Update app.py

app.py

@@ -5,9 +5,13 @@ from oauth2client.service_account import ServiceAccountCredentials
 from datetime import datetime, timedelta
 
 # -------------------- AUTH --------------------
-scope = ["https://spreadsheets.google.com/feeds","https://www.googleapis.com/auth/drive"]
+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
+    "deep-mile-461309-t8-0e90103411e0.json",
+    scope
 )
 client = gspread.authorize(creds)
 sheet_url = "https://docs.google.com/spreadsheets/d/1if4KoVQvw5ZbhknfdZbzMkcTiPfsD6bz9V3a1th-bwQ"
@@ -41,9 +45,9 @@ def filter_week(df, date_col, rep_col=None, rep=None):
 
 def filter_date(df, date_col, rep_col, y, m, d, rep):
     try:
-        target = datetime(int(y),int(m),int(d)).date()
+        target = datetime(int(y), int(m), int(d)).date()
     except:
-        return pd.DataFrame([{"Error":"Invalid date input"}])
+        return pd.DataFrame([{"Error": "Invalid date input"}])
     df[date_col] = pd.to_datetime(df[date_col], errors="coerce").dt.date
     out = df[df[date_col] == target]
     if rep:
@@ -53,19 +57,21 @@ def filter_date(df, date_col, rep_col, y, m, d, rep):
 # -------------------- REPORT FUNCTIONS --------------------
 def get_calls(rep=None):
     df = load_sheet("Calls")
-    if "Call Date" not in df: return pd.DataFrame([{"Error":"Missing 'Call Date' column"}])
-    return filter_week(df,"Call Date","Rep",rep)
+    if "Call Date" not in 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):
+def search_calls_by_date(y, m, d, rep):
     df = load_sheet("Calls")
-    if "Call Date" not in df: return pd.DataFrame([{"Error":"Missing 'Call Date' column"}])
-    return filter_date(df,"Call Date","Rep",y,m,d,rep)
+    if "Call Date" not in df:
+        return pd.DataFrame([{"Error": "Missing 'Call Date' column"}])
+    return filter_date(df, "Call Date", "Rep", y, m, d, rep)
 
 # -------------------- APPOINTMENTS (UPCOMING) --------------------
 def upcoming_summary_and_detail(rep=None):
     df = load_sheet("Appointments")
     if "Appointment Date" not in df:
-        return pd.DataFrame([{"Error":"Missing 'Appointment Date' column"}]), pd.DataFrame()
+        return pd.DataFrame([{"Error": "Missing 'Appointment Date' column"}]), pd.DataFrame()
     df["Appointment Date"] = pd.to_datetime(df["Appointment Date"], errors="coerce").dt.date
     today = datetime.now().date()
     future = df[df["Appointment Date"] >= today]
@@ -74,14 +80,14 @@ def upcoming_summary_and_detail(rep=None):
     summary = future.groupby("Rep").size().reset_index(name="Appointment Count")
     return summary, future
 
-def search_appointments_by_date(y,m,d,rep):
+def search_appointments_by_date(y, m, d, rep):
     df = load_sheet("Appointments")
     if "Appointment Date" not in df:
-        return pd.DataFrame([{"Error":"Missing 'Appointment Date' column"}]), pd.DataFrame()
+        return pd.DataFrame([{"Error": "Missing 'Appointment Date' column"}]), pd.DataFrame()
     try:
-        target = datetime(int(y),int(m),int(d)).date()
+        target = datetime(int(y), int(m), int(d)).date()
     except:
-        return pd.DataFrame([{"Error":"Invalid date input"}]), pd.DataFrame()
+        return pd.DataFrame([{"Error": "Invalid date input"}]), pd.DataFrame()
     df["Appointment Date"] = pd.to_datetime(df["Appointment Date"], errors="coerce").dt.date
     out = df[df["Appointment Date"] == target]
     if rep:
@@ -89,16 +95,17 @@ def search_appointments_by_date(y,m,d,rep):
     summary = out.groupby("Rep").size().reset_index(name="Appointment Count")
     return summary, out
 
-# -------------------- LEADS --------------------
+# -------------------- APPOINTED LEADS --------------------
 def get_leads_detail():
     df = load_sheet("AllocatedLeads")
     if "Assigned Rep" not in df or "Company Name" not in df:
-        return pd.DataFrame([{"Error":"Missing 'Assigned Rep' or 'Company Name' column"}])
+        return pd.DataFrame([{"Error": "Missing 'Assigned Rep' or 'Company Name' column"}])
     return df
 
 def get_leads_summary():
     df = get_leads_detail()
-    if "Error" in df.columns: return df
+    if "Error" in df.columns:
+        return df
     return df.groupby("Assigned Rep").size().reset_index(name="Leads Count")
 
 # -------------------- INSIGHTS --------------------
@@ -106,14 +113,29 @@ def compute_insights():
     calls = get_calls()
     appt_summary, _ = upcoming_summary_and_detail()
     leads = get_leads_detail()
-    def top(df,col):
+    def top(df, col):
         return df[col].value_counts().idxmax() if not df.empty else "N/A"
     return pd.DataFrame([
-        {"Metric":"Most Calls This Week",       "Rep": top(calls,"Rep")},
-        {"Metric":"Most Upcoming Appointments", "Rep": top(appt_summary,"Rep")},
-        {"Metric":"Most Leads Allocated",       "Rep": top(leads,"Assigned Rep")},
+        {"Metric": "Most Calls This Week",        "Rep": top(calls, "Rep")},
+        {"Metric": "Most Upcoming Appointments",  "Rep": top(appt_summary, "Rep")},
+        {"Metric": "Most Leads Allocated",        "Rep": top(leads, "Assigned Rep")},
     ])
 
