Update app.py

app.py

@@ -1,149 +1,156 @@
 import gradio as gr
 import pandas as pd
 import gspread
-from gspread.exceptions import WorksheetNotFound
+from gspread_dataframe import set_with_dataframe
 from oauth2client.service_account import ServiceAccountCredentials
 from datetime import datetime, timedelta
-from gspread_dataframe import set_with_dataframe
 
 # -------------------- CONFIG --------------------
-SHEET_URL        = "https://docs.google.com/spreadsheets/d/1if4KoVQvw5ZbhknfdZbzMkcTiPfsD6bz9V3a1th-bwQ"
-USER_SHEET_NAME  = "Users"   # <-- must match (or contain) your “Users” tab
+SHEET_URL = "https://docs.google.com/spreadsheets/d/1if4KoVQvw5ZbhknfdZbzMkcTiPfsD6bz9V3a1th-bwQ"
+CREDS_JSON = "deep-mile-461309-t8-0e90103411e0.json"
 
 # -------------------- AUTH --------------------
 scope = [
     "https://spreadsheets.google.com/feeds",
-    "https://www.googleapis.com/auth/drive",
+    "https://www.googleapis.com/auth/drive"
 ]
-creds  = ServiceAccountCredentials.from_json_keyfile_name(
-    "deep-mile-461309-t8-0e90103411e0.json", scope
-)
+creds  = ServiceAccountCredentials.from_json_keyfile_name(CREDS_JSON, scope)
 client = gspread.authorize(creds)
 
-# -------------------- FUZZY WORKSHEET LOOKUP --------------------
-def open_ws_by_substring(substr: str):
-    """
-    Try exact match, then fall back to the first worksheet
-    whose title contains `substr` (case-insensitive).
-    """
-    sh = client.open_by_url(SHEET_URL)
-    try:
-        return sh.worksheet(substr)
-    except WorksheetNotFound:
-        for ws in sh.worksheets():
-            if substr.lower() in ws.title.lower():
-                return ws
-    raise WorksheetNotFound(f"No tab matching '{substr}'")
-
-# -------------------- SHEET UTILS --------------------
-def normalize_columns(df: pd.DataFrame) -> pd.DataFrame:
+# -------------------- SHEET LOAD/UTILS --------------------
+def normalize_columns(df):
     df.columns = df.columns.str.strip().str.title()
     return df
 
-def load_sheet(sheet_name: str) -> pd.DataFrame:
-    """Return a DataFrame of the entire sheet, or an Error row."""
+def load_sheet_df(sheet_name):
     try:
-        ws = open_ws_by_substring(sheet_name)
-        df = pd.DataFrame(ws.get_all_records())
+        ws     = client.open_by_url(SHEET_URL).worksheet(sheet_name)
+        records= ws.get_all_records()
+        df     = pd.DataFrame(records)
         return normalize_columns(df)
     except Exception as e:
+        # return a one-row DF with an Error column
         return pd.DataFrame([{"Error": str(e)}])
 
-def load_sheet_df(sheet_name: str) -> pd.DataFrame:
-    """Like load_sheet, but lets WorksheetNotFound bubble up."""
-    ws = open_ws_by_substring(sheet_name)
-    df = pd.DataFrame(ws.get_all_records())
-    return normalize_columns(df)
-
-# -------------------- DATE FILTER HELPERS --------------------
+# -------------------- DATE FILTERS --------------------
 def get_current_week_range():
-    today = datetime.now().date()
+    today = datetime.now()
     start = today - timedelta(days=today.weekday())
     end   = start + timedelta(days=6)
-    return start, end
-
-def filter_week(df, date_col, rep_col=None, rep=None):
-    df[date_col] = pd.to_datetime(df[date_col], errors="coerce").dt.date
-    start, end = get_current_week_range()
-    out = df[(df[date_col] >= start) & (df[date_col] <= end)]
-    if rep:
-        out = out[out[rep_col] == rep]
+    return start.date(), end.date()
+
+def filter_week(df, date_column, rep_column=None, rep=None):
+    df[date_column] = pd.to_datetime(df[date_column], errors="coerce").dt.date
+    start,end      = get_current_week_range()
+    out = df[(df[date_column] >= start) & (df[date_column] <= end)]
+    if rep and rep in out.columns:
+        out = out[out[rep_column] == rep]
     return out
 
