""" Docstrings are another source of information for functions and classes. :mod:`jedi.inference.dynamic_params` tries to find all executions of functions, while the docstring parsing is much easier. There are three different types of docstrings that |jedi| understands: - `Sphinx <http://sphinx-doc.org/markup/desc.html#info-field-lists>`_ - `Epydoc <http://epydoc.sourceforge.net/manual-fields.html>`_ - `Numpydoc <https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt>`_ For example, the sphinx annotation ``:type foo: str`` clearly states that the type of ``foo`` is ``str``. As an addition to parameter searching, this module also provides return annotations. """ import re import warnings from textwrap import dedent from parso import parse, ParserSyntaxError from jedi import debug from jedi.common import indent_block from jedi.inference.cache import inference_state_method_cache from jedi.inference.base_value import iterator_to_value_set, ValueSet, \ NO_VALUES from jedi.inference.lazy_value import LazyKnownValues DOCSTRING_PARAM_PATTERNS = [ r'\s*:type\s+%s:\s*([^\n]+)', # Sphinx r'\s*:param\s+(\w+)\s+%s:[^\n]*', # Sphinx param with type r'\s*@type\s+%s:\s*([^\n]+)', # Epydoc ] DOCSTRING_RETURN_PATTERNS = [ re.compile(r'\s*:rtype:\s*([^\n]+)', re.M), # Sphinx re.compile(r'\s*@rtype:\s*([^\n]+)', re.M), # Epydoc ] REST_ROLE_PATTERN = re.compile(r':[^`]+:`([^`]+)`') _numpy_doc_string_cache = None def _get_numpy_doc_string_cls(): global _numpy_doc_string_cache if isinstance(_numpy_doc_string_cache, (ImportError, SyntaxError)): raise _numpy_doc_string_cache from numpydoc.docscrape import NumpyDocString # type: ignore[import] _numpy_doc_string_cache = NumpyDocString return _numpy_doc_string_cache def _search_param_in_numpydocstr(docstr, param_str): """Search `docstr` (in numpydoc format) for type(-s) of `param_str`.""" with warnings.catch_warnings(): warnings.simplefilter("ignore") try: # This is a non-public API. If it ever changes we should be # prepared and return gracefully. params = _get_numpy_doc_string_cls()(docstr)._parsed_data['Parameters'] except Exception: return [] for p_name, p_type, p_descr in params: if p_name == param_str: m = re.match(r'([^,]+(,[^,]+)*?)(,[ ]*optional)?$', p_type) if m: p_type = m.group(1) return list(_expand_typestr(p_type)) return [] def _search_return_in_numpydocstr(docstr): """ Search `docstr` (in numpydoc format) for type(-s) of function returns. """ with warnings.catch_warnings(): warnings.simplefilter("ignore") try: doc = _get_numpy_doc_string_cls()(docstr) except Exception: return try: # This is a non-public API. If it ever changes we should be # prepared and return gracefully. returns = doc._parsed_data['Returns'] returns += doc._parsed_data['Yields'] except Exception: return for r_name, r_type, r_descr in returns: # Return names are optional and if so the type is in the name if not r_type: r_type = r_name yield from _expand_typestr(r_type) def _expand_typestr(type_str): """ Attempts to interpret the possible types in `type_str` """ # Check if alternative types are specified with 'or' if re.search(r'\bor\b', type_str): for t in type_str.split('or'): yield t.split('of')[0].strip() # Check if like "list of `type`" and set type to list elif re.search(r'\bof\b', type_str): yield type_str.split('of')[0] # Check if type has is a set of valid literal values eg: {'C', 'F', 'A'} elif type_str.startswith('{'): node = parse(type_str, version='3.7').children[0] if node.type == 'atom': for leaf in getattr(node.children[1], "children", []): if leaf.type == 'number': if '.' in leaf.value: yield 'float' else: yield 'int' elif leaf.type == 'string': if 'b' in leaf.string_prefix.lower(): yield 'bytes' else: yield 'str' # Ignore everything else. # Otherwise just work with what we have. else: yield type_str def _search_param_in_docstr(docstr, param_str): """ Search `docstr` for type(-s) of `param_str`. >>> _search_param_in_docstr(':type param: int', 'param') ['int'] >>> _search_param_in_docstr('@type param: int', 'param') ['int'] >>> _search_param_in_docstr( ... ':type param: :class:`threading.Thread`', 'param') ['threading.Thread'] >>> bool(_search_param_in_docstr('no document', 'param')) False >>> _search_param_in_docstr(':param int param: some description', 'param') ['int'] """ # look at #40 to see definitions of those params patterns = [re.compile(p % re.escape(param_str)) for p in DOCSTRING_PARAM_PATTERNS] for