async def create_up_solution(dsg_arn):
solution_response = personalize.create_solution(
name=SOLUTION_NAME_UP,
datasetGroupArn=dsg_arn,
recipeArn='arn:aws:personalize:::recipe/aws-user-personalization')
solution_arn = solution_response['solutionArn']
PersistentValues[SOLUTION_UP] = solution_arn
write(PersistentValues)
await util.wait_until_status_async(
lambdaToGetStatus=lambda _="": personalize.describe_solution(
solutionArn=solution_arn)['solution']["status"],
messagePrefix="Creating a up solution...",
expectedStatus="ACTIVE")
solution_version_response = personalize.create_solution_version(
solutionArn=solution_arn)
solution_version_arn = solution_version_response['solutionVersionArn']
PersistentValues[SOLUTION_VERSION_UP] = solution_version_arn
write(PersistentValues)
await util.wait_until_status_async(
lambdaToGetStatus=lambda _="": personalize.describe_solution_version(
solutionVersionArn=solution_version_arn)['solutionVersion'][
'status'],
messagePrefix="Creating a up solution version...",
expectedStatus="ACTIVE")
def create_app():
logging.info('Create Pinpoint. Application name : {}, region: {}'.format(
APPLICATION_NAME, REGION))
app_response = pinpoint.create_app(
CreateApplicationRequest={'Name': APPLICATION_NAME})
app_id = app_response['ApplicationResponse']['Id']
PersistentValues[APPLICATION_NAME] = app_id
write(PersistentValues)
def create_app():
app_response = pinpoint.create_app(
CreateApplicationRequest={'Name': APPLICATION_NAME})
logger.info('Creating Pinpoint Application({}) >> Success'.format(
APPLICATION_NAME))
app_id = app_response['ApplicationResponse']['Id']
PersistentValues[APPLICATION_NAME] = app_id
write(PersistentValues)
def create_filter(dsg_arn):
filer_response = personalize.create_filter(
name='FILTER_USER_PERSONALIZATION',
datasetGroupArn=dsg_arn,
filterExpression=
'EXCLUDE itemId WHERE INTERACTIONS.event_type in ("title-read")')
filter_arn = filer_response['filterArn']
PersistentValues[FILTER_UP] = filter_arn
write(PersistentValues)
def create_dataset_group():
response = personalize.create_dataset_group(name=DSG_NAME)
dsg_arn = response['datasetGroupArn']
PersistentValues[DSG] = dsg_arn
write(PersistentValues)
logging.info("Dataset group has been created. ARN: " + dsg_arn)
util.wait_until_status(lambda _="": personalize.describe_dataset_group(
datasetGroupArn=dsg_arn)["datasetGroup"]["status"],
"Creating dataset group...",
"ACTIVE")
def create_import_job():
segment_response = pinpoint.create_import_job(
ApplicationId=PersistentValues[APPLICATION_NAME],
ImportJobRequest={
'Format': 'CSV',
'RoleArn': PersistentValues[ROLE_NAME],
'S3Url': f's3://{BUCKET_NAME}{SEGMENT_PATH}',
'SegmentName': SEGEMENT_NAME
})
logger.info('Creating Segment({}) >> Success'.format(SEGEMENT_NAME))
segment_id = segment_response['Definition']['SegmentId']
PersistentValues[SEGEMENT_NAME] = segment_id
write(PersistentValues)
def create_function():
logging.info('Create Lambda. Function name : {}'.format(FUNCTION_NAME))
function_response = function.create_function(
FunctionName=FUNCTION_NAME,
Runtime='python3.8',
Role=PersistentValues[LAMBDA_ROLE_NAME],
Handler='lambda_function.lambda_handler',
Code={
'S3Bucket': BUCKET_NAME,
'S3Key': LAMBDA_PATH
})
function_arn = function_response['FunctionArn']
PersistentValues[FUNCTION_NAME] = function_arn
write(PersistentValues)
def register_schema():
json_file_paths = util.get_file_paths_recursively(DATA_DIRECTORY, "json")
for p in json_file_paths:
with open(p) as f:
schema_name = p.split("/")[1]
createSchemaResponse = personalize.create_schema(name=schema_name,
schema=f.read())
schema_arn = createSchemaResponse['schemaArn']
logging.info('Schema Name: {}, ARN: {}'.format(schema_name,
schema_arn))
PersistentValues[schema_name] = schema_arn
write(PersistentValues)
async def create_up_campaign(solutionVersionArn):
response = personalize.create_campaign(
name=CAMPAIGN_NAME_UP,
solutionVersionArn=solutionVersionArn,
minProvisionedTPS=1)
arn = response['campaignArn']
PersistentValues[CAMPAIGN_UP] = arn
write(PersistentValues)
await util.wait_until_status_async(
lambdaToGetStatus=lambda _="": personalize.describe_campaign(
campaignArn=arn)['campaign']['status'],
messagePrefix="Creating a up campaign...",
expectedStatus="ACTIVE")
def create_import_job():
logging.info('Create Segment. Segment name : {}'.format(SEGEMENT_NAME))
segment_response = pinpoint.create_import_job(
ApplicationId=PersistentValues[APPLICATION_NAME],
ImportJobRequest={
'DefineSegment': True,
'Format': 'CSV',
'RoleArn': PersistentValues[S3_ROLE_NAME_FOR_PINPOINT],
'S3Url': f's3://{BUCKET_NAME}/{SEGMENT_PATH}',
'SegmentName': SEGEMENT_NAME
})
time.sleep(10) # 10초를 기다리지 않으면 SegmentId가 생성되지 않음...
