Update data_app.py

data_app.py

@@ -2,40 +2,29 @@ import streamlit as st
 import pandas as pd
 from datetime import datetime
 import os
-from huggingface_hub import HfApi, snapshot_download
+from huggingface_hub import HfApi
 
 st.set_page_config(page_title="🔧 Service Tech Tracker", layout="wide")
 st.title("🔧 Service Tech Fuel & Job Tracker")
 
-# ====================== HF DATASET SETUP ======================
-HF_REPO = "AddisonSwan/service-tech-tracker"
+# ====================== HF TOKEN SETUP ======================
 HF_TOKEN = st.secrets.get("HF_TOKEN")
+if not HF_TOKEN:
+    HF_TOKEN = st.sidebar.text_input("Enter your HF Token (for backup)", type="password")
 
-def load_mileage():
-    try:
-        # Try to download latest data
-        snapshot_download(repo_id=HF_REPO, repo_type="dataset", allow_patterns="mileage.csv", token=HF_TOKEN)
-        return pd.read_csv("mileage.csv")
-    except:
-        return pd.DataFrame(columns=["Date", "Country", "Region", "Price", "Miles", "Type", "Notes"])
+HF_REPO = "AddisonSwan/service-tech-tracker"
 
-def save_mileage(df):
-    df.to_csv("mileage.csv", index=False)
-    try:
-        api = HfApi(token=HF_TOKEN)
-        api.upload_file(
-            path_or_fileobj="mileage.csv",
-            path_in_repo="mileage.csv",
-            repo_id=HF_REPO,
-            repo_type="dataset"
-        )
-        st.success("✅ Saved to Hugging Face Dataset")
-    except:
-        st.warning("Saved locally only")
+def backup_to_hf(filename="mileage.csv"):
+    if HF_TOKEN and os.path.exists(filename):
+        try:
+            api = HfApi(token=HF_TOKEN)
+            api.upload_file(path_or_fileobj=filename, path_in_repo=filename, repo_id=HF_REPO, repo_type="dataset")
+            st.success("✅ Backed up to Hugging Face")
+        except:
+            st.warning("Backup failed - check token")
 
-# Create local folders
+# Create folders
 os.makedirs("data", exist_ok=True)
-os.makedirs("jobs", exist_ok=True)
 
 page = st.sidebar.radio("Go to", ["Gas & Mileage", "New Job", "All Data"])
 
@@ -63,13 +52,18 @@ if page == "Gas & Mileage":
             "Notes": notes
         }])
         
-        df = load_mileage()
-        df = pd.concat([df, new_row], ignore_index=True)
-        save_mileage(df)
-    
-    df = load_mileage()
-    if not df.empty:
-        st.dataframe(df)
+        try:
+            df = pd.read_csv("data/mileage.csv")
+            df = pd.concat([df, new_row], ignore_index=True)
+        except:
+            df = new_row
+        df.to_csv("data/mileage.csv", index=False)
+        
+        backup_to_hf("data/mileage.csv")
+        st.success("✅ Saved!")
+
+    if os.path.exists("data/mileage.csv"):
+        st.dataframe(pd.read_csv("data/mileage.csv"))
 
 elif page == "New Job":
     st.subheader("📁 New Job")
@@ -80,4 +74,9 @@ elif page == "New Job":
         os.makedirs(f"jobs/{job_id}", exist_ok=True)
         st.success(f"Job {job_id} created!")
 
-st.caption("Connected to Hugging Face Dataset • Private Cloud Backup")
+elif page == "All Data":
+    st.subheader("All Records")
+    if os.path.exists("data/mileage.csv"):
+        st.dataframe(pd.read_csv("data/mileage.csv"))
+
+st.caption("Service Tech Tracker • Connected to HF")