-
-
Notifications
You must be signed in to change notification settings - Fork 499
/
annotation.py
477 lines (404 loc) · 16.6 KB
/
annotation.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
"""
PEP 0484 ( https://www.python.org/dev/peps/pep-0484/ ) describes type hints
through function annotations. There is a strong suggestion in this document
that only the type of type hinting defined in PEP0484 should be allowed
as annotations in future python versions.
"""
import re
from parso import ParserSyntaxError, parse
from jedi._compatibility import force_unicode, Parameter
from jedi.inference.cache import inference_state_method_cache
from jedi.inference.base_value import ValueSet, NO_VALUES
from jedi.inference.gradual.base import DefineGenericBase, GenericClass
from jedi.inference.gradual.generics import TupleGenericManager
from jedi.inference.gradual.typing import TypingClassValueWithIndex
from jedi.inference.gradual.type_var import TypeVar
from jedi.inference.helpers import is_string
from jedi.inference.compiled import builtin_from_name
from jedi.inference.param import get_executed_param_names
from jedi import debug
from jedi import parser_utils
def infer_annotation(context, annotation):
"""
Inferes an annotation node. This means that it inferes the part of
`int` here:
foo: int = 3
Also checks for forward references (strings)
"""
value_set = context.infer_node(annotation)
if len(value_set) != 1:
debug.warning("Inferred typing index %s should lead to 1 object, "
" not %s" % (annotation, value_set))
return value_set
inferred_value = list(value_set)[0]
if is_string(inferred_value):
result = _get_forward_reference_node(context, inferred_value.get_safe_value())
if result is not None:
return context.infer_node(result)
return value_set
def _infer_annotation_string(context, string, index=None):
node = _get_forward_reference_node(context, string)
if node is None:
return NO_VALUES
value_set = context.infer_node(node)
if index is not None:
value_set = value_set.filter(
lambda value: value.array_type == u'tuple' # noqa
and len(list(value.py__iter__())) >= index
).py__simple_getitem__(index)
return value_set
def _get_forward_reference_node(context, string):
try:
new_node = context.inference_state.grammar.parse(
force_unicode(string),
start_symbol='eval_input',
error_recovery=False
)
except ParserSyntaxError:
debug.warning('Annotation not parsed: %s' % string)
return None
else:
module = context.tree_node.get_root_node()
parser_utils.move(new_node, module.end_pos[0])
new_node.parent = context.tree_node
return new_node
def _split_comment_param_declaration(decl_text):
"""
Split decl_text on commas, but group generic expressions
together.
For example, given "foo, Bar[baz, biz]" we return
['foo', 'Bar[baz, biz]'].
"""
try:
node = parse(decl_text, error_recovery=False).children[0]
except ParserSyntaxError:
debug.warning('Comment annotation is not valid Python: %s' % decl_text)
return []
if node.type in ['name', 'atom_expr', 'power']:
return [node.get_code().strip()]
params = []
try:
children = node.children
except AttributeError:
return []
else:
for child in children:
if child.type in ['name', 'atom_expr', 'power']:
params.append(child.get_code().strip())
return params
@inference_state_method_cache()
def infer_param(function_value, param, ignore_stars=False):
values = _infer_param(function_value, param)
if ignore_stars:
return values
inference_state = function_value.inference_state
if param.star_count == 1:
tuple_ = builtin_from_name(inference_state, 'tuple')
return ValueSet([GenericClass(
tuple_,
TupleGenericManager((values,)),
) for c in values])
elif param.star_count == 2:
dct = builtin_from_name(inference_state, 'dict')
generics = (
ValueSet([builtin_from_name(inference_state, 'str')]),
values
)
return ValueSet([GenericClass(
dct,
TupleGenericManager(generics),
) for c in values])
pass
return values
def _infer_param(function_value, param):
"""
Infers the type of a function parameter, using type annotations.