segment_id = segment_response['ImportJobResponse']['Definition'][
'SegmentId']
PersistentValues[SEGEMENT_NAME] = segment_id
write(PersistentValues)
def create_lambda_role():
logging.info("Creating a role for Lambda. Role name: " + LAMBDA_ROLE_NAME)
role_arn = iam_client.create_role(RoleName=LAMBDA_ROLE_NAME,
AssumeRolePolicyDocument='''{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Principal": {
"Service": "lambda.amazonaws.com"
},
"Action": "sts:AssumeRole"
}
]
}''')['Role']['Arn']
new_policy = iam_client.create_policy(PolicyName=LAMBDA_POLICY_NAME,
PolicyDocument=f'''{{
"Version": "2012-10-17",
"Id": "{LAMBDA_POLICY_NAME}",
"Statement": [
{{
"Effect": "Allow",
"Action": "logs:CreateLogGroup",
"Resource": "arn:aws:logs:{REGION}:{ACCOUNT_ID}:*"
}},
{{
"Effect": "Allow",
"Action": [
"logs:CreateLogStream",
"logs:PutLogEvents"
],
"Resource": [
"arn:aws:logs:{REGION}:{ACCOUNT_ID}:log-group:/aws/lambda/{FUNCTION_NAME}:*"
]
}}
]
}}''')
new_policy_arn = new_policy['Policy']['Arn']
policy = iam_resource.Policy(new_policy_arn)
policy.attach_role(RoleName=LAMBDA_ROLE_NAME)
PersistentValues[LAMBDA_ROLE_NAME] = role_arn
PersistentValues[LAMBDA_POLICY_NAME] = new_policy_arn
write(PersistentValues)
def create_recommender_configuration():
logging.info('Create ML Model. Recommender name : {}'.format(ML_NAME))
model_response = pinpoint.create_recommender_configuration(
CreateRecommenderConfiguration={
'Attributes': {
'Recommendations.Title': 'Title'
},
'Name': ML_NAME,
'RecommendationProviderIdType': 'PINPOINT_USER_ID',
'RecommendationProviderRoleArn': PersistentValues[ML_ROLE_NAME],
'RecommendationProviderUri': PersistentValues[CAMPAIGN_UP],
'RecommendationTransformerUri': FUNCTION_NAME,
'RecommendationsPerMessage': 5
})
model_id = model_response['RecommenderConfigurationResponse']['Id']
PersistentValues[ML_NAME] = model_id
write(PersistentValues)
def create_s3_role():
logging.info("Creating a role for Personalize. Role name: " +
S3_ROLE_NAME_FOR_PERSONALIZE)
role_arn = iam_client.create_role(RoleName=S3_ROLE_NAME_FOR_PERSONALIZE,
AssumeRolePolicyDocument='''{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Principal": {
"Service": "personalize.amazonaws.com"
},
"Action": "sts:AssumeRole"
}
]
}''')['Role']['Arn']
new_policy = iam_client.create_policy(
PolicyName=S3_POLICY_NAME_FOR_ROLE_FOR_PERSONALIZE,
PolicyDocument=f'''{{
"Version": "2012-10-17",
"Id": "{S3_POLICY_NAME_FOR_ROLE_FOR_PERSONALIZE}",
"Statement": [
{{
"Sid": "{S3_POLICY_NAME_FOR_ROLE_FOR_PERSONALIZE}",
"Effect": "Allow",
"Action": "s3:*",
"Resource": [
"arn:aws:s3:::{BUCKET_NAME}",
"arn:aws:s3:::{BUCKET_NAME}/*"
]
}}
]
}}''')
new_policy_arn = new_policy['Policy']['Arn']
policy = iam_resource.Policy(new_policy_arn)
policy.attach_role(RoleName=S3_ROLE_NAME_FOR_PERSONALIZE)
PersistentValues[S3_ROLE_NAME_FOR_PERSONALIZE] = role_arn
PersistentValues[S3_POLICY_NAME_FOR_ROLE_FOR_PERSONALIZE] = new_policy_arn
write(PersistentValues)
def create_campaign():
logging.info('Create Campaign. Campaign name : {}'.format(CAMPAIGN_NAME))
campaign_response = pinpoint.create_campaign(
ApplicationId=PersistentValues[APPLICATION_NAME],
WriteCampaignRequest={
'Name': CAMPAIGN_NAME,
'SegmentId': PersistentValues[SEGEMENT_NAME],
'TemplateConfiguration': {
'EmailTemplate': {
'Name': EMAIL_NAME
}
},
'Schedule': {
'StartTime': 'IMMEDIATE'
}
})
campaign_id = campaign_response['CampaignResponse']['Arn']
PersistentValues[CAMPAIGN_NAME] = campaign_id