-def filter_date(df, date_col, rep_col, y, m, d, rep):
+def filter_date(df, date_column, rep_column, y,m,d, rep):
     try:
         target = datetime(int(y), int(m), int(d)).date()
     except:
-        return pd.DataFrame([{"Error": "Invalid date"}])
-    df[date_col] = pd.to_datetime(df[date_col], errors="coerce").dt.date
-    out = df[df[date_col] == target]
-    if rep:
-        out = out[out[rep_col] == rep]
+        return pd.DataFrame([{"Error":"Invalid date"}])
+    df[date_column] = pd.to_datetime(df[date_column], errors="coerce").dt.date
+    out = df[df[date_column] == target]
+    if rep and rep in out.columns:
+        out = out[out[rep_column] == rep]
     return out
 
-# -------------------- REPORT FUNCTIONS --------------------
+# -------------------- REPORT DATA --------------------
 def get_calls(rep=None):
-    df = load_sheet("Calls")
+    df = load_sheet_df("Calls")
     if "Call Date" not in df.columns:
-        return df
+        return pd.DataFrame([{"Error":"Missing 'Call Date' column"}])
     return filter_week(df, "Call Date", "Rep", rep)
 
-def search_calls_by_date(y, m, d, rep):
-    df = load_sheet("Calls")
-    if "Call Date" not in df.columns:
+def get_calls_summary(rep=None):
+    df = get_calls(rep)
+    if "Error" in df.columns or df.empty:
         return df
-    return filter_date(df, "Call Date", "Rep", y, m, d, rep)
+    return (
+        df.groupby("Rep")
+          .size()
+          .reset_index(name="Count")
+          .sort_values("Count", ascending=False)
+    )
+
+def search_calls_by_date(y,m,d, rep):
+    df = load_sheet_df("Calls")
+    if "Call Date" not in df.columns:
+        return pd.DataFrame([{"Error":"Missing 'Call Date' column"}])
+    return filter_date(df, "Call Date", "Rep", y,m,d, rep)
 
 def get_appointments(rep=None):
-    df = load_sheet("Appointments")
+    df = load_sheet_df("Appointments")
     if "Appointment Date" not in df.columns:
-        return df
+        return pd.DataFrame([{"Error":"Missing 'Appointment Date' column"}])
     return filter_week(df, "Appointment Date", "Rep", rep)
 
-def search_appointments_by_date(y, m, d, rep):
-    df = load_sheet("Appointments")
-    if "Appointment Date" not in df.columns:
+def get_appointments_summary(rep=None):
+    df = get_appointments(rep)
+    if "Error" in df.columns or df.empty:
         return df
-    return filter_date(df, "Appointment Date", "Rep", y, m, d, rep)
+    return (
+        df.groupby("Rep")
+          .size()
+          .reset_index(name="Count")
+          .sort_values("Count", ascending=False)
+    )
+
+def search_appointments_by_date(y,m,d, rep):
+    df = load_sheet_df("Appointments")
+    if "Appointment Date" not in df.columns:
+        return pd.DataFrame([{"Error":"Missing 'Appointment Date' column"}])
+    return filter_date(df, "Appointment Date", "Rep", y,m,d, rep)
 
 def get_leads_detail():
-    return load_sheet("AllocatedLeads")
+    df = load_sheet_df("AllocatedLeads")
+    # rename if needed
+    df = df.rename(columns={"Assigned Rep":"Assigned Rep"})
+    if "Assigned Rep" not in df.columns:
+        return pd.DataFrame([{"Error":"Missing 'Assigned Rep' col"}])
+    return df
 
 def get_leads_summary():
     df = get_leads_detail()
     if "Error" in df.columns:
         return df
-    return df.groupby("Assigned Rep")\
-             .size()\
-             .reset_index(name="Leads Count")
+    return df.groupby("Assigned Rep").size().reset_index(name="Leads Count")
 
