https://github.com/mikoweb/symfony-inference-system

Inference System for Selecting the Optimal Programming Language written in Symfony and Angular.
https://github.com/mikoweb/symfony-inference-system

angular inference-engine rest symfony

Last synced: 6 days ago
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Inference System for Selecting the Optimal Programming Language written in Symfony and Angular.

• Host: GitHub
• URL: https://github.com/mikoweb/symfony-inference-system
• Owner: mikoweb
• Created: 2023-12-28T19:42:07.000Z (about 1 year ago)
• Default Branch: master
• Last Pushed: 2024-01-27T21:10:21.000Z (about 1 year ago)
• Last Synced: 2024-12-02T11:14:03.530Z (2 months ago)
• Topics: angular, inference-engine, rest, symfony
• Language: PHP
• Homepage: https://languages.mikoweb.usermd.net
• Size: 2.31 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# symfony-inference-system

Inference System for Selecting the Optimal Programming Language.

![Screen](./docs/screenshot.png)

## Demo Page

https://languages.mikoweb.usermd.net

## Technology stack

* PHP 8.3

* Symfony Framework 6.4

* TypeScript 5

* Angular Framework 17

* Ionic Components

* REST API

* No database!

## Criteria of choice

### Classical logic select box

There are two multi-select fields `Language Usage` and `Features` with `AND` and `OR` search methods.

These fields are used to narrow down your results.

### Fuzzy logic fields

There are three fields using fuzzy logic: `Minimum performance`, `Minimum popularity`,`Language experience` - they 

take the values `Very high`, `High`, `Medium`, `Low`, `Very low`, sometimes `None`.

Based on these values, a numerical score is calculated using a fuzzy logic mechanism.

### Popularity forecasts

There is a selectbox called `Popularity - Year` where you can select a year from the future. 

This is used to change the behavior of the `Minimum Popularity` field. By default, real data from 2023 are taken. 

However, years in the future can be selected and the data is predicted using the linear regression 

algorithm `sklearn.linear_model.BayesianRidge`. A Python command was used to generate the data - `ml` directory.

## Tests

The test kit is located in the folder `tests`.

To run the tests, run the command:

    php8.3 composer.phar run test

## Optimizations

Data is stored in read-only files in csv and json formats. Most of them were downloaded from kaggle.com. 

They are located in the `resources/dataset` folder.

This data is read and processed by the application only once and kept in memory. 

Data is also cached using the `Symfony Cache Component`. In fact, they are kept in the form of PHP serialization format.

## How to run

Go to project directory.

To run the backend, use docker:

    docker compose up --build

The backend is available at: 

    http://localhost:8741

Go to frontend directory:

    cd frontend

Set api url in the environment variable, i.e. in the file `src/environments/environment.ts`:

    apiBaseUrl: 'http://localhost:8741'    

To run the frontend, execute the following commands:

    nvm use 20

    npm install

    npm run start

The frontend is available at:

    http://localhost:4200

## Copyrights

Copyright © Rafał Mikołajun 2024.