def test_log_metric_invalid_unit(invalid_input, expected):
# GIVEN invalid units are provided
# WHEN log_metric is called
# THEN ValueError exception should be raised
with pytest.raises(expected):
log_metric(name="test_metric", **invalid_input)
def test_log_metric(capsys):
# GIVEN a service, unit and value have been provided
# WHEN log_metric is called
# THEN custom metric line should be match given values
log_metric(service="payment", name="test_metric", unit=MetricUnit.Seconds, value=60)
expected = "MONITORING|60|Seconds|test_metric|ServerlessAirline|service=payment\n"
captured = capsys.readouterr()
assert captured.out == expected
def test_log_metric_partially_correct_args(capsys, invalid_input, expected):
# GIVEN invalid arguments are provided such as empty dimension values and metric units in strings
# WHEN log_metric is called
# THEN default values should be used such as "Count" as a unit, invalid dimensions not included
# and no exception raised
log_metric(name="test_metric", **invalid_input)
captured = capsys.readouterr()
assert captured.out == expected
def test_log_metric_multiple_dimensions(capsys):
# GIVEN multiple optional dimensions are provided
# WHEN log_metric is called
# THEN dimensions should appear as dimenion=value
log_metric(
name="test_metric", unit=MetricUnit.Seconds, value=60, customer="abc", charge_id="123"
)
expected = "MONITORING|60|Seconds|test_metric|ServerlessAirline|service=service_undefined,customer=abc,charge_id=123\n"
captured = capsys.readouterr()
assert captured.out == expected
def test_log_metric_env_var(monkeypatch, capsys):
# GIVEN a service, unit and value have been provided
# WHEN log_metric is called
# THEN custom metric line should be match given values
service_name = "payment"
monkeypatch.setenv("POWERTOOLS_SERVICE_NAME", service_name)
log_metric(name="test_metric", unit=MetricUnit.Seconds, value=60)
expected = "MONITORING|60|Seconds|test_metric|ServerlessAirline|service=payment\n"
captured = capsys.readouterr()
assert captured.out == expected
def lambda_handler(event, context):
"""AWS Lambda Function entrypoint to cancel booking
Parameters
----------
event: dict, required
Step Functions State Machine event
chargeId: string
pre-authorization charge ID
context: object, required
Lambda Context runtime methods and attributes
Context doc: https://docs.aws.amazon.com/lambda/latest/dg/python-context-object.html
Returns
-------
boolean
Raises
------
BookingCancellationException
Booking Cancellation Exception including error message upon failure
"""
global _cold_start
if _cold_start:
log_metric(name="ColdStart",
unit=MetricUnit.Count,
value=1,
function_name=context.function_name)
_cold_start = False
booking_id = event.get("bookingId")
if not booking_id:
log_metric(name="InvalidBookingRequest",
unit=MetricUnit.Count,
value=1,
operation="cancel_booking")
logger.error({"operation": "invalid_event", "details": event})
raise ValueError("Invalid booking ID")
try:
logger.debug(f"Cancelling booking - {booking_id}")
ret = cancel_booking(booking_id)
log_metric(name="SuccessfulCancellation",
unit=MetricUnit.Count,
value=1)
logger.debug("Adding Booking Status annotation")
tracer.put_annotation("BookingStatus", "CANCELLED")
return ret
except BookingCancellationException as err:
log_metric(name="FailedCancellation", unit=MetricUnit.Count, value=1)
logger.debug("Adding Booking Status annotation before raising error")
tracer.put_annotation("BookingStatus", "ERROR")
logger.error({"operation": "cancel_booking", "details": err})
raise BookingCancellationException(details=err)
def lambda_handler(event, context):
"""AWS Lambda Function entrypoint to reserve a booking
Parameters
----------
event: dict, required
Step Functions State Machine event
chargeId: string
pre-authorization charge ID
stateExecutionId: string
Step Functions Process Booking Execution ID
chargeId: string
Pre-authorization payment token
customerId: string
Customer unique identifier
bookingOutboundFlightId: string
Outbound flight unique identifier
context: object, required
Lambda Context runtime methods and attributes
Context doc: https://docs.aws.amazon.com/lambda/latest/dg/python-context-object.html
Returns
-------
bookingId: string
booking ID generated
Raises
------
BookingReservationException
