Update app.py

app.py

@@ -4,109 +4,119 @@ import gspread
 from gspread_dataframe import set_with_dataframe
 from oauth2client.service_account import ServiceAccountCredentials
 from datetime import datetime, timedelta
-from collections import Counter
+
+# -------------------- CONFIG --------------------
+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"
 ]
-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)
 
-# YOUR SPREADSHEET URL
-SHEET_URL = "https://docs.google.com/spreadsheets/d/1if4KoVQvw5ZbhknfdZbzMkcTiPfsD6bz9V3a1th-bwQ"
+# -------------------- SHEET LOAD/UTILS --------------------
+def normalize_columns(df):
+    df.columns = df.columns.str.strip().str.title()
+    return df
 
-# -------------------- UTILS --------------------
-def normalize_columns(cols):
-    return [c.strip().title() for c in cols]
-
-def load_sheet_df(name):
-    """
-    Load a sheet into a DataFrame without confusing duplicates in
-    the header row. We fetch all values, dedupe the first row,
-    then build a DataFrame.
-    """
-    ws = client.open_by_url(SHEET_URL).worksheet(name)
-    data = ws.get_all_values()
-    if not data:
-        return pd.DataFrame()
-    raw_header, *rows = data
-    # make header unique
-    counts = Counter()
-    header = []
-    for col in raw_header:
-        counts[col] += 1
-        if counts[col] > 1:
-            header.append(f"{col}_{counts[col]}")
-        else:
-            header.append(col)
-    header = normalize_columns(header)
-    return pd.DataFrame(rows, columns=header)
+def load_sheet_df(sheet_name):
+    try:
+        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)}])
 
+# -------------------- 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_by_week(df, date_col, rep=None):
-    if date_col not in df.columns:
-        return pd.DataFrame([{"Error": f"Missing '{date_col}' column"}])
-    df = df.copy()
-    df[date_col] = pd.to_datetime(df[date_col], errors="coerce").dt.date
-    start, end = get_current_week_range()
-    m = df[date_col].between(start, end)
-    if rep:
-        m &= df.get("Rep", pd.Series()).astype(str) == rep
-    return df[m]
-
-def filter_by_date(df, date_col, y, m, d, rep=None):
+    end   = start + timedelta(days=6)
+    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_column, rep_column, y,m,d, rep):
     try:
         target = datetime(int(y), int(m), int(d)).date()
     except:
-        return pd.DataFrame([{"Error": "Invalid date"}])
-    if date_col not in df.columns:
-        return pd.DataFrame([{"Error": f"Missing '{date_col}' column"}])
-    df = df.copy()
-    df[date_col] = pd.to_datetime(df[date_col], errors="coerce").dt.date
-    m = df[date_col] == target
-    if rep:
-        m &= df.get("Rep", pd.Series()).astype(str) == rep
-    return df[m]
-
-def rep_choices(sheet, col="Rep"):
-    df = load_sheet_df(sheet)
-    return sorted(df[col].dropna().unique().tolist()) if col in df else []
-
-# -------------------- REPORT FUNCTIONS --------------------
+        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 DATA --------------------
 def get_calls(rep=None):
     df = load_sheet_df("Calls")
-    return filter_by_week(df, "Call Date", rep)
+    if "Call Date" not in df.columns:
+        return pd.DataFrame([{"Error":"Missing 'Call Date' column"}])
+    return filter_week(df, "Call Date", "Rep", rep)
+
+def get_calls_summary(rep=None):
+    df = get_calls(rep)
+    if "Error" in df.columns or df.empty:
+        return df
+    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_df("Appointments")
-    return filter_by_week(df, "Appointment Date", rep)
+    if "Appointment Date" not in df.columns:
+        return pd.DataFrame([{"Error":"Missing 'Appointment Date' column"}])
+    return filter_week(df, "Appointment Date", "Rep", rep)
 
