Added counting sort (Issue #23)

allalgorithms/sorting/__init__.py

@@ -7,3 +7,4 @@
 from .cocktail_shaker_sort import cocktail_shaker_sort
 from .tree_sort import tree_sort
 from .heap_sort import heap_sort
+from .counting_sort import counting_sort

allalgorithms/sorting/counting_sort.py

@@ -0,0 +1,56 @@
+# -*- coding: UTF-8 -*-
+#
+# Radix Sort Algorithm
+# The All ▲lgorithms library for python
+#
+# Contributed by: Nicholas Gao
+# Github: @n-gao
+#
+class BinaryTree:
+    def __init__(self, value):
+        self.value = value
+        self.left_child = None
+        self.right_child = None
+
+    def add_child(self, value):
+        if value < self.value:
+            if self.left_child is None:
+                self.left_child = BinaryTree(value)
+            else:
+                self.left_child.add_child(value)
+        else:
+            if self.right_child is None:
+                self.right_child = BinaryTree(value)
+            else:
+                self.right_child.add_child(value)
+
+    def get_sorted_values(self):
+        result = []
+        if self.left_child is not None:
+            result = self.left_child.get_sorted_values()
+        result.append(self.value)
+        if self.right_child is not None:
+            result = result + self.right_child.get_sorted_values()
+        return result
+
+def counting_sort(arr):
+    counts = {}
+    tree = None
+    for value in arr:
+        if value in counts:
+            counts[value] += 1
+        else:
+            counts[value] = counts[value] + 1 if value in counts else 1
+            if tree is None:
+                tree = BinaryTree(value)
+            else:
+                tree.add_child(value)
+
+    sorted_values = tree.get_sorted_values()
+    i = 0
+    for value in sorted_values:
+        for _ in range(counts[value]):
+            arr[i] = value
+            i += 1
+
+    return arr

docs/sorting/counting-sort.md

@@ -0,0 +1,39 @@
+# Counting sort
+Counting sort is a sorting algorithm which does not actually sort
+the array but rather reconstructs it. It operates by counting how
+often every unique item (e.g., a certain number) occurs, sorts the
+unique items by TreeSort and then reconstructs an array by copying
+every unique item (the number of occurences)th times into the result.
+Its advantage is the fast computation which is only linear with respect
+of the input array *if* the number of unique items is significantly
+smaller than the number of items.
+
+## Install
+
+```
+pip install allalgorithms
+```
+
+## Usage
+
+```py
+from allalgorithms.sorting import counting_sort
+
+arr = [77, 2, 10, -2, 1, 7]
+
+print(counting_sort(arr))
+# -> [-2, 1, 2, 7, 10, 77]
+```
+
+## API
+
+```
+counting_sort(array)
+```
+
+> Returns a sorted array (does in-place replacements)
+
+##### Params:
+
+- `array`: Array to sort
+

tests/test_sorting.py

@@ -11,6 +11,7 @@
     tree_sort,
     heap_sort,
     shell_sort,
+    counting_sort
 )
 
 
@@ -39,6 +40,9 @@ def test_cocktail_shaker_sort(self):
     def test_tree_sort(self):
         self.assertEqual([-44, 1, 2, 3, 7, 19], tree_sort([7, 3, 2, 19, -44, 1]))
 
+    def test_counting_sort(self):
+        self.assertEqual([-44, 1, 2, 3, 7, 19], counting_sort([7, 3, 2, 19, -44, 1]))
+
     def test_heap_sort(self):
         array = [7, 3, 2, 19, -44, 1]
         heap_sort(array)