Add Reservoir Sampling algorithm for random selection from data streams

Author: Kishara98

other/reservoir_sampling.py

@@ -0,0 +1,65 @@
+"""
+reservoir_sampling.py
+
+An implementation of Reservoir Sampling — a random algorithm to
+select `k` items from a stream of unknown or very large size with equal probability.
+
+Reference:
+https://en.wikipedia.org/wiki/Reservoir_sampling
+
+Example:
+>>> data_stream = [1, 2, 3, 4, 5, 6, 7, 8, 9]
+>>> len(reservoir_sampling(data_stream, 3))
+3
+>>> all(isinstance(i, int) for i in reservoir_sampling(data_stream, 3))
+True
+"""
+
+import random
+from typing import Iterable, List, TypeVar
+
+T = TypeVar("T")
+
+
+def reservoir_sampling(stream: Iterable[T], k: int) -> List[T]:
+    """
+    Return a random sample of size `k` from the given data stream.
+
+    :param stream: An iterable data stream (e.g., list, generator)
+    :param k: Number of elements to sample
+    :return: A list of `k` randomly selected items
+
+    >>> data = [10, 20, 30, 40, 50]
+    >>> len(reservoir_sampling(data, 2))
+    2
+    >>> isinstance(reservoir_sampling(data, 3), list)
+    True
+    >>> try:
+    ...     reservoir_sampling([], 1)
+    ... except ValueError:
+    ...     print("Error")
+    Error
+    """
+    if k <= 0:
+        raise ValueError("Sample size k must be greater than zero")
+
+    reservoir = []
+    for i, item in enumerate(stream):
+        if i < k:
+            reservoir.append(item)
+        else:
+            j = random.randint(0, i)
+            if j < k:
+                reservoir[j] = item
+
+    if len(reservoir) < k:
+        raise ValueError("Stream has fewer elements than the requested sample size")
+
+    return reservoir
+
+
+if __name__ == "__main__":
+    # Example usage
+    data_stream = range(1, 100)
+    sample = reservoir_sampling(data_stream, 5)
+    print("Random sample from stream:", sample)