Current File : //opt/imunify360/venv/lib/python3.11/site-packages/docutils/transforms/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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