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python_sandbox_finished/classes.py

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# A class is like a blueprint for creating objects. An object has properties and methods(functions) associated with it. Almost everything in Python is an object
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# Create class
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class User:
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# Constructor
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def __init__(self, name, email, age):
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self.name = name
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self.email = email
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self.age = age
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def greeting(self):
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return f'My name is {self.name} and I am {self.age}'
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def has_birthday(self):
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self.age += 1
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# Extend class
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class Customer(User):
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# Constructor
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def __init__(self, name, email, age):
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self.name = name
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self.email = email
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self.age = age
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self.balance = 0
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def set_balance(self, balance):
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self.balance = balance
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def greeting(self):
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return f'My name is {self.name} and I am {self.age} and my balance is {self.balance}'
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# Init user object
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brad = User('Brad Traversy', 'brad@gmail.com', 37)
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# Init customer object
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janet = Customer('Janet Johnson', 'janet@yahoo.com', 25)
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janet.set_balance(500)
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print(janet.greeting())
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brad.has_birthday()
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print(brad.greeting())
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# If/ Else conditions are used to decide to do something based on something being true or false
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x = 21
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y = 20
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# Comparison Operators (==, !=, >, <, >=, <=) - Used to compare values
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# Simple if
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if x > y:
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print(f'{x} is greater than {y}')
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# If/else
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if x > y:
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print(f'{x} is greater than {y}')
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else:
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print(f'{y} is greater than {x}')
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# elif
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if x > y:
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print(f'{x} is greater than {y}')
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elif x == y:
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print(f'{x} is equal to {y}')
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else:
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print(f'{y} is greater than {x}')
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# Nested if
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if x > 2:
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if x <= 10:
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print(f'{x} is greater than 2 and less than or equal to 10')
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# Logical operators (and, or, not) - Used to combine conditional statements
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# and
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if x > 2 and x <= 10:
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print(f'{x} is greater than 2 and less than or equal to 10')
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# or
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if x > 2 or x <= 10:
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print(f'{x} is greater than 2 or less than or equal to 10')
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# not
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if not(x == y):
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print(f'{x} is not equal to {y}')
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# Membership Operators (not, not in) - Membership operators are used to test if a sequence is presented in an object
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numbers = [1,2,3,4,5]
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# in
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if x in numbers:
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print(x in numbers)
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# not in
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if x not in numbers:
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print(x not in numbers)
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# Identity Operators (is, is not) - Compare the objects, not if they are equal, but if they are actually the same object, with the same memory location:
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# is
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if x is y:
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print(x is y)
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# is not
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if x is not y:
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print(x is not y)
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# A Dictionary is a collection which is unordered, changeable and indexed. No duplicate members.
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# Create dict
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person = {
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'first_name': 'John',
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'last_name': 'Doe',
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'age': 30
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}
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# Use constructor
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# person2 = dict(first_name='Sara', last_name='Williams')
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# Get value
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print(person['first_name'])
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print(person.get('last_name'))
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# Add key/value
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person['phone'] = '555-555-5555'
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# Get dict keys
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print(person.keys())
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# Get dict items
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print(person.items())
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# Copy dict
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person2 = person.copy()
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person2['city'] = 'Boston'
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# Remove item
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del(person['age'])
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person.pop('phone')
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# Clear
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person.clear()
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# Get length
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print(len(person2))
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# List of dict
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people = [
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{'name': 'Martha', 'age': 30},
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{'name': 'Kevin', 'age': 25}
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]
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print(people[1]['name'])

python_sandbox_finished/files.py

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# Python has functions for creating, reading, updating, and deleting files.
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# Open a file
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myFile = open('myfile.txt', 'w')
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# Get some info
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print('Name: ', myFile.name)
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print('Is Closed : ', myFile.closed)
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print('Opening Mode: ', myFile.mode)
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# Write to file
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myFile.write('I love Python')
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myFile.write(' and JavaScript')
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myFile.close()
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# Append to file
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myFile = open('myfile.txt', 'a')
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myFile.write(' I also like PHP')
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myFile.close()
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# Read from file
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myFile = open('myfile.txt', 'r+')
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text = myFile.read(100)
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print(text)

