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"""
Docstrings are another source of information for functions and classes.
:mod:`jedi.evaluate.dynamic` 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
from textwrap import dedent
from parso import parse, ParserSyntaxError
from jedi._compatibility import u
from jedi.evaluate.utils import indent_block
from jedi.evaluate.cache import evaluator_method_cache
from jedi.evaluate.base_context import iterator_to_context_set, ContextSet, \
NO_CONTEXTS
from jedi.evaluate.lazy_context import LazyKnownContexts
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):
raise _numpy_doc_string_cache
try:
from numpydoc.docscrape import NumpyDocString
_numpy_doc_string_cache = NumpyDocString
except ImportError as e:
_numpy_doc_string_cache = e
raise
return _numpy_doc_string_cache
def _search_param_in_numpydocstr(docstr, param_str):
"""Search `docstr` (in numpydoc format) for type(-s) of `param_str`."""
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 (KeyError, AttributeError, ImportError):
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.
"""
try:
doc = _get_numpy_doc_string_cls()(docstr)
except ImportError:
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 (KeyError, AttributeError):
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
for type_ in _expand_typestr(r_type):
yield 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='3.6').children[0]
if node.type == 'atom':
for leaf in 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 _evaluate_for_statement_string(module_context, string):
code = dedent(u("""
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
# Take the default grammar here, if we load the Python 2.7 grammar here, it
# will be impossible to use `...` (Ellipsis) as a token. Docstring types
# don't need to conform with the current grammar.
grammar = module_context.evaluator.latest_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.evaluate.context import FunctionContext
function_context = FunctionContext(
module_context.evaluator,
module_context,
funcdef
)
func_execution_context = function_context.get_function_execution()
# 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.eval_node(stmt)
return ContextSet.from_sets(
_execute_array_values(module_context.evaluator, d)
for d in definitions
)
def _execute_array_values(evaluator, 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.evaluate.context.iterable import SequenceLiteralContext, FakeSequence
if isinstance(array, SequenceLiteralContext):
values = []
for lazy_context in array.py__iter__():
objects = ContextSet.from_sets(
_execute_array_values(evaluator, typ)
for typ in lazy_context.infer()
)
values.append(LazyKnownContexts(objects))
return {FakeSequence(evaluator, array.array_type, values)}
else:
return array.execute_evaluated()
@evaluator_method_cache()
def infer_param(execution_context, param):
from jedi.evaluate.context.instance import InstanceArguments
from jedi.evaluate.context import FunctionExecutionContext
def eval_docstring(docstring):
return ContextSet.from_iterable(
p
for param_str in _search_param_in_docstr(docstring, param.name.value)
for p in _evaluate_for_statement_string(module_context, param_str)
)
module_context = execution_context.get_root_context()
func = param.get_parent_function()
if func.type == 'lambdef':
return NO_CONTEXTS
types = eval_docstring(execution_context.py__doc__())
if isinstance(execution_context, FunctionExecutionContext) \
and isinstance(execution_context.var_args, InstanceArguments) \
and execution_context.function_context.py__name__() == '__init__':
class_context = execution_context.var_args.instance.class_context
types |= eval_docstring(class_context.py__doc__())
return types
@evaluator_method_cache()
@iterator_to_context_set
def infer_return_types(function_context):
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
for type_ in _search_return_in_numpydocstr(code):
yield type_
for type_str in search_return_in_docstr(function_context.py__doc__()):
for type_eval in _evaluate_for_statement_string(function_context.get_root_context(), type_str):
yield type_eval
|