Python3
Встроенные объекты
Object type Example literals/creation
Numbers 1234, 3.1415, 3+4j, 0b111, Decimal(), Fraction()
Strings 'spam', "Bob's", b'a\x01c', u'sp\xc4m'
Lists [1, [2, 'three'], 4.5], list(range(10))
Dictionaries {'food': 'spam', 'taste': 'yum'}, dict(hours=10)
Tuples (1, 'spam', 4, 'U'), tuple('spam'), namedtuple
Files open('eggs.txt'), open(r'C:\ham.bin', 'wb')
Sets set('abc'), {'a', 'b', 'c'}
Other core types Booleans, types, None
Numbers
>>> 123 + 222 # Integer addition 345 >>> 1.5 * 4 # Floating-point multiplication 6.0 >>> 2 ** 100 # 2 to the power 100, again 1267650600228229401496703205376
>>> len(str(2 ** 1000000)) # How many digits in a really BIG number? 301030
start experimenting with floating-point numbers, you’re likely to stumble across something that may look a bit odd at first glance: >>> 3.1415 * 2 # repr: as code (Pythons < 2.7 and 3.1) 6.2830000000000004 >>> print(3.1415 * 2) # str: user-friendly 6.283
>>> import math >>> math.pi 3.141592653589793 >>> math.sqrt(85) 9.219544457292887
>>> import random >>> random.random() 0.7082048489415967 >>> random.choice([1, 2, 3, 4]) 1
String
>>> S = 'Spam' # Make a 4-character string, and assign it to a name >>> len(S) # Length 4 >>> S[0] # The first item in S, indexing by zero-based position 'S' >>> S[1] # The second item from the left 'p'
In Python, we can also index backward, from the end—positive indexes count from
the left, and negative indexes count back from the right:
>>> S[-1] # The last item from the end in S 'm' >>> S[-2] # The second-to-last item from the end 'a'
Formally, a negative index is simply added to the string’s length, so the following two
operations are equivalent (though the first is easier to code and less easy to get wrong):
>>> S[-1] # The last item in S 'm' >>> S[len(S)-1] # Negative indexing, the hard way 'm'
In addition to simple positional indexing, sequences also support a more general form
of indexing known as slicing, which is a way to extract an entire section (slice) in a single
step. For example:
>>> S # A 4-character string 'Spam' >>> S[1:3] # Slice of S from offsets 1 through 2 (not 3) 'pa'
>>> S[1:] # Everything past the first (1:len(S)) 'pam' >>> S # S itself hasn't changed 'Spam' >>> S[0:3] # Everything but the last 'Spa' >>> S[:3] # Same as S[0:3] 'Spa' >>> S[:-1] # Everything but the last again, but simpler (0:-1) 'Spa' >>> S[:] # All of S as a top-level copy (0:len(S)) 'Spam'
>>> S + 'xyz' # Concatenation 'Spamxyz' >>> S # S is unchanged 'Spam' >>> S * 8 # Repetition 'SpamSpamSpamSpamSpamSpamSpamSpam'
Immutability
Also notice in the prior examples that we were not changing the original string with
any of the operations we ran on it. Every string operation is defined to produce a new
string as its result, because strings are immutable in Python—they cannot be changed
in place after they are created. In other words, you can never overwrite the values of
immutable objects. For example, you can’t change a string by assigning to one of its
positions, but you can always build a new one and assign it to the same name. Because
Python cleans up old objects as you go (as you’ll see later), this isn’t as inefficient as it
may sound:
>>> S 'Spam' >>> S[0] = 'z' # Immutable objects cannot be changed ...error text omitted... TypeError: 'str' object does not support item assignment >>> S = 'z' + S[1:] # But we can run expressions to make new objects >>> S 'zpam'
Every object in Python is classified as either immutable (unchangeable) or not. In terms
of the core types, numbers, strings, and tuples are immutable; lists, dictionaries, and
sets are not—they can be changed in place freely, as can most new objects you’ll code
with classes.
Strictly speaking, you can change text-based data in place if you either expand it into a
list of individual characters and join it back together with nothing between, or use the
newer bytearray type available in Pythons 2.6, 3.0, and later:
>>> S = 'shrubbery' >>> L = list(S) # Expand to a list: [...] >>> L ['s', 'h', 'r', 'u', 'b', 'b', 'e', 'r', 'y'] >>> L[1] = 'c' # Change it in place >>> ''.join(L) # Join with empty delimiter 'scrubbery' >>> B = bytearray(b'spam') # A bytes/list hybrid (ahead) >>> B.extend(b'eggs') # 'b' needed in 3.X, not 2.X >>> B # B[i] = ord(c) works here too bytearray(b'spameggs') >>> B.decode() # Translate to normal string 'spameggs'
Type-Specific Methods
For example, the string find method is the basic substring search operation (it returns
the offset of the passed-in substring, or −1 if it is not present), and the string replace
method performs global searches and replacements; both act on the subject that they
are attached to and called from:
>>> S = 'Spam'
>>> S.find('pa') # Find the offset of a substring in S
1
>>> S
'Spam'
>>> S.replace('pa', 'XYZ') # Replace occurrences of a string in S with another
'SXYZm'
>>> S
'Spam'
>> line = 'aaa,bbb,ccccc,dd'
>>> line.split(',') # Split on a delimiter into a list of substrings
['aaa', 'bbb', 'ccccc', 'dd']
>>> S = 'spam'
>>> S.upper() # Upper- and lowercase conversions
'SPAM'
>>> S.isalpha() # Content tests: isalpha, isdigit, etc.
True
>>> line = 'aaa,bbb,ccccc,dd\n'
>>> line.rstrip() # Remove whitespace characters on the right side
'aaa,bbb,ccccc,dd'
>>> line.rstrip().split(',') # Combine two operations
['aaa', 'bbb', 'ccccc', 'dd']
Notice the last command here—it strips before it splits because Python runs from left
to right, making a temporary result along the way. Strings also support an advanced
substitution operation known as formatting, available as both an expression (the original)
and a string method call (new as of 2.6 and 3.0); the second of these allows you
to omit relative argument value numbers as of 2.7 and 3.1:
>> '%s, eggs, and %s' % ('spam', 'SPAM!') # Formatting expression (all)
'spam, eggs, and SPAM!'
>>> '{0}, eggs, and {1}'.format('spam', 'SPAM!') # Formatting method (2.6+, 3.0+)
'spam, eggs, and SPAM!'
>>> '{}, eggs, and {}'.format('spam', 'SPAM!') # Numbers optional (2.7+, 3.1+)
'spam, eggs, and SPAM!'
Formatting is rich with features, which we’ll postpone discussing until later in this
book, and which tend to matter most when you must generate numeric reports:
>>> '{:,.2f}'.format(296999.2567) # Separators, decimal digits
'296,999.26'
>>> '%.2f | %+05d' % (3.14159, −42) # Digits, padding, signs
'3.14 | −0042'