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Merge pull request #13 from aws-solutions/feature/v1.2.0
Update to version v1.2.0
2 parents b761be0 + 835fb0a commit 010fbdf

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‎CHANGELOG.md‎

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@@ -4,6 +4,15 @@ All notable changes to this project will be documented in this file.
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [1.2.0] - 2022-01-31
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### Added
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- The solution now supports batch segment jobs to get user segments with your solution version. Each user segment is
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sorted in descending order based on the probability that each user will interact with items in your inventory.
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- The solution now supports domain dataset groups.
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### Changed
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- Upgraded to CDKv2.
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## [1.1.0] - 2021-11-22
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### Added
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- The solution now creates an Amazon EventBridge event bus, and puts messages to the bus when resources have been

‎README.md‎

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@@ -293,7 +293,7 @@ The following procedures assumes that all the OS-level configuration has been co
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* [AWS Command Line Interface](https://aws.amazon.com/cli/)
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* [Python](https://www.python.org/) 3.9 or newer
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* [Node.js](https://nodejs.org/en/) 16.x or newer
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* [AWS CDK](https://aws.amazon.com/cdk/) 1.126.0 or newer
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* [AWS CDK](https://aws.amazon.com/cdk/) 2.7.0 or newer
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* [Amazon Corretto OpenJDK](https://docs.aws.amazon.com/corretto/) 11
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> **Please ensure you test the templates before updating any production deployments.**
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export VERSION=my-version
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export REGION_NAME=my-region
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build-s3-cdk-dist \
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build-s3-cdk-dist deploy \
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--source-bucket-name DIST_BUCKET_PREFIX \
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--solution-name SOLUTION_NAME \
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--version_code VERSION \

‎deployment/run-unit-tests.sh‎

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source .venv/bin/activate
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cd $source_dir
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pip install --upgrade pip
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pip install -r $source_dir/requirements-dev.txt
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cd -
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‎source/aws_lambda/create_batch_inference_job/handler.py‎

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from shared.sfn_middleware import PersonalizeResource
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RESOURCE = "batchInferenceJob"
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STATUS = "batchInferenceJob.status"
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CONFIG = {
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"jobName": {
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"source": "event",
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"path": "serviceConfig.jobName",
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},
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"solutionVersionArn": {
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"source": "event",
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"path": "serviceConfig.solutionVersionArn",
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},
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"filterArn": {
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"source": "event",
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"path": "serviceConfig.filterArn",
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"default": "omit",
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},
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"numResults": {
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"source": "event",
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"path": "serviceConfig.numResults",
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"default": "omit",
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},
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"jobInput": {
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"source": "event",
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"path": "serviceConfig.jobInput",
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},
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"jobOutput": {"source": "event", "path": "serviceConfig.jobOutput"},
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"roleArn": {"source": "environment", "path": "ROLE_ARN"},
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"batchInferenceJobConfig": {
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"source": "event",
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"path": "serviceConfig.batchInferenceJobConfig",
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"default": "omit",
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},
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"maxAge": {
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"source": "event",
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"path": "workflowConfig.maxAge",
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"default": "omit",
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"as": "seconds",
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},
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"timeStarted": {
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"source": "event",
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"path": "workflowConfig.timeStarted",
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"default": "omit",
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"as": "iso8601",
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},
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}
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logger = Logger()
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tracer = Tracer()
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metrics = Metrics()
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@metrics.log_metrics
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@tracer.capture_lambda_handler
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@PersonalizeResource(
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resource="batchInferenceJob",
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status="batchInferenceJob.status",
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config={
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"jobName": {
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"source": "event",
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"path": "serviceConfig.jobName",
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},
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"solutionVersionArn": {
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"source": "event",
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"path": "serviceConfig.solutionVersionArn",
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},
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"filterArn": {
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"source": "event",
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"path": "serviceConfig.filterArn",
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"default": "omit",
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},
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"numResults": {
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"source": "event",
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"path": "serviceConfig.numResults",
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"default": "omit",
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},
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"jobInput": {
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"source": "event",
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"path": "serviceConfig.jobInput",
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},
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"jobOutput": {"source": "event", "path": "serviceConfig.jobOutput"},
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"roleArn": {"source": "environment", "path": "ROLE_ARN"},
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"batchInferenceJobConfig": {
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"source": "event",
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"path": "serviceConfig.batchInferenceJobConfig",
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"default": "omit",
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},
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"maxAge": {
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"source": "event",
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"path": "workflowConfig.maxAge",
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"default": "omit",
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"as": "seconds",
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},
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"timeStarted": {
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"source": "event",
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"path": "workflowConfig.timeStarted",
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"default": "omit",
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"as": "iso8601",
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},
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},
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resource=RESOURCE,
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status=STATUS,
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config=CONFIG,
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)
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def lambda_handler(event: Dict[str, Any], context: LambdaContext) -> Dict:
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"""Create a batch inference job in Amazon Personalize based on the configuration in `event`