write(PersistentValues)
def create_ml_role():
logging.info("Creating a role for Lambda. Role name: " + ML_ROLE_NAME)
role_arn = iam_client.create_role(RoleName=ML_ROLE_NAME,
AssumeRolePolicyDocument='''{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Principal": {
"Service": "pinpoint.amazonaws.com"
},
"Action": "sts:AssumeRole"
}
]
}''')['Role']['Arn']
new_policy = iam_client.create_policy(PolicyName=ML_POLICY_NAME,
PolicyDocument=f'''{{
"Version": "2012-10-17",
"Id": "{ML_POLICY_NAME}",
"Statement": [
{{
"Effect": "Allow",
"Action": [
"personalize:*"
],
"Resource": [
"{PersistentValues[CAMPAIGN_UP]}",
"{PersistentValues[SOLUTION_UP]}"
]
}}
]
}}''')
new_policy_arn = new_policy['Policy']['Arn']
policy = iam_resource.Policy(new_policy_arn)
policy.attach_role(RoleName=ML_ROLE_NAME)
PersistentValues[ML_ROLE_NAME] = role_arn
PersistentValues[ML_POLICY_NAME] = new_policy_arn
write(PersistentValues)
def create_role():
ASSUME_POLICY = '''{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Principal": {
"Service": "pinpoint.amazonaws.com"
},
"Action": "sts:AssumeRole"
}
]
}'''
role_response = iam.creat_role(RoleName=ROLE_NAME,
AssumeRolePolicyDocument=ASSUME_POLICY,
PermissionsBoundary=POLICY_NAME)
logger.info('Creating IAM Role({}) >> Success'.format(ROLE_NAME))
role_arn = role_response['Role']['Arn']
PersistentValues[ROLE_NAME] = role_arn
write(PersistentValues)
def create_campaign():
campaign_response = pinpoint.create_campaign(
ApplicationId=PersistentValues[APPLICATION_NAME],
WriteCampaignRequest={
'Name': CAMPAIGN_NAME,
'SegmentId': PersistentValues[SEGEMENT_NAME],
'TemplateConfiguration': {
'EmailTemplate': {
'Name': EMAIL_NAME
}
},
'Schedule': {
'StartTime': 'IMMEDIATE',
'Timezone': 'UTC+09'
}
})
logger.info('Creating Campaign({}) >> Success'.format(CAMPAIGN_NAME))
campaign_arn = campaign_response['campaignArn']
PersistentValues[CAMPAIGN_NAME] = campaign_arn
write(PersistentValues)
def create_dataset(datasetGroupArn, titleSchemaArn, userSchemaArn,
titleReadSchemaArn):
dataset_arn = 'datasetArn'
title_dataset = personalize.create_dataset(name=TITLE,
schemaArn=titleSchemaArn,
datasetGroupArn=datasetGroupArn,
datasetType="Items")
logging.info("titleDatasetArn: " + title_dataset[dataset_arn])
PersistentValues[TITLE_DATASET] = title_dataset[dataset_arn]
write(PersistentValues)
user_dataset = personalize.create_dataset(name=USER,
schemaArn=userSchemaArn,
datasetGroupArn=datasetGroupArn,
datasetType="Users")
logging.info("userDatasetArn: " + user_dataset[dataset_arn])
PersistentValues[USER_DATASET] = user_dataset[dataset_arn]
write(PersistentValues)
title_read_dataset = personalize.create_dataset(
name=TITLE_READ,
schemaArn=titleReadSchemaArn,
datasetGroupArn=datasetGroupArn,
datasetType="Interactions")
logging.info("titleReadDatasetArn: " + title_read_dataset[dataset_arn])
PersistentValues[TITLE_READ_DATASET] = title_read_dataset[dataset_arn]
write(PersistentValues)
def create_policy():
POLICY = f'''{{
"Version": "2012-10-17",
"Id": {POLICY_NAME},
"Statement": [
{{
"Effect": "Allow",
"Action": "s3:*"
"Resource": [
"arn:aws:s3:::{BUCKET_NAME}",
"arn:aws:s3:::{BUCKET_NAME}/*"
]
}}
]
}}'''
policy_response = iam.create_policy(PolicyName=POLICY_NAME,
PolicyDocument=POLICY)
logger.info('Creating IAM Policy({}) >> Success'.format(POLICY_NAME))
policy_arn = policy_response['Policy']['Arn']
PersistentValues[POLICY_NAME] = policy_arn
write(PersistentValues)
