I Foundations for efficiencies.py

"""DEFINING EFFICIENT
---------------------
    - Fast runtime(- time)
    - Minimal resource consumption(- memory)
\\"""## example
  # Non pythonic
  doubled_numbers= []
  for i in range(len(numbers)):
     doubled_numbers.append(numbers[i]*2)
  # Pythonic
  doubled_numbers= [x * 2 for x in numbers]
#``````````````````````````````````````````````````````````````````````````````````````````````````
"""
##Pop quiz: what is efficient

In the context of this course, what is meant by efficient Python code?

    # Code that executes quickly for the task at hand, minimizes the memory footprint and follows Python's coding style principles."""
#``````````````````````````````````````````````````````````````````````````````````````````````````
## A taste of things to come 1== Non-pythonic

 names = ['Jerry', 'Kramer', 'Elaine', 'George', 'Newman']
    
# Print the list w/ Non-Pythonic approach
i = 0
new_list= []
while i < len(names):
    if len(names[i]) >= 6:
        new_list.append(names[i])
    i += 1
print(new_list)
#``````````````````````````````````````````````````````````````````````````````````````````````````
## A taste of things to come 2== more Pythonic way

# Print the list created by looping over the contents of names
better_list = []
for name in names:
    if len(name) >= 6:
        better_list.append(name)
print(better_list)
#``````````````````````````````````````````````````````````````````````````````````````````````````
## A taste of things to come 3== The Pythoniest way

# Print the list created by using list comprehension
best_list = [name for name in names if len(name) >= 6]
print(best_list)
#``````````````````````````````````````````````````````````````````````````````````````````````````
### What is the 7th idiom of the Zen of Python?

import this
#The Zen of Python, by Tim Peters
        # Readability counts.
"""*********************************************************************************************************************
Built-in types
===============
    >>>>>> list, >>>>>> tuple, >>>>>> set, >>>>>> dict
    
Built-in functions
=================    
    >>>>>> print(), >>>>>> len(), >>>>>> range(), >>>>>> enumerate(), >>>>>> round(), >>>>>> map(), >>>>>> zip()
    
    map() === (returnedValue, toWhat)--- in iterables
    
Built-in modules
================= 
    >>>>>> os, >>>>>> sys, >>>>>> itertools, >>>>>> collections, >>>>>> math   
******************************************************************************************************************"""
### Built-in practice: range()

# Create a range object that goes from 0 to 5
nums = range(0,6)
print(type(nums))

# Convert nums to a list
nums_list = list(nums)
print(nums_list)

# Create a new list of odd numbers from 1 to 11 by unpacking a range object
nums_list2 = [*range(1,12,2)] # start , end(exclusive), step
print(nums_list2)

#$$$ unpacking a range object(*) same as using-----nums_list = list(nums) $$$
# <class 'range'>
# [0, 1, 2, 3, 4]
# [1, 3, 5, 7, 9, 11]
#``````````````````````````````````````````````````````````````````````````````````````````````````
### Built-in practice: enumerate()

# Non-Pythonic
# Rewrite the for loop to use enumerate
indexed_names = []
for i,name in enumerate(names):
    index_name = (i,name)
    indexed_names.append(index_name) 
print(indexed_names)

# more Pythonic 
# Rewrite the above for loop using list comprehension
indexed_names_comp = [(i,name) for i,name in enumerate(names)]
print(indexed_names_comp)

# The Pythoniest
# Unpack an enumerate object with a starting index of one
indexed_names_unpack = [*enumerate(names, 1)] 
print(indexed_names_unpack)
"""read as: list, unpack & enumerate(names, startingWithOne)"""
#``````````````````````````````````````````````````````````````````````````````````````````````````
### Built-in practice: map()

# names = ['Jerry', 'Kramer', 'Elaine', 'George', 'Newman']

# Use map to apply str.upper to each element in names
names_map  = map(str.upper, names)

# Print the type of the names_map
print(type(names_map))

# Unpack names_map into a list
names_uppercase = [*names_map]

# Print the list created above
print(names_uppercase)
"""******************************************************************************************************************
NumPy arrays
=================
$$ Alternative to Python Lists

    - np is homogeneous.same type
    
                    import numpy as np
                    nums_np = ap.array(range(5))
            