"""
annotation = param.annotation
if annotation is None:
# If no Python 3-style annotation, look for a Python 2-style comment
# annotation.
# Identify parameters to function in the same sequence as they would
# appear in a type comment.
all_params = [child for child in param.parent.children
if child.type == 'param']
node = param.parent.parent
comment = parser_utils.get_following_comment_same_line(node)
if comment is None:
return NO_VALUES
match = re.match(r"^#\s*type:\s*\(([^#]*)\)\s*->", comment)
if not match:
return NO_VALUES
params_comments = _split_comment_param_declaration(match.group(1))
# Find the specific param being investigated
index = all_params.index(param)
# If the number of parameters doesn't match length of type comment,
# ignore first parameter (assume it's self).
if len(params_comments) != len(all_params):
debug.warning(
"Comments length != Params length %s %s",
params_comments, all_params
)
if function_value.is_bound_method():
if index == 0:
# Assume it's self, which is already handled
return NO_VALUES
index -= 1
if index >= len(params_comments):
return NO_VALUES
param_comment = params_comments[index]
return _infer_annotation_string(
function_value.get_default_param_context(),
param_comment
)
# Annotations are like default params and resolve in the same way.
context = function_value.get_default_param_context()
return infer_annotation(context, annotation)
def py__annotations__(funcdef):
dct = {}
for function_param in funcdef.get_params():
param_annotation = function_param.annotation
if param_annotation is not None:
dct[function_param.name.value] = param_annotation
return_annotation = funcdef.annotation
if return_annotation:
dct['return'] = return_annotation
return dct
@inference_state_method_cache()
def infer_return_types(function, arguments):
"""
Infers the type of a function's return value,
according to type annotations.
"""
all_annotations = py__annotations__(function.tree_node)
annotation = all_annotations.get("return", None)
if annotation is None:
# If there is no Python 3-type annotation, look for a Python 2-type annotation
node = function.tree_node
comment = parser_utils.get_following_comment_same_line(node)
if comment is None:
return NO_VALUES
match = re.match(r"^#\s*type:\s*\([^#]*\)\s*->\s*([^#]*)", comment)
if not match:
return NO_VALUES
return _infer_annotation_string(
function.get_default_param_context(),
match.group(1).strip()
).execute_annotation()
if annotation is None:
return NO_VALUES
context = function.get_default_param_context()
unknown_type_vars = find_unknown_type_vars(context, annotation)
annotation_values = infer_annotation(context, annotation)
if not unknown_type_vars:
return annotation_values.execute_annotation()
type_var_dict = infer_type_vars_for_execution(function, arguments, all_annotations)
return ValueSet.from_sets(
ann.define_generics(type_var_dict)
if isinstance(ann, (DefineGenericBase, TypeVar)) else ValueSet({ann})
for ann in annotation_values
).execute_annotation()
def infer_type_vars_for_execution(function, arguments, annotation_dict):
"""
Some functions use type vars that are not defined by the class, but rather
only defined in the function. See for example `iter`. In those cases we
want to:
1. Search for undefined type vars.
2. Infer type vars with the execution state we have.
3. Return the union of all type vars that have been found.
"""
context = function.get_default_param_context()
annotation_variable_results = {}
executed_param_names = get_executed_param_names(function, arguments)
for executed_param_name in executed_param_names:
try:
annotation_node = annotation_dict[executed_param_name.string_name]
except KeyError:
continue
annotation_variables = find_unknown_type_vars(context, annotation_node)
if annotation_variables:
# Infer unknown type var
annotation_value_set = context.infer_node(annotation_node)
kind = executed_param_name.get_kind()
actual_value_set = executed_param_name.infer()
if kind is Parameter.VAR_POSITIONAL:
actual_value_set = actual_value_set.merge_types_of_iterate()
elif kind is Parameter.VAR_KEYWORD:
# TODO _dict_values is not public.
actual_value_set = actual_value_set.try_merge('_dict_values')
for ann in annotation_value_set:
_merge_type_var_dicts(
annotation_variable_results,
_infer_type_vars(ann, actual_value_set),
)
return annotation_variable_results
def infer_return_for_callable(arguments, param_values, result_values):
all_type_vars = {}
for pv in param_values:
if pv.array_type == 'list':
type_var_dict = infer_type_vars_for_callable(arguments, pv.py__iter__())
all_type_vars.update(type_var_dict)
return ValueSet.from_sets(
v.define_generics(all_type_vars)
if isinstance(v, (DefineGenericBase, TypeVar)) else ValueSet({v})
for v in result_values
).execute_annotation()
def infer_type_vars_for_callable(arguments, lazy_params):
"""
Infers type vars for the Calllable class:
def x() -> Callable[[Callable[..., _T]], _T]: ...
