Python 学习笔记（一）Data type
Data types:
Sequence types: (有序的类型)
- strings
- tuples
- lists
Immutable types: (不可变的类型)
- numbers
- strings
- tuples
#String:
text = "Lists and Strings can be accessed via indices!"
String 的几种表示法：
• Single quotes: 'spa"m'
• Double quotes: "spa'm"
• Triple quotes: '''... spam ...''', """... spam ..."""
• Escape sequences: "s\tp\na\0m"
• Raw strings: r"C:\new\test.spm"
>>> mantra = """Always look ... on the bright ... side of life.""" >>> >>> mantra 'Always look\n on the bright\nside of life.' >>> print(mantra) Always look on the bright side of life.
反转字符串
>>> S = 'hello' >>> S[::−1] 'olleh'
str and repr: (convert number to string)
>>> print(str('b'),repr('a')) b 'a' >>> print(str('42'),repr('42')) 42 '42' >>> print(str("42"),repr("42")) 42 '42'
character to ASCII:
>>> ord('s') 115 >>> chr(115) 's'
如何改变String :
>>> S = S + 'SPAM!' # To change a string, make a new one >>> S 'spamSPAM!' >>> S = 'splot' >>> S = S.replace('pl', 'pamal') >>> S 'spamalot'
Format:
>>> 'That is %d %s bird!' % (1, 'dead') # Format expression That is 1 dead bird! >>> 'That is {0} {1} bird!'.format(1, 'dead') # Format method in 2.6 and 3.0 'That is 1 dead bird!'
#List []
L = ["London", "Paris", "Strasbourg", "Zurich"]
The main properties of Python lists:
- They are ordered
- The contain arbitrary objects
- Elements of a list can be accessed by an index
- They are arbitrarily nestable, i.e. they can contain other lists as sublists
- Variable size
- They mutable, i.e. they elements of a list can be changed
简单的copy会改变原来list的值，如果不想改变原来的值，则需要深度copy (deepcopy):
>>> lst1 = ['a','b',['ab','ba']] >>> lst2 = lst1[:] >>> lst2[0] = 'c' >>> lst2[2][1] = 'd' >>> print(lst1) ['a', 'b', ['ab', 'd']]
Deepcopy:
>>> from copy import deepcopy >>> lst1 = ['a','b',['ab','ba']] >>> lst2 = deepcopy(lst1) >>> lst2[2][1] = "d" >>> lst2[0] = "c" >>> print(lst2) ['c', 'b', ['ab', 'd']] >>> print(lst1) ['a', 'b', ['ab', 'ba']]
string to list:
>>> S = 'spammy' >>> L = list(S) >>> L ['s', 'p', 'a', 'm', 'm', 'y']
Operation:
>>> s = "Test List" >>> l = list(s) >>> l ['T', 'e', 's', 't', ' ', 'L', 'i', 's', 't'] >>> l.append('h') >>> l ['T', 'e', 's', 't', ' ', 'L', 'i', 's', 't', 'h'] >>> l.extend(['a','b']) >>> l ['T', 'e', 's', 't', ' ', 'L', 'i', 's', 't', 'h', 'a', 'b'] >>> l.insert(2,'c') >>> l ['T', 'e', 'c', 's', 't', ' ', 'L', 'i', 's', 't', 'h', 'a', 'b'] >>> del l[2] >>> l ['T', 'e', 's', 't', ' ', 'L', 'i', 's', 't', 'h', 'a', 'b'] >>> l.remove('t') >>> l ['T', 'e', 's', ' ', 'L', 'i', 's', 't', 'h', 'a', 'b'] #remove all matched characters >>> for i in l: if i =='s': l.remove(i) >>> l ['T', 'e', ' ', 'L', 'i', 'h', 'a', 'b']
>>> L = [x**2 for x in range(5)] >>> L [0, 1, 4, 9, 16]
排序：
>>> L = ['abc', 'ABD', 'aBe'] >>> L.sort() # Sort with mixed case >>> L ['ABD', 'aBe', 'abc'] >>> L = ['abc', 'ABD', 'aBe'] >>> L.sort(key=str.lower) # Normalize to lowercase >>> L ['abc', 'ABD', 'aBe'] >>> >>> L = ['abc', 'ABD', 'aBe'] >>> L.sort(key=str.lower, reverse=True) # Change sort order >>> L ['aBe', 'ABD', 'abc']
#Tuple ()
tup1 = ('physics', 'chemistry', 1997, 2000);
A tuple is an immutable list:
- Tuples are faster than lists.
