Python Built-In Types

Simple Values

Integers

• Integer values are numbers without decimal points.

  >>> x = 1
  >>> type(x)
  int

• Python integers are variable precision; computations do not overflow

Floating-Point Numbers

• Floating-point values can store fractional numbers

• Floating-point values can be defined in standard or exponential notation

  x = 0.000005
  y = 5e-6

• An integer can be converted to a float with the float constructor

  float(1)

Complex Numbers

• Complex numbers have real and imaginary parts (both floating point values).

• Complex numbers can be created with the complex constuctor:

  >>> complex(1, 2)
  (1+2j)

• Or alternatively with the “j” suffix

  >>> 1 + 2j
  (1+2j)

String Type

• Strings in Python can be created with single or double quotes

  message = "what do you like?"
  response = 'spam'

• Python strings have useful functions and methods

• Examples:

  >>> len(response)
  4
  >>> response.upper()
  'SPAM'
  >>> message[0] # zero-based indexing
  'w'

Boolean Type

• The Boolean type has two possible values: True and False.

• Values of any other type can be converted into boolean values with the bool constructor.

• Examples:

  >>> bool(123)
  True
  >>> bool(0)
  False
  >>> bool('')
  False

None Type

• The NoneType has only a single possible value: None

  >>> type(None)
  NoneType

• A Python function that does not return a value returns None

Built-In Data Structures

Lists

• Lists are the basic ordered and mutable data collection

• Lists can be defined comma-separated values between square brackets

  >>> L = [2, 3, 5, 7]

• Lists have many useful methods

• Examples:

  >>> len(L)
  4
  >>> L.append(11)
  [2, 3, 5, 7, 11]

List Indexing

• Elements of a list can be indexed for single values.

• Lists use zero based indexing

  >>> L = [2, 3, 5, 7, 11]
  >>> L[0]
  2

• Lists can be indexed from the end with negative integers

  >>> L[-1]
  11
  >>> L[-2]
  7

List Slicing

• Elements of a list can be sliced for multiple values.

• List slicing syntax uses a colon to indicate the (inclusive) start point and the (exclusive) end point.

  >>> L = [2, 3, 5, 7, 11]
  >>> L[0:3]
  [2, 3, 5]

• An optional third integer can be used to represent a step size

  >>> L[::2]
  [2, 5, 11]

Tuples

• Tuples are an immutable, ordered collection

• Immutable means that once a tuple is created it cannot be changed

• Tuple are defined with parentheses or using commas

  >>> t1 = (1, 2, 3)
  >>> t2 = 1, 2, 3

• Tuples can be indexed and sliced like lists

Dictionaries

• Dictionaries map keys to values

• Dictionaries are created by a comma separated list of key:value pairs between curly braces

  >>> numbers = {'one': 1, 'two': 2}

• Items are accessed using the key

  >>> numbers['two']
  2

Sets

• Sets are unordered collections of unique items

• Sets are defined by a comma separated list of values between curly braces

  >>> primes = {2, 3, 5, 7}
  >>> odds = {1, 3, 5, 7, 9}

• Sets support mathematical set operations

• Example:

  >>> primes | odds
  {1, 2, 3, 5, 7, 9}
  >>> primes.union(odds)
  {1, 2, 3, 5, 7, 9}