    - np. array broadcasting (calculations for entire array)
            
                    nums_np = np.array([-2,-1,0,1,2])
                    nums_np ** 2
                    # array([4,2,0,1,4])
            
    - np 2D array best indexing
    
        -- basic python:
                    nums2= [[1,2,3],[4,5,6]]
                    nums2[0][1]
                    # 2

        -- np python is easier
                    nums2[0,1]
                    # 2

                    # get both list first item
                    nums2[:,0]
                    # array([1,4])
                    
     - np boolean indexing
                    
                    nums= [-2, -1, 0, 1, 2]
                    nums_np = np.array(nums)
                    # boolean indexing
                    nums_np > 0
                    
                    #. array([False,False,False,True,True])
                    
                    # indexing/returning this array <-
                    
                    nums_np[nums_np > 0]
                    #. [1,2]
******************************************************************************************************************"""
### Practice with NumPy arrays 1

# Print second row of nums
print(nums[1,:])
# [ 6  7  8  9 10]

# Print all elements of nums that are greater than six
print(nums[nums > 6])
# [ 7  8  9 10]

# Double every element of nums
nums_dbl = nums * 2
print(nums_dbl)
# [[ 2  4  6  8 10]
# [12 14 16 18 20]]
    
# Replace the third column of nums, adding 1 to each item in original column
nums[:,2] = nums[:,2] + 1
print(nums)
# [[ 1  2  4  4  5]
# [ 6  7  9  9 10]]
#``````````````````````````````````````````````````````````````````````````````````````````````````
"""Question

When compared to a list object, what are two advantages of using a numpy array?
        
        #  A numpy array contains homogeneous data types (which reduces memory consumption) 
            and provides the ability to apply operations on all elements through broadcasting."""
#``````````````````````````````````````````````````````````````````````````````````````````````````
### Bringing it all together: Festivus!

# Create a list of arrival times, let them know how many minutes late they are to your party.
arrival_times = [*range(10,60,10)]

print(arrival_times)
# [10, 20, 30, 40, 50]
#``````````````````````````````````````````````````````````````````````````````````````````````````
## Festivus 2

# Create a list of arrival times
arrival_times = [*range(10,60,10)]

# Convert arrival_times to an array and update the times. your clock is three minutes fast.
arrival_times_np = np.array(arrival_times)
new_times = arrival_times_np - 3

print(new_times)
# [ 7 17 27 37 47]
#``````````````````````````````````````````````````````````````````````````````````````````````````
## Festivus 3

# Create a list of arrival times
arrival_times = [*range(10,60,10)]

# Convert arrival_times to an array and update the times
arrival_times_np = np.array(arrival_times)
new_times = arrival_times_np - 3

# Use list comprehension and enumerate to pair guests to new times
guest_arrivals = [(names[name],time) for name,time in enumerate(new_times)] 
"""using enumerate(): cause we use every name as an index for arrival times"""

print(guest_arrivals)
# [('Jerry', 7), ('Kramer', 17), ('Elaine', 27), ('George', 37), ('Newman', 47)]
#``````````````````````````````````````````````````````````````````````````````````````````````````
## Festivus 4

# Create a list of arrival times
arrival_times = [*range(10,60,10)]

# Convert arrival_times to an array and update the times
arrival_times_np = np.array(arrival_times)
new_times = arrival_times_np - 3

# Use list comprehension and enumerate to pair guests to new times
guest_arrivals = [(names[i],time) for i,time in enumerate(new_times)]
"""[('Jerry', 7), ('Kramer', 17), ('Elaine', 27), ('George', 37), ('Newman', 47)]"""

# Map the welcome_guest function(preloaded),  to each (guest,time)pair -->guest_arrivals 
welcome_map = map(welcome_guest, guest_arrivals)

# unpack welcome_map in a list , asign it to gest_welcomes
# unpuck previus var, sep with new line. print
guest_welcomes = [*welcome_map]
print(*guest_welcomes, sep='\n')
""" Welcome to Festivus Jerry... You're 7 min late.
    Welcome to Festivus Kramer... You're 17 min late.
    Welcome to Festivus Elaine... You're 27 min late.
    Welcome to Festivus George... You're 37 min late.
    Welcome to Festivus Newman... You're 47 min late."""