Пример #1
0
def nb_output_to_disc(ntbk: nbf.NotebookNode,
                      document: nodes.document) -> Path:
    """Write the notebook's output to disk

    We remove all the mime prefixes from "glue" step.
    This way, writing properly captures the glued images
    """
    replace_mime = []
    for cell in ntbk.cells:
        if hasattr(cell, "outputs"):
            for out in cell.outputs:
                if "data" in out:
                    # Only do the mimebundle replacing for the scrapbook outputs
                    mime_prefix = (out.get("metadata",
                                           {}).get("scrapbook",
                                                   {}).get("mime_prefix"))
                    if mime_prefix:
                        out["data"] = {
                            key.replace(mime_prefix, ""): val
                            for key, val in out["data"].items()
                        }
                        replace_mime.append(out)

    # Write the notebook's output to disk. This changes metadata in notebook cells
    path_doc = Path(document.settings.env.docname)
    doc_relpath = path_doc.parent
    doc_filename = path_doc.name
    build_dir = Path(document.settings.env.app.outdir).parent
    output_dir = build_dir.joinpath("jupyter_execute", doc_relpath)

    # Write a script too.
    if not ntbk.metadata.get("language_info"):
        # TODO: we can remove this
        # once https://github.com/executablebooks/MyST-NB/issues/177 is merged
        ntbk.metadata["language_info"] = {"file_extension": ".txt"}
        SPHINX_LOGGER.warning(
            "Notebook code has no file extension metadata, "
            "defaulting to `.txt`",
            location=document.settings.env.docname,
        )
    write_notebook_output(ntbk, str(output_dir), doc_filename)

    # Now add back the mime prefixes to the right outputs so they aren't rendered
    # until called from the role/directive
    for out in replace_mime:
        out["data"] = {
            f"{GLUE_PREFIX}{key}": val
            for key, val in out["data"].items()
        }

    return path_doc
Пример #2
0
def nb_output_to_disc(ntbk: nbf.NotebookNode,
                      document: nodes.document) -> Path:
    """Write the notebook's output to disk

    We remove all the mime prefixes from "glue" step.
    This way, writing properly captures the glued images
    """
    replace_mime = []
    for cell in ntbk.cells:
        if hasattr(cell, "outputs"):
            for out in cell.outputs:
                if "data" in out:
                    # Only do the mimebundle replacing for the scrapbook outputs
                    mime_prefix = (out.get("metadata",
                                           {}).get("scrapbook",
                                                   {}).get("mime_prefix"))
                    if mime_prefix:
                        out["data"] = {
                            key.replace(mime_prefix, ""): val
                            for key, val in out["data"].items()
                        }
                        replace_mime.append(out)

    # Write the notebook's output to disk. This changes metadata in notebook cells
    path_doc = Path(document.settings.env.docname)
    doc_relpath = path_doc.parent
    doc_filename = path_doc.name
    build_dir = Path(document.settings.env.app.outdir).parent
    output_dir = build_dir.joinpath("jupyter_execute", doc_relpath)
    write_notebook_output(ntbk, str(output_dir), doc_filename)

    # Now add back the mime prefixes to the right outputs so they aren't rendered
    # until called from the role/directive
    for out in replace_mime:
        out["data"] = {
            f"{GLUE_PREFIX}{key}": val
            for key, val in out["data"].items()
        }

    return path_doc
Пример #3
0
    def parse(self, inputstring, document):

        # de-serialize the notebook
        ntbk = nbf.reads(inputstring, nbf.NO_CONVERT)

        # This is a contaner for top level markdown tokens
        # which we will add to as we walk the document
        mkdown_tokens = []  # type: list[BlockToken]

        # First we ensure that we are using a 'clean' global context
        # for parsing, which is setup with the MyST parsing tokens
        # the logger will report on duplicate link/footnote definitions, etc
        parse_context = ParseContext(
            find_blocks=SphinxNBRenderer.default_block_tokens,
            find_spans=SphinxNBRenderer.default_span_tokens,
            logger=SPHINX_LOGGER,
        )
        set_parse_context(parse_context)

        for cell_index, nb_cell in enumerate(ntbk.cells):

