Update app.py

app.py

@@ -1,4 +1,4 @@
-# app.py (FULL REPLACEMENT - openpyxl engine forced + HF stable upload + Grade>=C pass)
+# app.py (FINAL FULL REPLACEMENT - no NoneType crashes + openpyxl forced + Grade>=C pass)
 import streamlit as st
 import pandas as pd
 import numpy as np
@@ -21,17 +21,14 @@ def grade_pass_fail(g):
         return "Unknown"
     g = str(g).strip().upper()
 
-    # Explicit FAIL
     if g.startswith(("D", "E", "F")):
         return "Fail"
 
-    # C- is FAIL, all other C variants are PASS
     if g.startswith("C"):
         if g == "C-" or g.startswith("C-"):
             return "Fail"
         return "Pass"
 
-    # A/B (with any +/-) are PASS
     if g.startswith(("A", "B")):
         return "Pass"
 
@@ -155,10 +152,8 @@ def make_fail_reason_hints(df: pd.DataFrame, component_cols: list[str]) -> pd.Da
 
 
 # -----------------------------
-# Upload (HF stable via session_state)
+# Session state init
 # -----------------------------
-uploaded = st.file_uploader("Upload Excel (.xlsx)", type=["xlsx"], key="uploader")
-
 if "file_bytes" not in st.session_state:
     st.session_state["file_bytes"] = None
 if "file_name" not in st.session_state:
@@ -166,21 +161,43 @@ if "file_name" not in st.session_state:
 if "sheet_names" not in st.session_state:
     st.session_state["sheet_names"] = None
 
-# Persist bytes across reruns
+# Reset button (helps a lot on HF reruns)
+topc1, topc2 = st.columns([1, 3])
+with topc1:
+    if st.button("🔄 Reset upload"):
+        st.session_state["file_bytes"] = None
+        st.session_state["file_name"] = None
+        st.session_state["sheet_names"] = None
+        st.rerun()
+
+with topc2:
+    if st.session_state["file_name"]:
+        st.info(f"Current file loaded: {st.session_state['file_name']}")
+
+# -----------------------------
+# Upload
+# -----------------------------
+uploaded = st.file_uploader("Upload Excel (.xlsx)", type=["xlsx"], key="uploader")
+
+# On upload, store bytes
 if uploaded is not None:
-    st.session_state["file_bytes"] = uploaded.getvalue()
-    st.session_state["file_name"] = uploaded.name
-    st.session_state["sheet_names"] = None  # reset on new upload
+    fb = uploaded.getvalue()
+    # fb can *rarely* be None/empty on buggy reruns; guard it
+    if fb:
+        st.session_state["file_bytes"] = fb
+        st.session_state["file_name"] = uploaded.name
+        st.session_state["sheet_names"] = None
 
-if st.session_state["file_bytes"] is None:
+# Re-check bytes RIGHT BEFORE use
+file_bytes = st.session_state.get("file_bytes", None)
+
+if file_bytes is None or not isinstance(file_bytes, (bytes, bytearray)) or len(file_bytes) == 0:
     st.info("Upload an Excel file to begin.")
     st.stop()
 
-file_bytes = st.session_state["file_bytes"]
-
-# Quick signature check (xlsx is a zip, starts with PK)
-if not (len(file_bytes) >= 2 and file_bytes[:2] == b"PK"):
-    st.error("This does not look like a valid .xlsx file. Please re-export/download as Excel (.xlsx) and upload again.")
+# Signature check for XLSX (zip => PK)
+if len(file_bytes) < 2 or file_bytes[:2] != b"PK":
+    st.error("This does not look like a valid .xlsx file. Please Save As → Excel Workbook (.xlsx) and upload again.")
     st.stop()
 
 # Load sheet names (FORCE openpyxl)
@@ -225,7 +242,7 @@ df = add_consistency(df, component_cols)
 df = make_fail_reason_hints(df, component_cols)
 
 # -----------------------------
-# Sidebar: "Power BI pages"
+# Sidebar: Views + Filters
 # -----------------------------
 st.sidebar.header("Perspective")
 view = st.sidebar.radio(
@@ -273,15 +290,15 @@ def executive_view(d: pd.DataFrame):
 
     with left:
         st.subheader("Grade Distribution")
-        grade_counts = d["Grade"].value_counts(dropna=False).reset_index()
-        grade_counts.columns = ["Grade", "Count"]
-        st.plotly_chart(px.bar(grade_counts, x="Grade", y="Count"), use_container_width=True)
+        gc = d["Grade"].value_counts(dropna=False).reset_index()
+        gc.columns = ["Grade", "Count"]
+        st.plotly_chart(px.bar(gc, x="Grade", y="Count"), use_container_width=True)
 
     with right:
         st.subheader("Pass/Fail Distribution")
-        pf_counts = d["PassFail"].value_counts(dropna=False).reset_index()
-        pf_counts.columns = ["Status", "Count"]
-        st.plotly_chart(px.pie(pf_counts, names="Status", values="Count"), use_container_width=True)
+        pc = d["PassFail"].value_counts(dropna=False).reset_index()
+        pc.columns = ["Status", "Count"]
+        st.plotly_chart(px.pie(pc, names="Status", values="Count"), use_container_width=True)
 
     st.subheader("Hidden Patterns (Quick Signals)")
     c1, c2, c3 = st.columns(3)
@@ -375,7 +392,6 @@ def export_view(d: pd.DataFrame):
     st.download_button("⬇️ Download Cleaned Data (CSV)", clean_csv, file_name="cleaned_marks_with_passfail.csv", mime="text/csv")
 
 
-# Render view
 if view == "Executive (Management)":
     executive_view(filtered)
 elif view == "Risk & Intervention":