从dict python获取与格式匹配的键字符串

Question

我的单子上有下列词典。你知道吗

[OrderedDict([('Employee Number', '1'), ('Employee Name', 'Ms. A'), ('RMG SPOC', 'X'), ('Total Experience (yrs)', '3.06'), ('Days Unallocated', '18'), ('Skill Details', 'Manual testing'), ('Contact Number', '1234')]), OrderedDict([('Employee Number', '2'), ('Employee Name', 'Mr. B'), ('RMG SPOC', 'Y'), ('Total Experience (yrs)', '2.51'), ('Days Unallocated', '28'), ('Skill Details', 'Manual Testing'), ('Contact Number', '2345')]), OrderedDict([('Employee Number', '3'), ('Employee Name', 'Mr. C'), ('RMG SPOC', 'Z'), ('Total Experience (yrs)', '1.86'), ('Days Unallocated', '9'), ('Skill Details', 'C++, Manual Testing, Oracle'), ('Contact Number', '4567')]), OrderedDict([('Employee Number', '4'), ('Employee Name', 'Mr. D'), ('RMG SPOC', 'xyz'), ('Total Experience (yrs)', '7.68'), ('Days Unallocated', '23'), ('Skill Details', 'Manual Testing, SQL, HCM'), ('Contact Number', '789')])]

我准备了一个字典，在上面的数据上使用for循环，将这些值推送到数据库中。你知道吗

emp_data = {"employee_name" : data['Employee Name'],
            "employee_number" : data['Employee Number'],
            "date_added" : datetime.datetime.now(),
            "rmg_spoc" : data['RMG SPOC'],
            "status" : "To be evaluated",
            "total_experience" : data['Total Experience (yrs)'],
            "days_unallocated" : data['Days Unallocated'],
            "skill_details" : data['Skill Details'],
            "contact_number" : data['Contact Number'],
            "reviewer" : "To be assigned",
            "comments" : "To be added"}

我从excel/csv获取原始数据。只要键与提供的excel/csv中的数据匹配，就可以正常工作。你知道吗

如果excel/csv将“Employee Name”作为“Employee Name”或“Employee Name”，则上述方法将不起作用。你知道吗

有没有一种方法可以处理这个问题，比如像“employee name”这样的键被映射到匹配任何格式（'employee name'、'employee name'、'employee name'）的值，匹配任何格式（'rmg'、'rmg'、'rmg spoc'、'rmg spoc'、'rmg*'）的“rmg\u spoc”，匹配任何格式（'total experience'）的“total\u experience”，'总经验'，'*[E][E]experience*'）。你知道吗

Answer 1

@C.Nivs是正确的，下面是一个代码片段，展示了它是如何工作的。你知道吗

options = ('Employee Number','EMPLOYEE NUMBER','employee number')

for option in options:
  assert option.strip().lower() == "employee number"
  print("true")

Answer 2

先规范化输入中的键怎么样？-也许下面这样做可以：

normalized_data = [{key.lower().replace(' ', '_'): val for key, val in datum.items()} for datum in data]

对于示例数据，您将获得：

[{'employee_number': '1', 'employee_name': 'Ms. A', 'rmg_spoc': 'X', 'total_experience_(yrs)': '3.06', 'days_unallocated': '18', 'skill_details': 'Manual testing', 'contact_number': '1234'},
 {'employee_number': '2', 'employee_name': 'Mr. B', 'rmg_spoc': 'Y', 'total_experience_(yrs)': '2.51', 'days_unallocated': '28', 'skill_details': 'Manual Testing', 'contact_number': '2345'},
 {'employee_number': '3', 'employee_name': 'Mr. C', 'rmg_spoc': 'Z', 'total_experience_(yrs)': '1.86', 'days_unallocated': '9', 'skill_details': 'C++, Manual Testing, Oracle', 'contact_number': '4567'},
 {'employee_number': '4', 'employee_name': 'Mr. D', 'rmg_spoc': 'xyz', 'total_experience_(yrs)': '7.68', 'days_unallocated': '23', 'skill_details': 'Manual Testing, SQL, HCM', 'contact_number': '789'}]

Answer 3

这似乎是不区分大小写的字典搜索（This SO question and all its duplicates）的重复问题的一个例子

post建议的解决方案是使用包装器来dict（或收藏.订购信息)像这样：

import collections

class CaseInsensitiveDict(collections.Mapping):
    def __init__(self, d):
        self._d = d
        self._s = dict((k.lower(), k) for k in d)
    def __contains__(self, k):
        return k.lower() in self._s
    def __len__(self):
        return len(self._s)
    def __iter__(self):
        return iter(self._s)
    def __getitem__(self, k):
        return self._d[self._s[k.lower()]]
    def actual_key_case(self, k):
        return self._s.get(k.lower())

在代码中，您只需使用此包装器包装dict，以便执行不区分大小写的键搜索：

data_items = [OrderedDict([('Employee Number', '1'), ('Employee Name', 'Ms. A'), ('RMG SPOC', 'X'), ('Total Experience (yrs)', '3.06'), ('Days Unallocated', '18'), ('Skill Details', 'Manual testing'), ('Contact Number', '1234')]), OrderedDict([('Employee Number', '2'), ('Employee Name', 'Mr. B'), ('RMG SPOC', 'Y'), ('Total Experience (yrs)', '2.51'), ('Days Unallocated', '28'), ('Skill Details', 'Manual Testing'), ('Contact Number', '2345')]), OrderedDict([('Employee Number', '3'), ('Employee Name', 'Mr. C'), ('RMG SPOC', 'Z'), ('Total Experience (yrs)', '1.86'), ('Days Unallocated', '9'), ('Skill Details', 'C++, Manual Testing, Oracle'), ('Contact Number', '4567')]), OrderedDict([('Employee Number', '4'), ('Employee Name', 'Mr. D'), ('RMG SPOC', 'xyz'), ('Total Experience (yrs)', '7.68'), ('Days Unallocated', '23'), ('Skill Details', 'Manual Testing, SQL, HCM'), ('Contact Number', '789')])]


data = CaseInsensitiveDict(data[0])

print(data['EmplOYee NAME'])
# should print 'Ms. A'
print(data['Employee NAME'])
# should print 'Ms. A'
print(data['EmploYee NAME'])
# should print 'Ms. A'
print(data['EmployeE NAME'])
# should print 'Ms. A'
print(data['Employee Name'])
# should print 'Ms. A'