Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.8/site-packages/astroid/brain/brain_random.py: 35%

1# Licensed under the LGPL: https://www.gnu.org/licenses/old-licenses/lgpl-2.1.en.html 

2# For details: https://github.com/pylint-dev/astroid/blob/main/LICENSE 

3# Copyright (c) https://github.com/pylint-dev/astroid/blob/main/CONTRIBUTORS.txt 

4 

5from __future__ import annotations 

6 

7import random 

8 

9from astroid import helpers 

10from astroid.context import InferenceContext 

11from astroid.exceptions import UseInferenceDefault 

12from astroid.inference_tip import inference_tip 

13from astroid.manager import AstroidManager 

14from astroid.nodes.node_classes import ( 

15 Attribute, 

16 Call, 

17 Const, 

18 EvaluatedObject, 

19 List, 

20 Name, 

21 Set, 

22 Tuple, 

23) 

24 

25ACCEPTED_ITERABLES_FOR_SAMPLE = (List, Set, Tuple) 

26 

27 

28def _clone_node_with_lineno(node, parent, lineno): 

29 if isinstance(node, EvaluatedObject): 

30 node = node.original 

31 cls = node.__class__ 

32 other_fields = node._other_fields 

33 _astroid_fields = node._astroid_fields 

34 init_params = { 

35 "lineno": lineno, 

36 "col_offset": node.col_offset, 

37 "parent": parent, 

38 "end_lineno": node.end_lineno, 

39 "end_col_offset": node.end_col_offset, 

40 } 

41 postinit_params = {param: getattr(node, param) for param in _astroid_fields} 

42 if other_fields: 

43 init_params.update({param: getattr(node, param) for param in other_fields}) 

44 new_node = cls(**init_params) 

45 if hasattr(node, "postinit") and _astroid_fields: 

46 new_node.postinit(**postinit_params) 

47 return new_node 

48 

49 

50def infer_random_sample(node, context: InferenceContext | None = None): 

51 if len(node.args) != 2: 

52 raise UseInferenceDefault 

53 

54 inferred_length = helpers.safe_infer(node.args[1], context=context) 

55 if not isinstance(inferred_length, Const): 

56 raise UseInferenceDefault 

57 if not isinstance(inferred_length.value, int): 

58 raise UseInferenceDefault 

59 

60 inferred_sequence = helpers.safe_infer(node.args[0], context=context) 

61 if not inferred_sequence: 

62 raise UseInferenceDefault 

63 

64 if not isinstance(inferred_sequence, ACCEPTED_ITERABLES_FOR_SAMPLE): 

65 raise UseInferenceDefault 

66 

67 if inferred_length.value > len(inferred_sequence.elts): 

68 # In this case, this will raise a ValueError 

69 raise UseInferenceDefault 

70 

71 try: 

72 elts = random.sample(inferred_sequence.elts, inferred_length.value) 

73 except ValueError as exc: 

74 raise UseInferenceDefault from exc 

75 

76 new_node = List( 

77 lineno=node.lineno, 

78 col_offset=node.col_offset, 

79 parent=node.scope(), 

80 end_lineno=node.end_lineno, 

81 end_col_offset=node.end_col_offset, 

82 ) 

83 new_elts = [ 

84 _clone_node_with_lineno(elt, parent=new_node, lineno=new_node.lineno) 

85 for elt in elts 

86 ] 

87 new_node.postinit(new_elts) 

88 return iter((new_node,)) 

89 

90 

91def _looks_like_random_sample(node) -> bool: 

92 func = node.func 

93 if isinstance(func, Attribute): 

94 return func.attrname == "sample" 

95 if isinstance(func, Name): 

96 return func.name == "sample" 

97 return False 

98 

99 

100AstroidManager().register_transform( 

101 Call, inference_tip(infer_random_sample), _looks_like_random_sample 

102)