python 字典的一些操作
特点：无序，是唯一内置的映射类型。多用于实现哈希表或者关联数组。
key具有唯一性，可以使用固定长度的对象，不能使用列表、字典和包含可变长度类型的元组。访问形式：m[k]，k是key。如果找不到，报错：KeyError。
方法和操作如下：
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项目 |
功能 |
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len(m) |
Key的长度 |
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m[k] |
字典m中，key为k的值 |
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m[k]=x |
字典m中，k的值为x |
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del m[k] |
删除字典键 |
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k in m |
有没有k的key |
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m.clear() |
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m.copy() |
浅复制 |
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m.fromkeys(s [,value]) |
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m.get(k [,v]) |
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m.has_key(k) |
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m.items() |
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m.keys() |
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m.pop(k [,default]) |
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m.popitem() |
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m.setdefault(k [, v]) |
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m.update(b) |
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m.values() |
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＊构建字典
字典举例：
phonebook = {‘Alice‘: ‘2341‘, ‘Beth‘: ‘9102‘, ‘Cecil‘: ‘3258‘}
函数Dict可以从其他映射或者序列构建字典
>>> items = [(‘name‘, ‘Gumby‘), (‘age‘, 42)]
>>> d = dict(items)
>>> d
{‘age‘: 42, ‘name‘: ‘Gumby‘}
>>> d[‘name‘]
‘Gumby‘
也可以使用参数的方法：
>>> d = dict(name=‘Gumby‘, age=42)
>>> d
{‘age‘: 42, ‘name‘: ‘Gumby‘}
初始化空字典：
>>> x = {}
>>> x[42] = ‘Foobar‘
>>> x
{42: ‘Foobar‘}
＊格式化输出：
>>> phonebook
{‘Beth‘: ‘9102‘, ‘Alice‘: ‘2341‘, ‘Cecil‘: ‘3258‘}
>>> "Cecil‘s phone number is %(Cecil)s." % phonebook
"Cecil‘s phone number is 3258."
>>> template = ‘‘‘
%(title)s
%(text)s
‘‘‘
>>> data = {‘title‘: ‘My Home Page‘, ‘text‘: ‘Welcome to my home page!‘}
>>> print template % data
My Home Page
Welcome to my home page!
另外string.Template 类也很适合这种应用。
＊字典方法：
-＊清除：clear
下面例子展示clear和把字典置空字典的区别：
>>> x = {}
>>> y = x
>>> x[‘key‘] = ‘value‘
>>> y
{‘key‘: ‘value‘}
>>> x = {}
>>> y
{‘key‘: ‘value‘}
>>> x = {}
>>> y = x
>>> x[‘key‘] = ‘value‘
>>> y
{‘key‘: ‘value‘}
>>> x.clear()
>>> y
{}
-＊复制：copy
>>> x = {‘username‘: ‘admin‘, ‘machines‘: [‘foo‘, ‘bar‘, ‘baz‘]}
>>> y = x.copy()
>>> y[‘username‘] = ‘mlh‘
>>> y[‘machines‘].remove(‘bar‘)
>>> y
{‘username‘: ‘mlh‘, ‘machines‘: [‘foo‘, ‘baz‘]}
>>> x
{‘username‘: ‘admin‘, ‘machines‘: [‘foo‘, ‘baz‘]}
浅拷贝的元素指向原有元素，所以改变原有的可变元素，新的也会受影响，反之亦然。换种说法，对元素进行替换，不会对新老都产生影响，但是修改则会有影响。
>>> from copy import deepcopy
>>> d = {}
>>> d[‘names‘] = [‘Alfred‘, ‘Bertrand‘]
>>> c = d.copy()
>>> dc = deepcopy(d)
>>> d[‘names‘].append(‘Clive‘)
>>> c
{‘names‘: [‘Alfred‘, ‘Bertrand‘, ‘Clive‘]}
>>> dc
{‘names‘: [‘Alfred‘, ‘Bertrand‘]}
-＊复制key：fromkeys
>>> {}.fromkeys([‘name‘, ‘age‘])
{‘age‘: None, ‘name‘: None}
也可以用dict代替{}
>>> dict.fromkeys([‘name‘, ‘age‘])
{‘age‘: None, ‘name‘: None}
设置其他默认值：
>>> dict.fromkeys([‘name‘, ‘age‘], ‘(unknown)‘)
{‘age‘: ‘(unknown)‘, ‘name‘: ‘(unknown)‘}
-＊获取：get
>>> d = {}
>>> print d[‘name‘]
Traceback (most recent call last):
File "", line 1, in ?
