1.2.2. Basic types

1.2.2.1. Numerical types

Tip

Pythonは、以下の数値型、スカラー型をサポートしています:

Integer:

>>> 1 + 1
2
>>> a = 4
>>> type(a)
<class 'int'>

Floats:

>>> c = 2.1
>>> type(c)
<class 'float'>

Complex:

>>> a = 1.5 + 0.5j
>>> a.real
1.5
>>> a.imag
0.5
>>> type(1. + 0j)
<class 'complex'>

Booleans:

>>> 3 > 4
False
>>> test = (3 > 4)
>>> test
False
>>> type(test)
<class 'bool'>

Tip

A Python shell can therefore replace your pocket calculator, with the basic arithmetic operations +, -, *, /, % (modulo) natively implemented

>>> 7 * 3.
21.0
>>> 2**10
1024
>>> 8 % 3
2

Type conversion (casting):

>>> float(1)
1.0

1.2.2.2. Containers

Tip

Pythonは、オブジェクトのコレクションを格納できる効率的なコンテナの種類を数多く提供しています。

Lists

Tip

リストは、異なる型を持つ可能性のあるオブジェクトの順序付けられたコレクションです。例えば:

>>> colors = ['red', 'blue', 'green', 'black', 'white']
>>> type(colors)
<class 'list'>

Indexing: accessing individual objects contained in the list:

>>> colors[2]
'green'

Counting from the end with negative indices:

>>> colors[-1]
'white'
>>> colors[-2]
'black'

警告

Indexing starts at 0 (as in C), not at 1 (as in Fortran or Matlab)!

Slicing: obtaining sublists of regularly-spaced elements:

>>> colors
['red', 'blue', 'green', 'black', 'white']
>>> colors[2:4]
['green', 'black']

警告

Note that colors[start:stop] contains the elements with indices i such as start<= i < stop (i ranging from start to stop-1). Therefore, colors[start:stop] has (stop - start) elements.

Slicing syntax: colors[start:stop:stride]

Tip

All slicing parameters are optional:

>>> colors
['red', 'blue', 'green', 'black', 'white']
>>> colors[3:]
['black', 'white']
>>> colors[:3]
['red', 'blue', 'green']
>>> colors[::2]
['red', 'green', 'white']

Lists are mutable objects and can be modified:

>>> colors[0] = 'yellow'
>>> colors
['yellow', 'blue', 'green', 'black', 'white']
>>> colors[2:4] = ['gray', 'purple']
>>> colors
['yellow', 'blue', 'gray', 'purple', 'white']

注釈

リストの要素には、さまざまな型があります:

>>> colors = [3, -200, 'hello']
>>> colors
[3, -200, 'hello']
>>> colors[1], colors[2]
(-200, 'hello')

Tip

For collections of numerical data that all have the same type, it is often more efficient to use the array type provided by the numpy module. A NumPy array is a chunk of memory containing fixed-sized items. With NumPy arrays, operations on elements can be faster because elements are regularly spaced in memory and more operations are performed through specialized C functions instead of Python loops.

Tip

Python offers a large panel of functions to modify lists, or query them. Here are a few examples; for more details, see https://docs.python.org/3/tutorial/datastructures.html#more-on-lists

Add and remove elements:

>>> colors = ['red', 'blue', 'green', 'black', 'white']
>>> colors.append('pink')
>>> colors
['red', 'blue', 'green', 'black', 'white', 'pink']
>>> colors.pop() # removes and returns the last item
'pink'
>>> colors
['red', 'blue', 'green', 'black', 'white']
>>> colors.extend(['pink', 'purple']) # extend colors, in-place
>>> colors
['red', 'blue', 'green', 'black', 'white', 'pink', 'purple']
>>> colors = colors[:-2]
>>> colors
['red', 'blue', 'green', 'black', 'white']

Reverse:

>>> rcolors = colors[::-1]
>>> rcolors
['white', 'black', 'green', 'blue', 'red']
>>> rcolors2 = list(colors) # new object that is a copy of colors in a different memory area
>>> rcolors2
['red', 'blue', 'green', 'black', 'white']
>>> rcolors2.reverse() # in-place; reversing rcolors2 does not affect colors
>>> rcolors2
['white', 'black', 'green', 'blue', 'red']

Concatenate and repeat lists:

>>> rcolors + colors
['white', 'black', 'green', 'blue', 'red', 'red', 'blue', 'green', 'black', 'white']
>>> rcolors * 2
['white', 'black', 'green', 'blue', 'red', 'white', 'black', 'green', 'blue', 'red']

Tip

Sort:

>>> sorted(rcolors) # new object
['black', 'blue', 'green', 'red', 'white']
>>> rcolors
['white', 'black', 'green', 'blue', 'red']
>>> rcolors.sort()  # in-place
>>> rcolors
['black', 'blue', 'green', 'red', 'white']

メソッドとオブジェクト指向プログラミング

The notation rcolors.method() (e.g. rcolors.append(3) and colors.pop()) is our first example of object-oriented programming (OOP). Being a list, the object rcolors owns the method function that is called using the notation .. No further knowledge of OOP than understanding the notation . is necessary for going through this tutorial.

