GitHub - niyasrad/RhythmB: Your music, elevated. RhythmB is a music streaming service that allows users to listen to their favorite songs and discover new music.

Welcome to the RhythmB Docs!

RhythmB is a music streaming service that allows users to listen to their favorite songs and discover new music. It is built using Python, FastAPI, PostgreSQL, Elasticsearch, and Kibana for the backend and React and Typescript for the frontend.

Tech Stack, Tools and Libraries

Backend

Frontend

Others

DB, Index and Design

Database

We're using PostgreSQL for the database.

ORM - SQLAlchemy

We're using SQLAlchemy as the ORM, and we're using the declarative approach. The relationships are defined using the relationship function, and are used to create the foreign key constraints. This allows for cascading deletes and updates.

Note

If an Artist is deleted, all the Albums and Songs associated with the Artist are deleted.
If an Album is deleted, all the Songs associated with the Album are deleted.
If a Song is deleted, all the Ratings associated with the Song are deleted, and the Song is removed from all the Playlists it is associated with.

Song Schema (Example)

class Song(Base):
    __tablename__ = "songs"

    id = Column(UUID(as_uuid=True), primary_key=True, index=True, default=uuid.uuid4)
    title = Column(String, index=True)
    artist_id = Column(
        UUID(as_uuid=True), ForeignKey("artists.id", ondelete="CASCADE"), index=True
    )
    album_id = Column(
        UUID(as_uuid=True), ForeignKey("albums.id", ondelete="CASCADE"), index=True
    )
    genre = Column(String, index=True)
    length = Column(Integer, index=True)

    artist = relationship("Artist", back_populates="songs")
    playlist = relationship(
        "Playlist", secondary=songs_playlists_association, back_populates="songs"
    )
    album = relationship("Album", back_populates="songs")
    ratings = relationship("Rating", back_populates="song", cascade="all, delete")

    def __repr__(self):
        return (
            f"<Song {self.title} {self.artist} {self.album} {self.genre} {self.length}>"
        )

Search Index

We're using Elasticsearch for the search index. It is set up locally.

Index Mapping

We have defined the index mapping in the search.py file. The difference between Postgres data, and Elasticsearch data is the storing of the tags field. The tags field is a list of strings, and is used for searching.

Song Index Mapping (Example)

song_mapping = {
        "mappings": {
            "properties": {
                "id": {"type": "keyword"},
                "title": {"type": "text"},
                "artist_id": {"type": "keyword"},
                "album_id": {"type": "keyword"},
                "artist_name": {"type": "text"},
                "album_title": {"type": "text"},
                "genre": {"type": "keyword"},
                "length": {"type": "integer"},
                "tags": {"type": "keyword"},
            }
        }
    }

Note

The tags field is a list of strings, and is used for searching.
The tags are populated for songs, albums, and artists.

API Documentation

You can use the Swagger UI to test the API. It is available at http://localhost:8080/docs. Additionally, check the API Postman Documentation with examples, and sample requests.

Setup

To set the project up locally, we'll be using venvs.

Create a virtual environment

pip install virtualenv
virtualenv venv

Activate the virtual environment

.\venv\Scripts\activate

Install the dependencies

pip install -r requirements.txt

Run the project

uvicorn app:app --reload --port 8080

Backing up PostgreSQL

Backup Steps

Open a Command Prompt and navigate to the PostgreSQL bin directory. Replace 16 with your PostgreSQL version.

cd "C:\Program Files\PostgreSQL\16\bin"

Replace postgres, rhythmb, and the output file path accordingly.

pg_dump -U postgres -d rhythmb > "C:\Users\Niyas Hameed\Desktop\rhythmb.sql"

Enter your PostgreSQL password when prompted.
Open the output file in a text editor and verify that it contains the database schema and data.

Restore Steps

Open a Command Prompt and navigate to the PostgreSQL bin directory. Replace 16 with your PostgreSQL version.

cd "C:\Program Files\PostgreSQL\16\bin"

Replace postgres, rhythmb, and the input file path accordingly.

psql -U postgres -d rhythmb < "C:\Users\Niyas Hameed\Desktop\rhythmb.sql"

Enter your PostgreSQL password when prompted.

