Introducing Python Object Types

---

The Python Conceptual Hierarchy

• Programs are composed of modules.
• Modules contain statements.
• Statements contain expressions.
• Expressions create and process objects.

Python Object

• Traditional programming often stress its three pillars of
  • sequence (“Do this, then that”)
  • selection (“Do this if that is true”)
  • repetition (“Do this many times”)

• Python has tools in all three categories, along with some for definition—of functions and classes.

• object : the more strongly unifying principle in Python
  • Everything we process in Python programs is a kind of object.

Python’s Core Data Types

• built-in objects (types) : the core of every Python program
  • The principal built-in types : numerics, sequences, mappings, classes, instances and exceptions
    • Numeric types : int, float, complex
    • Sequence types : list, tuple, range
    • Text sequence type : str
    • Binary sequence types : bytes, bytearray, memoryview
    • Set types : set, frozenset
    • Mapping types : dict

• literal : an expression whose syntax generates an object—sometimes also called a constant.
  • Literals are notations for constant values of some built-in types.
  • There are no type declarations in Python. The syntax of the expressions (object-generation expressions) determines the types of obejcts.

# a literal expression that generates and returns a new string object
'spam'

• Identifier or Variable
  • Python은 모든 것을 object로 다루기 때문에 variable(변수)보다는 변수, 상수, 함수, 사용자 정의 타입 등의 ‘이름’을 지칭하는 identifier(식별자)라는 용어를 사용한다.
  • 이름을 잘 짓는 것이 매우 중요하다!
    • (저장된 값의) 의미가 명확하게 드러나도록!
    • 기본적인 형식(규약)을 지켜서!
  • Case-sensitive names
    • Camel case : Python에서는 잘 사용하지 않는다.
      • e.g. camelCaseExample
    • Pascal case : class
      • e.g. PascalCaseExample
    • Snake case : function and variable
      • e.g. snake_case_example
  • 이름을 잘 짓는 것이 중요하다!
• Assignment (할당, 대입) vs. Binding (Python에서의 표현)
  • A variable is created when you assign it a value, may be assigned any type of object.
  • = : assignment operator (할당 연산자)

# [Error] 'obj'라는 변수는 정의(선언)되지 않았으므로 사용할 수 없다.
obj

# Print all interactive variables, with some minimal formatting.
%who

# Return a sorted list of all interactive variables.
%who_ls

# Like %who, but gives some extra information about each variable.
%whos

• Once you create an object, you bind its operation set for all time.
  • Python is dynamically typed.
    • A model keeps track of types automatically instead of requiring declaration code.
  • But it is also strongly typed.
    • A constraint that means you can perform on an object only operations that are valid for its type.

# 1. 'obj' is a string object.
obj = 'spam'

# 자동으로
type(obj)

len(obj)

# 2. 'obj' is a list object.
obj = [1, 2, 3]

type(obj)

len(obj)

# 3. Now, 'obj' is a numeric (integer) object.
obj = 10

type(obj)

# [Error] int object에는 len function을 사용할 수 없다. (또는 int object는 len method를 가지고 있지 않다.) 
len(obj)

Numbers

---

Numeric Objects

• integers that have no fractional part
• floating-point numbers with fractional part
• complex numbers with imaginary parts
• decimals with fixed precision
• rational numbers (유리수) with numerator (분자) and denominator (분모)
• full-featured sets
• Booleans : True or False

Numeric objects를 통해서 다시 한 번 binding 과정을 살펴봅시다. Assignment operator를 통해 값을 할당할 수 있습니다.

x = 1

x

Assignment operator를 수학 기호인 등호와 혼동하면 안 됩니다.

