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๐Ÿฟ๐Ÿฟ A movie ML recommender service built with Python.

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Recommender Service logo

Introduction

You see the 'P2EM' in the Logo above? Do you have any idea what that means?

Let me help you.

P2EM refers to "Plan to Embarass Myself"

To understand the background story, read my article, * How I Plan to Embarass Myself ...

Hey, read it :)

What does this do?

If you read the article above, you should get a sense of what this is about.

The service (largely written in Python) recommends movies based on a user's previous movie ratings using Machine Learning.

Oops. That was a mouthful.

Where can I try this out?

I'm currently building out a web client where you can try this.

I'll have the link here, when there's something pretty for you to see :)

How do I run the app locally?

Yeah, I've got your back.

  1. Clone the repo
git clone https://github.com/ohansemmanuel/recommender-service.git
  1. Create a .env file
cd recommender-service
touch .env
  1. The env file requires 4 important variables
JWT_SECRET_KEY
USERNAME
PASSWORD
USER_ID
  • JWT_SECRET_KEY is required by Flask-JWT for some encryption.

  • USERNAME and PASSWORD will be used to access authorized resources. These should be unique strings.

  • USER_ID is required, just like the username and password. This should be an Integer

  1. Install the app dependencies
pip install
  1. If you have some experience with Python development, you may need to have the app loaded from a virtual environment.

Where is this currently deployed?

Heroku, baby!

I should move this over to Digital Ocean for some customized control later.

If you wanna try something out, here's the endpoint for retrieving a list of movies ๐Ÿ‘‰ /movies

Does this explanation suck?

I'll refactor pretty soon. Still writing out the code. It never gets completed, does it? :(

Catch you later! ๐Ÿ‘Š

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๐Ÿฟ๐Ÿฟ A movie ML recommender service built with Python.

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