Elasticsearch Installation Steps

Download the Elasticsearch zip file from here.
Extract the zip file to a location of your choice.
Navigate to the Elasticsearch bin directory and run the elasticsearch.bat file.

cd "C:\Users\Niyas Hameed\Desktop\elasticsearch-7.12.1\bin"
elasticsearch.bat

Open a browser and navigate to http://localhost:9200/. You should see a json response

{
  "name" : "DESKTOP-1QJQJ8J",
  "cluster_name" : "elasticsearch",
  "cluster_uuid" : "2bY5QXZrQX2Z3Z2Z3Z2Z3Q",
  "version" : {
    "number" : "7.12.1",
    "build_flavor" : "default",
    "build_type" : "zip",
    "build_hash" : "3186837139b9c6b6d23c3200870651f10d3343b7",
    "build_date" : "2021-04-20T20:56:39.040728659Z",
    "build_snapshot" : false,
    "lucene_version" : "8.8.0",
    "minimum_wire_compatibility_version" : "6.8.0",
    "minimum_index_compatibility_version" : "6.0.0-beta1"
  },
  "tagline" : "You Know, for Search"
}

Kibana Installation Steps

Download the Kibana zip file from here.
Extract the zip file to a location of your choice.
Navigate to the Kibana bin directory and run the kibana.bat file.

cd "C:\Users\Niyas Hameed\Desktop\kibana-7.12.1-windows-x86_64\bin"
kibana.bat

Open a browser and navigate to http://localhost:5601/. You should see the Kibana home page.

Note

If you are unable to run Kibana, try changing the server.port and server.host properties in the kibana.yml file. You can find the file in the Kibana config directory.

C:\Users\Niyas Hameed\Desktop\kibana-7.12.1-windows-x86_64\config

Make sure that, if you run Elasticsearch locally, you have changed the elasticsearch.hosts property in the kibana.yml file to http://localhost:9200.

Backing up Elasticsearch

Set up path.repo

Open the elasticsearch.yml file and add the following lines.

path.repo: "C:/Users/Niyas Hameed/Desktop/backup"

Open Kibana and navigate to Management > Stack Management > Snapshot and Restore > Repositories.
Click on Create repository and enter the details.
Click on Create policy and enter the details.
Navigate to Management > Stack Management > Snapshot and Restore > Snapshots.

Run the policy, and it will create a snapshot and store it in the repository.

More about the dataset

The dataset was manually curated by @niyasrad, which contains over

172 Songs
41 Albums
14 Artists
4 Main Genres

The data is populated via the /populate route, which takes in a CSV of all the song meta data - Title, Aritst, Album, Genre, Length. The CSV is parsed, and the data is inserted into the database. The tags field is populated for songs, albums, and artists. The tags field is a list of strings, and is used for searching.

MP3 Files, are directly downloaded over from YouTube using FFMpeg, and at the worst possible quality, download and audio conversion for 172 songs takes roughly, 90 minutes.

Album Artwork, and song tags are taken via the Last FM API. All of the MP3, and all of the album artwork is stored as a static file over cdn_assets/ folder in the backend, and is accessible easily for the front-end.

K8s Deployment & Services

First, we'll need a certificate (.PEM format) to bypass the https error. Once minikube is installed,

minikube start

If you're using Windows, This is to use the docker daemon inside minikube. Else, use eval $(minikube docker-env) for Linux.

$(minikube docker-env)

To activate the minikube docker daemon in powershell, use the following command,

& minikube -p minikube docker-env --shell powershell | Invoke-Expression

To access the minikube dashboard,

minikube dashboard

Postgres K8

Create a Dockerfile, sample given here with the back-up script

FROM postgres:latest

ENV POSTGRES_USER=postgres
ENV POSTGRES_PASSWORD=user
ENV POSTGRES_DB=rhythmb

ENV PGDATA=/var/tmp/hostpath-provisioner/postgresql/data
RUN mkdir -p $PGDATA && chown -R postgres:postgres $PGDATA

COPY ./rhythmb.sql /docker-entrypoint-initdb.d/

EXPOSE 5432

Build the image,

docker build -t rhythmb-postgres .

Create a deployment, service refer to the k8.yaml in the repo for sample. This is an example for the Persistent Volume,

apiVersion: v1
kind: PersistentVolume
metadata:
  name: postgres-pv
  labels:
    type: local
    app: postgres
spec:
  capacity:
    storage: 1Gi
  volumeMode: Filesystem
  accessModes:
    - ReadWriteOnce
  persistentVolumeReclaimPolicy: Retain
  storageClassName: manual
  hostPath:
    path: /var/tmp/hostpath-provisioner/postgresql/data

Frontend NGINX K8

Create a Dockerfile, sample given here with the back-up script

FROM node:21-alpine3.18 as build-stage
WORKDIR /usr/src/app

COPY package*.json ./
RUN npm install
COPY . .

