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Summary

Basics

Basics

Data Types

In Python we have the following data types:
- int
- float
- bool
- str
- list
- tuple
- set
- dict
- complex (imaginary numbers)

Binary Representation

  bin(5)

Gives us the binary representation of 5, that is 0b101 -> 0b represents in python the this is a binary number the actual binary is number is 101
to convert a binary number into an integer we can use the int() with the base of 2

  int('0b101', 2)

Strings

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Print Multiple Lines

Use ''' to print multiple lines

  multiple_lines = '''
  print
  multiple
  lines
  '''
  print(multiple_lines)

Escape Sequence

To escape a special character we use \ before the character
```
  weather = "It\'s \"kind of\" sunny"
  print(weather)
```
- \t - Tab
- \n - New Line
- \\ - Backslash
- \r - Carriage Return
- \b - Backspace
- \f - Form Feed
- \ooo - Octal value
- \xhh - Hex value

String Interpolation

Using Python 3 format

  name = 'Roger'
  age = 33

  print(f'Hi {name}. You are {age} years old')

Using Python 2 format
- ATTENTION the .format() is right after the string. The .format() will evaluate the string
```
  name = 'Roger'
  age = 33

  print('Hi {0}. You are {1} years old'.format(name, age))
```

Using custom variables

Using custom variables we have to call them between {}

  print('Hi {new_name}. You are {new_age} years old'.format(new_name="Yumi", new_age=3))

String Indexes

To work with string we have [start:stop:stepover]

the start starts at index 0
stepover, by default the step over is 1 but we can choose any number of our choice

  numbers = '0123456'

  print(numbers[1:])
  # 123456
  print(numbers[:3])
  # 012
  print(numbers[::1])
  # 0123456
  print(numbers[-1])
  # 6
  print(numbers[::-1])
  # 6543210

Immutability

String are immutable, this means that once we assign a value to a string we cannot change the content (different from JavaScript), the only way to change the string content is to re-assign a complete new value to the variable

Built-in Functions

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		Built-in Functions
abs()	delattr()	hash()	memoryview()	set()
all()	dict()	help()	min()	setattr()
any()	dir()	hex()	next()	slice()
ascii()	divmod()	id()	object()	sorted()
bin()	enumerate()	input()	oct()	staticmethod()
bool()	eval()	int()	open()	str()
breakpoint()	exec()	isinstance()	ord()	sum()
bytearray()	filter()	issubclass()	pow()	super()
bytes()	float()	iter()	print()	tuple()
callable()	format()	len()	property()	type()
chr()	frozenset()	list()	range()	vars()
classmethod()	getattr()	locals()	repr()	zip()
compile()	globals()	map()	reversed()	import()
complex()	hasattr()	max()	round()

Lists

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Lists are like Arrays in other languages, it's an ordered list

List Slicing

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With list slicing we create a new list

One way to create a new list with all the values from the previous list is by adding [:]

  amazon_cart = [
    'notebook',
    'sunglass',
    'toys',
    'grapes'
  ]

  new_list = amazon_cart[:]
  print(new_list)
  # ['notebook', 'sunglass', 'toys', 'grapes']

  # another option is to use .copy();
  new_list2 = amazon_cart.copy();
  print(new_list2)
  # ['notebook', 'sunglass', 'toys', 'grapes']

List Methods

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the .append() method changes the list in place, it doesn't return a new new copy of the list modified.

  basket = [1, 2, 3, 4, 5]

  new_list = basket.append(100)
  print(basket)
  print(new_list)
  # [1, 2, 3, 4, 5, 100]
  # None

the .insert() method inserts a new item base on the index.
- Just like .append(), .insert() modifies the list in place (it doesn't return anything)
```
  basket = [1, 2, 3, 4, 5]

  basket.insert(3, 100)
  print(basket)
  # [1, 2, 3, 100, 4, 5]
```
the .extend() method extends the list, in other words, it concatenates two objects (lists)
- .extend() modifies the list in place
```
  basket = [1, 2, 3, 4, 5]

  basket.extend([100, 101])
  print(basket)
  # [1, 2, 3, 4, 5, 100, 101]
```

the .pop() method removes the index from the list and return the removed item

  basket = [1, 2, 3, 4, 5]

  removed_item = basket.pop(3)
  print(removed_item)
  # 4

the .remove() method removes the value of the list, but doesn't return anything

  basket = [1, 2, 3, 4, 5]

  basket.remove(3)
  print(basket)
  # [1, 2, 4, 5]

the .clear() method removes everything in place from the list.

