integeralex/netflix-recommendation-system

This Netflix Recommendation System is a web application developed using Node.js and Express. It utilizes a recommendation engine written in Python

Hi there! 👋 I'm Akshat K

I'm passionate about building projects that solve real-world problems. Instead of being tied to frameworks, I believe in understanding the core principles and engineering solutions that fit the unique challenges at hand. My Workflow ->

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✨ Projects

• netflix-recommendation-system
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• I have created and maintain multiple npm packages with a combined download count of over 15,000, used by many in the community. This makes me an active open-source contributor and maintainer.

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netflix-recommendation-system's Issues

Fix code scanning alert - Missing rate limiting

Tracking issue for:

• https://github.com/IntegerAlex/netflix-recommendation-system/security/code-scanning/4

(JS-R1000) Found multiple import of the same path

Description

It is always recommended to group all imports of a single path or source in a single import declaration. These usually happen in a codebase when multiple developers are working on the same codebase. It helps improving code refactoring and code readability as well.

Occurrences

There are 2 occurrences of this issue in the repository.

See all occurrences on DeepSource → app.deepsource.com/gh/IntegerAlex/netflix-recommendation-system/issue/JS-R1000/occurrences/

(JS-A1004) Audit: Unsanitized user input passed to server logs

Description

Logs serve as important records that are used by monitoring services and developers to investigate incidents. Logging unsanitized user input to the server allows the user to forge custom server logs.

Occurrences

There is 1 occurrence of this issue in the repository.

See all occurrences on DeepSource → app.deepsource.com/gh/IntegerAlex/netflix-recommendation-system/issue/JS-A1004/occurrences/

Requests taking too long

Great work on the app! After forking it and experimenting with it, I noticed that the cosine matrix is regenerated every time a user requests a recommendation. While I attempted to store it using JSON, the file size turned out to be too large. In light of this, I believe utilizing a cache or a database would be a more efficient solution. Additionally, implementing caching for repeated requests could further optimize performance. Best of luck with the continued development of the app!

Rate limiter needs to be reconfigured