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Editing: frontmatter.py
# $Id: frontmatter.py 9351 2023-04-17 20:26:33Z milde $ # Author: David Goodger, Ueli Schlaepfer <goodger@python.org> # Copyright: This module has been placed in the public domain. """ Transforms related to the front matter of a document or a section (information found before the main text): - `DocTitle`: Used to transform a lone top level section's title to the document title, promote a remaining lone top-level section's title to the document subtitle, and determine the document's title metadata (document['title']) based on the document title and/or the "title" setting. - `SectionSubTitle`: Used to transform a lone subsection into a subtitle. - `DocInfo`: Used to transform a bibliographic field list into docinfo elements. """ __docformat__ = 'reStructuredText' import re from docutils import nodes, parsers, utils from docutils.transforms import TransformError, Transform class TitlePromoter(Transform): """ Abstract base class for DocTitle and SectionSubTitle transforms. """ def promote_title(self, node): """ Transform the following tree:: <node> <section> <title> ... into :: <node> <title> ... `node` is normally a document. """ # Type check if not isinstance(node, nodes.Element): raise TypeError('node must be of Element-derived type.') # `node` must not have a title yet. assert not (len(node) and isinstance(node[0], nodes.title)) section, index = self.candidate_index(node) if index is None: return False # Transfer the section's attributes to the node: # NOTE: Change `replace` to False to NOT replace attributes that # already exist in node with those in section. # NOTE: Remove `and_source` to NOT copy the 'source' # attribute from section node.update_all_atts_concatenating(section, replace=True, and_source=True) # setup_child is called automatically for all nodes. node[:] = (section[:1] # section title + node[:index] # everything that was in the # node before the section + section[1:]) # everything that was in the section assert isinstance(node[0], nodes.title) return True def promote_subtitle(self, node): """ Transform the following node tree:: <node> <title> <section> <title> ... into :: <node> <title> <subtitle> ... """ # Type check if not isinstance(node, nodes.Element): raise TypeError('node must be of Element-derived type.') subsection, index = self.candidate_index(node) if index is None: return False subtitle = nodes.subtitle() # Transfer the subsection's attributes to the new subtitle # NOTE: Change `replace` to False to NOT replace attributes # that already exist in node with those in section. # NOTE: Remove `and_source` to NOT copy the 'source' # attribute from section. subtitle.update_all_atts_concatenating(subsection, replace=True, and_source=True) # Transfer the contents of the subsection's title to the # subtitle: subtitle[:] = subsection[0][:] node[:] = (node[:1] # title + [subtitle] # everything that was before the section: + node[1:index] # everything that was in the subsection: + subsection[1:]) return True def candidate_index(self, node): """ Find and return the promotion candidate and its index. Return (None, None) if no valid candidate was found. """ index = node.first_child_not_matching_class( nodes.PreBibliographic) if (index is None or len(node) > (index + 1) or not isinstance(node[index], nodes.section)): return None, None else: return node[index], index class DocTitle(TitlePromoter): """ In reStructuredText_, there is no way to specify a document title and subtitle explicitly. Instead, we can supply the document title (and possibly the subtitle as well) implicitly, and use this two-step transform to "raise" or "promote" the title(s) (and their corresponding section contents) to the document level. 1. If the document contains a single top-level section as its first non-comment element, the top-level section's title becomes the document's title, and the top-level section's contents become the document's immediate contents. The lone top-level section header must be the first non-comment element in the document. For example, take this input text:: ================= Top-Level Title ================= A paragraph. Once parsed, it looks like this:: <document> <section names="top-level title"> <title> Top-Level Title <paragraph> A paragraph. After running the DocTitle transform, we have:: <document names="top-level title"> <title> Top-Level Title <paragraph> A paragraph. 2. If step 1 successfully determines the document title, we continue by checking for a subtitle. If the lone top-level section itself contains a single second-level section as its first non-comment element, that section's title is promoted to the document's subtitle, and that section's contents become the document's immediate contents. Given this input text:: ================= Top-Level Title ================= Second-Level Title ~~~~~~~~~~~~~~~~~~ A paragraph. After parsing and running the Section Promotion transform, the result is:: <document names="top-level title"> <title> Top-Level Title <subtitle names="second-level title"> Second-Level Title <paragraph> A paragraph. (Note that the implicit hyperlink target generated by the "Second-Level Title" is preserved on the "subtitle" element itself.) Any comment elements occurring before the document title or subtitle are accumulated and inserted as the