基于python中嵌套的多个条件过滤Json数组（没有根节点名称）

Question

我正在尝试根据多个条件使用 Python 过滤 Json 数组。我的 Json 与此类似（无根名称）：

     {           
       "id": "123455",           
       "outter": {
          "inner": [
            {
              "nox": "abc:6666",
              "code": "1329",        
            }
           ],    
        },
        "topic": {
         "reference": "excel"
        }, 
        "date1": "1990-07-28T03:52:44-04:00",
        "finalDate": "1990-07-28T03:52:44-04:00"
      }
      {           
       "id": "123435",           
       "outter": {
          "inner": [
            {
              "nox": "abc:6666",
              "code": "9351",        
            }
           ],    
        },
        "topic": {
         "reference": "excel"
        }, 
        "date1": "1990-07-28T03:52:44-04:00",
        "finalDate": "1995-07-28T03:52:44-04:00"
      }

我的目标是根据 2 个条件进行过滤并返回所有匹配的条件。

1: 外部 --> 内部 --> 代码 = 9351 AND

2：最终日期 >= 1995

到目前为止，我可以使用以下代码单独执行此检查：

   data = pd.read_json('myFile.ndjson', lines = True)

   for item in data['outter']:
      for x in item['inner']:
         if(x['code'] == '9351'):
            found....

但不确定如何同时执行这两项操作，因为我必须使用data['outter'] 或data['finalDate'] 启动循环，并且在循环内我只能看到数组的那个元素，而不是完整的数组。

感谢任何帮助，谢谢！

Answer 1

这是一种可以如上所述过滤列表的解决方案。我使用的是列表推导而不是循环，其中可能有一些可以改进的东西，但结果似乎至少符合预期。

注意：这使用了 Python 3.8 中引入的 walrus := 运算符。如果您运行的是较早的 Python 版本，您可能可以删除使用它的代码，但在这种情况下我并没有过多打扰。

from pprint import pprint


data_list = [
    {
        "id": "123455",
        "outter": {
            "inner": [
                {
                    "nox": "abc:6666",
                    "code": "1329",
                }
            ],
        },
        "topic": {
            "reference": "excel"
        },
        "date1": "1990-07-28T03:52:44-04:00",
        "finalDate": "1990-07-28T03:52:44-04:00"
    },
    {
        "id": "123435",
        "outter": {
            "inner": [
                {
                    "nox": "abc:6666",
                    "code": "9351",
                }
            ],
        },
        "topic": {
            "reference": "excel"
        },
        "date1": "1990-07-28T03:52:44-04:00",
        "finalDate": "1995-07-28T03:52:44-04:00"
    }
]

result = [d for d in data_list
          if (year := d['finalDate'][:4]).isnumeric() and year >= '1995'
          and any(str(inner['code']) == '9351'
                  for inner in d['outter']['inner'] or [])]

pprint(result)

@ted 提出了一个很好的观点，即可读性很重要，所以我有时间回过头来以典型的循环格式编写它（基本上与上面的逻辑相同）。我还有很多 cmets 希望澄清代码中发生的事情，希望对您有所帮助:-)

from pprint import pprint
from typing import Dict, List

result = []

# Looping over each dictionary in list
for d in data_list:
    # Grab the year part, first four characters of `finalDate`
    year = d['finalDate'][:4]
    # isnumeric() to confirm the year part is an an integer
    # then check if string (now confirmed to be numeric) has a higher
    # ASCII value than 1995.
    valid_year = year.isnumeric() and year >= '1995'
    # Simple, if it doesn't match our desired year then continue
    # with next loop iteration
    if not valid_year:
        continue
    # Get inner list, then loop over it
    inner_list: List[Dict] = d['outter']['inner']
    for inner in inner_list:
        if inner['code'] == '9351':
            # We found an inner with our desired code!
            break
    # The for-else syntax is pretty self-explanatory. This `else` statement is
    # only run when we don't `break` out of the loop above.
    else:
        # No break statement was run, so the desired code did not match
        # any elements. Again, continue with the next iteration.
        continue
    # At this point, we know it's valid since it matched both our
    # conditions, so we add it to the result list.
    result.append(d)

# Print the result, but it should be the same
pprint(result)

Answer 2

试试这样的..根据您的需要更改过滤器:)

for item in data:
    if item['finalDate'].startswith("1995"):
        for inner in item['outter']['inner']:
            if inner['code'] == '9351':
                print(item)