‎source/aws_lambda/create_batch_segment_job/__init__.py‎

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# ######################################################################################################################
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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. #
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# #
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# Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance #
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# with the License. You may obtain a copy of the License at #
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# #
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# http://www.apache.org/licenses/LICENSE-2.0 #
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# #
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# Unless required by applicable law or agreed to in writing, software distributed under the License is distributed #
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# on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for #
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# the specific language governing permissions and limitations under the License. #
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# ######################################################################################################################

‎source/aws_lambda/create_batch_segment_job/handler.py‎

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# ######################################################################################################################
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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. #
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# #
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# Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance #
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# with the License. You may obtain a copy of the License at #
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# #
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# http://www.apache.org/licenses/LICENSE-2.0 #
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# #
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# Unless required by applicable law or agreed to in writing, software distributed under the License is distributed #
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# on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for #
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# the specific language governing permissions and limitations under the License. #
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# ######################################################################################################################
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from typing import Dict, Any
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from aws_lambda_powertools import Logger, Tracer, Metrics
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from aws_lambda_powertools.utilities.typing import LambdaContext
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from shared.sfn_middleware import PersonalizeResource
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RESOURCE = "batchSegmentJob"
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STATUS = "batchSegmentJob.status"
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CONFIG = {
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"filterArn": {
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"source": "event",
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"path": "serviceConfig.filterArn",
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"default": "omit",
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},
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"jobInput": {
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"source": "event",
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"path": "serviceConfig.jobInput",
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},
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"jobName": {
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"source": "event",
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"path": "serviceConfig.jobName",
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},
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"jobOutput": {"source": "event", "path": "serviceConfig.jobOutput"},
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"solutionVersionArn": {
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"source": "event",
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"path": "serviceConfig.solutionVersionArn",
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},
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"numResults": {
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"source": "event",
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"path": "serviceConfig.numResults",
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"default": "omit",
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},
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"roleArn": {"source": "environment", "path": "ROLE_ARN"},
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"maxAge": {
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"source": "event",
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"path": "workflowConfig.maxAge",
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"default": "omit",
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"as": "seconds",
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},
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"timeStarted": {
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"source": "event",
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"path": "workflowConfig.timeStarted",
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"default": "omit",
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"as": "iso8601",
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},
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}
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logger = Logger()
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tracer = Tracer()
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metrics = Metrics()
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@metrics.log_metrics
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@tracer.capture_lambda_handler
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@PersonalizeResource(
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resource=RESOURCE,
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status=STATUS,
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config=CONFIG,
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)
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def lambda_handler(event: Dict[str, Any], context: LambdaContext) -> Dict:
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"""Create a batch segment job in Amazon Personalize based on the configuration in `event`
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:param event: AWS Lambda Event
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:param context: AWS Lambda Context
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:return: the configured batch inference job
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"""
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return event.get("resource") # return the batch inference job

