在Python中，如何简明地获取json数据中的嵌套值? [英] In Python, how to concisely get nested values in json data?

问题描述

我从JSON加载了数据，并尝试使用列表作为输入提取任意嵌套值，其中该列表对应于连续子代的名称.我想要一个函数 get_value(data，lookup)，该函数通过将 lookup 中的每个条目视为嵌套子项，从数据中返回值.

I have data loaded from JSON and am trying to extract arbitrary nested values using a list as input, where the list corresponds to the names of successive children. I want a function get_value(data,lookup) that returns the value from data by treating each entry in lookup as a nested child.

在下面的示例中，当lookup=['alldata','TimeSeries','rates']时，返回值应为[1.3241,1.3233].

In the example below, when lookup=['alldata','TimeSeries','rates'], the return value should be [1.3241,1.3233].

json_data = {'alldata':{'name':'CAD/USD','TimeSeries':{'dates':['2018-01-01','2018-01-02'],'rates':[1.3241,1.3233]}}}

def get_value(data,lookup):
    res = data
    for item in lookup:
        res = res[item]
    return res

lookup = ['alldata','TimeSeries','rates']
get_value(json_data,lookup)

我的示例有效，但是有两个问题:

My example works, but there are two problems:

1. 这是低效-在我的 for循环中，我将整个TimeSeries对象复制到 res 中，然后才将其替换为如@Andrej Kesely所述， res 是每次迭代的参考，因此不会复制数据.
2. 不简洁-我希望能够找到一种简洁的(例如，一两行)使用列表理解语法的方式提取数据的方式

1. It's inefficient - In my for loop, I copy the whole TimeSeries object to res, only to then replace it with the rates list. As @Andrej Kesely explained, res is a reference at each iteration, so data isn't being copied.
2. It's not concise - I was hoping to be able to find a concise (eg one or two line) way of extracting the data using something like list comprehension syntax

推荐答案

如果您希望使用单行代码，并且正在使用Python 3.8，则可以使用赋值表达式("walrus operator" ):

If you want one-liner and you are using Python 3.8, you can use assignment expression ("walrus operator"):

json_data = {'alldata':{'name':'CAD/USD','TimeSeries':{'dates':['2018-01-01','2018-01-02'],'rates':[1.3241,1.3233]}}}

def get_value(data,lookup):
    return [data:=data[item] for item in lookup][-1]

lookup = ['alldata','TimeSeries','rates']
print( get_value(json_data,lookup) )

打印:

[1.3241, 1.3233]

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