# '1 = 1 + 10'이라니?
x = x + 10

x

float type and numeric operation

x = 1.1
y = 2.2
z = 3.3

# Why?
z == x + y

The other numeric objects in third-party libraries (e.g. matrixes and vectors)

from decimal import Decimal

a = Decimal('.2')
b = Decimal('.1')
c = a + b

c

Strings

---

• string: immutable sequence of Unicode code points
  • Python은 문자(낱자)와 문자열을 별도로 구분하지 않는다.
  • String literal은 ' (single quotes) 또는 " (double quotes)로 묶어준다.

type('A')

type('Hello, world!')

type("Apple")

Q. 문자열 안에 ‘ 또는 “를 포함시키고 싶다면?

# TODO:

• 여러 줄의 string literal은 ''' 또는 """ (triple quoted)로 묶어준다.
  • Triple quoted strings may span multiple lines - all associated whitespace will be included in the string literal.

s = '''Hello,
world
and
Python!'''

s

s = """Hello,
world
and
Python!"""

s

print(s)

s = '이렇게도 줄바꿈이 가능하지만, \
연결만 해줄 뿐 \
실제로 개행이 들어가지는 않는다.'

s

print(s)

Escape Code

\n는 갑자기 어디서 튀어나온 건가요?

# TODO: 점프 투 파이썬 참조

String Prefix

• bytes literals: b'', B''
  • They produce an instance of the bytes type instead of the str type.
• raw strings: r'', R''
  • They treat backslashes as literal characters.
• formatted string literal (f-string): f'', F''
  • These strings may contain replacement fields, which are expressions delimited by curly braces {}. While other string literals always have a constant value, formatted strings are really expressions evaluated at run time.

b = b'It is not the str type but the bytes type.'

type(b)

b

r = r'Backslash(\)를 literal character로 다룸으로써 \n, \t 등 escape characters를 허용하지 않는다.'

r

print(r)

a = 1
b = ': it is a expression evaluated at run time.'
f = f'a is {a}{b}'

f

String Formatting

# TODO: 점프 투 파이썬 참조

Sequence

• sequence : a positionally ordered collection of other objects
  • Sequence types hold values in an indexable and sliceable order. (순서가 있다. = Indexing과 slicing이 가능하다.)
  • left-to-right order
  • Sequence operations
    • built-in len function
    • indexing: Indexes are coded as offsets from the front, and so start form 0.
      • Positive indexes count from the left, and negative indexes count back from the right.
      • We can use an arbitrary expression in the square brackets.
    • slicing: a way to extract an entire section (slice)
    • concatenation with +
    • repetition with *

Length of sequence

s = 'Hello, Python!'

len(s)

Indexing

# Positive index
s[0]

# Negative index
s[-1]

Q. 숫자만 index로 사용할 수 있을까?

# TODO:

Slicing

# 세미콜론 뒤에 위치하는 index의 의미에 주의!
s[7:13]

Q. 위와 동일한 결과를 만드는 slicing 방법?

# TODO:

s[7:]

s[:7]

s[:]

자유롭게 indexing과 slicing 연습을 하다보면 문득 궁긍해질 것이다. 기존 object ‘s’는 어떻게 되었을까?

# 's'는 변하지 않았다. Indexing과 slicing이 return(반환)하는 것은 새로운 object이기 때문이다.
s

Polymorphism

• polymorphism (다형성): A general property of Python. The meaning of an operation depends on the objects operated on.

# Plus sign (+) means addition for numbers.
1 + 1

# Plus sign (+) means concatenation for string.
'Hello, ' + 'Python!'

Mutability

• Mutable : list, dict, set, bytearray, memoryview
  • Mutable objects can change their value but keep their id.
• Immutable : numeric, str, tuple, frozenset, bytes
  • An object with a fixed value. Immutable objects include numbers, strings and tuples. Such an object cannot be altered. A new object has to be created if a different value has to be stored. They play an important role in places where a constant hash value is needed, for example as a key in a dictionary.

