diff --git a/AbstractHeap.py b/AbstractHeap.py
new file mode 100644
index 0000000..ebf0301
--- /dev/null
+++ b/AbstractHeap.py
@@ -0,0 +1,80 @@
+from abc import ABCMeta, abstractmethod
+
+class AbstractHeap(metaclass=ABCMeta):
+    """Abstract Class for Binary Heap."""
+    def __init__(self):
+        pass
+    @abstractmethod
+    def perc_up(self, i):
+        pass
+    @abstractmethod
+    def insert(self, val):
+        pass
+    @abstractmethod
+    def perc_down(self,i):
+        pass
+    @abstractmethod
+    def min_child(self,i):
+        pass
+    @abstractmethod
+    def remove_min(self,i):
+        pass
+class BinaryHeap(AbstractHeap):
+    def __init__(self):
+        self.currentSize = 0
+        self.heap = [(0)]
+
+    def perc_up(self, i):
+        while i // 2 > 0:
+            if self.heap[i] < self.heap[i // 2]:
+                # Swap value of child with value of its parent
+                self.heap[i], self.heap[i//2] = self.heap[i//2], self.heap[i]
+            i = i // 2
+
+    """
+        Method insert always start by inserting the element at the bottom.
+        it inserts rightmost spot so as to maintain the complete tree property
+        Then, it fix the tree by swapping the new element with its parent,
+        until it finds an appropriate spot for the element. It essentially
+        perc_up the minimum element
+        Complexity: O(logN)
+    """
+    def insert(self, val):
+        self.heap.append(val)
+        self.currentSize = self.currentSize + 1
+        self.perc_up(self.currentSize)
+
+    """
+        Method min_child returns index of smaller 2 childs of its parent
+    """
+    def min_child(self, i):
+        if 2 * i + 1 > self.currentSize:  # No right child
+            return 2 * i
+        else:
+            # left child > right child
+            if self.heap[2 * i] > self.heap[2 * i +1]:
+                return 2 * i + 1
+            else:
+                return 2 * i
+
+    def perc_down(self, i):
+        while 2 * i < self.currentSize:
+            min_child = self.min_child(i)
+            if self.heap[min_child] < self.heap[i]:
+                # Swap min child with parent
+                self.heap[min_child], self.heap[i] = self.heap[i], self.heap[min_child]
+            i = min_child
+    """
+        Remove Min method removes the minimum element and swap it with the last
+        element in the heap( the bottommost, rightmost element). Then, it
+        perc_down this element, swapping it with one of its children until the
+        min heap property is restored
+        Complexity: O(logN)
+    """
+    def remove_min(self):
+        ret = self.heap[1]      # the smallest value at beginning
+        self.heap[1] = self.heap[self.currentSize] # Repalce it by the last value
+        self.currentSize = self.currentSize - 1
+        self.heap.pop()
+        self.perc_down(1)
+        return ret