  basket = [1, 2, 3, 4, 5]

  basket.clear()
  print(basket)
  # []

the .index() method, return the index of the item that we are search on the list
```
  basket = [1, 2, 3, 4, 5]

  print(basket.index(2))
  # 1
```
- We can also give a start and stop point to search for the item
- .index(value, start, stop)

the 'value' in object/list, we can check True/False if the item exists in the list

  basket = ['a', 'b', 'c', 'd', 'e']

  print('a' in basket)
  # True
  print('f' in basket)
  # False

the .count() method counts how many time the item occurs

  basket = ['a', 'b', 'c', 'd', 'e' , 'd']

  print(basket.count('d'))
  # 2

the .sort() method sorts the list in place

  basket = ['a', 'b', 'c', 'd', 'e' , 'd']

  basket.sort()
  print(basket)
  # ['a', 'b', 'c', 'd', 'd', 'e']

the sorted() function do the same thing as .sort() but it creates a new sorted array

  basket = ['a', 'b', 'c', 'd', 'e' , 'd']

  print(sorted(basket))
  print(basket)
  # ['a', 'b', 'c', 'd', 'd', 'e']
  # ['a', 'b', 'c', 'd', 'e', 'd']

the .reverse() method reverts the list in place

  basket = ['a', 'b', 'c', 'd', 'e' , 'd']

  basket.reverse()
  print(basket)
  # ['d', 'e', 'd', 'c', 'b', 'a']

create a list using range()

  new_list = list(range(1, 100));
  print(new_list)

the .join() method iterates through the list and add join with the left part (sentence in this case)

  sentence = ' '
  new_sentence = sentence.join(['hi', 'my', 'name', 'is', 'roger'])

  print(new_sentence)
  # hi my name is roger

  # alternative
  new_sentence = ' '.join(['hi', 'my', 'name', 'is', 'roger'])

  print(new_sentence)
  # hi my name is roger

List Unpacking

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We can assign variables to each item of the list

  a, b, c, *other, last_item = [1, 2, 3, 4, 5, 6, 7, 8, 9]

  print(a)
  print(b)
  print(c)
  print(other)
  print(last_item)
  # 1
  # 2
  # 3
  # [4, 5, 6, 7, 8]
  # 9

Dictionary

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Dictionary is equal to an object in JavaScript, it's un-ordered key/value pairs

  dictionary = {
    'a': 1,
    'b': 2
  }

  print(dictionary['a'])
  # 1

the .get() method accepts the first argument is the key that we are looking for, if not found we can assign a default value (second argument).

  user = {
      'basket': [1, 2, 3],
      'greet': 'hello',
  }

  print(user.get('age',55))
  # 55

  user2 = {
      'basket': [1, 2, 3],
      'greet': 'hello',
      'age' : 20
  }

  print(user.get('age',55))
  # 20

<value> in dict.key(), loops through the dictionary and checks if the key exists

  user = {
      'basket': [1, 2, 3],
      'greet': 'hello',
      'age': 20
  }

  print('hello' in user.keys())
  # false
  print('greet' in user.keys())
  # true

<value> in dict.value(), loops through the dictionary and checks if the value exists

  user = {
      'basket': [1, 2, 3],
      'greet': 'hello',
      'age': 20
  }

  print('hello' in user.values())
  # true

dict.items(), returns an array of tuples where the fist position ([0]) is the key and the second position ([1]) is the value (the value could be anything, number, string, object...)

  user = {
      'basket': [1, 2, 3],
      'greet': 'hello',
      'age': 20
  }

  print(user.items())
  # dict_items([('basket', [1, 2, 3]), ('greet', 'hello'), ('age', 20)])

.clear(), clear the object in place, it removes all the items of the object. In the end we have and empty object
.copy() creates a brand new copy of the object (not referencing the pointer, it creates a new object)
.pop() removes the target item and returns the removed item.