Immutable objects cannot be changed in place after they are created.

s

# [Error] String은 immutable이므로 값을 직접 변경할 수 없다.
s[0] = 'h'

Q. 그렇다면, 첫 글자 H를 소문자로 변경하기 위해 어떻게 해야 할까?

# TODO:

Type-Specific Methods

• method: functions that are attached to and act upon a specific object, which are triggered with a call expression.
  • Methods act on the subject that they are attached to and called form.
  • Generic operations that span multiple types show up as
    • built-in functions: len()
    • expression: str[0]
  • but type-specific operations are
    • method calls: str.find()
  • Although some types share some method names, string method operations generally work only on strings, and nothing else.

※ built-in functions: The Python interpreter has a number of functions and types built into it that are always available.

s

s.find('ll')

s.replace('Hello', 'hello')

Q. replace method를 사용했는데도 ‘s’는 변하지 않았다. 왜 그럴까?

s

Q. str에 속하는 methods는 어떤 것들이 있는지 확인해보자. ‘r’로 시작하는 methods는 몇 개일까?

# TODO:

Q. 다음 코드는 어떻게 해석해야 할까?

s.upper().split(',')

Formatting

• formatting: an advanced substitution operation which strings support
  • formatting expression
  • formatting method

Getting Help

---

dir

• dir: a built-in function. It returns a list of all the attributes available for any object passed to it.

Q. dir을 알았으니 이제 우리는 str에 속한 모든 attributes와 methods(function attributes)의 개수를 알 수 있다. 총 몇 개일까?

# TODO:

Built-in functions의 개수와 각각의 이름도 알 수 있다.

len(dir(__builtin__))

dir(__builtin__)

Help

• help: a built-in function to ask what they do (to see pydoc.help)
  • PyDoc: a tool for extracting documentation from objects
  • Docstring: a string literal that occurs as the first statement in a module, function, class, or method definition

help()
help(str)
help(s)
help('literal')
help(str.lower)

# Shitf + Tab: cell을 실행하지 않고 바로 Docstring 보기
# Shitf + Tab을 연속으로 두 번 누르면 스크롤이 생성되면서 Docstring 전체를 볼 수 있다.
s.lower()

# Introduction and overview of IPython's features
?

# Details about 'object'.
str?

# More detailed, verbose information about 'object'.
sys??

Lists

---

• list: positionally ordered collections of arbitrarily typed objects
  • the most general sequence provided by Python (list may be reminiscent of arrays in other languages.)
  • no fixed type constraint (list can contain different types.)
  • no fixed size (list can grow and shrink.)
  • mutable (list can be changed inplace)

l = [1, 'item in list', [10, 10., 0o10, 0x10]]

l

id(l)

l.append('new item')

l

id(l)

l[0] = 817

l

id(l)

Q. Sequence operations를 사용해보자.

# TODO:

Q. Type-specific operations를 사용해보자.

# TODO:

Bounds Checking

l

# [Error] 범위를 벗어난 위치에 대해 indexing 할 수 없다.
l[100]

# [Error] 범위를 벗어난 위치에 값을 할당할 수 없다.
l[100] = 42

Nesting

# a 3 × 3 matrix, as nested lists
list_with_nested_lists = [[1, 2, 3],
                          [4, 5, 6],
                          [7, 8, 9]]

list_with_nested_lists

Q. list_with_nested_lists의 길이는?

# TODO:

Q. Indexing을 어떻게 해야 할까. 먼저 두 번째 row [4, 5, 6]을 가져온 후, 세 번째 item 6만 가져와보자.

# TODO:

Comprehensions

• List comprehensions make new lists of results.
• They derive from set notation; they are a way to build a new list by running an expression on each item in a sequence, one at a time, from left to right.
• They tend to be very useful in practice and often provide a substantial processing speed advantage.
• Other roles: it’s not just for making lists today.
  • List, sets, dictionaries, and generators can all be built with comprehensions.

