我做了一个函数,它将在字典中查找年龄并显示匹配的名字:

dictionary = {'george' : 16, 'amber' : 19}
search_age = raw_input("Provide age")
for age in dictionary.values():
    if age == search_age:
        name = dictionary[age]
        print name

我知道如何比较和查找年龄,只是不知道如何显示这个人的名字。此外,由于第5行,我得到了一个KeyError。我知道这是不正确的,但我不知道如何让它向后搜索。


当前回答

以下是我对这个问题的看法。:) 我刚刚开始学习Python,所以我称之为:

“初学者可以理解的”解决方案。

#Code without comments.

list1 = {'george':16,'amber':19, 'Garry':19}
search_age = raw_input("Provide age: ")
print
search_age = int(search_age)

listByAge = {}

for name, age in list1.items():
    if age == search_age:
        age = str(age)
        results = name + " " +age
        print results

        age2 = int(age)
        listByAge[name] = listByAge.get(name,0)+age2

print
print listByAge

.

#Code with comments.
#I've added another name with the same age to the list.
list1 = {'george':16,'amber':19, 'Garry':19}
#Original code.
search_age = raw_input("Provide age: ")
print
#Because raw_input gives a string, we need to convert it to int,
#so we can search the dictionary list with it.
search_age = int(search_age)

#Here we define another empty dictionary, to store the results in a more 
#permanent way.
listByAge = {}

#We use double variable iteration, so we get both the name and age 
#on each run of the loop.
for name, age in list1.items():
    #Here we check if the User Defined age = the age parameter 
    #for this run of the loop.
    if age == search_age:
        #Here we convert Age back to string, because we will concatenate it 
        #with the person's name. 
        age = str(age)
        #Here we concatenate.
        results = name + " " +age
        #If you want just the names and ages displayed you can delete
        #the code after "print results". If you want them stored, don't...
        print results

        #Here we create a second variable that uses the value of
        #the age for the current person in the list.
        #For example if "Anna" is "10", age2 = 10,
        #integer value which we can use in addition.
        age2 = int(age)
        #Here we use the method that checks or creates values in dictionaries.
        #We create a new entry for each name that matches the User Defined Age
        #with default value of 0, and then we add the value from age2.
        listByAge[name] = listByAge.get(name,0)+age2

#Here we print the new dictionary with the users with User Defined Age.
print
print listByAge

.

#Results
Running: *\test.py (Thu Jun 06 05:10:02 2013)

Provide age: 19

amber 19
Garry 19

{'amber': 19, 'Garry': 19}

Execution Successful!

其他回答

在我的情况下,最简单的方法是实例化字典在你的代码,然后你可以从它调用键如下

这是我们班有字典

class Config:

def local(self):
    return {
        "temp_dir": "/tmp/dirtest/",
        "devops": "Mansur",
    }

实例化你的字典

config =  vars.Config()
local_config = config.local()

最后调用你的字典键

patched = local_config.get("devops")

我意识到已经有很长一段时间了,最初的提问者可能不再需要答案,但如果您实际上可以控制这段代码,那么这些答案都不是好的答案。您只是使用了错误的数据结构。这是双向字典用例的完美说明:

>>> from collections import defaultdict, UserDict
>>> class TwoWayDict(UserDict):
...     def __init__(self, *args, **kwargs):
...         super().__init__(*args, **kwargs)
...         self.val_to_keys = defaultdict(list)
...     def __setitem__(self, key, value):
...         super().__setitem__(key, value)
...         self.val_to_keys[value].append(key)
...     def get_keys_for_val(self, value):
...         return self.val_to_keys[value]
... 
>>> d = TwoWayDict()
>>> d['a'] = 1
>>> d['b'] = 1
>>> d.get_keys_for_val(1)
['a', 'b']

为插入增加了极小的开销,但您保持了恒定的查找时间,除了现在是双向查找。不需要在每次需要时从头构造反向映射。只要在你需要的时候存储它并访问它。

此外,这些答案中有许多甚至是不正确的,因为很明显,许多人可能具有相同的年龄,但他们只返回第一个匹配的键,而不是所有的键。

这里,recover_key接受dictionary和要在dictionary中查找的值。然后循环遍历dictionary中的键,并与value的键进行比较,然后返回特定的键。

def recover_key(dicty,value):
    for a_key in dicty.keys():
        if (dicty[a_key] == value):
            return a_key

它被回答了,但它可以用一个奇特的“映射/减少”使用来完成,例如:

def find_key(value, dictionary):
    return reduce(lambda x, y: x if x is not None else y,
                  map(lambda x: x[0] if x[1] == value else None, 
                      dictionary.iteritems()))

我认为指出哪些方法是最快的,以及在什么情况下是最快的会很有趣:

以下是我在一台2012年的MacBook Pro上进行的一些测试

def method1(dict, search_age):
    for name, age in dict.iteritems():
        if age == search_age:
            return name

def method2(dict, search_age):
    return [name for name,age in dict.iteritems() if age == search_age]

def method3(dict, search_age):
    return dict.keys()[dict.values().index(search_age)]

profile.run()在每个方法上100,000次的结果:

方法1:

>>> profile.run("for i in range(0,100000): method1(dict, 16)")
     200004 function calls in 1.173 seconds

方法2:

>>> profile.run("for i in range(0,100000): method2(dict, 16)")
     200004 function calls in 1.222 seconds

方法3:

>>> profile.run("for i in range(0,100000): method3(dict, 16)")
     400004 function calls in 2.125 seconds

所以这表明,对于一个小字典,方法1是最快的。这很可能是因为它返回第一个匹配,而不是像方法2那样返回所有匹配(参见下面的注释)。


有趣的是,在我有2700个条目的字典上执行相同的测试,我得到了完全不同的结果(这次运行了10,000次):

方法1:

>>> profile.run("for i in range(0,10000): method1(UIC_CRS,'7088380')")
     20004 function calls in 2.928 seconds

方法2:

>>> profile.run("for i in range(0,10000): method2(UIC_CRS,'7088380')")
     20004 function calls in 3.872 seconds

方法3:

>>> profile.run("for i in range(0,10000): method3(UIC_CRS,'7088380')")
     40004 function calls in 1.176 seconds

这里,方法3要快得多。这表明字典的大小会影响你选择的方法。

注:

方法2返回所有名称的列表,而方法1和3只返回第一个匹配项。 我没有考虑内存使用情况。我不确定方法3是否创建了2个额外的列表(keys()和values())并将它们存储在内存中。