KeyError: ‘name‘
>>> print d.get(‘name‘)
None
也可以用其他字符替代None
>>> d.get(‘name‘, ‘N/A‘)
‘N/A‘
-＊has_key：是否有key
和k in d是等效的，Python 3.0将取消这个，建议不要使用
>>> d = {}
>>> d.has_key(‘name‘)
False
>>> d[‘name‘] = ‘Eric‘
>>> d.has_key(‘name‘)
True
-＊列出值：items and iteritems
>>> d = {‘title‘: ‘Python Web Site‘, ‘url‘: ‘http://www.python.org‘, ‘spam‘: 0}
>>> d.items()
[(‘url‘, ‘http://www.python.org‘), (‘spam‘, 0), (‘title‘, ‘Python Web Site‘)]
>>> it = d.iteritems()
>>> it
>>> list(it) # Convert the iterator to a list
[(‘url‘, ‘http://www.python.org‘), (‘spam‘, 0), (‘title‘, ‘Python Web Site‘)]
Iteritems生成迭代器，一般的情况下使用iteritems比iteritem更有效，尤其是循环的时候。
注：Python 3 items 返回的是迭代器
-＊列出关键字：keys and iterkeys
后者是迭代器
根据key出栈：pop
>>> d = {‘x‘: 1, ‘y‘: 2}
>>> d.pop(‘x‘)
1
>>> d
{‘y‘: 2}
-＊出栈：popitem
>>> d
{‘url‘: ‘http://www.python.org‘, ‘spam‘: 0, ‘title‘: ‘Python Web Site‘}
>>> d.popitem()
(‘url‘, ‘http://www.python.org‘)
>>> d
{‘spam‘: 0, ‘title‘: ‘Python Web Site‘}
出栈和列表和类似，但是没有append。
-＊setdefault：设置默认值。
>>> d = {}
>>> d.setdefault(‘name‘, ‘N/A‘)
‘N/A‘
>>> d
{‘name‘: ‘N/A‘}
>>> d[‘name‘] = ‘Gumby‘
>>> d.setdefault(‘name‘, ‘N/A‘)
‘Gumby‘
>>> d
{‘name‘: ‘Gumby‘}
默认值的默认值为None。
>>> d = {}
>>> print d.setdefault(‘name‘)
None
>>> d
{‘name‘: None}
-＊更新：update
>>> d = {
‘title‘: ‘Python Web Site‘,
‘url‘: ‘http://www.python.org‘,
‘changed‘: ‘Mar 14 22:09:15 MET 2008‘
}
>>> x = {‘title‘: ‘Python Language Website‘}
>>> d.update(x)
>>> d
{‘url‘: ‘http://www.python.org‘, ‘changed‘:
‘Mar 14 22:09:15 MET 2008‘, ‘title‘: ‘Python Language Website‘}
-＊取值：values and itervalues
>>> d = {}
>>> d[1] = 1
>>> d[2] = 2
>>> d[3] = 3
>>> d[4] = 1
>>> d.values()
[1, 2, 3, 1]
＊实例：
存储个人的电话和地址的脚本：
# A simple database
# A dictionary with person names as keys. Each person is represented as
# another dictionary with the keys ‘phone‘ and ‘addr‘ referring to their phone
# number and address, respectively.
people = {
‘Alice‘: {
‘phone‘: ‘2341‘,
‘addr‘: ‘Foo drive 23‘
},
‘Beth‘: {
‘phone‘: ‘9102‘,
‘addr‘: ‘Bar street 42‘
},
‘Cecil‘: {
‘phone‘: ‘3158‘,
‘addr‘: ‘Baz avenue 90‘
}
}
# Descriptive labels for the phone number and address. These will be used
# when printing the output.
labels = {
‘phone‘: ‘phone number‘,
‘addr‘: ‘address‘
}
name = raw_input(‘Name: ‘)
# Are we looking for a phone number or an address?
request = raw_input(‘Phone number (p) or address (a)? ‘)
# Use the correct key:
if request == ‘p‘: key = ‘phone‘
if request == ‘a‘: key = ‘addr‘
# Only try to print information if the name is a valid key in
# our dictionary:
if name in people: print "%s‘s %s is %s." % \
(name, labels[key], people[name][key])
将上述例子改为getkey
# A simple database
# A dictionary with person names as keys. Each person is represented as
# another dictionary with the keys ‘phone‘ and ‘addr‘ referring to their phone
# number and address, respectively.
people = {
‘Alice‘: {
‘phone‘: ‘2341‘,
‘addr‘: ‘Foo drive 23‘
},
‘Beth‘: {
‘phone‘: ‘9102‘,
‘addr‘: ‘Bar street 42‘
},
‘Cecil‘: {
‘phone‘: ‘3158‘,
‘addr‘: ‘Baz avenue 90‘
}
}
labels = {
‘phone‘: ‘phone number‘,
‘addr‘: ‘address‘
}
name = raw_input(‘Name: ‘)
# Are we looking for a phone number or an address?
request = raw_input(‘Phone number (p) or address (a)? ‘)
# Use the correct key:
key = request # In case the request is neither ‘p‘ nor ‘a‘
if request == ‘p‘: key = ‘phone‘
if request == ‘a‘: key = ‘addr‘
# Use get to provide default values:
person = people.get(name, {})
label = labels.get(key, key)
result = person.get(key, ‘not available‘)
print "%s‘s %s is %s." % (name, label, result)