‎source/aws_lambda/create_campaign/handler.py‎

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from shared.sfn_middleware import PersonalizeResource
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RESOURCE = "campaign"
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STATUS = "campaign.latestCampaignUpdate.status || campaign.status"
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CONFIG = {
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"name": {
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"source": "event",
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"path": "serviceConfig.name",
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},
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"solutionVersionArn": {
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"source": "event",
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"path": "serviceConfig.solutionVersionArn",
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},
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"minProvisionedTPS": {
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"source": "event",
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"path": "serviceConfig.minProvisionedTPS",
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"as": "int",
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},
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"campaignConfig": {
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"source": "event",
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"path": "serviceConfig.campaignConfig",
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"default": "omit",
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},
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"maxAge": {
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"source": "event",
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"path": "workflowConfig.maxAge",
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"default": "omit",
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"as": "seconds",
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},
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"timeStarted": {
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"source": "event",
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"path": "workflowConfig.timeStarted",
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"default": "omit",
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"as": "iso8601",
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},
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}
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logger = Logger()
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tracer = Tracer()
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metrics = Metrics()
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@metrics.log_metrics
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@tracer.capture_lambda_handler
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@PersonalizeResource(
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resource="campaign",
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config={
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"name": {
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"source": "event",
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"path": "serviceConfig.name",
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},
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"solutionVersionArn": {
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"source": "event",
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"path": "serviceConfig.solutionVersionArn",
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},
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"minProvisionedTPS": {
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"source": "event",
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"path": "serviceConfig.minProvisionedTPS",
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"as": "int",
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},
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"campaignConfig": {
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"source": "event",
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"path": "serviceConfig.campaignConfig",
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"default": "omit",
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},
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"maxAge": {
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"source": "event",
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"path": "workflowConfig.maxAge",
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"default": "omit",
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"as": "seconds",
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},
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"timeStarted": {
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"source": "event",
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"path": "workflowConfig.timeStarted",
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"default": "omit",
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"as": "iso8601",
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},
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},
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status="campaign.latestCampaignUpdate.status || campaign.status",
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resource=RESOURCE,
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config=CONFIG,
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status=STATUS,
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)
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def lambda_handler(event: Dict[str, Any], context: LambdaContext) -> Dict:
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"""Create a campaign in Amazon Personalize based on the configuration in `event`

‎source/aws_lambda/create_dataset/handler.py‎

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from shared.sfn_middleware import PersonalizeResource
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RESOURCE = "dataset"
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CONFIG = {
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"name": {
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"source": "event",
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"path": "serviceConfig.name",
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},
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"datasetType": {
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"source": "event",
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"path": "serviceConfig.datasetType",
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},
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"datasetGroupArn": {
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"source": "event",
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"path": "serviceConfig.datasetGroupArn",
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},
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"schemaArn": {"source": "event", "path": "serviceConfig.schemaArn"},
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"timeStarted": {
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"source": "event",
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"path": "workflowConfig.timeStarted",
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"default": "omit",
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"as": "iso8601",
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},
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}
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logger = Logger()
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tracer = Tracer()
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metrics = Metrics()
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@metrics.log_metrics
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@tracer.capture_lambda_handler
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@PersonalizeResource(
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resource="dataset",
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config={
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"name": {
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"source": "event",
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"path": "serviceConfig.name",
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},
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"datasetType": {
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"source": "event",
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"path": "serviceConfig.datasetType",
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},
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"datasetGroupArn": {
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"source": "event",
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"path": "serviceConfig.datasetGroupArn",
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},
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"schemaArn": {"source": "event", "path": "serviceConfig.schemaArn"},
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"timeStarted": {
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"source": "event",
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"path": "workflowConfig.timeStarted",
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"default": "omit",
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"as": "iso8601",
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},
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},
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resource=RESOURCE,
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config=CONFIG,
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)
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def lambda_handler(event: Dict[str, Any], context: LambdaContext) -> Dict:
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"""Create a dataset in Amazon Personalize based on the configuration in `event`

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