我正在尝试编写以下嵌套的字典列表,其中包含另一个到 csv 的字典列表。我尝试了多种方法,但无法正确编写它:
[
{
"Basic_Information_Source": [
{
"Image": "image1.png",
"Image_Format": "PNG",
"Image_Mode": "RGB",
"Image_Width": 574,
"Image_Height": 262,
"Image_Size": 277274
}
],
"Basic_Information_Destination": [
{
"Image": "image1_dst.png",
"Image_Format": "PNG",
"Image_Mode": "RGB",
"Image_Width": 574,
"Image_Height": 262,
"Image_Size": 277539
}
],
"Values": [
{
"Value1": 75.05045463635267,
"Value2": 0.006097560975609756,
"Value3": 0.045083481733371615,
"Value4": 0.008639858263904898
}
]
},
{
"Basic_Information_Source": [
{
"Image": "image2.png",
"Image_Format": "PNG",
"Image_Mode": "RGB",
"Image_Width": 1600,
"Image_Height": 1066,
"Image_Size": 1786254
}
],
"Basic_Information_Destination": [
{
"Image": "image2_dst.png",
"Image_Format": "PNG",
"Image_Mode": "RGB",
"Image_Width": 1600,
"Image_Height": 1066,
"Image_Size": 1782197
}
],
"Values": [
{
"Value1": 85.52662890580055,
"Value2": 0.0005464352720450282,
"Value3": 0.013496113910369758,
"Value4": 0.003800236380811839
}
]
}
]
我尝试使用以下代码并且它有效,但它只保存标题,然后将所有底层列表作为文本转储到 csv 文件中:
import json
import csv
def Convert_CSV():
ar_enc_file = open('analysis_results_enc.json','r')
json_data = json.load(ar_enc_file)
keys = json_data[0].keys()
with open('test.csv', 'w', encoding='utf8', newline='') as output_file:
dict_writer = csv.DictWriter(output_file, keys)
dict_writer.writeheader()
dict_writer.writerows(json_data)
ar_enc_file.close()
Convert_CSV()
输出写入以下标题:
然后它将每个标头中的所有其他数据转储为如下列表:
[{'Image': 'image1.png', 'Image_Format': 'PNG', 'Image_Mode': 'RGB', 'Image_Width': 574, 'Image_Height': 262, 'Image_Size': 277274}]
尝试为字典数组中的每个字典生成上述类型的输出。
怎么写才合适?
答案 0 :(得分:1)
我相信有人会提出更优雅的解决方案。话虽如此:
您遇到了一些问题。
list
。DictWriter
AFAIK 期望它是 [{'column': 'entry'},{'column': 'entry'}
格式的数据,因此即使您执行了前面的所有步骤,您仍然没有采用正确的格式。那么让我们开始吧。
对于前两部分,我们可以结合起来。
def pad_list(lst, size, padding=None):
# we wouldn't have to make a copy but I prefer to
# avoid the possibility of getting bitten by mutability
_lst = lst[:]
for _ in range(len(lst), size):
_lst.append(padding)
return _lst
# this expects already parsed json data
def flatten(json_data):
lst = []
for dct in json_data:
# here we're just setting a max size of all dict entries
# this is in case the shorter entry is in the first iteration
max_size = 0
# we initialize a dict for each of the list entries
# this is in case you have inconsistent lengths between lists
flattened = dict()
for k, v in dct.items():
entries = list(next(iter(v), dict()).values())
flattened[k] = entries
max_size = max(len(entries), max_size)
# here we append the padded version of the keys for the dict
lst.append({k: pad_list(v, max_size) for k, v in flattened.items()})
return lst
所以现在我们有一个扁平的 dict
列表,其值是具有一致长度的 list
。本质上:
[
{
"Basic_Information_Source": [
"image1.png",
"PNG",
"RGB",
574,
262,
277274
],
"Basic_Information_Destination": [
"image1_dst.png",
"PNG",
"RGB",
574,
262,
277539
],
"Values": [
75.05045463635267,
0.006097560975609756,
0.045083481733371615,
0.008639858263904898,
None,
None
]
}
]
但是这个 list
有多个 dict
需要合并,而不是一个。
所以我们需要合并。
# this should be self explanatory
def merge(flattened):
merged = dict()
for dct in flattened:
for k, v in dct.items():
if k not in merged:
merged[k] = []
merged[k].extend(v)
return merged
这给了我们一些接近于此的东西:
{
"Basic_Information_Source": [
"image1.png",
"PNG",
"RGB",
574,
262,
277274,
"image2.png",