"""
annotation_variable_results = {}
for (_, lazy_value), lazy_callable_param in zip(arguments.unpack(), lazy_params):
callable_param_values = lazy_callable_param.infer()
# Infer unknown type var
actual_value_set = lazy_value.infer()
for v in callable_param_values:
_merge_type_var_dicts(
annotation_variable_results,
_infer_type_vars(v, actual_value_set),
)
return annotation_variable_results
def _merge_type_var_dicts(base_dict, new_dict):
for type_var_name, values in new_dict.items():
if values:
try:
base_dict[type_var_name] |= values
except KeyError:
base_dict[type_var_name] = values
def _infer_type_vars(annotation_value, value_set, is_class_value=False):
"""
This function tries to find information about undefined type vars and
returns a dict from type var name to value set.
This is for example important to understand what `iter([1])` returns.
According to typeshed, `iter` returns an `Iterator[_T]`:
def iter(iterable: Iterable[_T]) -> Iterator[_T]: ...
This functions would generate `int` for `_T` in this case, because it
unpacks the `Iterable`.
"""
type_var_dict = {}
if isinstance(annotation_value, TypeVar):
if not is_class_value:
return {annotation_value.py__name__(): value_set.py__class__()}
return {annotation_value.py__name__(): value_set}
elif isinstance(annotation_value, TypingClassValueWithIndex):
name = annotation_value.py__name__()
if name == 'Type':
given = annotation_value.get_generics()
if given:
for nested_annotation_value in given[0]:
_merge_type_var_dicts(
type_var_dict,
_infer_type_vars(
nested_annotation_value,
value_set,
is_class_value=True,
)
)
elif name == 'Callable':
given = annotation_value.get_generics()
if len(given) == 2:
for nested_annotation_value in given[1]:
_merge_type_var_dicts(
type_var_dict,
_infer_type_vars(
nested_annotation_value,
value_set.execute_annotation(),
)
)
elif isinstance(annotation_value, GenericClass):
name = annotation_value.py__name__()
if name == 'Iterable':
given = annotation_value.get_generics()
if given:
for nested_annotation_value in given[0]:
_merge_type_var_dicts(
type_var_dict,
_infer_type_vars(
nested_annotation_value,
value_set.merge_types_of_iterate()
)
)
elif name == 'Mapping':
given = annotation_value.get_generics()
if len(given) == 2:
for value in value_set:
try:
method = value.get_mapping_item_values
except AttributeError:
continue
key_values, value_values = method()
for nested_annotation_value in given[0]:
_merge_type_var_dicts(
type_var_dict,
_infer_type_vars(
nested_annotation_value,
key_values,
)
)
for nested_annotation_value in given[1]:
_merge_type_var_dicts(
type_var_dict,
_infer_type_vars(
nested_annotation_value,
value_values,
)
)
return type_var_dict
def find_type_from_comment_hint_for(context, node, name):
return _find_type_from_comment_hint(context, node, node.children[1], name)
def find_type_from_comment_hint_with(context, node, name):
assert len(node.children[1].children) == 3, \
"Can only be here when children[1] is 'foo() as f'"
varlist = node.children[1].children[2]
return _find_type_from_comment_hint(context, node, varlist, name)
def find_type_from_comment_hint_assign(context, node, name):
return _find_type_from_comment_hint(context, node, node.children[0], name)
def _find_type_from_comment_hint(context, node, varlist, name):
index = None
if varlist.type in ("testlist_star_expr", "exprlist", "testlist"):
# something like "a, b = 1, 2"
index = 0
for child in varlist.children:
if child == name:
break
if child.type == "operator":
continue
index += 1
else:
return []
comment = parser_utils.get_following_comment_same_line(node)
if comment is None:
return []
match = re.match(r"^#\s*type:\s*([^#]*)", comment)
if match is None:
return []
return _infer_annotation_string(
context, match.group(1).strip(), index
).execute_annotation()
def find_unknown_type_vars(context, node):
def check_node(node):
if node.type in ('atom_expr', 'power'):
trailer = node.children[-1]
if trailer.type == 'trailer' and trailer.children[0] == '[':
for subscript_node in _unpack_subscriptlist(trailer.children[1]):
check_node(subscript_node)
else:
found[:] = _filter_type_vars(context.infer_node(node), found)
found = [] # We're not using a set, because the order matters.
check_node(node)
return found
def _filter_type_vars(value_set, found=()):
new_found = list(found)
for type_var in value_set:
if isinstance(type_var, TypeVar) and type_var not in found:
new_found.append(type_var)
return new_found
def _unpack_subscriptlist(subscriptlist):
if subscriptlist.type == 'subscriptlist':
for subscript in subscriptlist.children[::2]:
if subscript.type != 'subscript':
yield subscript
else:
if subscriptlist.type != 'subscript':
yield subscriptlist