def step_impl(context):
context.event = {
'Records': [{
'messageAttributes': {
'consultant': {
'stringValue': 'BehaveTest1',
'dataType': 'String'
},
'type': {
'stringValue': 'scheduled',
'dataType': 'String.type'
},
'checkin-date': {
'stringValue': '2020-01-01',
'dataType': 'String'
}
}
}]
}
prediction_arn = get_export('predict-topic-arn')
os.environ['TIMES_UP_MACHINE'] = 'times_up_machine'
context.response = checkin_consumer(
context.event, None, context.sns_client, context.sfn_client,
context.checkin_model, context.consultant_model, context.request_model,
context.consultant_model, context.contract_model)
assert context.sns_client.publish.call_args.kwargs[
'TopicArn'] == prediction_arn
class Meta:
'''Online Statuses Meta Class'''
if 'CustomersTableName' in os.environ:
table_name = os.environ['CustomersTableName']
else:
table_name = get_export('database-CustomersTableName')
region = 'eu-central-1'
host = 'https://dynamodb.eu-central-1.amazonaws.com'
class Meta:
'''Consultants Meta Class'''
if 'ConsultantsTableName' in os.environ:
table_name = os.environ['ConsultantsTableName']
else:
table_name = get_export('database-ConsultantsTableName')
region = 'eu-central-1'
host = 'https://dynamodb.eu-central-1.amazonaws.com'
def send_to_sqs(self, action_id: str, action_type: str, value: str,\
message_type: Types, consultant_uuid = None):
'''
Sends message to SQS
-
:param action_id: action id of message
:param action_type: type of message
:param value: value of message
'''
if action_type == 'checkboxes':
value = [{'value': x['value'].split(';')[1]} for x in value]
if action_type == 'static_select':
value = value['value'].split(';')[1]
message_payload = {
"action_id": action_id,
"type": action_type,
"value": value
}
if self.metadata is not None:
if 'current_activity' in self.metadata and\
self.metadata['current_activity'] is not None:
message_payload['customer'] = self.metadata['current_activity']
elif 'current_customer' in self.metadata and\
self.metadata['current_customer'] is not None:
message_payload['customer'] = self.metadata['current_customer']
checkin = self.checkin_model.get(self.metadata['checkin_id'])
message = write_message(checkin.consultant_uuid,
message_type,
checkin_id=checkin.uuid,
device_id=self.payload['api_app_id'],
trigger_id=self.payload['trigger_id'],
payload=message_payload)
else:
message = write_message(consultant_uuid,
message_type,
checkin_id=None,
device_id=self.payload['api_app_id'],
trigger_id=self.payload['trigger_id'],
payload=message_payload)
slack_app_url = get_export('checkin-action-queue-url')
send = self.sqs_client.send_message(QueueUrl=slack_app_url,
MessageBody='Slack User Input',
MessageAttributes=message,
MessageGroupId='UserInput',
MessageDeduplicationId=str(
uuid.uuid4()))
print("SEND TO SQS:", send)
return send
def publisher(event: Dict, context, sqs_client: Boto3SQS) -> None:
'''
Publishes to Slack App Queue
-
:param event: AWS event
:param context: AWS context
:param sqs_client: Boto3 SQS client
'''
print("Request ID: ", context.aws_request_id)
print("Event: ", event)
slack_app_queue_url = get_export('slack-app-queue-url')
send_message = sqs_client.send_message(QueueUrl=slack_app_queue_url,
MessageBody='Prediction done',
MessageAttributes=event)
print(send_message)
def scheduled(message: Dict, unique_id: str, sns_client: Boto3SNS,
stepfunctions_client: Boto3SFN, checkin_model: PynamoDBCheckIn)\
-> Tuple[Boto3SNS, Boto3SFN]:
'''
Method for scheduled action. Saves "null" checkin in database
and publish message to prediction queue.
-
:param message: The message from start "event" e.g. message will be received at 9am.
:param unique_id: Unique id for checkin in database.
:param sns_client: boto3 client for Simple Notification Server.
:param stepfunctions_client: boto3 client for stepfunctions.
:param checkin_model: PynamoDB CheckIn Model
'''
prediction_arn = get_export('predict-topic-arn')
times_up_machine = os.environ['TIMES_UP_MACHINE']
reminder = 'checkin-id' in message
if not reminder:
checkin_date = datetime.strptime(message['checkin-date'], '%Y-%m-%d').date()
checkin = checkin_model(uuid=unique_id,
consultant_uuid=message['consultant'],
date=str(checkin_date), completed='False',
predictions='[]', user_input='[]')
# Write the checkin to the database
checkin.save()
# Send message to predict
sns_pub = sns_client.publish(
TopicArn=prediction_arn,
Message='Ready for prediction',
MessageAttributes=write_message(
message['consultant'], Types.Predict, checkin_id=unique_id)
)
print(sns_pub)
# Start TimesUp
start = stepfunctions_client.start_execution(
stateMachineArn=times_up_machine,
input=json.dumps(write_message(
message['consultant'], Types.Slack if not reminder else Types.Slack_Reminder,\
checkin_id=unique_id if not reminder else message['checkin-id']))
)
print(start)
import os
import boto3
import time
from src.modules.get_export import get_export
from src.modules.queue_message_writer import write_message
from src.modules.type_enum import Types
from src.predictors.predict_customers import make_prediction
from src.dependencies.boto3_sqs_provider import get_sqs_provider
from src.dependencies.pynamodb_online_statuses_provider import get_online_statuses_provider
from src.dependencies.pynamodb_customers_provider import get_customers_provider
from src.dependencies.pynamodb_checkin_provider import get_checkin_provider
PREDICT_TOPIC_ARN = get_export('predict-topic-arn')
ENV_TYPE = get_export('pipeline-enviroment-type')
@given(u'a lambda function')
def step_impl(context):
# Pass as the import to the lambda didn't fail
context.sqs_client = get_sqs_provider(test=True)
context.online_statuses_model = get_online_statuses_provider(test=True)
context.customer_model = get_customers_provider(test=True)
context.checkin_model = get_checkin_provider(test=True)
pass
@when(u'a message is consumed from a predict topic')
def step_impl(context):
context.event = {
'Records': [{
'Sns': {