.update() updates an existing item or adds if not exist

  user = {
      'basket': [1, 2, 3],
      'greet': 'hello',
      'age': 20
  }

  user.update({'age': 55})
  print(user)

  user.update({'ages': 100})
  print(user)
  # {'basket': [1, 2, 3], 'greet': 'hello', 'age': 55}
  # {'basket': [1, 2, 3], 'greet': 'hello', 'age': 55, 'ages': 100}

Tuples

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it's just like a list but we cannot change the content

  days_of_the_week = ('monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday', 'sunday')
  shopping_cart = ['cucumbers', 'potatoes', 'celery', 'oranges', 'avocado', 'grapes', 'banana']

  days_of_the_week[0] = 'not monday'
  print(days_of_the_week)
  # TypeError: 'tuple' object does not support item assignment

  shopping_cart[2] = 'cheese'
  print(shopping_cart)
  # ['cucumbers', 'potatoes', 'cheese', 'oranges', 'avocado', 'grapes', 'banana']

working we tuples, we only have 2 methods available
- .count() returns how many times the item appeared
- .index() returns the index of the item (the first found index)

Sets

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Removes all the duplicates from an "object"

  unique_set = {1, 3, 5, 4, 3, 2, 6}
  print(unique_set)
  # {1, 2, 3, 4, 5, 6}

.difference() returns the difference (who is calling)

  my_set = {1, 2, 3, 4, 5}
  your_set = {4, 5, 6, 7, 8, 9, 10}

  print(my_set.difference(your_set))
  # {1, 2, 3}

.discard() removes an item from the set

  my_set = {1, 2, 3, 4, 5}

  my_set.discard(5)
  print(my_set)
  # {1, 2, 3, 4}

.difference_update() returns the difference (who is calling) and modifies the original set

  my_set = {1, 2, 3, 4, 5}
  your_set = {4, 5, 6, 7, 8, 9, 10}

  my_set.difference_update(your_set)
  print(my_set)
  # {1, 2, 3}

.intersection() or & returns the intersection between two sets

  my_set = {1, 2, 3, 4, 5}
  your_set = {4, 5, 6, 7, 8, 9, 10}

  # alternative 1
  my_set.intersection(your_set)
  print(my_set)
  # {4, 5}

  # alternative 2
  print(my_set & your_set)
  # {4, 5}

.isdisjoint() returns true/false where true means that the two sets don't have items in common

  my_set2 = {1, 2, 3, 4, 5}
  your_set2 = {6, 7, 8, 9, 10}

  print(my_set2.isdisjoint(your_set2))
  # True

.union() or | concatenate two sets and remove duplicates

  my_set = {1, 2, 3, 4, 5}
  your_set = {4, 5, 6, 7, 8, 9, 10}

  print(my_set.union(your_set))
  # {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}

.issubset() checks if the left part (who is calling) is a subset of the other set, returns true/false

  my_set3 = {4, 5}
  your_set3 = {4, 5, 6, 7, 8, 9, 10}

  print(my_set3.issubset(your_set3))
  # True

.issuperset() checks if the left part (who is calling) is a superset of the other set, returns true/false

  my_set3 = {4, 5}
  your_set3 = {4, 5, 6, 7, 8, 9, 10}

  print(your_set3.issuperset(my_set3))
  # True

Ternary Operator

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Ternary Operator - Official Docs
Ternary operators are more commonly known as conditional expressions in Python. These operators evaluate something based on a condition being true or not. They became a part of Python in version 2.4
```
  value_if_true if condition else value_if_false
```
```
  is_nice = True

  state = "nice" if is_nice else "not nice"
  print(state)
  # nice
```

== vs is

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== checks for equality value

is checks for memory location

  print(True == True)
  print('1' == '1')
  print([] == [])
  print(10 == 10)
  print([1,2,3] == [1,2,3])
  # True
  # True
  # True
  # True
  # True

  print()
  print(True is True)
  print('1' is '1')
  print([] is [])
  print(10 is 10)
  print([1,2,3] is [1,2,3])
  # True
  # True
  # False
  # True
  # False

Iterables

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We can iterate through a list/dictionary/tuples/sets/string and use a shorthand to get the key/value

  user = {
    'name': 'Roger',
    'age': 33,
    'can_swim': False
  }

  for key, value in user.items():
    print(key, value)
  print()
  for value in user.values():
    print(value)
  print()
  for key in user.keys():
    print(key)

