, notebook_name + ".ipynb"),
)
# Write a script too. Note that utf-8 is the de facto
# standard encoding for notebooks.
ext = notebook.metadata.get("language_info", {}).get("file_extension", None)
if ext is None:
ext = ".txt"
js.logger.warning(
"Notebook code has no file extension metadata, " "defaulting to `.txt`",
location=location,
)
contents = "\n\n".join(cell.source for cell in notebook.cells)
notebook_file = notebook_name + ext
output_dir = Path(output_dir)
(output_dir / notebook_file).write_text(contents, encoding = "utf8")
def write_notebook_output(notebook, output_dir, notebook_name):
"""Extract output from notebook cells and write to files in output_dir.
This also modifies 'notebook' in-place, adding metadata to each cell that
maps output mime-types to the filenames the output was saved under.
"""
resources = dict(unique_key=os.path.join(output_dir, notebook_name),
outputs={})
# Modifies 'resources' in-place
ExtractOutputPreprocessor().preprocess(notebook, resources)
# Write the cell outputs to files where we can (images and PDFs),
# as well as the notebook file.
FilesWriter(build_directory=output_dir).write(
nbformat.writes(notebook),
resources,
os.path.join(output_dir, notebook_name + ".ipynb"),
)
# Write a script too. Note that utf-8 is the de facto
# standard encoding for notebooks.
ext = notebook.metadata.language_info.file_extension
contents = "\n\n".join(cell.source for cell in notebook.cells)
with open(os.path.join(output_dir, notebook_name + ext),
"w",
encoding="utf8") as f:
f.write(contents)
def remove_solutions(nb, nb_name):
"""Convert solution cells to markdown; embed images from Python output."""
# -- Extract image data from the cell outputs
c = Config()
template = (f"../static/{nb_name}"
"_Solution_{cell_index}_{index}{extension}")
c.ExtractOutputPreprocessor.output_filename_template = template
# Note: using the RST exporter means we need to install pandoc as a dep
# in the github workflow, which adds a little bit of latency, and we don't
# actually care about the RST output. It's just a convenient way to get the
# image resources the way we want them.
exporter = RSTExporter()
extractor = ExtractOutputPreprocessor(config=c)
exporter.register_preprocessor(extractor, True)
_, resources = exporter.from_notebook_node(nb)
# -- Convert solution cells to markdown with embedded image
nb_cells = nb.get("cells", [])
outputs = resources["outputs"]
solution_resources = {}
for i, cell in enumerate(nb_cells):
cell_text = cell["source"].replace(" ", "").lower()
if cell_text.startswith("#@titlesolution"):
# Just remove solution cells that generate no outputs
if not cell["outputs"]:
nb_cells.remove(cell)
continue
# Filter the resources for solution images
image_paths = [k for k in outputs if f"Solution_{i}" in k]
solution_resources.update({k: outputs[k] for k in image_paths})
# Conver the solution cell to markdown, strip the source,
# and embed the image as a link to static resource
new_source = "**Example output:**\n\n" + "\n\n".join(
[f"<img src='{f}' align='left'>" for f in image_paths])
cell["source"] = new_source
cell["cell_type"] = "markdown"
del cell["outputs"]
del cell["execution_count"]
return nb, solution_resources
def write_notebook_output(notebook, output_dir, notebook_name):
"""Extract output from notebook cells and write to files in output_dir.
This also modifies 'notebook' in-place, adding metadata to each cell that
maps output mime-types to the filenames the output was saved under.
"""
resources = dict(unique_key=os.path.join(output_dir, notebook_name),
outputs={})
# Modifies 'resources' in-place
ExtractOutputPreprocessor().preprocess(notebook, resources)
# Write the cell outputs to files where we can (images and PDFs),
# as well as the notebook file.
FilesWriter(build_directory=output_dir).write(
nbformat.writes(notebook), resources,
os.path.join(output_dir, notebook_name + '.ipynb'))
# Write a Python script too.
contents = '\n\n'.join(cell.source for cell in notebook.cells)
with open(os.path.join(output_dir, notebook_name + '.py'), 'w') as f:
f.write(contents)
def convert_to_rst(nb, basedir, fpath, fstem):
# Convert to .rst formats
exp = RSTExporter()
c = Config()
c.TagRemovePreprocessor.remove_cell_tags = {"hide"}
c.TagRemovePreprocessor.remove_input_tags = {"hide-input"}
c.TagRemovePreprocessor.remove_all_outputs_tags = {"hide-output"}
c.ExtractOutputPreprocessor.output_filename_template = (
f"{fstem}_files/{fstem}_" + "{cell_index}_{index}{extension}"
)
exp.register_preprocessor(TagRemovePreprocessor(config=c), True)
exp.register_preprocessor(ExtractOutputPreprocessor(config=c), True)
body, resources = exp.from_notebook_node(nb)
# Clean the output on the notebook and save a .ipynb back to disk
print(f"Writing clean {fpath} ... ", end=" ", flush=True)
nb = strip_output(nb)
with open(fpath, "wt") as f:
nbformat.write(nb, f)
# Write the .rst file
rst_path = os.path.join(basedir, f"{fstem}.rst")
print(f"Writing {rst_path}")
with open(rst_path, "w") as f:
f.write(body)
print(resources["outputs"])
# Write the individual image outputs
imdir = os.path.join(basedir, f"{fstem}_files")
if not os.path.exists(imdir):
os.mkdir(imdir)
for imname, imdata in resources["outputs"].items():
if imname.startswith(fstem):
impath = os.path.join(basedir, f"{imname}")
with open(impath, "wb") as f:
f.write(imdata)
f.write(imdata)
field["data"].pop(key)
if not field["data"]:
fields.remove(field)
# Convert to .rst formats
exp = RSTExporter()
c = Config()
c.TagRemovePreprocessor.remove_cell_tags = {"hide"}
c.TagRemovePreprocessor.remove_input_tags = {"hide-input"}
c.TagRemovePreprocessor.remove_all_outputs_tags = {"hide-output"}
c.ExtractOutputPreprocessor.output_filename_template = \
f"{fstem}_files/{fstem}_" + "{cell_index}_{index}{extension}"
exp.register_preprocessor(TagRemovePreprocessor(config=c), True)
exp.register_preprocessor(ExtractOutputPreprocessor(config=c), True)
body, resources = exp.from_notebook_node(nb)
# Clean the output on the notebook and save a .ipynb back to disk
print(f"Writing clean {fpath} ... ", end=" ", flush=True)
nb = strip_output(nb)
with open(fpath, "wt") as f:
nbformat.write(nb, f)
# Write the .rst file
rst_path = os.path.join(basedir, f"{fstem}.rst")
print(f"Writing {rst_path}")
with open(rst_path, "w") as f:
f.write(body)
def extract_resources(self, nb, resources):
output_filename_template = "image_{cell_index}_{index}{extension}"
return ExtractOutputPreprocessor(output_filename_template=output_filename_template) \
.preprocess(nb, resources)
