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KIVA_SNAPSHOT_URL = 'http://s3.kiva.org/snapshots/kiva_ds_json.zip' | |
PRUNE_FIELDS = ['terms', 'payments', 'basket_amount', 'description', 'name', | |
'borrowers', 'translator', 'video', 'image', | |
'funded_date', 'paid_date', 'paid_amount', 'funded_amount', | |
'planned_expiration_date', 'bonus_credit_eligibility', | |
'partner_id'] | |
KEYS = ['sector', 'use', 'posted_date', 'location.country', | |
'journal_totals.entries', 'activity', | |
'loan_amount', 'status', 'lender_count'] | |
INPUT_FIELD_IDS = ['000000', # sector | |
'000001', # use | |
'000003', # location.country | |
'000004', # journal_totals.entries | |
'000005', # activity | |
'000006', # loan_amount | |
'000008', # lender_count | |
'000002-0', | |
'000002-1', | |
'000002-2', | |
'000002-3', | |
# posted-date.{year,month,day-of-month,day-of-week,'hour'} | |
'000002-4'] | |
EXCLUDED_FIELD_IDS = ['000002', '000002-5', '000002-6'] | |
OBJECTIVE_FIELD_ID = '000007' # status | |
if __name__ == '__main__': | |
api = BigML() | |
datasets = api.list_datasets("name=kiva-data;order_by=created")['objects'] | |
if len(datasets) == 0: | |
# no pre-existing data, create from Kiva snapshot | |
# download kiva snapshot to tmp file | |
make_ds_from_snapshot() | |
else: | |
# find date of most recent BigML dataset | |
last_date = dateutil.parser.parse( | |
datasets[0]['created']).replace(tzinfo=dateutil.tz.tzutc()) | |
# use kiva api to grab new loan data | |
make_ds_from_api(last_date) | |
print 'building model' | |
datasets = api.list_datasets("name=kiva-data;order_by=created")['objects'] | |
model = api.create_model([obj['resource'] for obj in datasets], | |
{'name': 'kiva-model', | |
'objective_field': OBJECTIVE_FIELD_ID, | |
'input_fields': INPUT_FIELD_IDS, | |
'excluded_fields': EXCLUDED_FIELD_IDS, | |
'balance_objective': True}) | |
print 'Done!' |
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