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movie_recommendation_system's Introduction

Team-4

Notes:

  • requirements.txt in docker does not seem to be working. Would be good idea to keep track on what is pip installd in order to add to the Dockerfile
  • in order to start api server, all files imported under data_collection must have data_collection. before the imported file's name.
  • main.py not meant to be ran under api, is meant to be an example on how to use the other util files under data_collection. main.py must be ran under data_collection directory.

Setup for dev:

Install python requirements

pip3 install flask kafka-python requests

Start kafka stream

docker run -it --log-opt max-size=50m --log-opt max-file=5 bitnami/kafka kafka-console-consumer.sh --bootstrap-server fall2022-comp585.cs.mcgill.ca:9092 --topic movielog4 --from-beginning

Test Kafka docker run -it --log-opt max-size=50m --log-opt max-file=5 bitnami/kafka kafka-console-consumer.sh --bootstrap-server fall2022-comp585.cs.mcgill.ca:9092 --topic movielog4

How to start API server:

Build and run docker container docker build -t "movierecc4" .

docker run -d -m 8192m -p 8082:8082 movierecc4

Get movie reccomendations for user_id curl fall2022-comp585-4.cs.mcgill.ca:8082/recommend/{user_id}

Find docker container id

docker container ls

Stop docker container docker stop {container_id}

delete docker

docker ps -a to see all the containers

docker rm {container_id}

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