def parse_numpy_docstring(docstring):
'''
Parse a numpy docstring for summary and parameter information.
Parameters
----------
docstring : str
Docstring to parse.
Returns
-------
info : dict
info['summary'] is a string summary.
info['params'] is a dictionary of parameter name to a list of
description lines.
'''
info = {}
parsed = docscrape.NumpyDocString(docstring)
info['summary'] = '\n'.join(parsed['Summary'])
params = parsed['Parameters']
# numpydoc v0.8.0 uses just a tuple for parameters, but later versions use
# a namedtuple. here, only assume a tuple:
info['params'] = {name: lines for name, type_, lines in params}
return info
def get_constructor_doc_dict(self, name):
model_class = self.registry[name]
docs = inspect.getdoc(model_class)
param_docs = docscrape.NumpyDocString(docs)
param_docs_dict = {}
for param in param_docs["Parameters"]:
param_docs_dict[param.name] = param.desc[0]
return param_docs_dict
def get_parameters(self, doc, type_table):
"""Get parameters from the doc of a class, function, or property object.
Given the sklean docstring follows the numpy conventions, this function use the numpy docstring parser to read the doc of sklean.
"""
scraper = TypeScraper(type_table=type_table)
r = docscrape.NumpyDocString(doc)
paras = {}
for p in r['Parameters']:
para_str = str(p.type)
para_type = scraper.scrap(para_str)
if self.is_valid_para(para_type, type_table):
paras[p.name] = scraper.scrap(para_str)
else:
continue
return paras
def __init__(self, doc_string):
self.doc_string = docscrape.NumpyDocString(doc_string)
