Comprehension.md

Comprehension:

Comprehension helps programmers to create lists/generator object/dictionary in a concise way.

Syntax:

    [output iteration condition]

List Comprehensions:

Python supports completed lists called list comprehension.

Syntax:

  a_list = [expression for variable in sequence]
  '''
  where,
  the expression is evaluated once, for every item in the sequence.
  '''

List comprehension help programmers to create lists in a concise way. This is mainly beneficial to make new lists where each element is obtained applying some operations to each member of another sequence or iterable.

List comprehension is also used to create a subsequence of those elements that satisfy a certain condition.

  # Example:
  squares = [(i**2) for i in range(11)]
  print(squares)
  # Output: [0, 1, 4, 9, 16, 25, 36, 49, 64, 81, 100]

  # Example:
  names = ['nik', 'fury']
  print([len(name) for name in names])
  # output: [3, 4]

  # Example: First letter Capitalize
  print([name.capitalize() for name in names])
  # output: ['Nik', 'Fury']

  # Example: only those whose length>3
  print([name.capitalize() for name in names if len(name)>3])
  # output: ['Fury']

Ternary Operator: if condition else

Syntax example: num1 if num1>num2 else num2

  # Example: Ternary Operator
  names = ['nik', 'fury', 'james', 'lex', 'anna', 'king', 'blake']
  print([name.upper() if len(name)>4 else name for name in names]) 
  # output: ['nik', 'fury', 'JAMES', 'lex', 'anna', 'king', 'BLAKE']

  # Example: Create a new dictionary using dictionary comprehension with key and value square.
  print({i: i*i for i in range(1, 11)})
  # output: {1: 1, 2: 4, 3: 9, 4: 16, 5: 25, 6: 36, 7: 49, 8: 64, 9: 81, 10: 100}

  # Example: create a new set using set comprehension
  print({i*i for i in range(1, 11)})
  # output: {64, 1, 4, 36, 100, 9, 16, 49, 81, 25}