pattern in patterns: match = pattern.search(docstr) if match: return [_strip_rst_role(match.group(1))] return _search_param_in_numpydocstr(docstr, param_str) def _strip_rst_role(type_str): """ Strip off the part looks like a ReST role in `type_str`. >>> _strip_rst_role(':class:`ClassName`') # strip off :class: 'ClassName' >>> _strip_rst_role(':py:obj:`module.Object`') # works with domain 'module.Object' >>> _strip_rst_role('ClassName') # do nothing when not ReST role 'ClassName' See also: http://sphinx-doc.org/domains.html#cross-referencing-python-objects """ match = REST_ROLE_PATTERN.match(type_str) if match: return match.group(1) else: return type_str def _infer_for_statement_string(module_context, string): code = dedent(""" def pseudo_docstring_stuff(): ''' Create a pseudo function for docstring statements. Need this docstring so that if the below part is not valid Python this is still a function. ''' {} """) if string is None: return [] for element in re.findall(r'((?:\w+\.)*\w+)\.', string): # Try to import module part in dotted name. # (e.g., 'threading' in 'threading.Thread'). string = 'import %s\n' % element + string debug.dbg('Parse docstring code %s', string, color='BLUE') grammar = module_context.inference_state.grammar try: module = grammar.parse(code.format(indent_block(string)), error_recovery=False) except ParserSyntaxError: return [] try: funcdef = next(module.iter_funcdefs()) # First pick suite, then simple_stmt and then the node, # which is also not the last item, because there's a newline. stmt = funcdef.children[-1].children[-1].children[-2] except (AttributeError, IndexError): return [] if stmt.type not in ('name', 'atom', 'atom_expr'): return [] from jedi.inference.value import FunctionValue function_value = FunctionValue( module_context.inference_state, module_context, funcdef ) func_execution_context = function_value.as_context() # Use the module of the param. # TODO this module is not the module of the param in case of a function # call. In that case it's the module of the function call. # stuffed with content from a function call. return list(_execute_types_in_stmt(func_execution_context, stmt)) def _execute_types_in_stmt(module_context, stmt): """ Executing all types or general elements that we find in a statement. This doesn't include tuple, list and dict literals, because the stuff they contain is executed. (Used as type information). """ definitions = module_context.infer_node(stmt) return ValueSet.from_sets( _execute_array_values(module_context.inference_state, d) for d in definitions ) def _execute_array_values(inference_state, array): """ Tuples indicate that there's not just one return value, but the listed ones. `(str, int)` means that it returns a tuple with both types. """ from jedi.inference.value.iterable import SequenceLiteralValue, FakeTuple, FakeList if isinstance(array, SequenceLiteralValue) and array.array_type in ('tuple', 'list'): values = [] for lazy_value in array.py__iter__(): objects = ValueSet.from_sets( _execute_array_values(inference_state, typ) for typ in lazy_value.infer() ) values.append(LazyKnownValues(objects)) cls = FakeTuple if array.array_type == 'tuple' else FakeList return {cls(inference_state, values)} else: return array.execute_annotation() @inference_state_method_cache() def infer_param(function_value, param): def infer_docstring(docstring): return ValueSet( p for param_str in _search_param_in_docstr(docstring, param.name.value) for p in _infer_for_statement_string(module_context, param_str) ) module_context = function_value.get_root_context() func = param.get_parent_function() if func.type == 'lambdef': return NO_VALUES types = infer_docstring(function_value.py__doc__()) if function_value.is_bound_method() \ and function_value.py__name__() == '__init__': types |= infer_docstring(function_value.class_context.py__doc__()) debug.dbg('Found param types for docstring: %s', types, color='BLUE') return types @inference_state_method_cache() @iterator_to_value_set def infer_return_types(function_value): def search_return_in_docstr(code): for p in DOCSTRING_RETURN_PATTERNS: match = p.search(code) if match: yield _strip_rst_role(match.group(1)) # Check for numpy style return hint yield from _search_return_in_numpydocstr(code) for type_str in search_return_in_docstr(function_value.py__doc__()): yield from _infer_for_statement_string(function_value.get_root_context(), type_str)