python_sandbox_finished/functions.py

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# A function is a block of code which only runs when it is called. In Python, we do not use curly brackets, we use indentation with tabs or spaces
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# Create function
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def sayHello(name='Sam'):
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print(f'Hello {name}')
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# Return values
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def getSum(num1, num2):
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total = num1 + num2
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return total
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# A lambda function is a small anonymous function.
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# A lambda function can take any number of arguments, but can only have one expression. Very similar to JS arrow functions
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getSum = lambda num1, num2: num1 + num2
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print(getSum(10, 3))

python_sandbox_finished/lists.py

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# A List is a collection which is ordered and changeable. Allows duplicate members.
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# Create list
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numbers = [1, 2, 3, 4, 5]
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fruits = ['Apples', 'Oranges', 'Grapes', 'Pears']
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# Use a constructor
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# numbers2 = list((1, 2, 3, 4, 5))
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# Get a value
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print(fruits[1])
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# Get length
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print(len(fruits))
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# Append to list
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fruits.append('Mangos')
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# Remove from list
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fruits.remove('Grapes')
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# Insert into position
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fruits.insert(2, 'Strawberries')
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# Change value
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fruits[0] = 'Blueberries'
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# Remove with pop
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fruits.pop(2)
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# Reverse list
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fruits.reverse()
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# Sort list
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fruits.sort()
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# Reverse sort
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fruits.sort(reverse=True)
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print(fruits)

python_sandbox_finished/loops.py

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# A for loop is used for iterating over a sequence (that is either a list, a tuple, a dictionary, a set, or a string).
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people = ['John', 'Paul', 'Sara', 'Susan']
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# Simple for loop
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for person in people:
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print(f'Current Person: {person}')
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# Break
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for person in people:
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if person == 'Sara':
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break
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print(f'Current Person: {person}')
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# Continue
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for person in people:
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if person == 'Sara':
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continue
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print(f'Current Person: {person}')
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# range
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for i in range(len(people)):
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print(people[i])
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for i in range(0, 11):
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print(f'Number: {i}')
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# While loops execute a set of statements as long as a condition is true.
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count = 0
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while count < 10:
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print(f'Count: {count}')
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count += 1

python_sandbox_finished/modules.py

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# A module is basically a file containing a set of functions to include in your application. There are core python modules, modules you can install using the pip package manager (including Django) as well as custom modules
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# Core modules
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import datetime
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from datetime import date
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import time
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from time import time
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# Pip module
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from camelcase import CamelCase
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# Import custom module
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import validator
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from validator import validate_email
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# today = datetime.date.today()
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today = date.today()
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timestamp = time()
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c = CamelCase()
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# print(c.hump('hello there world'))
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email = 'test#test.com'
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if validate_email(email):
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print('Email is valid')
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else:
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print('Email is bad')

python_sandbox_finished/myfile.txt

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I love Python and JavaScript I also like PHP

python_sandbox_finished/py_json.py

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# JSON is commonly used with data APIS. Here how we can parse JSON into a Python dictionary
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import json
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# Sample JSON
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userJSON = '{"first_name": "John", "last_name": "Doe", "age": 30}'
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# Parse to dict
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user = json.loads(userJSON)
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# print(user)
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# print(user['first_name'])
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car = {'make': 'Ford', 'model': 'Mustang', 'year': 1970}
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carJSON = json.dumps(car)
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print(carJSON)

python_sandbox_finished/strings.py

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# Strings in python are surrounded by either single or double quotation marks. Let's look at string formatting and some string methods
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name = 'Brad'
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age = 37
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# Concatenate
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print('Hello, my name is ' + name + ' and I am ' + str(age))
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# String Formatting
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# Arguments by position
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print('My name is {name} and I am {age}'.format(name=name, age=age))
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# F-Strings (3.6+)
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print(f'Hello, my name is {name} and I am {age}')
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# String Methods
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s = 'helloworld'
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# Capitalize string
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print(s.capitalize())
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# Make all uppercase
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print(s.upper())
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# Make all lower
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print(s.lower())
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# Swap case
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print(s.swapcase())
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# Get length
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print(len(s))
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# Replace
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print(s.replace('world', 'everyone'))
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# Count
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sub = 'h'
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print(s.count(sub))
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# Starts with
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print(s.startswith('hello'))
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# Ends with
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print(s.endswith('d'))
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# Split into a list
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print(s.split())
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# Find position
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print(s.find('r'))
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# Is all alphanumeric
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print(s.isalnum())
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# Is all alphabetic
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print(s.isalpha())
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# Is all numeric
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print(s.isnumeric())

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