def get_new_resolved_trends():
with open("data/trends.json", "r") as trends_file:
trends = json.load(trends_file)
trends_file.close()
new_findings = trends["results"]["New"]["buckets"]
resolved_findings = trends["results"]["Resolved"]["buckets"]
result = []
trend_month = []
data = []
for findings in new_findings:
parse_date = parsers.datetime(findings).date().month
trend_month.append(calendar.month_abbr[parse_date])
if ("count" in new_findings[findings]):
data.append(new_findings[findings]["count"])
else:
data.append(0)
result.append(data)
data = []
for findings in resolved_findings:
if ("count" in resolved_findings[findings]):
data.append(resolved_findings[findings]["count"])
else:
data.append(0)
result.append(data)
return result, trend_month
def test_datetime():
assert parsers.datetime('2007-04-05T14:30') == datetime_(2007, 4, 5, 14, 30, tzinfo=utc)
assert parsers.datetime('2007-08-09T12:30Z') == datetime_(2007, 8, 9, 12, 30, tzinfo=utc)
assert parsers.datetime('2007-01-01T24:00:00') == datetime_(2007, 1, 2, 0, 0, 0, tzinfo=utc)
assert parsers.datetime('2007-01-01T24:00:00') == parsers.datetime('2007-01-02T00:00:00')
assert parsers.datetime('2007-08-09T12:30-02:00') == datetime_(2007, 8, 9, 12, 30,
tzinfo=-timezone(hours=2, minutes=0))
with pytest.raises(ValueError):
parsers.datetime('invalid')
def lambda_handler(event, context='payments'):
dataset_bearer_token = os.getenv('DATASET_BEARER_TOKEN', '')
sumo_access_id = os.getenv('SUMO_ACCESS_ID', '')
sumo_access_key = os.getenv('SUMO_ACCESS_KEY', '')
env_vars_are_encrypted = os.getenv('ENCRYPTED', 'false')
if env_vars_are_encrypted == 'true':
dataset_bearer_token = boto3.client('kms').decrypt(
CiphertextBlob=b64decode(dataset_bearer_token))['Plaintext']
sumo_access_id = boto3.client('kms').decrypt(
CiphertextBlob=b64decode(sumo_access_id))['Plaintext']
sumo_access_key = boto3.client('kms').decrypt(
CiphertextBlob=b64decode(sumo_access_key))['Plaintext']
headers = {
'Authorization': 'Bearer {0}'.format(dataset_bearer_token),
'Accept': 'application/json',
'Content-Type': 'application/json'
}
trigger_time_of_cloudwatch_event = event['time']
current_day_time = parsers.datetime(trigger_time_of_cloudwatch_event)
sumo = pay_sumo.query_transaction_value_and_volume(sumo_access_id,
sumo_access_key,
current_day_time)
midnight_iso_date = current_day_time.replace(
hour=0, minute=0, second=0, microsecond=0,
tzinfo=SimpleUtc()).isoformat()
payload = generate_payload(midnight_iso_date, 'govuk-pay', 'day',
sumo.total_amount_paid(), sumo.payment_volume(),
sumo.average_amount_paid())
print payload
resp = requests.post(URL.substitute(context=context),
json=payload,
headers=headers)
if resp.status_code != 200:
# This means something went wrong.
print '{0}'.format(resp.status_code)
print resp.json()
def get_open_findings_trends():
with open("data/trends.json", "r") as trends_file:
trends = json.load(trends_file)
trends_file.close()
open_findings = trends["results"]["Open"]["buckets"]
result = []
trend_month = []
data = []
for findings in open_findings:
parse_date = parsers.datetime(findings).date().month
trend_month.append(calendar.month_abbr[parse_date])
data.append(open_findings[findings]["count"])
result.append(data)
return result, trend_month
def parseXML(filename):
# the prefix is the name of your file without the extention
# example: sample_file1
file_prefix = filename[:-4]
handler = open(filename).read()
soup = Soup(handler, "lxml")
# creates an interable results set of worksheets
worksheet = soup.findAll('worksheet')
print(len(worksheet))
# iterate through each worksheet, get name, start writer
for ws in worksheet:
ws_name = dict(ws.attrs)['ss:name']
writer = csv.writer(open(file_prefix + "_" + ws_name + ".csv", 'w'))
print("processing ", file_prefix + "_" + ws_name + "as a csv file...")
columns = int(dict(ws.find('table').attrs)['ss:expandedcolumncount'])
this_rec = []
for record in ws.findAll("data"):
rec_attrs = dict(record.attrs)
if len(record.contents) == 0:
this_rec.append('')
else:
if rec_attrs['ss:type'] == "Number":
this_rec.append(float(record.contents[0]))
if rec_attrs['ss:type'] == "DateTime":
this_rec.append(parsers.datetime(record.contents[0]))
if rec_attrs['ss:type'] == "String":
this_rec.append(record.contents[0])
# if the list is the right length, write the row to the file
if len(this_rec) == columns:
writer.writerow(this_rec)
this_rec = []