# Chapter 7 Pythonic

# Python -> required way to code "syntax"
# Pythonic -> readability, framework, resource allocation

# Variable Declaration -> readability, resource allocation
print("==== Variable Declaration Example ====")
# Python syntax
a = 7  # EOL python interpreter
b = 3
c = 4
z = a + b + c
print(z)  # 14
# Pythonic
a1, b1, c1 = 7, 3, 4
z1 = a1 + b1 + c1
print(z1)

# String Interpolation -> framework
print("==== String Interpolation Example ====")
# join operator vs template variables
# join operator is data type dependent "all types have to be friends"
# Don't talk to strangers only talk to friends
# https://en.wikipedia.org/wiki/Law_of_Demeter
# join operator framework works at the object level
# Python
firstName = "Bob"
lastName = "Smith"
fullName = firstName + " " + lastName   # string + string + string
print(fullName)

# Pythonic
# if we only need to get the value, use template variables
# template variables do not care about data type
# template variables framework works at the value level
name, age = "Bob Smith", 21  # string, int
contactInfo = name + " " + str(age) # Python object level str()
contactInfo1 = f"{name} {age}"  # Pythonic value level
print(contactInfo)
print(contactInfo1)

# List Comprehension -> framework, resource allocation
print("==== List Comprehension Example ====")
# dataset for our example
data = ['Bob','Beth','Joe','Mary'] # List
# Python syntax using range() function
# len() and range() are called manually after the in keyword
# the index id and the data value need to be called as 2 seperate variables
for x in range(0, len(data)):
    # x as a local variable is the index id, NOT the value
    print(f"Index Id: {x} Value: {data[x]}")   # x = 0 data[0]='Bob'
print("=======")
# Pythonic
# the in ys is handling all the len() and range() for us
for x in data:
    print(x) # x is the value that we are looping thru

# EAFP vs LBYL Principles
print("==== EAFP vs LBYL Principles Example ====")
# control variable
y = 'Bob'
# Python LBYL -> Look Before You Leap
# if else statements
print("=== if statement ===")
if y == 'Bob': # Fail at the if, IF the data type is assumed correct
    # return True
    print("Bob is the value tested")
else:
    # return false
    print("The value tested is not equal to the control")

# Pythonic EAFP -> Easier to Ask for Forgiveness than Permission
# try except handlers "finally" optional BUT highly recommended
try:
    if y == 'Bob':
    # return True
        print("Bob is the value tested")
    else:
    # return false
        print("The value tested is not equal to the control")
except ValueError:
    print("Something about the value error")

except TypeError:
    print("Something about the type error.")

# if else test for data validation -> Python
# Regular Expressions -> Pythonic
# pattern matching -> match a defined string pattern
# regex101.com
# regexlib.com
# [a-zA-Z0-9]
# (555) 555-5555
# [(][1-9]\d{2}[)] \d{3}-\d{4}
# Ask the user to enter phone number
phone_number = input("Enter your phone number ex. (xxx) xxx-xxxx: ")

# re is a standard module
import re

# define the pattern to test
pattern_phone = r"[(][1-9]\d{2}[)] \d{3}-\d{4}"

# variable to hold the true or false
match = re.search(pattern_phone, phone_number) 

# return true or false
if match:
    print("Valid phone number.")
else:
    print("Invalid phone number")

# EOF