+# -------------------- INSIGHTS --------------------
 def compute_insights():
     calls = get_calls()
     appts = get_appointments()
     leads = get_leads_detail()
 
     def top_rep(df, col):
-        if "Error" in df.columns or df.empty or col not in df.columns:
+        if "Error" in df.columns or df.empty:
             return "N/A"
-        return df.groupby(col).size().idxmax()
+        counts = df.groupby(col).size()
+        if counts.empty:
+            return "N/A"
+        return counts.idxmax()
 
-    data = [
-        {"Metric": "Most Calls This Week",        "Rep": top_rep(calls, "Rep")},
-        {"Metric": "Most Appointments This Week", "Rep": top_rep(appts, "Rep")},
-        {"Metric": "Most Leads Allocated",        "Rep": top_rep(leads, "Assigned Rep")},
-    ]
-    return pd.DataFrame(data)
+    top_calls = top_rep(calls, "Rep")
+    top_appts = top_rep(appts, "Rep")
+    # unify column name for leads
+    leads = leads.rename(columns={"Assigned Rep":"Rep"})
+    top_leads = top_rep(leads, "Rep")
 
-def rep_options(sheet, col):
-    df = load_sheet(sheet)
-    if col in df.columns:
-        return sorted(df[col].dropna().unique().tolist())
-    return []
+    return pd.DataFrame([
+        {"Metric":"Most Calls This Week",        "Rep":top_calls},
+        {"Metric":"Most Appointments This Week", "Rep":top_appts},
+        {"Metric":"Most Leads Allocated",        "Rep":top_leads},
+    ])
 
 # -------------------- USER MANAGEMENT --------------------
-def load_users() -> pd.DataFrame:
-    cols = [
-        "ID","Email","Name","Business","Role",
+def load_users():
+    df = load_sheet_df("userAccess")  # your actual tab name
+    # pick & title-case only the cols you want
+    wanted = [
+        "Id","Email","Name","Business","Role",
         "Daily Phone Call Target","Daily Phone Appointment Target",
         "Daily Quote Number Target","Daily Quote Revenue Target",
         "Weekly Phone Call Target","Weekly Phone Appointment Target",
@@ -152,151 +159,115 @@ def load_users() -> pd.DataFrame:
         "Monthly Quote Number Target","Monthly Quote Revenue Target",
         "Monthly Sales Revenue Target"
     ]
-    try:
-        return load_sheet_df(USER_SHEET_NAME)
-    except WorksheetNotFound:
-        return pd.DataFrame(columns=cols)
+    exist = [c for c in wanted if c in df.columns]
+    return df[exist]
 
-def save_users(df: pd.DataFrame):
-    ws = client.open_by_url(SHEET_URL).worksheet(USER_SHEET_NAME)
+def save_users(df):
+    ws = client.open_by_url(SHEET_URL).worksheet("userAccess")
     ws.clear()
     set_with_dataframe(ws, df)
     return "✅ Users saved!"
 
-# -------------------- BUILD UI --------------------
-with gr.Blocks(title="Graffiti Admin Dashboard") as app:
+# -------------------- GRADIO UI --------------------
+with gr.Blocks(title="📆 Graffiti Admin Dashboard") as app:
     gr.Markdown("# 📆 Graffiti Admin Dashboard")
 
