def test_only_old_emails(self, load_file):
n = ActionNetwork()
n.load()
old_data = [{
'first_name': 'Henry',
'last_name': 'Kissinger',
'email': '*****@*****.**'
}, {
'zip': '01234',
'ward_precinct': 'MA1',
'email': '*****@*****.**',
'first_name': 'Libby',
'last_name': 'Snowflake',
'vanid': '999'
}]
# Libby Snowflake exists in the old data and the new. Expect to see her gone.
combed = n.only_email_matches(other_data=old_data)
self.assertEqual([{
'vanid': '999',
'last_name': 'Snowflake',
'zip': '01234',
'event': 'ice cream social',
'ward_precinct': 'MA1',
'first_name': 'Libby',
'email': '*****@*****.**'
}], combed)
def test_minus_old_emails(self, load_file):
n = ActionNetwork()
n.load()
old_data = [{
'first_name': 'Henry',
'last_name': 'Kissinger',
'email': '*****@*****.**'
}, {
'zip': '01234',
'ward_precinct': 'MA1',
'email': '*****@*****.**',
'first_name': 'Libby',
'last_name': 'Snowflake',
'vanid': '999'
}]
# Libby Snowflake exists in the old data and the new. Expect to see only her.
combed = n.minus_email_matches(other_data=old_data)
self.assertEqual([{
'ward_precinct': 'MA2',
'zip': '02345',
'last_name': 'Provocateur',
'vanid': '888',
'event': 'boxing match',
'email': '*****@*****.**',
'first_name': 'Agent'
}], combed)
def test_to_csv(self, load_file):
n = ActionNetwork()
n.load()
csv = n.to_csv()
self.assertEqual(
"first_name,last_name,email,zip_code,ORMA Supporter,VoterVANID,Ward/PrecinctName,Zip\r\nLibby,Snowflake,[email protected],01234,,999,MA1,\r\nAgent,Provocateur,[email protected],02345,,888,MA2,\r\n",
csv)
def test_map_row_zeropads_zip(self):
raw_row = {
'last_name': 'Snowflake',
'zip_code': '1234',
'first_name': 'Libby',
'Ward/PrecinctName': 'MA1',
'email': '*****@*****.**',
'VoterVANID': '999',
'Event': 'ice cream social'
}
n = ActionNetwork()
row = n.map_row(row=raw_row)
self.assertEqual('0' + raw_row['zip_code'], row['zip'])
def test_map_row_lowercases_event(self):
raw_row = {
'last_name': 'Snowflake',
'zip_code': '1234',
'first_name': 'Libby',
'Ward/PrecinctName': 'MA1',
'email': '*****@*****.**',
'VoterVANID': '999',
'Event': 'ICE cream social'
}
n = ActionNetwork()
row = n.map_row(row=raw_row)
self.assertEqual(raw_row['Event'].lower(), row['event'])
def test_load(self, load_file):
n = ActionNetwork()
n.load()
self.assertEqual([{
'zip': '01234',
'ward_precinct': 'MA1',
'email': '*****@*****.**',
'first_name': 'Libby',
'last_name': 'Snowflake',
'vanid': '999',
'event': 'ice cream social'
}, {
'zip': '02345',
'ward_precinct': 'MA2',
'email': '*****@*****.**',
'first_name': 'Agent',
'last_name': 'Provocateur',
'vanid': '888',
'event': 'boxing match'
}], n.rows)
def test_map_row_results(self):
raw_row = {
'last_name': 'Snowflake',
'zip_code': '1234',
'first_name': 'Libby',
'Ward/PrecinctName': 'MA1',
'email': '*****@*****.**',
'VoterVANID': '999',
'Event': 'ice cream social'
}
n = ActionNetwork()
row = n.map_row(row=raw_row)
self.assertEqual(
{
'zip': '01234',
'last_name': 'Snowflake',
'first_name': 'Libby',
'email': '*****@*****.**',
'ward_precinct': 'MA1',
'vanid': '999',
'event': 'ice cream social'
}, row)
"""
generates count of records for each "Event" type
"""
from objects.ActionNetwork import ActionNetwork
from collections import OrderedDict
import operator
a = ActionNetwork()
a.load()
events = {}
for row in a.rows:
event = str(row['event']).strip()
if event not in events:
events[event] = 0
events[event] += 1
events = OrderedDict(
sorted(events.items(), key=operator.itemgetter(1), reverse=True))
[print(row, ':', count) for row, count in events.items()]
""" takes National data and Action Network data, figures out which rows in National data have an email address not present in existing Action Network data, and creates a CSV upload """ from objects.National import National from objects.ActionNetwork import ActionNetwork # load our two data sources a = ActionNetwork() a.load() n = National() n.load() # minus email matches national_minus_email_matches = n.minus_email_matches(other_data=a.rows) # create a csv upload for action network based removing those with matching email a_upload = ActionNetwork() a_upload.feed(rows=national_minus_email_matches) print(a_upload.to_csv())