diff --git a/Functional-programming/list_comp.py b/Functional-programming/list_comp.py
new file mode 100644
index 0000000..f293325
--- /dev/null
+++ b/Functional-programming/list_comp.py
@@ -0,0 +1,21 @@
+my_list = [char for char in 'hello']
+my_list2 = [num*2 for num in range(0,100)]
+
+my_list3 = [num for num in range(0,100) if num % 2 == 0]
+
+simple_dict = {
+    'a' : 1,
+    'b' : 2
+}
+
+my_dict = {key:value for key,value in simple_dict.items()}
+
+my_dict1 = {num: num*2 for num in [1,2,3]}
+# print(my_list)
+# print(my_list3)
+
+print(my_dict)
+print(my_dict1)
+
+# <param> for <param> in <iterable>
+# same for set comprehension
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diff --git a/Functional-programming/reduce.py b/Functional-programming/reduce.py
new file mode 100644
index 0000000..cacaec5
--- /dev/null
+++ b/Functional-programming/reduce.py
@@ -0,0 +1,19 @@
+from functools import reduce
+
+my_list = [1,2,3]
+
+def accumalator(acc, item):
+    print(acc, item)
+    return acc + item
+
+print(reduce(accumalator, my_list, 10))
+
+# What reduce does?
+
+# reduce take the function given and take item from the
+# iterable and pass to function given to it. The first
+# parameter is the value initialized as the 3rd argument
+# to the reduce function. It do the processing and returns
+# a value which is used as next initialiizing value for the
+# first argument of the function provided in the reduce function
+# and so on for all items in iterable.
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diff --git a/Functional-programming/wiki.txt b/Functional-programming/wiki.txt
index e69de29..6f47dd6 100644
--- a/Functional-programming/wiki.txt
+++ b/Functional-programming/wiki.txt
@@ -0,0 +1,104 @@
+-> Common function used in python:
+
+    map, filter, zip, and replace
+
+-> map:
+
+    Prototype:
+
+        map(<function>, <iterable>)
+
+        Whatever the first argument, i.e., function can do, map will do
+        the same logic for each item in the iterable and return the
+        iterable with same structure.
+
+
+    for ex:
+
+        my_list = [1,2,3]
+        def multiply_by2(item):
+            return item*2
+
+        print(list(map(multiply_by2, my_list)))
+        print(my_list)
+
+-> filter:
+
+    Prototype:
+
+        filter(<function>, <iterable>)
+
+        To filter some items from the iterable based on the condition
+        defined in the function which return some boolean value.
+
+    
+    for ex:
+
+        my_list = [1,2,3]
+        def only_odd(item):
+            return item % 2 == 0
+
+        print(list(filter(only_odd, my_list)))
+        print(my_list)
+
+
+-> zip:
+
+    Prototype:
+
+        zip(<iterable1> , <iterable2>)
+
+        combine each items from both iterable together.
+
+
+    for ex:
+
+        my_list = [1, 2, 3]
+        your_list = [10, 20, 30]
+
+        print(list(zip(my_list, your_list)))
+        print(my_list)    
+
+    Output:
+
+        [(1,10), (2,20), (3,30)]
+
+-> reduce:
+
+    to use reduce add the below line:
+
+        from functools import reduce
+
+
+    # What reduce does?
+
+    # reduce take the function given and take item from the
+    # iterable and pass to function given to it. The first
+    # parameter is the value initialized as the 3rd argument
+    # to the reduce function. It do the processing and returns
+    # a value which is used as next initialiizing value for the
+    # first argument of the function provided in the reduce function
+    # and so on for all items in iterable.
+
+-> lambda expressions:
+
+    one time anonymous function.
+
+    Prototype:
+
+        lambda item: <action on param>
+
+
+    for ex:
+
+        my_list = [1,2,3]
+
+        print(list(map(lambda item: item*2, my_list)))
+
+-> list comprehension:
+
+    for ex:
+
+        my_list = [char for char in 'hello']
+
+        print(my_list)
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