1. Intro to Programming Functional Programming
CIT 590
Intro to Programming
Functional Programming

2. What is a function? f(x) = 2x
Very crudely put function turns inputs into outputs
Can I pass a function as an argument to another function
YES!
The first time you see this, it looks crazy
Just start thinking of a function as a machine that turns something into something else

3. Is functional programming actually used?
YES YES YES
C# uses it like you wouldn’t believe. Even more so if you use LINQ
Scala, being taught in 591 uses it a lot!
It offers way more flexibility
Do not dismiss it the way I once did

4. Functional programming
Functions taking other functions as an argument are called higher order functions
We have already seen an example of this – sort
Check out example of complex number sorting

5. Lambda functions Lambda x : x + 2 Lambda x, y : x + y
think of lambda’s as ‘I am lazy and I do not want to write a function so let us do this instead’.

6. Map, filter and reduce Python provides this as
Map – transform everything in the iterable (things you can loop through)
Filter – filter those that return the value true
Reduce – a two argument function
ls1 = map(lambda x: x +2, a)
ls2 = filter(lambda x: x%2 == 0, a)
ls3 = reduce(lambda x, y : x+y, a )

7. Map filter reduce on strings
names = ['Kevin Lee', 'Arvind Bhusnurmath', 'Di Lu', 'Ce Wang']
n1 = filter(lambda x: len(x) > 8, names)
What is n1?
[‘Kevin Lee’, ‘Arvind Bhusnurmath’]
‘Arvind Bhusnurmath’
[‘Arvind Bhusnurmath’]
set([‘Kevin Lee’, ‘Arvind Bhusnurmath’])
(‘Kevin Lee’, ‘Arvind Bhusnurmath’)

8. Map filter reduce on strings
names = ['Kevin Lee', 'Arvind Bhusnurmath', 'Di Lu', 'Ce Wang']
n2 = reduce(lambda x,y : x + y[0], names)
What is n2?
[‘KADC’]
‘KADC’
‘Kevin Arvind Di Ce’
‘Kevin LeeADC’
[‘Kevin’, ‘A’, ‘D’, ‘C’]

9. Map filter reduce on strings
names = ['Kevin Lee', 'Arvind Bhusnurmath', 'Di Lu', 'Ce Wang']
n3 = map(lambda x : x.split()[-1] + x.split()[0], names)
What is n3?
[‘Lee Kevin’, ‘Bhusnurmath Arvind’, ‘Lu Di’, ‘Wang Ce’]
[‘Lee’, ‘Bhusnurmath’, ‘Lu’, ‘Wang’]
[‘Klee’, ‘Abhusnurmath’, ‘Dlu’, ‘Cwang’]
None
[‘LeeKevin’ ‘BhusnurmathArvind’, ‘LiDu’, ‘WangCe’]

10. List comprehensions [expr for var in list if expr]
Basically a cool way of combining the map and filter functions
[x*2 for x in a if x<2]
These, thankfully, do not work by side effect
Lst = [x*2 for x in a if x < 2]
d = {'fred' : 1, 'arv': 5, 'li': 7, 'aash': 4, 'bye': 5}
reduce(lambda x,y: (x+y)/2, [d[x]/2 for x in d.keys() if len(x)%2 == 0])

11. Sieve example
Functional programming lends itself to recursion really easily
Erasthothenes algorithm for getting rid of composite numbers in a list of increasing numbers beginning with the number 2
An ancient algorithm for finding prime numbers
From any list of increasing numbers remove the multiples of any number in the list
Easy for list of size 1
Can I do this recursively???

12. The 3 argument version of the reduce function
We have already seem reduce(function, list)
There is a 3 argument variant which is
Reduce(function, list, identity element/first element for the process
Sorting examples
Define insertion of an element into a sorted list
Now use a reduce operation

13. Quicksort
List comprehension = badass 
Quicksort.py

14. Common super useful reductions
Reduce(lambda x,y : x+y ,a)
Sigma/summation
Reduce(lambda x,y: x*y , a, 1)
product
Reduce(lambda x,y: x + 1, a, 0)
Num elements
Reduce(lambda x,y: [y] + x, a, [])
reverse
the usage of reductions when dealing with lists