"PNG",
"RGB",
1600,
1066,
1786254
],
"Basic_Information_Destination": [
"image1_dst.png",
"PNG",
"RGB",
574,
262,
277539,
"image2_dst.png",
"PNG",
"RGB",
1600,
1066,
1782197
],
"Values": [
75.05045463635267,
0.006097560975609756,
0.045083481733371615,
0.008639858263904898,
None,
None,
85.52662890580055,
0.0005464352720450282,
0.013496113910369758,
0.003800236380811839,
None,
None
]
}
但是等等,我们仍然需要为作者格式化它。
我们的数据需要采用 [{'column_1': 'entry', column_2: 'entry'},{'column_1': 'entry', column_2: 'entry'}
所以我们格式化:
def format_for_writer(merged):
formatted = []
for k, v in merged.items():
for i, item in enumerate(v):
# on the first pass this will append an empty dict
# on subsequent passes it will be ignored
# and add keys into the existing dict
if i >= len(formatted):
formatted.append(dict())
formatted[i][k] = item
return formatted
最后,我们有一个漂亮干净的格式化数据结构,我们可以将其交给我们的 writer 函数。
def convert_csv(formatted):
keys = formatted[0].keys()
with open('test.csv', 'w', encoding='utf8', newline='') as output_file:
dict_writer = csv.DictWriter(output_file, keys)
dict_writer.writeheader()
dict_writer.writerows(formatted)
带有 json
字符串的完整代码:
import json
import csv
json_raw = """\
[
{
"Basic_Information_Source": [
{
"Image": "image1.png",
"Image_Format": "PNG",
"Image_Mode": "RGB",
"Image_Width": 574,
"Image_Height": 262,
"Image_Size": 277274
}
],
"Basic_Information_Destination": [
{
"Image": "image1_dst.png",
"Image_Format": "PNG",
"Image_Mode": "RGB",
"Image_Width": 574,
"Image_Height": 262,
"Image_Size": 277539
}
],
"Values": [
{
"Value1": 75.05045463635267,
"Value2": 0.006097560975609756,
"Value3": 0.045083481733371615,
"Value4": 0.008639858263904898
}
]
},
{
"Basic_Information_Source": [
{
"Image": "image2.png",
"Image_Format": "PNG",
"Image_Mode": "RGB",
"Image_Width": 1600,
"Image_Height": 1066,
"Image_Size": 1786254
}
],
"Basic_Information_Destination": [
{
"Image": "image2_dst.png",
"Image_Format": "PNG",
"Image_Mode": "RGB",
"Image_Width": 1600,
"Image_Height": 1066,
"Image_Size": 1782197
}
],
"Values": [
{
"Value1": 85.52662890580055,
"Value2": 0.0005464352720450282,
"Value3": 0.013496113910369758,
"Value4": 0.003800236380811839
}
]
}
]
"""
def pad_list(lst, size, padding=None):
_lst = lst[:]
for _ in range(len(lst), size):
_lst.append(padding)
return _lst
def flatten(json_data):
lst = []
for dct in json_data:
max_size = 0
flattened = dict()
for k, v in dct.items():
entries = list(next(iter(v), dict()).values())
flattened[k] = entries
max_size = max(len(entries), max_size)
lst.append({k: pad_list(v, max_size) for k, v in flattened.items()})
return lst
def merge(flattened):
merged = dict()
for dct in flattened:
for k, v in dct.items():
if k not in merged:
merged[k] = []
merged[k].extend(v)
return merged
def format_for_writer(merged):
formatted = []
for k, v in merged.items():
for i, item in enumerate(v):
if i >= len(formatted):
formatted.append(dict())
formatted[i][k] = item
return formatted
def convert_csv(formatted):
keys = formatted[0].keys()
with open('test.csv', 'w', encoding='utf8', newline='') as output_file:
dict_writer = csv.DictWriter(output_file, keys)
dict_writer.writeheader()
dict_writer.writerows(formatted)
def main():
json_data = json.loads(json_raw)
flattened = flatten(json_data)
merged = merge(flattened)
formatted = format_for_writer(merged)
convert_csv(formatted)
if __name__ == '__main__':
main()