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# Licensed under the LGPL: https://www.gnu.org/licenses/old-licenses/lgpl-2.1.en.html
# For details: https://github.com/PyCQA/astroid/blob/master/COPYING.LESSER
import random
import astroid
from astroid import helpers
from astroid import MANAGER
ACCEPTED_ITERABLES_FOR_SAMPLE = (astroid.List, astroid.Set, astroid.Tuple)
def _clone_node_with_lineno(node, parent, lineno):
cls = node.__class__
other_fields = node._other_fields
_astroid_fields = node._astroid_fields
init_params = {"lineno": lineno, "col_offset": node.col_offset, "parent": parent}
postinit_params = {param: getattr(node, param) for param in _astroid_fields}
if other_fields:
init_params.update({param: getattr(node, param) for param in other_fields})
new_node = cls(**init_params)
if hasattr(node, "postinit") and _astroid_fields:
new_node.postinit(**postinit_params)
return new_node
def infer_random_sample(node, context=None):
if len(node.args) != 2:
raise astroid.UseInferenceDefault
length = node.args[1]
if not isinstance(length, astroid.Const):
raise astroid.UseInferenceDefault
if not isinstance(length.value, int):
raise astroid.UseInferenceDefault
inferred_sequence = helpers.safe_infer(node.args[0], context=context)
if not inferred_sequence:
raise astroid.UseInferenceDefault
if not isinstance(inferred_sequence, ACCEPTED_ITERABLES_FOR_SAMPLE):
raise astroid.UseInferenceDefault
if length.value > len(inferred_sequence.elts):
# In this case, this will raise a ValueError
raise astroid.UseInferenceDefault
try:
elts = random.sample(inferred_sequence.elts, length.value)
except ValueError:
raise astroid.UseInferenceDefault
new_node = astroid.List(
lineno=node.lineno, col_offset=node.col_offset, parent=node.scope()
)
new_elts = [
_clone_node_with_lineno(elt, parent=new_node, lineno=new_node.lineno)
for elt in elts
]
new_node.postinit(new_elts)
return iter((new_node,))
def _looks_like_random_sample(node):
func = node.func
if isinstance(func, astroid.Attribute):
return func.attrname == "sample"
if isinstance(func, astroid.Name):
return func.name == "sample"
return False
MANAGER.register_transform(
astroid.Call, astroid.inference_tip(infer_random_sample), _looks_like_random_sample
)
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