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# Random Operations
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Functions for generating random selections and samples from combinatorial spaces.
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## Capabilities
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### Random Combinatorial Selections
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Functions for generating random elements from combinatorial spaces.
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```python { .api }
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def random_product(*iterables: Iterable[Any], repeat: int = 1) -> tuple[Any, ...]: ...
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def random_permutation(iterable: Iterable[Any], r: int = None) -> tuple[Any, ...]: ...
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def random_combination(iterable: Iterable[Any], r: int) -> tuple[Any, ...]: ...
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def random_combination_with_replacement(iterable: Iterable[Any], r: int) -> tuple[Any, ...]: ...
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```
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**Usage:**
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```python
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from more_itertools import random_product, random_permutation, random_combination
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# Generate random Cartesian product element
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pools = ['ABC', '123']
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rand_prod = random_product(*pools)  # e.g., ('B', '3')
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# Generate random permutation
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data = 'ABCDE'
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rand_perm = random_permutation(data, 3)  # e.g., ('D', 'A', 'C')
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# Generate random combination
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rand_combo = random_combination(data, 3)  # e.g., ('A', 'C', 'E')
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# Generate random combination with replacement
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rand_combo_repl = random_combination_with_replacement(data, 3)  # e.g., ('A', 'A', 'D')
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```
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### Sampling Operations
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Functions for sampling elements from iterables.
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```python { .api }
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def sample(iterable: Iterable[Any], k: int, *, counts: Iterable[int] = None) -> list[Any]: ...
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```
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**Usage:**
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```python
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from more_itertools import sample
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# Sample k elements from iterable
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data = range(100)
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sampled = sample(data, 5)  # e.g., [23, 7, 45, 12, 89]
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# Sample with weights (counts)
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items = ['A', 'B', 'C']
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weights = [1, 3, 2]  # B is 3x more likely than A
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weighted_sample = sample(items, 10, counts=weights)
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# e.g., ['B', 'C', 'B', 'A', 'B', 'C', 'B', 'B', 'C', 'B']
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```