list_with_nested_lists = [[1, 2, 3],
                          [4, 5, 6],
                          [7, 8, 9]]

col_list = [row[1] for row in list_with_nested_lists]

col_list

col_list = [row[1] + 1 for row in list_with_nested_lists]

col_list

col_list = [row[1] for row in list_with_nested_lists if row[1] > 3]

col_list

Dictionaries

---

• dict: They are mappings; the only mapping type in Python’s core objects set.
  • collections of other objects
  • not sequence: Mappings don’t maintain any reliable left-to-right order; it may be scrambled.
  • mapping (a series of key and value pairs): They simply map mnemonic keys to associated values.
    • Keys must be of immutable types.
  • mutable

d = {'이름': '김태진', '학교': '가천대', '학년': 4, '수강과목': ['의료영상', '생체신호처리']}

d = {'name': 'Taejin Kim', 'university': 'Gachon Univ.', 'grade': 3, 'lectures': ['Medical Imaging', 'Biosignal Processing']}

d

• Dictionaries can also be used to replace searching operations—indexing a dictionary by key is often the fastest way to code a search in Python.

We can index dictionary by key to fetch and change the keys’ associated values.

# Fetch
d['name']

# Change
d['grade'] = 4

d

Unlike out-of-bounds assignments in lists, which are forbidden, assignments to new dictionary keys create those keys.

# An empty dictionary
d = {}

d

# Add a new key and the keys' associated value.
d['name'] = 'Taejin Kim'

d

d['university'] = 'Gachon Univ.'
d['grade'] = 4
d['lectures'] = ['Medical Imaging', 'Biosignal Processing']

d

Nesting

d['name'] = {'first': 'Taejin', 'last': 'Kim'}

d

Q. Indexing dictionary by key로 first name 가져오기.

# TODO:

Q. 수강과목 추가하기.

# TODO:

Q. 마지막으로 추가한 수강과목 indexing 하기.

# TODO:

Missing Keys

# [Error] 'age'란 Key는 존재하지 않는다. Referencing a nonexistent key is an error.
d['age']

• How to avoid KeyError? 1) To test ahead of time

d.items()

d.keys()

d.values()

in: membership expression

1 in [1, 2, 3]

't' in 'Python'

'th' in 'Python'

1.0 in [1, 2, 3]

'p' in 'Python'

'age' in d

if statement: the main selection statement tool in Python

if 'age' in d:
    d['age']

• How to avoid KeyError? 2) get method: a conditional index with a default

d.get('age')

# Key가 존재하지 않을 경우 반환되는 default 값은 None
print(d.get('age'))

# Key가 존재하지 않을 경우 반환되는 값을 0(get method에 전달되는 두 번째 argument(인자))으로 지정
d.get('age', 0)

사실 get method는 if/else ternary expression(an if statement squeezed onto a single line)으로 정의되어 있다.

d['age'] if 'age' in d else 0

Iteration and Optimization

• iterable: either a physically stored sequence in memory or an object that generates one item at a time in the context of an iteration operation.
  • For loop and list comprehension expression work on any iterable object.
  • Iterables vs. Iterators vs. Generators

• Iterable objects support the iteration protocol—they respond to the iter call with an object that advances in response to next calls and raises an exception when finished producing values.

• generator: its values are not stored in memory all at once, but are produced as requested, usually by iteration tools.
• file object: it similarly iterate line by line; it’s fetched on demand.
• Every Python tool that scans an object from left to right uses the iteration protocol.

Q. 아니 그런데, 코딩만 잘 하면 되지 이런 걸 꼭 알아야 해요?

# TODO: 빈 list 생성
list()

# TODO: list의 소괄호 안에 커서를 두고 Shitf + Tab을 눌러보자!
list(d.keys())

Tuples

---

• tuple: toughly like a list that cannot be changed; they’re used to represent fixed collections of items.
  • immutable sequence
  • They support arbitrary types, arbitrary nesting, and the usual sequence operations.

