bradfield folder

Author: Joshua Goller

bradfield/quicksort.py

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+"""
+Statement: Sort an array with quicksort and try different partitioning strategies.
+Input: List of Ints; may be empty, singleton or very large
+Out: List of Ints
+-----------
+Understand:
+- Problem statement calls for quicksort.
+- Quicksort (wikipedia):
+    1. Pick an element, called a pivot, from the array.
+    2. Partitioning: reorder the array so that all elements with values less than
+       the pivot come before the pivot, while all elements with values greater than
+       the pivot come after it (equal values can go either way). After this partitioning,
+       the pivot is in its final position. This is called the partition operation.
+    3. Recursively apply the above steps to the sub-array of elements with smaller 
+       values and separately to the sub-array of elements with greater values.
+- We should be able to easily change which partitioning strategy we use in the implementation.
+- Skiena points out that some inputs (which?) can be pathological, but that pre-shuffling our input takes care of most of these
+"""
+
+
+
+def lomuto_partition():
+    pass
+
+def hoare_partition():
+    pass
+
+def sort(arr, partition_fn):
+    return arr
+
+def quicksort(arr, partition_fn, shuffle=True):
+    if shuffle:
+        # do shuffling here
+        pass
+    return sort(arr, partition_fn)
+
+if __name__ == '__main__':
+    test_arrs = [
+        [],
+        [1]
+        [6, 5, 4, 3, 2, 1],
+        [1, 2, 3, 4, 5, 6]
+        [1, 1, 1, 1, 1, 1],
+        [5, 1, 3, 4, 5, 10],
+    ]
+    for arr in test_arrs:
+        assert quicksort(arr, lomuto_partition) == sorted(arr)
+        assert quicksort(arr, hoare_partition) == sorted(arr)