-def search_calls(y, m, d, rep=None):
-    df = load_sheet_df("Calls")
-    return filter_by_date(df, "Call Date", y, m, d, rep)
+def get_appointments_summary(rep=None):
+    df = get_appointments(rep)
+    if "Error" in df.columns or df.empty:
+        return df
+    return (
+        df.groupby("Rep")
+          .size()
+          .reset_index(name="Count")
+          .sort_values("Count", ascending=False)
+    )
 
-def search_appointments(y, m, d, rep=None):
+def search_appointments_by_date(y,m,d, rep):
     df = load_sheet_df("Appointments")
-    return filter_by_date(df, "Appointment Date", y, m, d, rep)
+    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)
 
-# -------------------- LEADS --------------------
 def get_leads_detail():
     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 "Assigned Rep" not in df:
-        return pd.DataFrame([{"Error": "Missing 'Assigned Rep'"}])
+    if "Error" in df.columns:
+        return df
     return df.groupby("Assigned Rep").size().reset_index(name="Leads Count")
 
 # -------------------- INSIGHTS --------------------
@@ -115,101 +125,149 @@ def compute_insights():
     appts = get_appointments()
     leads = get_leads_detail()
 
-    def top(df, col="Rep"):
-        if col in df and not df.empty:
-            vc = df[col].value_counts()
-            return vc.idxmax() if not vc.empty else "N/A"
-        return "N/A"
+    def top_rep(df, col):
+        if "Error" in df.columns or df.empty:
+            return "N/A"
+        counts = df.groupby(col).size()
+        if counts.empty:
+            return "N/A"
+        return counts.idxmax()
 
-    data = [
-        {"Metric": "Most Calls This Week",        "Rep": top(calls, "Rep")},
-        {"Metric": "Most Appointments This Week", "Rep": top(appts, "Rep")},
-        {"Metric": "Most Leads Allocated",        "Rep": top(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")
+
+    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():
-    df = load_sheet_df("Users")
-    # select & rename your columns as needed
-    want = [
-        "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",
-        "Weekly Quote Number Target", "Weekly Quote Revenue Target",
-        "Monthly Phone Call Target", "Monthly Phone Appointment Target",
-        "Monthly Quote Number Target", "Monthly Quote Revenue Target",
+    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",
+        "Weekly Quote Number Target","Weekly Quote Revenue Target",
+        "Monthly Phone Call Target","Monthly Phone Appointment Target",
+        "Monthly Quote Number Target","Monthly Quote Revenue Target",
         "Monthly Sales Revenue Target"
     ]
-    exist = [c for c in want if c in df.columns]
+    exist = [c for c in wanted if c in df.columns]
     return df[exist]
 
 def save_users(df):
-    ws = client.open_by_url(SHEET_URL).worksheet("Users")
+    ws = client.open_by_url(SHEET_URL).worksheet("userAccess")
     ws.clear()
-    set_with_dataframe(ws, df)  # writes headers + data
+    set_with_dataframe(ws, df)
     return "✅ Users saved!"
 
-# -------------------- UI LAYOUT --------------------
-with gr.Blocks(title="Graffiti Admin Dashboard") as app:
-    gr.Markdown("# 📆 Graffiti Admin Dashboard")
+# -------------------- GRADIO UI --------------------
+with gr.Blocks(title="📆 Graffiti Field App Admin Dashboard") as app:
+    gr.Markdown("# 📆 Graffiti Field App Admin Dashboard")
 