first body elements after the title(s). This transform also sets the document's metadata title (document['title']). .. _reStructuredText: https://docutils.sourceforge.io/rst.html """ default_priority = 320 def set_metadata(self): """ Set document['title'] metadata title from the following sources, listed in order of priority: * Existing document['title'] attribute. * "title" setting. * Document title node (as promoted by promote_title). """ if not self.document.hasattr('title'): if self.document.settings.title is not None: self.document['title'] = self.document.settings.title elif len(self.document) and isinstance(self.document[0], nodes.title): self.document['title'] = self.document[0].astext() def apply(self): if self.document.settings.setdefault('doctitle_xform', True): # promote_(sub)title defined in TitlePromoter base class. if self.promote_title(self.document): # If a title has been promoted, also try to promote a # subtitle. self.promote_subtitle(self.document) # Set document['title']. self.set_metadata() class SectionSubTitle(TitlePromoter): """ This works like document subtitles, but for sections. For example, :: <section> <title> Title <section> <title> Subtitle ... is transformed into :: <section> <title> Title <subtitle> Subtitle ... For details refer to the docstring of DocTitle. """ default_priority = 350 def apply(self): if not self.document.settings.setdefault('sectsubtitle_xform', True): return for section in self.document.findall(nodes.section): # On our way through the node tree, we are modifying it # but only the not-yet-visited part, so that the iterator # returned by findall() is not corrupted. self.promote_subtitle(section) class DocInfo(Transform): """ This transform is specific to the reStructuredText_ markup syntax; see "Bibliographic Fields" in the `reStructuredText Markup Specification`_ for a high-level description. This transform should be run *after* the `DocTitle` transform. Given a field list as the first non-comment element after the document title and subtitle (if present), registered bibliographic field names are transformed to the corresponding DTD elements, becoming child elements of the "docinfo" element (except for a dedication and/or an abstract, which become "topic" elements after "docinfo"). For example, given this document fragment after parsing:: <document> <title> Document Title <field_list> <field> <field_name> Author <field_body> <paragraph> A. Name <field> <field_name> Status <field_body> <paragraph> $RCSfile$ ... After running the bibliographic field list transform, the resulting document tree would look like this:: <document> <title> Document Title <docinfo> <author> A. Name <status> frontmatter.py ... The "Status" field contained an expanded RCS keyword, which is normally (but optionally) cleaned up by the transform. The sole contents of the field body must be a paragraph containing an expanded RCS keyword of the form "$keyword: expansion text $". Any RCS keyword can be processed in any bibliographic field. The dollar signs and leading RCS keyword name are removed. Extra processing is done for the following RCS keywords: - "RCSfile" expands to the name of the file in the RCS or CVS repository, which is the name of the source file with a ",v" suffix appended. The transform will remove the ",v" suffix. - "Date" expands to the format "YYYY/MM/DD hh:mm:ss" (in the UTC time zone). The RCS Keywords transform will extract just the date itself and transform it to an ISO 8601 format date, as in "2000-12-31". (Since the source file for this text is itself stored under CVS, we can't show an example of the "Date" RCS keyword because we can't prevent any RCS keywords used in this explanation from being expanded. Only the "RCSfile" keyword is stable; its expansion text changes only if the file name changes.) .. _reStructuredText: https://docutils.sourceforge.io/rst.html .. _reStructuredText Markup Specification: https://docutils.sourceforge.io/docs/ref/rst/restructuredtext.html """ default_priority = 340 biblio_nodes = { 'author': nodes.author, 'authors': nodes.authors, 'organization': nodes.organization, 'address': nodes.address, 'contact': nodes.contact, 'version': nodes.version, 'revision': nodes.revision, 'status': nodes.status, 'date': nodes.date, 'copyright': nodes.copyright, 'dedication': nodes.topic, 'abstract': nodes.topic} """Canonical field name (lowcased) to node class name mapping for bibliographic fields (field_list).""" def apply(self): if not self.document.settings.setdefault('docinfo_xform', True): return document = self.document index = document.first_child_not_matching_class( nodes.PreBibliographic) if index is None: return candidate = document[index] if isinstance(candidate, nodes.field_list): biblioindex = document.first_child_not_matching_class( (nodes.Titular, nodes.Decorative, nodes.meta)) nodelist = self.extract_bibliographic(candidate) del document[index] # untransformed field list (candidate) document[biblioindex:biblioindex] = nodelist def extract_bibliographic(self, field_list): docinfo = nodes.docinfo() bibliofields = self.language.bibliographic_fields labels = self.language.labels topics = {'dedication': None, 'abstract': None} for field in field_list: try: name = field[0][0].astext() normedname = nodes.fully_normalize_name(name) if not (len(field) == 2 and normedname in bibliofields and