我正在尝试从我的csv文件构建一个分层的dict(请参阅下面我想要的输出)。
以下是我的代码到目前为止,我正在搜索itertools
,我认为这是我完成此任务所需的最佳工具。我无法使用pandas
。我想我可能需要将密钥的值放入一个新的字典中,然后尝试映射策略接口并构建一个新的dict
?
import csv
import pprint
from itertools import groupby
new_dict=[]
with open("test_.csv", "rb") as file_data:
reader = csv.DictReader(file_data)
for keys, grouping in groupby(reader, lambda x: x['groupA_policy']):
new_dict.append(list(grouping))
pprint.pprint(new_dict)
我的csv文件如下所示:
GroupA_Host,groupA_policy,groupA_policy_interface,GroupB_Host,GroupB_policy,GroupB_policy_interface
host1,policy10,eth0,host_R,policy90,eth9
host1,policy10,eth0.1,host_R,policy90,eth9.1
host2,policy20,eth2,host_Q,policy80,eth8
host2,policy20,eth2.1,host_Q,policy80,eth8.1
我想要实现的所需输出是:
[{'GroupA_Host': 'host1',
'GroupB_Host': 'host_R',
'GroupB_policy': 'policy90',
'groupA_policy': 'policy10',
'interfaces': [{'GroupB_policy_interface': 'eth9',
'group_a_policy_interfaces': 'eth0'},
{'GroupB_policy_interface': 'eth9.1',
'group_a_policy_interface': 'eth0.1'}]},
{'GroupA_host': 'host2',
'GroupB_Host': 'host_Q',
'GroupB_policy': 'policy80',
'groupA_policy': 'policy20',
'interfaces': [{'GroupB_policy_interface': 'eth8',
'groupA_policy_interfaces': 'eth2'},
{'groupA_policy_interface': 'eth8.1',
'groupA_policy_interfaces': 'eth2.1'}]}]
答案 0 :(得分:0)
我认为这里不需要itertools。重要的是要认识到你正在使用('GroupA_Host', 'GroupB_Host', 'groupA_policy', 'GroupB_policy')
作为分组的关键 - 所以你可以使用字典来收集键上这个键的接口:
d = {}
for row in reader:
key = row['GroupA_Host'], row['GroupB_Host'], row['groupA_policy'], row['GroupB_policy']
interface = {'groupA_policy_interface': row['groupA_policy_interface'],
'GroupB_policy_interface': row['GroupB_policy_interface']
}
if key in d:
d[key].append(interface)
else:
d[key] = [interface]
as_list = []
for key, interfaces in d.iteritems():
record = {}
record['GroupA_Host'] = key[0]
record['GroupB_Host'] = key[1]
record['groupA_policy'] = key[2]
record['GroupB_policy'] = key[3]
record['interfaces'] = interfaces
as_list.append(record)