-    # -- Calls Tab --
+    # ─── Calls Report ─────────────────────────────
     with gr.Tab("Calls Report"):
-        rep_c = gr.Dropdown(choices=rep_choices("Calls"), label="Filter by Rep", allow_custom_value=True)
-        btn_c = gr.Button("Load This Week’s Calls")
-        tbl_c = gr.Dataframe()
-        btn_c.click(get_calls, rep_c, tbl_c)
-
-        gr.Markdown("### Search Calls by Date")
-        y1, m1, d1 = gr.Textbox(label="Year"), gr.Textbox(label="Month"), gr.Textbox(label="Day")
-        rep_c2 = gr.Dropdown(choices=rep_choices("Calls"), label="Filter by Rep", allow_custom_value=True)
-        btn_c2 = gr.Button("Search")
-        tbl_c2 = gr.Dataframe()
-        btn_c2.click(search_calls, [y1, m1, d1, rep_c2], tbl_c2)
-
-    # -- Appointments Tab --
+        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_summary(r), get_calls(r)),
+            inputs=rep_calls,
+            outputs=[calls_summary, calls_table]
+        )
+
+        gr.Markdown("### 🔍 Search Calls by Specific 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=search_calls_by_date,
+            inputs=[y1,m1,d1,rep1],
+            outputs=calls_date_table
+        )
+
+    # ─── Appointments Report ─────────────────────
     with gr.Tab("Appointments Report"):
-        rep_a = gr.Dropdown(choices=rep_choices("Appointments"), label="Filter by Rep", allow_custom_value=True)
-        btn_a = gr.Button("Load This Week’s Appts")
-        sum_a = gr.Dataframe(label="📊 Appts by Rep")
-        tbl_a = gr.Dataframe()
-        def _load_appts(r):
-            df = get_appointments(r)
-            return df.groupby("Rep").size().reset_index(name="Count"), df
-        btn_a.click(_load_appts, rep_a, [sum_a, tbl_a])
-
-        gr.Markdown("### Search Appts by Date")
-        y2, m2, d2 = gr.Textbox(label="Year"), gr.Textbox(label="Month"), gr.Textbox(label="Day")
-        rep_a2 = gr.Dropdown(choices=rep_choices("Appointments"), label="Filter by Rep", allow_custom_value=True)
-        btn_a2 = gr.Button("Search")
-        sum_a2 = gr.Dataframe(label="📊 Appts by Rep")
-        tbl_a2 = gr.Dataframe()
-        def _search_appts(y,m,d,r):
-            df = search_appointments(y,m,d,r)
-            return df.groupby("Rep").size().reset_index(name="Count"), df
-        btn_a2.click(_search_appts, [y2,m2,d2,rep_a2], [sum_a2, tbl_a2])
-
-    # -- Appointed Leads --
+        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_summary(r), get_appointments(r)),
+            inputs=rep_appt,
+            outputs=[appt_summary, appt_table]
+        )
+
+        gr.Markdown("### 🔍 Search Appointments by Specific 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: (
+                (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_summary, appt_date_table]
+        )
+
+    # ─── Appointed Leads ─���────────────────────────
     with gr.Tab("Appointed Leads"):
-        btn_l = gr.Button("View Leads")
-        sum_l = gr.Dataframe(label="📊 Leads by Rep")
-        det_l = gr.Dataframe(label="🔎 Details")
-        btn_l.click(lambda: (get_leads_summary(), get_leads_detail()), None, [sum_l, det_l])
+        leads_btn     = gr.Button("View Appointed Leads")
+        leads_summary = gr.Dataframe(label="📊 Leads Count by Rep")
+        leads_detail  = gr.Dataframe(label="🔎 Detailed Leads")
 
-    # -- Insights --
+        leads_btn.click(
+            fn=lambda: (get_leads_summary(), get_leads_detail()),
+            outputs=[leads_summary, leads_detail]
+        )
+
+    # ─── Insights ─────────────────────────────────
     with gr.Tab("Insights"):
-        btn_i = gr.Button("Generate Insights")
-        out_i = gr.Dataframe()
-        btn_i.click(compute_insights, None, out_i)
+        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 below then click **Save Users** to push back to the sheet.")
+        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_out = gr.Textbox()
-        save_btn.click(save_users, users_tbl, save_out)
+        save_btn  = gr.Button("Save Users")
+        status    = gr.Textbox()
+
+        save_btn.click(fn=save_users, inputs=users_tbl, outputs=status)
 
-    app.launch()
+    # end Blocks
+app.launch()