def test_sponsors():
"""
Do an end-to-end sponsor check.
"""
opportunities = DataFrame({
"AccountId": ["A01", "B01", "A01", "B01", "B01"],
"Amount": [5, 20, 4, 40, 30],
"CloseDate": ['2009-01-02', '2009-01-03', '2009-01-04',
'2010-01-02', '2010-01-02'],
"RecordTypeId": ['01216000001IhIEAA0', '01216000001IhIEAA0',
'01216000001IhmxAAC', '01216000001IhmxAAC', '01216000001IhmxAAC'],
"Type": ['Standard', 'In-Kind', '', 'In-Kind', ''],
})
accounts = DataFrame({
"AccountId": ["A01", "B01"],
"Text_For_Donor_Wall__c": ["Donor A", "Donor B"],
"Website": ['http://A01.com', 'http://B01.com'],
})
expected = """{
"2009": [
{
"events_revenue": "$4",
"digital_in_kind": "$0",
"sponsor": "Donor A",
"url": "http://A01.com",
"events_in_kind": "$0",
"total": "$9",
"digital_revenue": "$5"
},
{
"events_revenue": "$0",
"digital_in_kind": "$20",
"sponsor": "Donor B",
"url": "http://B01.com",
"events_in_kind": "$0",
"total": "$20",
"digital_revenue": "$0"
}
],
"2010": [
{
"events_revenue": "$30",
"digital_in_kind": "$0",
"sponsor": "Donor B",
"url": "http://B01.com",
"events_in_kind": "$40",
"total": "$70",
"digital_revenue": "$0"
}
],
"all-time": [
{
"events_revenue": "$4",
"digital_in_kind": "$0",
"sponsor": "Donor A",
"url": "http://A01.com",
"events_in_kind": "$0",
"total": "$9",
"digital_revenue": "$5"
},
{
"events_revenue": "$30",
"digital_in_kind": "$20",
"sponsor": "Donor B",
"url": "http://B01.com",
"events_in_kind": "$40",
"total": "$90",
"digital_revenue": "$0"
}
]
}
"""
actual = convert_sponsors(opportunities=opportunities, accounts=accounts)
assert json.loads(actual) == json.loads(expected)
def test_sponsors_sort_order():
"""
Confirm that sponsors are sorted by their name, not ID.
"""
opportunities = DataFrame({
"AccountId": ["A01", "B01", "C01"],
"Amount": [20, 20, 20],
"CloseDate": ['2009-01-02', '2009-01-02', '2009-01-02'],
"RecordTypeId": ['01216000001IhIEAA0', '01216000001IhIEAA0',
'01216000001IhIEAA0'],
"Type": ['Standard', 'Standard', 'Standard'],
})
accounts = DataFrame({
"AccountId": ["A01", "B01", "C01"],
"Text_For_Donor_Wall__c": ["Donor Z", "Donor A", "Donor B"],
"Website": ['http://Z01.com', 'http://A01.com', 'http://B01.com'],
})
expected = """
{
"2009": [
{
"url": "http://A01.com",
"events_in_kind": "$0",
"digital_revenue": "$20",
"digital_in_kind": "$0",
"sponsor": "Donor A",
"events_revenue": "$0",
"total": "$20"
},
{
"url": "http://B01.com",
"events_in_kind": "$0",
"digital_revenue": "$20",
"digital_in_kind": "$0",
"sponsor": "Donor B",
"events_revenue": "$0",
"total": "$20"
},
{
"url": "http://Z01.com",
"events_in_kind": "$0",
"digital_revenue": "$20",
"digital_in_kind": "$0",
"sponsor": "Donor Z",
"events_revenue": "$0",
"total": "$20"
}
],
"all-time": [
{
"url": "http://A01.com",
"events_in_kind": "$0",
"digital_revenue": "$20",
"digital_in_kind": "$0",
"sponsor": "Donor A",
"events_revenue": "$0",
"total": "$20"
},
{
"url": "http://B01.com",
"events_in_kind": "$0",
"digital_revenue": "$20",
"digital_in_kind": "$0",
"sponsor": "Donor B",
"events_revenue": "$0",
"total": "$20"
},
{
"url": "http://Z01.com",
"events_in_kind": "$0",
"digital_revenue": "$20",
"digital_in_kind": "$0",
"sponsor": "Donor Z",
"events_revenue": "$0",
"total": "$20"
}
]
}
"""
actual = convert_sponsors(opportunities=opportunities, accounts=accounts)
assert json.loads(actual) == json.loads(expected)
sleep(3)
bulk.close_job(job)
rows = bulk.get_batch_result_iter(job, batch, parse_csv=True)
accts = DataFrame.from_dict(list(rows))
accts.rename(columns={'Id': 'AccountId'}, inplace=True)
return opps, accts
# Circles
print "Fetching Circle data..."
generate_circle_data()
# Sponsors
opps, accts = sf_data(sponsors_query)
print "Transforming and exporting to JSON..."
json_output = convert_sponsors(opportunities=opps, accounts=accts)
print "Saving sponsors to S3..."
push_to_s3(filename='sponsors.json', contents=json_output)
# Donors
opps, accounts = sf_data(donors_query)
print "Transforming and exporting to JSON..."
json_output = convert_donors(opportunities=opps, accounts=accts)
print "Saving donors to S3..."
push_to_s3(filename='donors.json', contents=json_output)