Discovering methods:

Reminder: in Ipython: tab-completion (press tab)

In [1]: rcolors.<TAB>
                 append()  count()   insert()  reverse()
                 clear()   extend()  pop()     sort()
                 copy()    index()   remove()

Strings

Different string syntaxes (simple, double or triple quotes):

s = 'Hello, how are you?'
s = "Hi, what's up"
s = '''Hello,
       how are you'''         # tripling the quotes allows the
                              # string to span more than one line
s = """Hi,
what's up?"""

In [2]: 'Hi, what's up?'
  Cell In[2], line 1
    'Hi, what's up?'
                   ^
SyntaxError: unterminated string literal (detected at line 1)

この構文エラーは、文字列をシングルクォートではなくダブルクォートで囲むことで回避できます。あるいは、2つ目のシングルクォートの前にバックスラッシュを付ける方法もあります。バックスラッシュの他の使い方としては、改行を表す \n やタブを表す \t などがあります。

Tip

文字列はリストと同じコレクションです。 したがって、同じ構文とルールでインデックスを作成したり、スライスしたりすることができます。

Indexing:

>>> a = "hello"
>>> a[0]
'h'
>>> a[1]
'e'
>>> a[-1]
'o'

Tip

(Remember that negative indices correspond to counting from the right end.)

Slicing:

>>> a = "hello, world!"
>>> a[3:6] # 3rd to 6th (excluded) elements: elements 3, 4, 5
'lo,'
>>> a[2:10:2] # Syntax: a[start:stop:step]
'lo o'
>>> a[::3] # every three characters, from beginning to end
'hl r!'

Tip

アクセント記号や特殊文字も、Python 3 の文字列と同様に Unicode 文字として扱われます。

A string is an immutable object and it is not possible to modify its contents. One may however create new strings from the original one.

In [3]: a = "hello, world!"

In [4]: a.replace('l', 'z', 1)
Out[4]: 'hezlo, world!'

Tip

Strings have many useful methods, such as a.replace as seen above. Remember the a. object-oriented notation and use tab completion or help(str) to search for new methods.

参考

Python offers advanced possibilities for manipulating strings, looking for patterns or formatting. The interested reader is referred to https://docs.python.org/3/library/stdtypes.html#string-methods and https://docs.python.org/3/library/string.html#format-string-syntax

String formatting:

>>> 'An integer: %i; a float: %f; another string: %s' % (1, 0.1, 'string') # with more values use tuple after %
'An integer: 1; a float: 0.100000; another string: string'

>>> i = 102
>>> filename = 'processing_of_dataset_%d.txt' % i   # no need for tuples with just one value after %
>>> filename
'processing_of_dataset_102.txt'

Dictionaries

Tip

A dictionary is basically an efficient table that maps keys to values.

>>> tel = {'emmanuelle': 5752, 'sebastian': 5578}
>>> tel['francis'] = 5915
>>> tel
{'emmanuelle': 5752, 'sebastian': 5578, 'francis': 5915}
>>> tel['sebastian']
5578
>>> tel.keys()
dict_keys(['emmanuelle', 'sebastian', 'francis'])
>>> tel.values()
dict_values([5752, 5578, 5915])
>>> 'francis' in tel
True

Tip

It can be used to conveniently store and retrieve values associated with a name (a string for a date, a name, etc.). See https://docs.python.org/3/tutorial/datastructures.html#dictionaries for more information.

A dictionary can have keys (resp. values) with different types:

>>> d = {'a':1, 'b':2, 3:'hello'}
>>> d
{'a': 1, 'b': 2, 3: 'hello'}

More container types

Tuples

Tuples are basically immutable lists. The elements of a tuple are written between parentheses, or just separated by commas:

>>> t = 12345, 54321, 'hello!'
>>> t[0]
12345
>>> t
(12345, 54321, 'hello!')
>>> u = (0, 2)

Sets: unordered, unique items:

>>> s = set(('a', 'b', 'c', 'a'))
>>> s
{'a', 'b', 'c'}
>>> s.difference(('a', 'b'))
{'c'}

1.2.2.3. 代入演算子

Tip

Python library reference says:

Assignment statements are used to (re)bind names to values and to modify attributes or items of mutable objects.

In short, it works as follows (simple assignment):

1. an expression on the right hand side is evaluated, the corresponding object is created/obtained

2. a name on the left hand side is assigned, or bound, to the r.h.s. object

Things to note:

• 単一のオブジェクトには複数の名前が紐付けられることがあります:

In [5]: a = [1, 2, 3]

In [6]: b = a

In [7]: a
Out[7]: [1, 2, 3]

In [8]: b
Out[8]: [1, 2, 3]

In [9]: a is b
Out[9]: True

In [10]: b[1] = 'hi!'

In [11]: a
Out[11]: [1, 'hi!', 3]

• to change a list in place, use indexing/slices:

In [12]: a = [1, 2, 3]

In [13]: a
Out[13]: [1, 2, 3]

In [14]: a = ['a', 'b', 'c'] # Creates another object.

In [15]: a
Out[15]: ['a', 'b', 'c']

In [16]: id(a)
Out[16]: 135379168527360

In [17]: a[:] = [1, 2, 3] # Modifies object in place.

In [18]: a
Out[18]: [1, 2, 3]

In [19]: id(a)
Out[19]: 135379168527360

• the key concept here is mutable vs. immutable

  • mutable objects can be changed in place

  • immutable objects cannot be modified once created

参考

A very good and detailed explanation of the above issues can be found in David M. Beazley's article Types and Objects in Python.