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dictmapper /

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dictmapper

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