def test_filter_conversations_by_request_started_time_rejects_conversations_outside_of_range(
):
date_range = DateTimeRange(start=datetime(year=2020, month=6, day=1),
end=datetime(year=2020, month=7, day=1))
conversation_within_range = build_parsed_conversation(
request_started=build_message(
time=datetime(year=2020, month=6, day=15)))
conversation_before_range = build_parsed_conversation(
request_started=build_message(
time=datetime(year=2020, month=5, day=28)))
conversation_after_range = build_parsed_conversation(
request_started=build_message(
time=datetime(year=2020, month=7, day=28)))
parsed_conversations = [
conversation_before_range,
conversation_within_range,
conversation_after_range,
]
expected = [conversation_within_range]
actual = filter_conversations_by_request_started_time(
parsed_conversations, date_range)
assert list(actual) == expected
def test_parses_transfer_correctly_given_valid_message_list():
time_range = DateTimeRange(start=datetime(2019, 12, 1, tzinfo=UTC),
end=datetime(2020, 1, 1, tzinfo=UTC))
requesting_asid_with_transfer = "343434343434"
sending_asid_with_transfer = "111134343434"
requesting_supplier = "EMIS"
sending_supplier = "Vision"
conversation_id = "abcdefg_1234"
spine_messages = _build_successful_conversation(
conversation_id=conversation_id,
requesting_asid=requesting_asid_with_transfer,
sending_asid=sending_asid_with_transfer,
requesting_supplier=requesting_supplier,
sending_supplier=sending_supplier,
ehr_request_started_on=datetime(2019, 12, 30, 18, 2, 29, tzinfo=UTC),
ehr_request_completed_on=datetime(2019, 12, 30, 18, 3, 21, tzinfo=UTC),
ehr_request_started_acknowledged_on=datetime(2019,
12,
30,
18,
3,
23,
tzinfo=UTC),
ehr_request_completed_acknowledged_on=datetime(2020,
1,
1,
8,
41,
48,
tzinfo=UTC),
)
expected = [
Transfer(
conversation_id=conversation_id,
sla_duration=timedelta(days=1, seconds=52707),
requesting_practice_asid=requesting_asid_with_transfer,
sending_practice_asid=sending_asid_with_transfer,
requesting_supplier=requesting_supplier,
sending_supplier=sending_supplier,
status=TransferStatus.INTEGRATED,
date_requested=datetime(2019, 12, 30, 18, 2, 29, tzinfo=UTC),
date_completed=datetime(2020, 1, 1, 8, 41, 48, tzinfo=UTC),
sender_error_code=None,
final_error_code=None,
intermediate_error_codes=[],
)
]
actual = list(parse_transfers_from_messages(spine_messages, time_range))
assert actual == expected
def test_calculates_correct_national_metrics_given_series_of_messages():
sla_duration_within_3_days = timedelta(seconds=THREE_DAYS_IN_SECONDS)
sla_duration_within_8_days = timedelta(seconds=EIGHT_DAYS_IN_SECONDS)
sla_duration_beyond_8_days = timedelta(seconds=EIGHT_DAYS_IN_SECONDS + 1)
transfers = [
build_transfer(status=TransferStatus.PENDING),
build_transfer(status=TransferStatus.PENDING_WITH_ERROR),
build_transfer(status=TransferStatus.INTEGRATED,
sla_duration=sla_duration_within_3_days),
build_transfer(status=TransferStatus.INTEGRATED,
sla_duration=sla_duration_within_8_days),
build_transfer(status=TransferStatus.INTEGRATED,
sla_duration=sla_duration_within_8_days),
build_transfer(status=TransferStatus.INTEGRATED,
sla_duration=sla_duration_beyond_8_days),
build_transfer(status=TransferStatus.INTEGRATED,
sla_duration=sla_duration_beyond_8_days),
build_transfer(status=TransferStatus.INTEGRATED,
sla_duration=sla_duration_beyond_8_days),
build_transfer(status=TransferStatus.FAILED),
]
time_range = DateTimeRange(start=datetime(2019, 12, 1, tzinfo=UTC),
end=datetime(2020, 1, 1, tzinfo=UTC))
current_datetime = datetime.now(tzutc())
expected_national_metrics = MonthlyNationalMetrics(
transfer_count=9,
integrated=IntegratedMetrics(
transfer_percentage=66.67,
transfer_count=6,
within_3_days=1,
within_8_days=2,
beyond_8_days=3,
),
