python 数据字典应用
一、什么是字典?
字典是Python语言中唯一的映射类型。
映射类型对象里哈希值(键,key)和指向的对象(值,value)是一对多的的关系,通常被认为是可变的哈希表。
字典对象是可变的,它是一个容器类型,能存储任意个数的Python对象,其中也可包括其他容器类型。
字典类型与序列类型的区别:
1.存取和访问数据的方式不同。
2.序列类型只用数字类型的键(从序列的开始按数值顺序索引);
3.映射类型可以用其他对象类型作键(如:数字、字符串、元祖,一般用字符串作键),和序列类型的键不同,映射类型的键直4.接或间接地和存储数据值相关联。
5.映射类型中的数据是无序排列的。这和序列类型是不一样的,序列类型是以数值序排列的。
6.映射类型用键直接“映射”到值。
字典是Python中最强大的数据类型之一。
二、如何创建字典和给字典赋值
简单地说字典就是用大括号包裹的键值对的集合。(键值对也被称作项)
一般形式:
id_db = {'wang':{
'name':"delong",
'age':31,
"addr":'juye'},
'liu':{
'name':"jun",
'age':42,
"addr":'shanghai'},
'wan':{
'name':"li",
'age':18,
"addr":'biyang'}, }
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" alt="" width="420" height="252" />
特点:
1、键与值用冒号“:”分开;
2、项与项用逗号“,”分开;
3、字典中的键必须是唯一的,而值可以不唯一。
三、字典的基本操作
1、如何访问字典中的值?
adict[key] 形式返回键key对应的值value,如果key不在字典中会引发一个KeyError。
2、如何检查key是否在字典中?
a、has_key()方法 形如:adict.haskey(‘name') 有–>True,无–>False
b、in 、not in 形如:'name' in adict 有–>True,无–>False
3、如何更新字典?
a、添加一个数据项(新元素)或键值对
adict[new_key] = value 形式添加一个项
b、更新一个数据项(元素)或键值对
adict[old_key] = new_value
c、删除一个数据项(元素)或键值对
del adict[key] 删除键key的项 / del adict 删除整个字典
adict.pop(key) 删除键key的项并返回key对应的 value值
四、映射类型操作符
标准类型操作符(+,-,*,<,>,<=,>=,==,!=,and,or, not)
a、字典不支持拼接和重复操作符(+,*)
b、字典的比较操作
先比较字典的长度也就是字典的元素个数
键比较
值比较
五、映射相关的函数
1、len() 返回字典的长度
2、hash() 返回对象的哈希值,可以用来判断一个对象能否用来作为字典的键
3、dict() 工厂函数,用来创建字典
六、字典的方法
1、adict.keys() 返回一个包含字典所有KEY的列表;
2、adict.values() 返回一个包含字典所有value的列表;
3、adict.items() 返回一个包含所有(键,值)元祖的列表;
4、adict.clear() 删除字典中的所有项或元素;
5、adict.copy() 返回一个字典浅拷贝的副本;
6、adict.fromkeys(seq, val=None) 创建并返回一个新字典,以seq中的元素做该字典的键,val做该字典中所有键对应的初始值(默认为None);
7、adict.get(key, default = None) 返回字典中key对应的值,若key不存在字典中,则返回default的值(default默认为None);
8、adict.has_key(key) 如果key在字典中,返回True,否则返回False。 现在用 in 、 not in;
9、adict.iteritems()、adict.iterkeys()、adict.itervalues() 与它们对应的非迭代方法一样,不同的是它们返回一个迭代子,而不是一个列表;
10、adict.pop(key[,default]) 和get方法相似。如果字典中存在key,删除并返回key对应的vuale;如果key不存在,且没有给出default的值,则引发keyerror异常;
11、adict.setdefault(key, default=None) 和set()方法相似,但如果字典中不存在Key键,由 adict[key] = default 为它赋值;
12、adict.update(bdict) 将字典bdict的键值对添加到字典adict中。
七、字典的遍历
1、遍历字典的key(键)
for key in adict.keys():print key
2、遍历字典的value(值)
for value in adict.values(): print value
3、遍历字典的项(元素)
for item in adict.items():print item
4、遍历字典的key-value
for item,value in adict.items(): print ‘key=%s, value=%s' %(item, value) 或 for item,value in adict.iteritems(): print ‘key=%s, value=%s' %(item, value)