RUN npm run build

FROM nginx:latest
COPY nginx.conf /etc/nginx/conf.d/default.conf
COPY --from=build-stage /usr/src/app/dist /usr/share/nginx/html
EXPOSE 80

CMD ["nginx", "-g", "daemon off;"]

And here, let's focus on the proxy to back-end in nginx.conf file,

location /api/ {
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;
        proxy_set_header content_type "application/json";

        add_header Access-Control-Allow-Origin *;
        add_header Access-Control-Allow-Methods "GET, POST, OPTIONS, PUT, DELETE";
        add_header Access-Control-Allow-Headers "Authorization";

        proxy_set_header Authorization $http_authorization;

        proxy_pass_request_headers on;
        proxy_http_version 1.1;
        proxy_request_buffering off;
        proxy_buffering off;

        rewrite ^/api(/.*)$ $1 break;
        proxy_pass http://backend-service:8000/;
    }

The concept here is that, the nginx container will be running on port 80, and the backend-service will be running on port 8000. So, we're proxying the requests from nginx to backend-service. This ensures that, the browser doesn't throw not found errors, and the requests are proxied to the backend service in K8s without any issues.

This is useful when you're using a single domain, and you want to proxy the requests to the backend service. This is also useful when you're using a single domain, and you want to proxy the requests to the backend service, and you want to use a single domain for both the frontend and the backend.

Redis Caching

The project involves Redis caching. The way it works is, instead of hitting the DB for every single UUID query with GET endpoint, we'll store the song data, and cache it in Redis, which runs as a k8 depoyment, and is accessed via service. This ensures optimal way of using the Database, and avoids a lot of performance issues.

FROM redis:latest
COPY redis.conf /usr/local/etc/redis/redis.conf
EXPOSE 6379

CMD ["redis-server", "/usr/local/etc/redis/redis.conf"]

The Dockerfile for Redis, uses a .conf file, which ensures security and other options.

Note

You can use imagePullPolicy: Never, if you're using a local image.
You can use imagePullPolicy: Always, if you're using a remote image.
Also write the PVC, PV for the postgres instance. Refer to the k8.yaml in the repo for sample.
Do not have multiple replicas for the postgres instance, as it will cause issues with the database, and the storing of data. (Might store different data in different pods, and will cause issues with the database)
Instead of port-forwarding, using the proxy with nginx is a better option, as it will ensure that the requests are proxied to the backend service in K8s without any issues in local development, as well as in production.

Once done, apply the yaml file,

kubectl apply -f k8.yaml

This will create a deployment, and a service for the postgres instance. Check the status of these using,

kubectl get deployments
kubectl get services
kubectl get pods
kubectl get pvc
kubectl get pv

If you have any issues, you can check the logs using,

kubectl describe pods

Helm Chart for K8s

Helm is a package manager for Kubernetes. It is the best way to find, share, and use software built for Kubernetes. Helm is a tool that streamlines installing and managing Kubernetes applications. Think of it like apt/yum/homebrew for Kubernetes.

Frontend - Deployment, Service
Backend - Deployment, Service
Redis - Deployment, Service
Postgres - Deployment, Service, PV, PV-Claim

To use the helm chart, install helm in your local machine, and run the following commands,

helm install rhythmb ./helm-rhythmb/helm-rhythmb-0.1.0.tgz

You can edit the values.yaml file in the helm-rhythmb folder to change the values, and the number of replicas, and other options. But if you're running locally, it's preferred to use the default values.

If you did not make any changes to the values.yaml file, you can use the following command to install the helm chart,

helm package ./helm-rhythmb

This will create a .tgz file, which you can use to install the helm chart.

To check the status of the helm chart, use the following command,

helm ls

To check the status of the pods, and services, use the following command,

kubectl get pods
kubectl get services

Name		Name	Last commit message	Last commit date
Latest commit History 73 Commits
.github		.github
backend		backend
docs_assets		docs_assets
frontend		frontend
helm-rhythmb		helm-rhythmb
postgres		postgres
redis		redis
.gitignore		.gitignore
README.md		README.md

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Welcome to the RhythmB Docs!

Contents

Tech Stack, Tools and Libraries

Backend

Frontend

Others

DB, Index and Design

Database

ORM - SQLAlchemy

Note

Song Schema (Example)

Search Index

Index Mapping

Song Index Mapping (Example)

Note

API Documentation

Setup

Backing up PostgreSQL

Backup Steps

Restore Steps

Elasticsearch Installation Steps

Kibana Installation Steps

Note

Backing up Elasticsearch

More about the dataset

K8s Deployment & Services

Postgres K8

Frontend NGINX K8

Redis Caching

Note

Helm Chart for K8s

Thank you! You can check out my other projects!

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