#!/usr/bin/env python
# coding: utf-8

# # List Comprehensions & Higher order functions
# - list is a very powerful and commonly used container
# - list shortcuts can make you an efficient programmer
# - Ref: http://www.secnetix.de/olli/Python/list_comprehensions.hawk
# - E.g., in maths: S = {x<sup>2</sup> : x in {0 ... 9}} 

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# Typical way to create a list of squared values of list 0 to 9?
sq = []
for i in range(10):
    sq.append(i**2)


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print(sq)


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# List comprehension -- handy technique:
S = [x**2 for x in range(10)]


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S


# In maths: V = (1, 2, 4, 8, ... 2 <sup>12</sup>)

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# In python ?:
V = [2**x for x in range(13)]
print(V)


# In maths: M = {x | x in S and x even}

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# In python:
M = [x for x in S if x%2==0]


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M


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#sentence = "The quick brown fox jumps over the lazy dog"
#words = sentence.split()
# can make a list of tuples or list of lists
wlist = [(w.upper(), w.lower(), len(w)) for w in "The quick brown fox jumps over the lazy dog".split()]


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wlist


# # Lambda Functions
# - anonymous functions (no name)
# - typically used in conjunction with higher order functions such as: map(), reduce(), filter()
# - Reference: http://www.secnetix.de/olli/Python/lambda_functions.hawk

# ## Difference between lambda and normal function

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def func(x): return x**2


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print(func(4))


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g = lambda x: x**2 # no name, no parenthesis, and no return keyword


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print(g(4))


# ### lambda function properties and usage
# - single line simple functions
# - no explicit return keyword is used
# - always contains an expression that is implictly returned
# - can use a lambda definition anywere a function is expected without assigning to a variable
# - syntax: ** lambda argument(s): expression **

# ### higher order functions and lambda application
# - map, reduce, filter, sorted built-in functions

# ### sorted()

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list1 = ['Apple', 'apple', 'ball', 'Ball', 'cat']
list2 = sorted(list1, key=lambda x: x.lower())


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print(list2) 


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list3 = [('cat', 10), ('ball', 20), ('apple', 3)] 
from operator import itemgetter
list5 = sorted(list3, key=itemgetter(1), reverse=True)


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print(list5)


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list6 = sorted(list3, key=lambda x: x[1], reverse=True)


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print(list6)


# ### filter()
# - filter elemets in the list by returning a new list for each element the function returns True

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help(filter)


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list7 = [2, 18, 9, 22, 17, 24, 8, 12, 27]
list8 = list(filter(lambda x: x%3==0, list7))


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print(list8)


# ### map()

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help(map)


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items = list(range(1, 11))
squared = list(map(lambda x: x**2, items))


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print(squared)


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# map each words with its length
words = "The quick fox jumps over the lazy dog".split()
words = [word.lower() for word in words]


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print(words)


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w_len = list(map(lambda w: (w, w.upper(), len(w)), words))


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print(w_len)


# ### reduce()
# - reduce() is found in functools module
# - used to reduce a list of values to a single output

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import functools
help(functools)


# ### find sum of first n values

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s = functools.reduce(lambda x,y:x+y, range(1, 11))


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assert sum(range(1, 11)) == s


# ### find factorial (or product of) first n values

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fact = functools.reduce(lambda x,y:x*y, range(1, 11))


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fact


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import math
assert math.factorial(10) == fact


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