failed=FailedMetrics(transfer_count=1, transfer_percentage=11.11),
pending=PendingMetrics(transfer_count=2, transfer_percentage=22.22),
paper_fallback=PaperFallbackMetrics(transfer_count=6,
transfer_percentage=66.67),
year=2019,
month=12,
)
expected = NationalMetricsPresentation(generated_on=current_datetime,
metrics=[expected_national_metrics])
actual = calculate_national_metrics_data(transfers, time_range)
assert actual == expected
def test_filter_conversations_by_request_started_time_accepts_conversation_on_range_start(
):
date_range = DateTimeRange(start=datetime(year=2020, month=6, day=1),
end=datetime(year=2020, month=7, day=1))
parsed_conversations = [
build_parsed_conversation(request_started=build_message(
time=datetime(year=2020, month=6, day=1)))
]
expected = parsed_conversations
actual = filter_conversations_by_request_started_time(
parsed_conversations, date_range)
assert list(actual) == expected
def _get_time_range(year, month):
metric_month = datetime(year, month, 1, tzinfo=tzutc())
next_month = metric_month + relativedelta(months=1)
return DateTimeRange(metric_month, next_month)
EHR_REQUEST_STARTED,
EHR_REQUEST_COMPLETED,
COMMON_POINT_TO_POINT,
APPLICATION_ACK,
)
from prmdata.utils.date.range import DateTimeRange
from prmdata.utils.io.csv import read_gzip_csv_files
input_files = [
"./Jan-2021.csv.gz",
"./Feb-2021.csv.gz",
]
metric_month = datetime(2021, 1, 1, tzinfo=tzutc())
next_month = metric_month + relativedelta(months=1)
date_range = DateTimeRange(metric_month, next_month)
abbreviations = {
EHR_REQUEST_STARTED: "RQS",
EHR_REQUEST_COMPLETED: "RQC",
COMMON_POINT_TO_POINT: "P2P",
APPLICATION_ACK: "ACK"
}
def read_spine_csv_gz_files(file_paths):
items = read_gzip_csv_files(file_paths)
return construct_messages_from_splunk_items(items)
def conversation_is_started_in(conversation, date_range):
def test_calculates_correct_metrics_given_a_successful_transfer():
time_range = DateTimeRange(start=datetime(2019, 12, 1, tzinfo=UTC),
end=datetime(2020, 1, 1, tzinfo=UTC))
requesting_practice_name = "Test GP"
requesting_ods_code = "A12345"
requesting_asid_with_transfer = "343434343434"
sending_asid_with_transfer = "111134343434"
requesting_supplier = "SystemOne"
sending_supplier = "Unknown"
conversation_id = "abcdefg_1234"
transfers = [
Transfer(
conversation_id=conversation_id,
sla_duration=timedelta(days=1, seconds=52707),
requesting_practice_asid=requesting_asid_with_transfer,
sending_practice_asid=sending_asid_with_transfer,
requesting_supplier=requesting_supplier,
sending_supplier=sending_supplier,
status=TransferStatus.INTEGRATED,
date_requested=datetime(2019, 12, 30, 18, 2, 29, tzinfo=UTC),
date_completed=datetime(2020, 1, 1, 8, 41, 48, tzinfo=UTC),
sender_error_code=None,
final_error_code=None,
intermediate_error_codes=[],
)
]
practice_list = [
PracticeDetails(
asids=[requesting_asid_with_transfer],
ods_code=requesting_ods_code,
name=requesting_practice_name,
)
]
expected = PracticeMetricsPresentation(
generated_on=datetime(year=2020,
month=1,
day=15,
hour=23,
second=42,
tzinfo=UTC),
practices=[
PracticeSummary(
ods_code=requesting_ods_code,
name=requesting_practice_name,
metrics=[
MonthlyMetrics(
year=2019,
month=12,
requester=RequesterMetrics(
integrated=IntegratedPracticeMetrics(
transfer_count=1,
within_3_days_percentage=100,
within_8_days_percentage=0,
beyond_8_days_percentage=0,
), ),
)
],
)
],
)
actual = calculate_practice_metrics_data(transfers, practice_list,
time_range)
assert actual == expected
def filter_conversations_by_request_started_time(
conversations: Iterable[ParsedConversation],
time_range: DateTimeRange) -> Iterator[ParsedConversation]:
return (conversation for conversation in conversations
if time_range.contains(conversation.request_started.time))