Booking Reservation Exception including error message upon failure
"""
global _cold_start
if _cold_start:
log_metric(name="ColdStart",
unit=MetricUnit.Count,
value=1,
function_name=context.function_name)
_cold_start = False
if not is_booking_request_valid(event):
log_metric(
name="InvalidBookingRequest",
unit=MetricUnit.Count,
value=1,
operation="reserve_booking",
)
logger.error({"operation": "invalid_event", "details": event})
raise ValueError("Invalid booking request")
try:
logger.debug(f"Reserving booking for customer {event['customerId']}")
ret = reserve_booking(event)
log_metric(name="SuccessfulReservation",
unit=MetricUnit.Count,
value=1)
logger.debug("Adding Booking Reservation annotation")
tracer.put_annotation("Booking", ret["bookingId"])
tracer.put_annotation("BookingStatus", "RESERVED")
# Step Functions use the return to append `bookingId` key into the overall output
return ret["bookingId"]
except BookingReservationException as err:
log_metric(name="FailedReservation", unit=MetricUnit.Count, value=1)
logger.debug(
"Adding Booking Reservation annotation before raising error")
tracer.put_annotation("BookingStatus", "ERROR")
logger.error({"operation": "reserve_booking", "details": err})
raise BookingReservationException(details=err)
def lambda_handler(event, context):
"""AWS Lambda Function entrypoint to confirm booking
Parameters
----------
event: dict, required
Step Functions State Machine event
bookingId: string
Unique Booking ID of an unconfirmed booking
context: object, required
Lambda Context runtime methods and attributes
Context doc: https://docs.aws.amazon.com/lambda/latest/dg/python-context-object.html
Returns
-------
string
bookingReference generated
Raises
------
BookingConfirmationException
Booking Confirmation Exception including error message upon failure
"""
global _cold_start
if _cold_start:
log_metric(name="ColdStart",
unit=MetricUnit.Count,
value=1,
function_name=context.function_name)
_cold_start = False
booking_id = event.get("bookingId")
if not booking_id:
log_metric(
name="InvalidBookingRequest",
unit=MetricUnit.Count,
value=1,
operation="confirm_booking",
)
logger.error({"operation": "invalid_event", "details": event})
raise ValueError("Invalid booking ID")
try:
logger.debug(f"Confirming booking - {booking_id}")
ret = confirm_booking(booking_id)
log_metric(name="SuccessfulBooking", unit=MetricUnit.Count, value=1)
logger.debug("Adding Booking Status annotation")
tracer.put_annotation("BookingReference", ret["bookingReference"])
tracer.put_annotation("BookingStatus", "CONFIRMED")
# Step Functions use the return to append `bookingReference` key into the overall output
return ret["bookingReference"]
except BookingConfirmationException as err:
log_metric(name="FailedBooking", unit=MetricUnit.Count, value=1)
logger.debug("Adding Booking Status annotation before raising error")
tracer.put_annotation("BookingStatus", "ERROR")
logger.error({"operation": "confirm_booking", "details": err})
raise BookingConfirmationException(details=err)
def lambda_handler(event, context):
"""AWS Lambda Function entrypoint to refund payment
Parameters
----------
event: dict, required
Step Functions State Machine event
chargeId: string
pre-authorization charge ID
context: object, required
Lambda Context runtime methods and attributes
Context doc: https://docs.aws.amazon.com/lambda/latest/dg/python-context-object.html
Returns
-------
string
JSON Stringified data containing refundId ID
Raises
------
RefundException
Refund Exception including error message upon failure
"""
global _cold_start
if _cold_start:
log_metric(name="ColdStart",
unit=MetricUnit.Count,
value=1,
function_name=context.function_name)
_cold_start = False
payment_token = event.get("chargeId")
customer_id = event.get("customerId")
if not payment_token:
log_metric(name="InvalidPaymentRequest",
unit=MetricUnit.Count,
value=1,
operation="refund_payment")
logger.error({"operation": "invalid_event", "details": event})
raise ValueError("Invalid Charge ID")
try:
logger.debug(
f"Refunding payment from customer {customer_id} using {payment_token} token"
)
ret = refund_payment(payment_token)
log_metric(name="SuccessfulRefund", unit=MetricUnit.Count, value=1)
logger.debug("Adding Payment Refund Status annotation")
