Development frontend

README.md

@@ -0,0 +1,43 @@
+This is a [Next.js](https://nextjs.org) project bootstrapped with [`create-next-app`](https://nextjs.org/docs/app/api-reference/cli/create-next-app).
+
+## Getting Started
+
+First, run the development server:
+
+```bash
+npm run dev
+# or
+yarn dev
+# or
+pnpm dev
+# or
+bun dev
+```
+# In our intermediate project we aimed to create a set of graphs indentifying key trends within our dataset as well as a gameplay that allows the user to input their choices in different attributes (ex. liveliness, energy, danceability, etc.) and the program will offer the user five songs that have matching outputs. This project not only has many implications for helping in the field of AI music, but offers some unique prospectives for the viewers. Additionally the program requires extensive use of databases to work. We were able to successfully create the set of graphs and design the website. 
+To run clone the repository and in one terminal run 
+  uvicorn backend.main:app --reload
+Second terminal for the frontend run
+  npm run dev
+There might be libary issues which might need to be installed either using homebrew or pip.
+Such as:
+  pip install kagglehub
+Open [http://localhost:3000](http://localhost:3000) with your browser to see the result.
+
+You can start editing the page by modifying `app/page.tsx`. The page auto-updates as you edit the file.
+
+This project uses [`next/font`](https://nextjs.org/docs/app/building-your-application/optimizing/fonts) to automatically optimize and load [Geist](https://vercel.com/font), a new font family for Vercel.
+
+## Learn More
+
+To learn more about Next.js, take a look at the following resources:
+
+- [Next.js Documentation](https://nextjs.org/docs) - learn about Next.js features and API.
+- [Learn Next.js](https://nextjs.org/learn) - an interactive Next.js tutorial.
+
+You can check out [the Next.js GitHub repository](https://github.com/vercel/next.js) - your feedback and contributions are welcome!
+
+## Deploy on Vercel
+
+The easiest way to deploy your Next.js app is to use the [Vercel Platform](https://vercel.com/new?utm_medium=default-template&filter=next.js&utm_source=create-next-app&utm_campaign=create-next-app-readme) from the creators of Next.js.
+
+Check out our [Next.js deployment documentation](https://nextjs.org/docs/app/building-your-application/deploying) for more details.

backend/main.py

@@ -1,21 +1,115 @@
 from fastapi import FastAPI
+import csv
 from fastapi.middleware.cors import CORSMiddleware
+import kagglehub
+from fastapi.responses import JSONResponse
+import os
+import shutil
 
+song_features = {}
 app = FastAPI()
 
-# Allow frontend access
+song_features = {}
+
 app.add_middleware(
     CORSMiddleware,
-    allow_origins=["*"],  # Adjust in production
+    allow_origins=["*"],
     allow_credentials=True,
     allow_methods=["*"],
     allow_headers=["*"],
 )
 
+def copy_file(source, destination):
+    try:
+        shutil.copy(source, destination)
+        print(f"File copied from {source} to {destination}")
+    except Exception as e:
+        print(f"Error: {e}")
+
+def reduce_csv_file_inplace(input_file, num_lines):
+    try:
+        with open(input_file, 'r+', newline='', encoding='utf-8') as file:
+            lines = file.readlines()
+            if len(lines) > num_lines:
+                file.seek(0)
+                file.writelines(lines[:num_lines])
+                file.truncate() 
+            else:
+                print("The CSV file has fewer than 500 lines, no truncation needed.")
+    except Exception as e:
+        print(f"Error: {e}")
+
+@app.get("/api/download_dataset")
+async def download_dataset():
+    try:
+        folder_path = 'data'
+        if os.path.exists(folder_path):
+            shutil.rmtree(folder_path)
+        os.makedirs(folder_path, exist_ok=True)
+        temp_path = kagglehub.dataset_download("amitanshjoshi/spotify-1million-tracks")
+        filename = os.path.basename(temp_path)
+        final_path = os.path.join(folder_path, filename)
+        shutil.move(temp_path, final_path)
+        input_file = 'data/1/spotify_data.csv'
+        reduce_csv_file_inplace(input_file, 1000)
+        parseData(input_file)
+    except Exception as e:
+      return JSONResponse(status_code=400, content={"message": str(e)})
+
 @app.get("/api/message")
 def get_message():
     return {"message": "Hello, World!"}
 
+@app.get("/api/data")
+def pass_value():
+    return song_features
+
 if __name__ == "__main__":
     import uvicorn
     uvicorn.run(app, host="0.0.0.0", port=8000)
+
+default_template = {
+    "artist_name": None,
+    "track_name": None,
+    "track_id": None,
+    "popularity": None,
+    "year": None,
+    "genre": None,
+    "danceability": None,
+    "energy": None,
+    "key": None,
+    "loudness": None,
+    "mode": None,
+    "speechiness": None,
+    "acousticness": None,
+    "instrumentalness": None,
+    "liveness": None,
+    "valence": None,
+    "tempo": None,
+    "duration_ms": None,
+    "time_signature": None
+}
+
+def parseData(inputfile):
+    with open(inputfile, newline="", encoding="utf-8") as file:
+        reader = csv.DictReader(file)
+        i = 1
+        for row in reader:
+            track_id = i
+            song_features[track_id] = default_template.copy()
+
+            song_features[track_id]["artist_name"] = row.get("artist_name")
+            song_features[track_id]["track_name"] = row.get("track_name")
+            song_features[track_id]["popularity"] = int(row.get("popularity", 0))/10
+            song_features[track_id]["key"] = int(row.get("key"))
+            song_features[track_id]["year"] = int(row.get("year", 0))
+            song_features[track_id]["danceability"] = float(row.get("danceability", 0.0))*10
+            song_features[track_id]["energy"] = float(row.get("energy", 0.0))*10
+            song_features[track_id]["loudness"] = float(row.get("loudness", -60.0))/2
+            song_features[track_id]["instrumentalness"] = float(row.get("instrumentalness", 0.0))*10
+            song_features[track_id]["liveness"] = float(row.get("liveness", 0.0))*10
+            song_features[track_id]["valence"] = float(row.get("valence", 0.0))*10
+            song_features[track_id]["tempo"] = float(row.get("tempo", 0))/20
+            song_features[track_id]["duration_ms"] = int(row.get("duration_ms", 0)) // 40000
+            song_features[track_id]["time_signature"] = int(row.get("time_signature", 0))
+            i+=1