djavu-asus/elpy/rpc-venv/lib/python3.11/site-packages/jedi/inference/param.py

   1 from collections import defaultdict
   2 from inspect import Parameter
   3
   4 from jedi import debug
   5 from jedi.inference.utils import PushBackIterator
   6 from jedi.inference import analysis
   7 from jedi.inference.lazy_value import LazyKnownValue, \
   8     LazyTreeValue, LazyUnknownValue
   9 from jedi.inference.value import iterable
  10 from jedi.inference.names import ParamName
  11
  12
  13 def _add_argument_issue(error_name, lazy_value, message):
  14     if isinstance(lazy_value, LazyTreeValue):
  15         node = lazy_value.data
  16         if node.parent.type == 'argument':
  17             node = node.parent
  18         return analysis.add(lazy_value.context, error_name, node, message)
  19
  20
  21 class ExecutedParamName(ParamName):
  22     def __init__(self, function_value, arguments, param_node, lazy_value, is_default=False):
  23         super().__init__(function_value, param_node.name, arguments=arguments)
  24         self._lazy_value = lazy_value
  25         self._is_default = is_default
  26
  27     def infer(self):
  28         return self._lazy_value.infer()
  29
  30     def matches_signature(self):
  31         if self._is_default:
  32             return True
  33         argument_values = self.infer().py__class__()
  34         if self.get_kind() in (Parameter.VAR_POSITIONAL, Parameter.VAR_KEYWORD):
  35             return True
  36         annotations = self.infer_annotation(execute_annotation=False)
  37         if not annotations:
  38             # If we cannot infer annotations - or there aren't any - pretend
  39             # that the signature matches.
  40             return True
  41         matches = any(c1.is_sub_class_of(c2)
  42                       for c1 in argument_values
  43                       for c2 in annotations.gather_annotation_classes())
  44         debug.dbg("param compare %s: %s <=> %s",
  45                   matches, argument_values, annotations, color='BLUE')
  46         return matches
  47
  48     def __repr__(self):
  49         return '<%s: %s>' % (self.__class__.__name__, self.string_name)
  50
  51
  52 def get_executed_param_names_and_issues(function_value, arguments):
  53     """
  54     Return a tuple of:
  55       - a list of `ExecutedParamName`s corresponding to the arguments of the
  56         function execution `function_value`, containing the inferred value of
  57         those arguments (whether explicit or default)
  58       - a list of the issues encountered while building that list
  59
  60     For example, given:
  61     ```
  62     def foo(a, b, c=None, d='d'): ...
  63
  64     foo(42, c='c')
  65     ```
  66
  67     Then for the execution of `foo`, this will return a tuple containing:
  68       - a list with entries for each parameter a, b, c & d; the entries for a,
  69         c, & d will have their values (42, 'c' and 'd' respectively) included.
  70       - a list with a single entry about the lack of a value for `b`
  71     """
  72     def too_many_args(argument):
  73         m = _error_argument_count(funcdef, len(unpacked_va))
  74         # Just report an error for the first param that is not needed (like
  75         # cPython).
  76         if arguments.get_calling_nodes():
  77             # There might not be a valid calling node so check for that first.
  78             issues.append(
  79                 _add_argument_issue(
  80                     'type-error-too-many-arguments',
  81                     argument,
  82                     message=m
  83                 )
  84             )
  85         else:
  86             issues.append(None)
  87             debug.warning('non-public warning: %s', m)
  88
  89     issues = []  # List[Optional[analysis issue]]
  90     result_params = []
  91     param_dict = {}
  92     funcdef = function_value.tree_node
  93     # Default params are part of the value where the function was defined.
  94     # This means that they might have access on class variables that the
  95     # function itself doesn't have.
  96     default_param_context = function_value.get_default_param_context()
  97
  98     for param in funcdef.get_params():
  99         param_dict[param.name.value] = param
 100     unpacked_va = list(arguments.unpack(funcdef))
 101     var_arg_iterator = PushBackIterator(iter(unpacked_va))
 102
 103     non_matching_keys = defaultdict(lambda: [])
 104     keys_used = {}
 105     keys_only = False
 106     had_multiple_value_error = False
 107     for param in funcdef.get_params():
 108         # The value and key can both be null. There, the defaults apply.
 109         # args / kwargs will just be empty arrays / dicts, respectively.
 110         # Wrong value count is just ignored. If you try to test cases that are
 111         # not allowed in Python, Jedi will maybe not show any completions.
 112         is_default = False
 113         key, argument = next(var_arg_iterator, (None, None))
 114         while key is not None:
 115             keys_only = True
 116             try:
 117                 key_param = param_dict[key]
 118             except KeyError:
 119                 non_matching_keys[key] = argument
 120             else:
 121                 if key in keys_used:
 122                     had_multiple_value_error = True
 123                     m = ("TypeError: %s() got multiple values for keyword argument '%s'."