- If you know, that some data doesn't have to be changed, you should use tuples instead of lists, because this protect your data against accidental changes to these data.
- Tuples can be used as keys in dictionaries, while lists can't.
Tuple 语法：Commas and parentheses
>>> x = (40) # An integer! >>> x 40 >>> y = (40,) # A tuple containing an integer >>> y (40,)
Tuple to list:
>>> T = (1, 2, 3, 4, 5) >>> L = [x + 20 for x in T] >>> L [21, 22, 23, 24, 25] >>> T = (1, 2, 3, 2, 4, 2) >>> T.index(2,3) #从index3开始找2 3
tuple immutability applies only to the top level of the ruple itself.
>>> T = (1, [2, 3], 4) >>> T[1] = 'spam' # This fails: can't change tuple itself TypeError: object doesn't support item assignment >>> T[1][0] = 'spam' # This works: can change mutables inside >>> T (1, ['spam', 3], 4)
#Set {}
- an unordered collection
- unique value
- like keys of valuesless dictionary, but supports extra operations
Can use to remove duplicates:
>>> L = [1, 2, 1, 3, 2, 4, 5] >>> set(L) {1, 2, 3, 4, 5} >>> L = list(set(L)) # Remove duplicates >>> L [1, 2, 3, 4, 5]
Extra operations:
>>> engineers = {'bob', 'sue', 'ann', 'vic'}
>>> managers = {'tom', 'sue'}
>>> engineers & managers
{'sue'}
>>> engineers | managers
{'ann', 'tom', 'bob', 'vic', 'sue'}
>>> engineers - managers
{'ann', 'vic', 'bob'}
>>> managers ^ engineers # Who is in one but not both?
{'ann', 'tom', 'vic', 'bob'}
#Dictionary {key:value}
- Sequence operations don’t work.
- Keys need not always be strings.
- Assigning to new indexes adds entries.
>>> food = {"ham" : "yes", "egg" : "yes", "spam" : "no" }
>>> D = {'spam': 2, 'ham': 1, 'eggs': 3}
>>> list(D.values())
[3, 1, 2]
>>> list(D.items())
[('eggs', 3), ('ham', 1), ('spam', 2)]
Using dictionaries as 'records':
>>> mel = {'name': 'Mark',
'jobs': ['trainer', 'writer'],
'web': 'www.rmi.net/˜lutz',
'home': {'state': 'CO', 'zip':80513}}
>>> mel['jobs']
['trainer', 'writer']
>>> mel['jobs'][1]
'writer'
>>> mel['home']['zip']
80513
Ways to make dictionaries:
{'name': 'mel', 'age': 45} # Traditional literal expression
D = {} # Assign by keys dynamically
D['name'] = 'mel'
D['age'] = 45
dict(name='mel', age=45) # dict keyword argument form
dict([('name', 'mel'), ('age', 45)]) # dict key/value tuples form
>>> dict.fromkeys(['a', 'b'], 0)
{'a': 0, 'b': 0}
Turn list to dictionary:
>>> list(zip(['a', 'b', 'c'], [1, 2, 3])) # Zip together keys and values [('a', 1), ('b', 2), ('c', 3)] >>> D = dict(zip(['a', 'b', 'c'], [1, 2, 3])) # Make a dict from zip result >>> D {'a': 1, 'c': 3, 'b': 2}
#new method in 3.0
>>> D = {k: v for (k, v) in zip(['a', 'b', 'c'], [1, 2, 3])}
>>> D
{'a': 1, 'c': 3, 'b': 2}
>>> D = {c.lower(): c + '!' for c in ['SPAM', 'EGGS', 'HAM']}
>>> D
{'eggs': 'EGGS!', 'ham': 'HAM!', 'spam': 'SPAM!'}
Sort:
>>> D {'a': 1, 'c': 3, 'b': 2} # Better yet, sort the dict directly >>> for k in sorted(D): print(k, D[k]) # dict iterators return keys ... a 1 b 2 c 3