            # Skip empty cells
            if len(nb_cell["source"].strip()) == 0:
                continue

            # skip cells tagged for removal
            tags = nb_cell.metadata.get("tags", [])
            if "remove_cell" in tags:
                continue

            if nb_cell["cell_type"] == "markdown":

                # we add the document path and cell index
                # to the source lines, so they can be included in the error logging
                # NOTE: currently the logic to report metadata is not written
                # into SphinxRenderer, but this will be introduced in a later update
                lines = SourceLines(
                    nb_cell["source"],
                    uri=document["source"],
                    metadata={"cell_index": cell_index},
                    standardize_ends=True,
                )

                # parse the source markdown text;
                # at this point span/inline level tokens are not yet processed, but
                # link/footnote definitions are collected/stored in the global context
                mkdown_tokens.extend(tokenize_block(lines))

                # TODO for md cells, think of a way to implement the previous
                # `if "hide_input" in tags:` logic

            elif nb_cell["cell_type"] == "code":
                # here we do nothing but store the cell as a custom token
                mkdown_tokens.append(
                    NbCodeCell(
                        cell=nb_cell,
                        position=Position(
                            line_start=0,
                            uri=document["source"],
                            data={"cell_index": cell_index},
                        ),
                    ))

        # Now all definitions have been gathered, we walk the tokens and
        # process any inline text
        for token in mkdown_tokens + list(
                get_parse_context().foot_definitions.values()):
            token.expand_spans()

        # If there are widgets, this will embed the state of all widgets in a script
        if contains_widgets(ntbk):
            mkdown_tokens.insert(0,
                                 JupyterWidgetState(state=get_widgets(ntbk)))

        # create the front matter token
        front_matter = FrontMatter(content=ntbk.metadata, position=None)

        # Finally, we create the top-level markdown document
        markdown_doc = Document(
            children=mkdown_tokens,
            front_matter=front_matter,
            link_definitions=parse_context.link_definitions,
            footnotes=parse_context.foot_definitions,
            footref_order=parse_context.foot_references,
        )

        self.reporter = document.reporter
        self.config = self.default_config.copy()
        try:
            new_cfg = document.settings.env.config.myst_config
            self.config.update(new_cfg)
        except AttributeError:
            pass

        # Remove all the mime prefixes from "glue" step.
        # This way, writing properly captures the glued images
        replace_mime = []
        for cell in ntbk.cells:
            if hasattr(cell, "outputs"):
                for out in cell.outputs:
                    if "data" in out:
                        # Only do the mimebundle replacing for the scrapbook outputs
                        mime_prefix = (out.get("metadata",
                                               {}).get("scrapbook",
                                                       {}).get("mime_prefix"))
                        if mime_prefix:
                            out["data"] = {
                                key.replace(mime_prefix, ""): val
                                for key, val in out["data"].items()
                            }
                            replace_mime.append(out)

        # Write the notebook's output to disk. This changes metadata in notebook cells
        path_doc = Path(document.settings.env.docname)
        doc_relpath = path_doc.parent
        doc_filename = path_doc.name
        build_dir = Path(document.settings.env.app.outdir).parent
        output_dir = build_dir.joinpath("jupyter_execute", doc_relpath)
        write_notebook_output(ntbk, str(output_dir), doc_filename)

        # Now add back the mime prefixes to the right outputs so they aren't rendered
        # until called from the role/directive
        for out in replace_mime:
            out["data"] = {
                f"{GLUE_PREFIX}{key}": val
                for key, val in out["data"].items()
            }

        # Update our glue key list with new ones defined in this page
        glue_domain = NbGlueDomain.from_env(document.settings.env)
        glue_domain.add_notebook(ntbk, path_doc)

        # render the Markdown AST to docutils AST
        renderer = SphinxNBRenderer(parse_context=parse_context,
                                    document=document,
                                    current_node=None)
        renderer.render(markdown_doc)