Q. lsit와 매우 비슷해보인다! 그리고 이제 우리는 sequence와 immutable이 무엇인지 안다! 그렇다면, tuple로 무엇을 할 수 있을지 추론해보자.

# TODO:

다음과 같이 한 개의 아이템을 갖는 튜플을 만들 때 주의!

t = (1)

type(t)

t

t = (1,)

type(t)

t

t = (1, 2, 3)

# [Error] Tuples are immutable sequences.
t[0] = 0

# [Error] Tuples don't grow and shrink.
t.append(4)

Tuple Packing

• 소괄호를 생략해도 값들이 묶여서(values are packed together) tuple이 된다.

d = 1, 2, 3, 4, 5

type(d)

d

Sequence Unpacking

• The reverse operation of tuple packing.
• Sequence unpacking requires that there are as many variables on the left side of the equals sign as there are elements in the sequence.
• Multiple assignment is really just a combination of tuple packing and sequence unpacking.

a, b, c = 1, 2, 3
# a, b, c = 1, 2, (3, )
# a, b, c = 1, 2, [3, 4]

type(a)

type(b)

type(c)

# [Error] 할당 연산자 왼쪽의 식별자 개수와 오른쪽의 값(요소) 개수가 같지 않은 경우
a, b, c = 1, 2

# [Error] 할당 연산자 왼쪽의 식별자 개수와 오른쪽의 값(요소) 개수가 같지 않은 경우
a, b, c = 1, 2, 3, 4

*을 사용하면 유동적인 packing, unpacking이 가능하다.

# 첫 요소만 a에 pack, 나머지 전부를 b에 pack
a, *b = 1, 2, 3, 4, 5

a

b

# 마지막 요소만 b에 pack, 나머지 전부를 a에 pack
*a, b = 1, 2, 3, 4, 5

a

b

# 첫 요소를 a에, 마지막 요소를 c에, 나머지 전부를 b에 pack
a, *b, c = 1, 2, 3, 4, 5

a

b

c

C에서는 temp 변수 만들어서 해야 했던 swapping arguments가 Python에서는 이렇게 간단하다.

a = 5
b = 10

"""
temp = a
a = b
b = temp
"""

a, b = b, a

a

b

Files

---

컴퓨터는 영원히, 제약 없이 모든 변수의 값을 기억할 수 있을까? 메모리상의 정보는 커널 또는 컴퓨터를 재시작하면 삭제되어 재사용할 수 없다. 따라서 파일로 저장해야 정보를 보존할 수 있다.

• file: main interface to external files on your computer
  • Files are a core type, but they’re something of an oddball—there is no specific literal syntax for creating them. Rather, to create a file object, you call the built-in open function.

# Write a file.
f = open('test.txt', 'w')
f.write('Hello\n')
f.write('word\n')
f.close()

# Read a file.
f = open('test.txt', 'r')
text = f.read()
f.close()

text

Two ways to print every object in Python

• repr: as-code

text

print(text.__repr__())

• str: user-friendly

print(text)

print(text.__str__())

Other Core Types

---

• set: unordered collections of unique and immutale objects: neither mappings nor sequences

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

l

set(l)

{n ** 2 for n in [1, -1, 2, -2, 3, -3]}

• decimal for fixed-precision floating-point numbers
• Fraction for rational numbers
• Booleans: True (1) or False (0) objects
• None: placeholder object

placeholder = None

plc

Q. 초록색 코드, 넌 누구냐?

# TODO:

Type

---

• type: obect that gives the type of another object; it’s returned by the type built-in function
• type are classes, and vice versa (Python 3.X)

l = [1, 2, 3]

print(type(l))

print(type(type(l)))

Type Testing

• Code to check the types of the objects

type(l) == type([])

type(l) == list

isinstance(l, list)

• But it is almost always the wrong thing to do in a Python program.

“Pythonic!”

• Polymorphism is probably the key idea behind using Python well.
• We code to object interfaces (operations supported), not to types. That is, We care what an object does, not what it is.

Again, everything in Python is an “object”.

Chapter Summary

---

• Python’s core object types: flexible and powerfule
• Generic operations
• Type-specific operations
• Key terms, such as immutability, sequences, and polymorphism

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