def lambda_handler(event, context):
query_cmd = "select count(*) from prediction"
conn = make_conn()
cur = conn.cursor()
lastUpdateDate = list(
fetch_data(
conn,
"""SELECT submission_date from prediction ORDER BY submission_date DESC Limit 1"""
)[0])[0]
cur.execute("""SELECT * from prediction WHERE submission_date = '%s';""" %
(lastUpdateDate))
rawData = cur.fetchall()
arrAverage = []
for data in rawData:
json_data = list(data)
arrAverage.append({
'year': json_data[0][u'year'],
'debt': json_data[1]
})
conn.close()
return json.dumps({'averages': arrAverage})
def getformname(custid):
conn = make_conn()
query_cmd = "select TemplateName, TemplateMasterID from TemplateMaster where UserID = " \
"" + str(custid) + ';'
result = fetch_data(conn, query_cmd)
conn.close()
return result
def getformdata(formid):
conn = make_conn()
query_cmd = "select FieldMaster.FieldName, FieldDetails.FieldValue from FieldDetails " \
"INNER JOIN FieldMaster ON FieldMaster.FieldMasterID = FieldDetails.FieldMasterID " \
"WHERE FieldDetails.TemplateCustomerMappingID = " + str(formid) + ";"
result = fetch_data(conn, query_cmd)
conn.close()
return result
def getformfields(formnumber):
conn = make_conn()
query_cmd = "select FieldMasterID, FieldName from FieldMaster where TemplateMasterID" \
" = " + str(formnumber) + ";"
# query_cmd = "select FieldMasterID, FieldName from FieldMaster where TemplateMasterID = 1;"
result = fetch_data(conn, query_cmd)
conn.close()
return result
def lambda_handler(event, context):
averageObj = []
query_cmd = "select count(*) from prediction"
conn = make_conn()
cur = conn.cursor()
events = fetch_data(conn, """SELECT event from prediction""")
dicAverage = {}
for data in events:
json_dict = list(data)[0]
if str(json_dict[u'year']) in dicAverage.keys():
dicAverage[str(json_dict[u'year'])].append(json_dict[u'debt'])
else:
dicAverage[str(json_dict[u'year'])] = [json_dict[u'debt']]
submission_date = datetime.datetime.now()
print("---> submission date\n", submission_date, "\n")
averages = {}
for data in event['data']:
def sum_list(items):
sum_numbers = 0
for x in items:
sum_numbers += x
return sum_numbers
average = data['debt']
if dicAverage.get(str(data['year'])) is not None:
prev_debts = dicAverage[str(data['year'])]
average = (sum_list(prev_debts) +
data['debt']) / (len(prev_debts) + 1)
averages[str(data['year'])] = average
cur.execute(
"""INSERT INTO prediction (event, submission_date, average) VALUES (%s::json, %s, %s);""",
(json.dumps(data), submission_date, average))
conn.commit()
conn.close()
return {
'statusCode': 200,
'headers': {
'Content-Type': 'application/json'
},
'body': averages
}