 124                          % (funcdef.name, key))
 125                     for contextualized_node in arguments.get_calling_nodes():
 126                         issues.append(
 127                             analysis.add(contextualized_node.context,
 128                                          'type-error-multiple-values',
 129                                          contextualized_node.node, message=m)
 130                         )
 131                 else:
 132                     keys_used[key] = ExecutedParamName(
 133                         function_value, arguments, key_param, argument)
 134             key, argument = next(var_arg_iterator, (None, None))
 135
 136         try:
 137             result_params.append(keys_used[param.name.value])
 138             continue
 139         except KeyError:
 140             pass
 141
 142         if param.star_count == 1:
 143             # *args param
 144             lazy_value_list = []
 145             if argument is not None:
 146                 lazy_value_list.append(argument)
 147                 for key, argument in var_arg_iterator:
 148                     # Iterate until a key argument is found.
 149                     if key:
 150                         var_arg_iterator.push_back((key, argument))
 151                         break
 152                     lazy_value_list.append(argument)
 153             seq = iterable.FakeTuple(function_value.inference_state, lazy_value_list)
 154             result_arg = LazyKnownValue(seq)
 155         elif param.star_count == 2:
 156             if argument is not None:
 157                 too_many_args(argument)
 158             # **kwargs param
 159             dct = iterable.FakeDict(function_value.inference_state, dict(non_matching_keys))
 160             result_arg = LazyKnownValue(dct)
 161             non_matching_keys = {}
 162         else:
 163             # normal param
 164             if argument is None:
 165                 # No value: Return an empty container
 166                 if param.default is None:
 167                     result_arg = LazyUnknownValue()
 168                     if not keys_only:
 169                         for contextualized_node in arguments.get_calling_nodes():
 170                             m = _error_argument_count(funcdef, len(unpacked_va))
 171                             issues.append(
 172                                 analysis.add(
 173                                     contextualized_node.context,
 174                                     'type-error-too-few-arguments',
 175                                     contextualized_node.node,
 176                                     message=m,
 177                                 )
 178                             )
 179                 else:
 180                     result_arg = LazyTreeValue(default_param_context, param.default)
 181                     is_default = True
 182             else:
 183                 result_arg = argument
 184
 185         result_params.append(ExecutedParamName(
 186             function_value, arguments, param, result_arg, is_default=is_default
 187         ))
 188         if not isinstance(result_arg, LazyUnknownValue):
 189             keys_used[param.name.value] = result_params[-1]
 190
 191     if keys_only:
 192         # All arguments should be handed over to the next function. It's not
 193         # about the values inside, it's about the names. Jedi needs to now that
 194         # there's nothing to find for certain names.
 195         for k in set(param_dict) - set(keys_used):
 196             param = param_dict[k]
 197
 198             if not (non_matching_keys or had_multiple_value_error
 199                     or param.star_count or param.default):
 200                 # add a warning only if there's not another one.
 201                 for contextualized_node in arguments.get_calling_nodes():
 202                     m = _error_argument_count(funcdef, len(unpacked_va))
 203                     issues.append(
 204                         analysis.add(contextualized_node.context,
 205                                      'type-error-too-few-arguments',
 206                                      contextualized_node.node, message=m)
 207                     )
 208
 209     for key, lazy_value in non_matching_keys.items():
 210         m = "TypeError: %s() got an unexpected keyword argument '%s'." \
 211             % (funcdef.name, key)
 212         issues.append(
 213             _add_argument_issue(
 214                 'type-error-keyword-argument',
 215                 lazy_value,
 216                 message=m
 217             )
 218         )
 219
 220     remaining_arguments = list(var_arg_iterator)
 221     if remaining_arguments:
 222         first_key, lazy_value = remaining_arguments[0]
 223         too_many_args(lazy_value)
 224     return result_params, issues
 225
 226
 227 def get_executed_param_names(function_value, arguments):
 228     """
 229     Return a list of `ExecutedParamName`s corresponding to the arguments of the
 230     function execution `function_value`, containing the inferred value of those
 231     arguments (whether explicit or default). Any issues building this list (for
 232     example required arguments which are missing in the invocation) are ignored.
 233
 234     For example, given:
 235     ```
 236     def foo(a, b, c=None, d='d'): ...
 237
 238     foo(42, c='c')
 239     ```
 240
 241     Then for the execution of `foo`, this will return a list containing entries
 242     for each parameter a, b, c & d; the entries for a, c, & d will have their
 243     values (42, 'c' and 'd' respectively) included.
 244     """
 245     return get_executed_param_names_and_issues(function_value, arguments)[0]
 246
 247
 248 def _error_argument_count(funcdef, actual_count):
 249     params = funcdef.get_params()
 250     default_arguments = sum(1 for p in params if p.default or p.star_count)
 251
 252     if default_arguments == 0:
 253         before = 'exactly '
 254     else:
 255         before = 'from %s to ' % (len(params) - default_arguments)
 256     return ('TypeError: %s() takes %s%s arguments (%s given).'
 257             % (funcdef.name, before, len(params), actual_count))