Range

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We can use range() that creates a special kind of object that we can iterate
range(start, stop, step)
- by default the step is not specified is 1
```
  for number in range(0,100):
    print(number)
```

Enumerate

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Using enumerate, it gives us accesses to the index for the list/dictionary/tuples/sets/string

  for index, value in enumerate('Helllloooooo'):
    print(index, value)

While/Else

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We can use else condition with while. The else part will be only executed if the while loop executed successfully

  i = 0
  while i < 10:
    print (i)
    i += 1;
    break
  else:
    print('This msg will never be printed')

  # 0

  j = 0
  while j < 10:
    print (j)
    j += 1;
  else:
    print('This msg will be printed after 9')
  # 0
  # 1
  # 2
  # 3
  # 4
  # 5
  # 6
  # 7
  # 8
  # 9
  # This msg will be printed after 9

Functions

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Function expressions do not exist in Python

Every function in Python is defined using the def keyword and are never assigned to variables as in JavaScript.

  msg = 'Welcome home'
  def say_greetings(name, emoji):
    print(f'{msg}, {name} {emoji}')

  say_greetings('Roger', '👍🏻')

Keyword Arguments vs Positional Arguments

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With keywords we don't need to pass the parameters in order as it appears

  msg = 'Welcome home'
  def say_greetings(name, emoji):
    print(f'{msg}, {name} {emoji}')

  say_greetings(emoji = '👍🏻', name = 'Roger')

Default Parameters

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We can assign default parameters if none is given

  msg = 'Welcome home'
  def say_greetings(name = 'Guest', emoji = '😎'):
    print(f'{msg}, {name} {emoji}')

  say_greetings()

Docstrings

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Docstrings is a way to add extra info / definitions to our function

  def extra_info_function(a):
    '''
    Info: this function prints param a
    '''
    print(a)

  extra_info_function('!!!!')

an alternative, we can use help() to know more about the function, we just need to point to the function, ot execute the function (())
```
  help(extra_info_function)
```
we could also use Dunder or Magic Methods
- Dunder or magic methods in Python are the methods having two prefix and suffix underscores in the method name. Dunder here means “Double Under (Underscores)”. These are commonly used for operator overloading. Few examples for magic methods are: init, add, len, repr etc.
- Python lets our classes inherit from built-in classes. An inheriting child class of a built-in shares all the same attributes, including methods as the built-in. We can take advantage of core built-in functionality, but customize selected operations through the use of magic methods.
```
  print(extra_info_function.__doc__)
```

args kwargs

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Rule: params, *args, default parameters, **kwargs

  def super_func(*args, **kwargs):
    total = 0
    for items in kwargs.values():
      total += items
    return sum(args) + total

  print(super_func(1,2,3,4,5, num1 = 5, num2 = 10))
  # 30

Anonymous Function

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More about Anonymous Function
Python has a different sort of anonymous functions
Python does have a the concept of anonymous functions but they are called lambda functions.

Think of lambda functions as a JavaScript arrow function that implicitly returns a single expression's result.

```Python
  nums = [1, 3, 2, 6, 5]
  odds = list( filter(lambda num: num % 2, nums) )

  print(odds)
  #[1, 3, 5]
```

```Python
  double = lambda x: x * 2

  print(double(5))
  # 10
```

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README.md

Summary

Basics

Data Types

Binary Representation

Strings

Print Multiple Lines

Escape Sequence

String Interpolation

String Indexes

Immutability

Built-in Functions

Lists

List Slicing

List Methods

List Unpacking

Dictionary

Tuples

Sets

Ternary Operator

== vs is

Iterables

Range

Enumerate

While/Else

Functions

Keyword Arguments vs Positional Arguments

Default Parameters

Docstrings

args kwargs

Anonymous Function

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parent directory

README.md

Summary

Basics

Data Types

Binary Representation

Strings

Print Multiple Lines

Escape Sequence

String Interpolation

String Indexes

Immutability

Built-in Functions

Lists

List Slicing

List Methods

List Unpacking

Dictionary

Tuples

Sets

Ternary Operator

== vs is

Iterables

Range

Enumerate

While/Else

Functions

Keyword Arguments vs Positional Arguments

Default Parameters

Docstrings

*args *kwargs

Anonymous Function

args kwargs