jedi-fork/jedi/evaluate/docstrings.py

"""
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 two 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>`_

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.
"""

from ast import literal_eval
import re
from textwrap import dedent

from jedi._compatibility import u
from jedi.common import unite
from jedi.evaluate import context
from jedi.evaluate.cache import memoize_default
from jedi.common import indent_block
from jedi.evaluate.iterable import SequenceLiteralContext, FakeSequence


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':[^`]+:`([^`]+)`')


try:
    from numpydoc.docscrape import NumpyDocString
except ImportError:
    def _search_param_in_numpydocstr(docstr, param_str):
        return []
else:
    def _search_param_in_numpydocstr(docstr, param_str):
        """Search `docstr` (in numpydoc format) for type(-s) of `param_str`."""
        params = NumpyDocString(docstr)._parsed_data['Parameters']
        for p_name, p_type, p_descr in params:
            if p_name == param_str:
                m = re.match('([^,]+(,[^,]+)*?)(,[ ]*optional)?$', p_type)
                if m:
                    p_type = m.group(1)

                if p_type.startswith('{'):
                    types = set(type(x).__name__ for x in literal_eval(p_type))
                    return list(types)
                else:
                    return [p_type]
        return []


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) or
            [])


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.
        '''
    {0}
    """))
    if string is None:
        return []

    for element in re.findall('((?:\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
    module = grammar.parse(code.format(indent_block(string)))
    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 []

    from jedi.evaluate.param import ValuesArguments
    from jedi.evaluate.representation import FunctionContext
    function_context = FunctionContext(
        module_context.evaluator,
        module_context,
        funcdef
    )
    func_execution_context = function_context.get_function_execution(
        ValuesArguments([])
    )
    # 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 unite(_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.
    """
    if isinstance(array, SequenceLiteralContext):
        values = []
        for lazy_context in array.py__iter__():
            objects = unite(_execute_array_values(evaluator, typ) for typ in lazy_context.infer())
            values.append(context.LazyKnownContexts(objects))
        return set([FakeSequence(evaluator, array.array_type, values)])
    else:
        return array.execute_evaluated()


@memoize_default()
def infer_param(execution_context, param):
    from jedi.evaluate.instance import InstanceFunctionExecution

    def eval_docstring(docstring):
        return set(
            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 set()

    types = eval_docstring(execution_context.py__doc__())
    if isinstance(execution_context, InstanceFunctionExecution) and \
            execution_context.function_context.name.string_name == '__init__':
        class_context = execution_context.instance.class_context
        types |= eval_docstring(class_context.py__doc__())

    return types


@memoize_default()
def infer_return_types(function_context):
    def search_return_in_docstr(code):
        for p in DOCSTRING_RETURN_PATTERNS:
            match = p.search(code)
            if match:
                return _strip_rst_role(match.group(1))

    type_str = search_return_in_docstr(function_context.py__doc__())
    return _evaluate_for_statement_string(function_context.get_root_context(), type_str)