diff --git a/dynamic_programming/longest_sub_array.py b/dynamic_programming/longest_sub_array.py
new file mode 100644
index 000000000..b9a5e8de7
--- /dev/null
+++ b/dynamic_programming/longest_sub_array.py
@@ -0,0 +1,32 @@
+'''
+Auther  : Yvonne
+
+This is a pure Python implementation of Dynamic Programming solution to the edit distance problem.
+
+The problem is  :
+Given an array, to find the longest and continuous sub array and get the max sum of the sub array in the given array.
+'''
+
+
+class SubArray:
+
+    def __init__(self, arr):
+        # we need a list not a string, so do something to change the type
+        self.array = arr.split(',')
+        print("the input array is:", self.array)
+
+    def solve_sub_array(self):
+        rear = [int(self.array[0])]*len(self.array)
+        sum_value = [int(self.array[0])]*len(self.array)
+        for i in range(1, len(self.array)):
+            sum_value[i] = max(int(self.array[i]) + sum_value[i-1], int(self.array[i]))
+            rear[i] = max(sum_value[i], rear[i-1])
+        return rear[len(self.array)-1]
+
+
+if __name__ == '__main__':
+    whole_array = input("please input some numbers:")
+    array = SubArray(whole_array)
+    re = array.solve_sub_array()
+    print("the results is:", re)
+