-    # -- Calls Report --
+    # ─── Calls Report ─────────────────────────────
     with gr.Tab("Calls Report"):
-        rep_calls = gr.Dropdown(choices=rep_options("Calls","Rep"),
-                                label="Optional Rep Filter",
-                                allow_custom_value=True)
-        calls_btn = gr.Button("Load Current Week Calls")
-
-        with gr.Row():
-            with gr.Column():
-                calls_sum = gr.Dataframe(label="📊 Calls by Rep")
-            with gr.Column():
-                calls_det = gr.Dataframe(label="🔎 Detailed Calls")
+        rep_calls = gr.Dropdown(
+            label="Optional Rep Filter",
+            choices=load_sheet_df("Calls")["Rep"].dropna().unique().tolist(),
+            allow_custom_value=True
+        )
+        calls_btn     = gr.Button("Load Current Week Calls")
+        calls_summary = gr.Dataframe(label="📊 Calls by Rep")
+        calls_table   = gr.Dataframe(label="🔎 Detailed Calls")
 
         calls_btn.click(
-            fn=lambda r: (
-                get_calls(r).groupby("Rep")
-                            .size()
-                            .reset_index(name="Count"),
-                get_calls(r)
-            ),
+            fn=lambda r: (get_calls_summary(r), get_calls(r)),
             inputs=rep_calls,
-            outputs=[calls_sum, calls_det]
+            outputs=[calls_summary, calls_table]
         )
 
         gr.Markdown("### 🔍 Search Calls by Specific Date")
-        y1 = gr.Textbox(label="Year")
-        m1 = gr.Textbox(label="Month")
-        d1 = gr.Textbox(label="Day")
-        rep1 = gr.Dropdown(choices=rep_options("Calls","Rep"),
-                           label="Optional Rep Filter",
-                           allow_custom_value=True)
-        calls_date_btn = gr.Button("Search Calls by Date")
-
-        with gr.Row():
-            with gr.Column():
-                calls_date_sum = gr.Dataframe(label="📊 Calls by Rep on Date")
-            with gr.Column():
-                calls_date_det = gr.Dataframe(label="🔎 Detailed Calls on Date")
+        y1,m1,d1 = gr.Textbox(label="Year"), gr.Textbox(label="Month"), gr.Textbox(label="Day")
+        rep1     = gr.Dropdown(
+            label="Optional Rep Filter",
+            choices=load_sheet_df("Calls")["Rep"].dropna().unique().tolist(),
+            allow_custom_value=True
+        )
+        calls_date_btn   = gr.Button("Search Calls by Date")
+        calls_date_table = gr.Dataframe()
 
         calls_date_btn.click(
-            fn=lambda y,m,d,r: (
-                search_calls_by_date(y,m,d,r)
-                  .groupby("Rep")
-                  .size()
-                  .reset_index(name="Count"),
-                search_calls_by_date(y,m,d,r)
-            ),
+            fn=search_calls_by_date,
             inputs=[y1,m1,d1,rep1],
-            outputs=[calls_date_sum, calls_date_det]
+            outputs=calls_date_table
         )
 
-    # -- Appointments Report --
+    # ─── Appointments Report ─────────────────────
     with gr.Tab("Appointments Report"):
-        rep_appt = gr.Dropdown(choices=rep_options("Appointments","Rep"),
-                               label="Optional Rep Filter",
-                               allow_custom_value=True)
-        appt_btn  = gr.Button("Load Current Week Appointments")
-
-        with gr.Row():
-            with gr.Column():
-                appt_sum = gr.Dataframe(label="📊 Weekly Appointments Summary by Rep")
-            with gr.Column():
-                appt_det = gr.Dataframe(label="🔎 Detailed Appointments")
+        rep_appt = gr.Dropdown(
+            label="Optional Rep Filter",
+            choices=load_sheet_df("Appointments")["Rep"].dropna().unique().tolist(),
+            allow_custom_value=True
+        )
+        appt_btn      = gr.Button("Load Current Week Appointments")
+        appt_summary  = gr.Dataframe(label="📊 Appts by Rep")
+        appt_table    = gr.Dataframe(label="🔎 Detailed Appointments")
 
         appt_btn.click(
-            fn=lambda r: (
-                get_appointments(r)
-                  .groupby("Rep")
-                  .size()
-                  .reset_index(name="Count"),
-                get_appointments(r)
-            ),
+            fn=lambda r: (get_appointments_summary(r), get_appointments(r)),
             inputs=rep_appt,
-            outputs=[appt_sum, appt_det]
+            outputs=[appt_summary, appt_table]
         )
 