self.check_empty_biblio_field(field, name)): raise TransformError canonical = bibliofields[normedname] biblioclass = self.biblio_nodes[canonical] if issubclass(biblioclass, nodes.TextElement): if not self.check_compound_biblio_field(field, name): raise TransformError utils.clean_rcs_keywords( field[1][0], self.rcs_keyword_substitutions) docinfo.append(biblioclass('', '', *field[1][0])) elif issubclass(biblioclass, nodes.authors): self.extract_authors(field, name, docinfo) elif issubclass(biblioclass, nodes.topic): if topics[canonical]: field[-1] += self.document.reporter.warning( 'There can only be one "%s" field.' % name, base_node=field) raise TransformError title = nodes.title(name, labels[canonical]) title[0].rawsource = labels[canonical] topics[canonical] = biblioclass( '', title, classes=[canonical], *field[1].children) else: docinfo.append(biblioclass('', *field[1].children)) except TransformError: if len(field[-1]) == 1 \ and isinstance(field[-1][0], nodes.paragraph): utils.clean_rcs_keywords( field[-1][0], self.rcs_keyword_substitutions) # if normedname not in bibliofields: classvalue = nodes.make_id(normedname) if classvalue: field['classes'].append(classvalue) docinfo.append(field) nodelist = [] if len(docinfo) != 0: nodelist.append(docinfo) for name in ('dedication', 'abstract'): if topics[name]: nodelist.append(topics[name]) return nodelist def check_empty_biblio_field(self, field, name): if len(field[-1]) < 1: field[-1] += self.document.reporter.warning( f'Cannot extract empty bibliographic field "{name}".', base_node=field) return False return True def check_compound_biblio_field(self, field, name): # Check that the `field` body contains a single paragraph # (i.e. it must *not* be a compound element). f_body = field[-1] if len(f_body) == 1 and isinstance(f_body[0], nodes.paragraph): return True # Restore single author name with initial (E. Xampl) parsed as # enumerated list # https://docutils.sourceforge.io/docs/ref/rst/restructuredtext.html#enumerated-lists if (isinstance(f_body[0], nodes.enumerated_list) and '\n' not in f_body.rawsource.strip()): # parse into a dummy document and use created nodes _document = utils.new_document('*DocInfo transform*', field.document.settings) parser = parsers.rst.Parser() parser.parse('\\'+f_body.rawsource, _document) if (len(_document.children) == 1 and isinstance(_document.children[0], nodes.paragraph)): f_body.children = _document.children return True # Check failed, add a warning content = [f'<{e.tagname}>' for e in f_body.children] if len(content) > 1: content = '[' + ', '.join(content) + ']' else: content = 'a ' + content[0] f_body += self.document.reporter.warning( f'Bibliographic field "{name}"\nmust contain ' f'a single <paragraph>, not {content}.', base_node=field) return False rcs_keyword_substitutions = [ (re.compile(r'\$' r'Date: (\d\d\d\d)[-/](\d\d)[-/](\d\d)[ T][\d:]+' r'[^$]* \$', re.IGNORECASE), r'\1-\2-\3'), (re.compile(r'\$' r'RCSfile: (.+),v \$', re.IGNORECASE), r'\1'), (re.compile(r'\$[a-zA-Z]+: (.+) \$'), r'\1')] def extract_authors(self, field, name, docinfo): try: if len(field[1]) == 1: if isinstance(field[1][0], nodes.paragraph): authors = self.authors_from_one_paragraph(field) elif isinstance(field[1][0], nodes.bullet_list): authors = self.authors_from_bullet_list(field) else: raise TransformError else: authors = self.authors_from_paragraphs(field) authornodes = [nodes.author('', '', *author) for author in authors if author] if len(authornodes) >= 1: docinfo.append(nodes.authors('', *authornodes)) else: raise TransformError except TransformError: field[-1] += self.document.reporter.warning( f'Cannot extract "{name}" from bibliographic field:\n' f'Bibliographic field "{name}" must contain either\n' ' a single paragraph (with author names separated by one of ' f'"{"".join(self.language.author_separators)}"),\n' ' multiple paragraphs (one per author),\n' ' or a bullet list with one author name per item.\n' 'Note: Leading initials can cause (mis)recognizing names ' 'as enumerated list.', base_node=field) raise def authors_from_one_paragraph(self, field): """Return list of Text nodes with author names in `field`. Author names must be separated by one of the "autor separators" defined for the document language (default: ";" or ","). """ # @@ keep original formatting? (e.g. ``:authors: A. Test, *et-al*``) text = ''.join(str(node) for node in field[1].findall(nodes.Text)) if not text: raise TransformError for authorsep in self.language.author_separators: # don't split at escaped `authorsep`: pattern = '(?<!\x00)%s' % authorsep authornames = re.split(pattern, text) if len(authornames) > 1: break authornames = (name.strip() for name in authornames) return [[nodes.Text(name)] for name in authornames if name] def authors_from_bullet_list(self, field): authors = [] for item in field[1][0]: if isinstance(item, nodes.comment): continue if len(item) != 1 or not isinstance(item[0], nodes.paragraph): raise TransformError authors.append(item[0].children) if not authors: raise TransformError return authors def authors_from_paragraphs(self, field): for item in field[1]: if not isinstance(item, (nodes.paragraph, nodes.comment)): raise TransformError authors = [item.children for item in field[1] if not isinstance(item, nodes.comment)] return authors
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