Update src/streamlit_app.py

src/streamlit_app.py

@@ -2,40 +2,24 @@ import streamlit as st
 import pandas as pd
 import joblib
 import matplotlib.pyplot as plt
-import os
 
 # --------------------------------------
 # PAGE CONFIG
 # --------------------------------------
 st.set_page_config(page_title="Spotify Clustering", layout="wide")
+st.title("🎵 Spotify Music Clustering / Spotify Müzik Kümeleme")
+st.markdown("---")
 
 # --------------------------------------
-# AUTO PATH (LOCAL + HUGGING FACE)
-# --------------------------------------
-def get_path(filename):
-    # Olası tüm konumları kontrol et
-    base_dirs = [
-        ".",                 # çalıştırıldığı klasör
-        "..",                # bir üst klasör
-        os.path.dirname(os.path.abspath(__file__)),  # script klasörü
-        os.path.join(os.path.dirname(os.path.abspath(__file__)), ".."),
-        os.getcwd(),         # working dir
-        os.path.join(os.getcwd(), "..")
-    ]
-    for d in base_dirs:
-        path = os.path.join(d, filename)
-        if os.path.exists(path):
-            return path
-    # Eğer bulunamazsa
-    st.error(f"{filename} bulunamadı! Mevcut dosyalar: {os.listdir()}")
-    st.stop()
-
-DATA_PATH = get_path("spotify_clustered.csv")
-MODEL_PATH = get_path("kmeans_music_model.pkl")
-SCALER_PATH = get_path("scaler_music.pkl")
+# FILE PATHS
+# Dosyalar aynı klasörde olduğu için sadece isim yeter
+# --------------------------------------
+DATA_PATH = "spotify_clustered.csv"
+MODEL_PATH = "kmeans_music_model.pkl"
+SCALER_PATH = "scaler_music.pkl"
 
 # --------------------------------------
-# LOAD DATA (CACHE)
+# LOAD DATA & MODEL
 # --------------------------------------
 @st.cache_data
 def load_data():
@@ -60,12 +44,6 @@ if "prediction" not in st.session_state:
     st.session_state.prediction = None
     st.session_state.samples = None
 
-# --------------------------------------
-# TITLE
-# --------------------------------------
-st.title("🎵 Spotify Music Clustering / Spotify Müzik Kümeleme")
-st.markdown("---")
-
 # --------------------------------------
 # DATA PREVIEW
 # --------------------------------------
@@ -73,7 +51,7 @@ st.subheader("📄 Dataset Preview / Veri Önizleme")
 st.dataframe(df_display.head(10), use_container_width=True)
 
 # --------------------------------------
-# VISUALS
+# VISUALIZATIONS
 # --------------------------------------
 col1, col2 = st.columns(2)
 
@@ -83,7 +61,7 @@ with col1:
 
 with col2:
     st.subheader("🎯 Feature Analysis / Özellik Analizi")
-    fig, ax = plt.subplots(figsize=(6, 4))
+    fig, ax = plt.subplots(figsize=(6,4))
     scatter = ax.scatter(df['danceability'], df['energy'], c=df['cluster'], cmap='viridis', alpha=0.6)
     ax.set_xlabel("Danceability / Dans Edilebilirlik")
     ax.set_ylabel("Energy / Enerji")
@@ -115,9 +93,9 @@ if st.button("Predict Cluster / Kümeyi Tahmin Et ✨"):
         new_data_scaled = scaler.transform(new_data)
         res = model.predict(new_data_scaled)[0]
         st.session_state.prediction = res
-        st.session_state.samples = df[df['cluster'] == res][['track_name', 'artists']].head(5)
+        st.session_state.samples = df[df['cluster']==res][['track_name','artists']].head(5)
     except Exception as e:
-        st.error(f"Error / Hata: {e}")
+        st.error(f"Prediction Error / Tahmin Hatası: {e}")
 
 if st.session_state.prediction is not None:
     st.success(f"### Predicted Cluster / Tahmin Edilen Küme: {st.session_state.prediction}")
@@ -125,17 +103,11 @@ if st.session_state.prediction is not None:
     st.table(st.session_state.samples)
 
 # --------------------------------------
-# CLUSTER ANALYSIS
+# CLUSTER CHARACTERISTICS
 # --------------------------------------
 st.divider()
 st.subheader("🔍 Cluster Characteristics / Küme Özellikleri")
-numeric_only = df.select_dtypes(include=['float64', 'int64'])
+numeric_only = df.select_dtypes(include=['float64','int64'])
 if 'cluster' in df.columns:
     means = numeric_only.groupby(df['cluster']).mean()
-    st.dataframe(means, use_container_width=True)
-
-# --------------------------------------
-# DEBUG (Opsiyonel)
-# --------------------------------------
-# st.write("Current working dir:", os.getcwd())
-# st.write("Files here:", os.listdir())
+    st.dataframe(means, use_container_width=True)