         gr.Markdown("### 🔍 Search Appointments by Specific Date")
-        y2 = gr.Textbox(label="Year")
-        m2 = gr.Textbox(label="Month")
-        d2 = gr.Textbox(label="Day")
-        rep2 = gr.Dropdown(choices=rep_options("Appointments","Rep"),
-                           label="Optional Rep Filter",
-                           allow_custom_value=True)
-        appt_date_btn = gr.Button("Search Appointments by Date")
-
-        with gr.Row():
-            with gr.Column():
-                appt_date_sum = gr.Dataframe(label="📊 Appts by Rep on Date")
-            with gr.Column():
-                appt_date_det = gr.Dataframe(label="🔎 Detailed Appts on Date")
+        y2,m2,d2 = gr.Textbox(label="Year"), gr.Textbox(label="Month"), gr.Textbox(label="Day")
+        rep2     = gr.Dropdown(
+            label="Optional Rep Filter",
+            choices=load_sheet_df("Appointments")["Rep"].dropna().unique().tolist(),
+            allow_custom_value=True
+        )
+        appt_date_btn     = gr.Button("Search Appts by Date")
+        appt_date_summary = gr.Dataframe(label="📊 Appts Summary by Rep")
+        appt_date_table   = gr.Dataframe()
 
         appt_date_btn.click(
             fn=lambda y,m,d,r: (
-                search_appointments_by_date(y,m,d,r)
-                  .groupby("Rep")
-                  .size()
-                  .reset_index(name="Count"),
+                (lambda df: df.groupby("Rep").size().reset_index(name="Count"))(search_appointments_by_date(y,m,d,r)),
                 search_appointments_by_date(y,m,d,r)
             ),
             inputs=[y2,m2,d2,rep2],
-            outputs=[appt_date_sum, appt_date_det]
+            outputs=[appt_date_summary, appt_date_table]
         )
 
-    # -- Appointed Leads --
+    # ─── Appointed Leads ──────────────────────────
     with gr.Tab("Appointed Leads"):
-        leads_btn = gr.Button("View Appointed Leads")
-
-        with gr.Row():
-            with gr.Column():
-                leads_sum    = gr.Dataframe(label="📊 Leads Count by Rep")
-            with gr.Column():
-                leads_det    = gr.Dataframe(label="🔎 Detailed Leads")
+        leads_btn     = gr.Button("View Appointed Leads")
+        leads_summary = gr.Dataframe(label="📊 Leads Count by Rep")
+        leads_detail  = gr.Dataframe(label="🔎 Detailed Leads")
 
         leads_btn.click(
             fn=lambda: (get_leads_summary(), get_leads_detail()),
-            outputs=[leads_sum, leads_det]
+            outputs=[leads_summary, leads_detail]
         )
 
-    # -- Insights --
+    # ─── Insights ─────────────────────────────────
     with gr.Tab("Insights"):
         insights_btn = gr.Button("Generate Insights")
         insights_tbl = gr.Dataframe()
+
         insights_btn.click(fn=compute_insights, outputs=insights_tbl)
 
-    # -- User Management --
+    # ─── User Management ──────────────────────────
     with gr.Tab("User Management"):
-        gr.Markdown("### 🙍 Manage Users  \nEdit the grid and click **Save Users**.")
+        gr.Markdown("## 👤 Manage Users\nEdit/add/remove rows below, then click **Save Users**.")
         users_tbl = gr.Dataframe(value=load_users(), interactive=True)
         save_btn  = gr.Button("Save Users")
-        save_msg  = gr.Textbox(interactive=False)
-        save_btn.click(fn=save_users, inputs=users_tbl, outputs=save_msg)
+        status    = gr.Textbox()
+
+        save_btn.click(fn=save_users, inputs=users_tbl, outputs=status)
 
-    app.launch()
+    # end Blocks
+app.launch()