class_docstr: A strategy responsible for fixed length tuples based on heterogeneous
  strategies for each of their elements.
class_docstr_tok: ["A","strategy","responsible","for","fixed","length","tuples","based","on","heterogeneous","strategies","for","each","of","their","elements","."]
code: def __init__(self, strategies: Iterable[SearchStrategy[Any]]):
      super().__init__()
      self.element_strategies = tuple(strategies)
  
imports: import copy
  from typing import Any, Iterable, Tuple, overload
  from hypothesis.errors import InvalidArgument
  from hypothesis.internal.conjecture import utils
  from hypothesis.internal.conjecture.junkdrawer import LazySequenceCopy
  from hypothesis.internal.conjecture.utils import combine_labels
  from hypothesis.internal.reflection import is_identity_function
  from hypothesis.strategies._internal.strategies import T3, T4, T5, Ex, MappedSearchStrategy, SearchStrategy, T, check_strategy, filter_not_satisfied
  from hypothesis.strategies._internal.utils import cacheable, defines_strategy
label_desc: Use image node_id 1 to create a new TupleStrategy object from inherited base classes: SearchStrategy with example: obj = TupleStrategy(strategies)