Function generate_global_index

tensorflow/tools/docs/parser.py:1702–1737

Given a dict of full names to python objects, generate an index page. The index page generated contains a list of links for all symbols in `index` that have their own documentation page. Args: library_name: The name for the documented library to use in the title. index: A dict mappin

(library_name, index, reference_resolver)

# TODO(markdaoust): This should just parse, pretty_docs should generate the md.
def generate_global_index(library_name, index, reference_resolver):
  """Given a dict of full names to python objects, generate an index page.

  The index page generated contains a list of links for all symbols in `index`
  that have their own documentation page.

  Args:
    library_name: The name for the documented library to use in the title.
    index: A dict mapping full names to python objects.
    reference_resolver: An instance of ReferenceResolver.

  Returns:
    A string containing an index page as Markdown.
  """
  symbol_links = []
  for full_name, py_object in six.iteritems(index):
    if (tf_inspect.ismodule(py_object) or tf_inspect.isfunction(py_object) or
        tf_inspect.isclass(py_object)):
      # In Python 3, unbound methods are functions, so eliminate those.
      if tf_inspect.isfunction(py_object):
        if full_name.count('.') == 0:
          parent_name = ''
        else:
          parent_name = full_name[:full_name.rfind('.')]
        if parent_name in index and tf_inspect.isclass(index[parent_name]):
          # Skip methods (=functions with class parents).
          continue
      symbol_links.append((
          full_name, reference_resolver.python_link(full_name, full_name, '.')))

  lines = ['# All symbols in %s' % library_name, '']
  for _, link in sorted(symbol_links, key=lambda x: x[0]):
    lines.append('*  %s' % link)

  # TODO(markdaoust): use a _ModulePageInfo -> prety_docs.build_md_page()
  return '\n'.join(lines)


class _Metadata(object):