Maps hierarchical dictionaries to flat structures
Project description
dictmapper was created to help transforming a sequence of python dictionaries to tabular format and specifically to transform json documents to be exported in csv fromat.
Usage
Create a mapper:
from dictmapper import Mapper, Mapping class UserMapper(Mapper): user_id = Mapping('user_id') email = Mapping('email') Name = Mapping(lambda u: '%s %s' % (u['first_name'], u['last_name']), name='User Name') nickname = Mapping('nickname', default='N/A') street = Mapping('address/street') city = Mapping('address/city') joined_at = Mapping('joined_at', transform=lambda d: d.strftime('%Y-%m-%d'))
Sample input:
users_docs = [ { 'user_id': '1000001', 'first_name': 'Test', 'last_name': 'User', 'email': 'user@test.com', 'address': { 'street': 'Example Road', 'city': 'Emerald City', }, 'joined_at': datetime.now(), }, { 'user_id': '1000002', 'first_name': 'Example', 'last_name': 'Member', 'nickname': 'exampy', 'email': 'example@member.com', 'address': { 'street': 'Sample Road', 'city': 'Emerald City', }, 'joined_at': datetime.now(), } ]
Output:
>>> mapper = UserMapper() >>> mapper.headers() ['User id', 'Email', 'Name', 'Nickname', 'Street', 'City', 'Joined at'] >>> res = mapper.map(users_docs) >>> res [['1000001', 'user@test.com', 'Test User', 'N/A', 'Example Road', 'Emerald City', '2012-03-18'], ['1000002', 'example@member.com', 'Example Member', 'exampy', 'Sample Road', 'Emerald City', '2012-03-18']]
Export to csv
I recommend using the excellent tablib:
import tablib data = tablib.Dataset(*res, headers=mapper.headers()) data.csv
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