注意:for item,value in adict.items(): print ‘key=%s', ‘value=%s', %(item, value) 这种写法是错误的
八、使用字典的注意事项
1、不能允许一键对应多个值;
2、键必须是可哈希的。
具体的应用实例:
#获取字典,数据字典有天然去重的功能,字典是无序的。
id_db = {'wang':{
'name':"delong",
'age':31,
"addr":'juye'},
'liu':{
'name':"jun",
'age':42,
"addr":'shanghai'},
'wan':{
'name':"li",
'age':18,
"addr":'biyang'}, } print(id_db)
print(id_db["wan"]) #打印一个key对应的value
id_db["wan"]["name"]="wanli" #修改一个对应的value,的值
print(id_db["wan"]) #打印一个key对应的value
id_db["wan"]["qq"]=28776 #天假一个新的。value对应的值
print(id_db["wan"]) #打印一个key对应的value
id_db["wan"].pop("age")#删除一个value的值
print(id_db["wan"])
v=id_db.get("liu") #去一个kye,对应的值
print(v)
v=id_db.get("") #去一个kye,对应的值对对对,当不存在时为None
vv =id("liu") #这样也可以,但是如果没有时会报错,建议用get方法获取
print(v)
print(id_db.keys()) #获取数据字典里面的,所有德kye,转换成列表
print(id_db.values()) #打印所有德value,转换成列表
打印效果:
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alt="" />
id_db = {'wang':{
'name':"delong",
'age':31,
"addr":'juye'},
'liu':{
'name':"jun",
'age':42,
"addr":'shanghai'},
'wan':{
'name':"li",
'age':18,
"addr":'biyang'}, }
d_db2 ={ "naem":"ddddddddd",
'wan':{ 'name':"liwan",
}
} id_db.update(d_db2) #把d_db2的内容更新到id_db里面去,如果id_db 有相同的内容会进行更细,没有回添加,注意如果有相同的key,会同步d_db2的内容 print(id_db)
print(id_db.items()) #把字典变成列表,但如果字典数据量大的时候不要做这种事情,转换很耗时间
"wang" in id_db #查看是否包含着key
print(id_db.setdefault("naem")) #如果存在就取出,不存在就添加一个key,kye的值是Noey
print(id_db.setdefault("wangdeeee")) #如果存在就取出,不存在就添加一个key,kye的值是None
print(id_db.setdefault("wangde","wdbdfbeebeb")) #如果存在就取出,不存在就添加一个key,给他附一个值values
print(dict.fromkeys([1,2,3,4,5,6,7],"dddd")) #把列表里面的按照顺序取出来,当做key,把后面的东西当做values
print(id_db.popitem()) #随机删除一个值,是随机删除没有顺序
print(id_db)
效果:
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alt="" />
循环的效果:
id_db = {'wang':{
'name':"delong",
'age':31,
"addr":'juye'},
'liu':{
'name':"jun",
'age':42,
"addr":'shanghai'},
'wan':{
'name':"li",
'age':18,
"addr":'biyang'}, }
d_db2 ={ "naem":"ddddddddd",
'wan':{ 'name':"liwan",
}
}
for k,v in id_db.items():#效率低,因为有一个转换过程,dict 转list
print(k,v)
for key in id_db: #效率高的用法
print(key,id_db[key])
for key in enumerate(id_db): #增加key序列选项,序列是下标值
print("%s:%s" % key)
效果:
aaarticlea/png;base64,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" alt="" />
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