tracer.put_annotation("Refund", ret["refundId"])
tracer.put_annotation("PaymentStatus", "REFUNDED")
return ret
except RefundException as err:
log_metric(name="FailedRefund", unit=MetricUnit.Count, value=1)
logger.debug(
"Adding Payment Refund Status annotation before raising error")
tracer.put_annotation("RefundStatus", "FAILED")
logger.error({"operation": "refund_payment", "details": err})
raise RefundException(details=err)
def lambda_handler(event, context):
"""AWS Lambda Function entrypoint to collect payment
Parameters
----------
event: dict, required
Step Functions State Machine event
chargeId: string
pre-authorization charge ID
context: object, required
Lambda Context runtime methods and attributes
Context doc: https://docs.aws.amazon.com/lambda/latest/dg/python-context-object.html
Returns
-------
dict
receiptUrl: string
receipt URL of charge collected
price: int
amount collected
Raises
------
BookingConfirmationException
Booking Confirmation Exception including error message upon failure
"""
global _cold_start
if _cold_start:
log_metric(
name="ColdStart", unit=MetricUnit.Count, value=1, function_name=context.function_name
)
_cold_start = False
pre_authorization_token = event.get("chargeId")
customer_id = event.get("customerId")
if not pre_authorization_token:
log_metric(
name="InvalidPaymentRequest",
unit=MetricUnit.Count,
value=1,
operation="collect_payment",
)
logger.error({"operation": "invalid_event", "details": event})
raise ValueError("Invalid Charge ID")
try:
logger.debug(
f"Collecting payment from customer {customer_id} using {pre_authorization_token} token"
)
ret = collect_payment(pre_authorization_token)
log_metric(name="SuccessfulPayment", unit=MetricUnit.Count, value=1)
logger.debug("Adding Payment Status annotation")
tracer.put_annotation("PaymentStatus", "SUCCESS")
# Step Functions can append multiple values if you return a single dict
return ret
except PaymentException as err:
log_metric(name="FailedPayment", unit=MetricUnit.Count, value=1)
logger.debug("Adding Payment Status annotation before raising error")
tracer.put_annotation("PaymentStatus", "FAILED")
logger.error({"operation": "collect_payment", "details": err})
raise PaymentException(details=err)
def lambda_handler(event, context):
"""AWS Lambda Function entrypoint to notify booking
Parameters
----------
event: dict, required
Step Functions State Machine event
customer_id: string
Unique Customer ID
price: string
Flight price
bookingReference: string
Confirmed booking reference
context: object, required
Lambda Context runtime methods and attributes
Context doc: https://docs.aws.amazon.com/lambda/latest/dg/python-context-object.html
Returns
-------
string
notificationId
Unique ID confirming notification delivery
Raises
------
BookingNotificationException
Booking Notification Exception including error message upon failure
"""
global _cold_start
if _cold_start:
log_metric(name="ColdStart",
unit=MetricUnit.Count,
value=1,
function_name=context.function_name)
_cold_start = False
customer_id = event.get("customerId", False)
payment = event.get("payment", {})
price = payment.get("price", False)
booking_reference = event.get("bookingReference", False)
if not customer_id and not price:
log_metric(name="InvalidBookingRequest",
unit=MetricUnit.Count,
value=1,
operation="notify_booking")
logger.error({"operation": "invalid_event", "details": event})
raise ValueError("Invalid customer and price")
try:
payload = {"customerId": customer_id, "price": price}
ret = notify_booking(payload, booking_reference)
log_metric(name="SuccessfulNotification",
unit=MetricUnit.Count,
value=1)
logger.debug("Adding Booking Notification annotation")
tracer.put_annotation("BookingNotification", ret["notificationId"])
tracer.put_annotation("BookingNotificationStatus", "SUCCESS")
# Step Functions use the return to append `notificationId` key into the overall output
return ret["notificationId"]
except BookingNotificationException as err:
log_metric(name="FailedNotification", unit=MetricUnit.Count, value=1)
logger.debug(
"Adding Booking Notification annotation before raising error")
tracer.put_annotation("BookingNotificationStatus", "FAILED")
logger.error({"operation": "notify_booking", "details": err})
raise BookingNotificationException(details=err)