+# -------------------- USER MANAGEMENT --------------------
+def load_users():
+    df = load_sheet("User")
+    for col in ["Name", "Email", "Company", "Target Figures"]:
+        if col not in df.columns:
+            df[col] = ""
+    return df[["Name", "Email", "Company", "Target Figures"]]
+
+def save_users(df):
+    ws = client.open_by_url(sheet_url).worksheet("User")
+    ws.clear()
+    rows = [df.columns.tolist()] + df.fillna("").values.tolist()
+    ws.update(rows)
+    return df
+
 # -------------------- DROPDOWN OPTIONS --------------------
 def rep_options(sheet, col):
     df = load_sheet(sheet)
@@ -123,50 +145,71 @@ def rep_options(sheet, col):
 with gr.Blocks(title="Graffiti Admin Dashboard") as app:
     gr.Markdown("# 📆 Graffiti Admin Dashboard")
 
-    # Calls Report
+    # Calls Report Tab
     with gr.Tab("Calls Report"):
-        rc = gr.Dropdown("Optional Rep Filter", choices=rep_options("Calls","Rep"))
+        rc = gr.Dropdown(label="Optional Rep Filter", choices=rep_options("Calls", "Rep"))
         btn_calls = gr.Button("Load Current Week Calls")
         tbl_calls = gr.Dataframe()
         btn_calls.click(fn=get_calls, inputs=rc, outputs=tbl_calls)
 
         gr.Markdown("### 🔍 Search Calls by Specific Date")
-        y1,m1,d1 = gr.Textbox("Year"), gr.Textbox("Month"), gr.Textbox("Day")
-        rc2 = gr.Dropdown("Optional Rep Filter", choices=rep_options("Calls","Rep"))
+        y1, m1, d1 = gr.Textbox(label="Year"), gr.Textbox(label="Month"), gr.Textbox(label="Day")
+        rc2 = gr.Dropdown(label="Optional Rep Filter", choices=rep_options("Calls", "Rep"))
         btn_cd = gr.Button("Search Calls by Date")
         tbl_cd = gr.Dataframe()
-        btn_cd.click(fn=search_calls_by_date, inputs=[y1,m1,d1,rc2], outputs=tbl_cd)
+        btn_cd.click(fn=search_calls_by_date, inputs=[y1, m1, d1, rc2], outputs=tbl_cd)
 
-    # Appointments Report
+    # Appointments Report Tab
     with gr.Tab("Appointments Report"):
-        ra = gr.Dropdown("Optional Rep Filter", choices=rep_options("Appointments","Rep"))
+        ra = gr.Dropdown(label="Optional Rep Filter", choices=rep_options("Appointments", "Rep"))
         btn_appt = gr.Button("Load Upcoming Appointments")
-        sum_appt = gr.Dataframe(label="📊 Summary by Rep")
-        det_appt = gr.Dataframe(label="🔎 Detailed")
-        btn_appt.click(fn=upcoming_summary_and_detail, inputs=ra, outputs=[sum_appt,det_appt])
+        sum_appt = gr.Dataframe(label="📊 Upcoming Appointments Summary by Rep")
+        det_appt = gr.Dataframe(label="🔎 Detailed Upcoming Appointments")
+        btn_appt.click(fn=upcoming_summary_and_detail, inputs=ra, outputs=[sum_appt, det_appt])
 
         gr.Markdown("### 🔍 Search Appointments by Specific Date")
-        y2,m2,d2 = gr.Textbox("Year"), gr.Textbox("Month"), gr.Textbox("Day")
-        ra2 = gr.Dropdown("Optional Rep Filter", choices=rep_options("Appointments","Rep"))
+        y2, m2, d2 = gr.Textbox(label="Year"), gr.Textbox(label="Month"), gr.Textbox(label="Day")
+        ra2 = gr.Dropdown(label="Optional Rep Filter", choices=rep_options("Appointments", "Rep"))
         btn_ad = gr.Button("Search Appointments by Date")
-        sum_ad = gr.Dataframe(label="📊 Summary by Rep")
-        det_ad = gr.Dataframe(label="🔎 Detailed")
+        sum_ad = gr.Dataframe(label="📊 Appointments Summary for Date by Rep")
+        det_ad = gr.Dataframe(label="🔎 Detailed Appointments for Date")
         btn_ad.click(fn=search_appointments_by_date,
-                     inputs=[y2,m2,d2,ra2],
-                     outputs=[sum_ad,det_ad])
+                     inputs=[y2, m2, d2, ra2],
+                     outputs=[sum_ad, det_ad])
 
-    # Appointed Leads
+    # Appointed Leads Tab
     with gr.Tab("Appointed Leads"):
         btn_leads = gr.Button("View Appointed Leads")
         sum_leads = gr.Dataframe(label="📊 Leads Count by Rep")
-        det_leads = gr.Dataframe(label="🔎 Detailed")
-        btn_leads.click(fn=lambda:(get_leads_summary(),get_leads_detail()),
-                        outputs=[sum_leads,det_leads])
+        det_leads = gr.Dataframe(label="🔎 Detailed Leads")
+        btn_leads.click(fn=lambda: (get_leads_summary(), get_leads_detail()),
+                        outputs=[sum_leads, det_leads])
 
-    # Insights
+    # Insights Tab
     with gr.Tab("Insights"):
         btn_ins = gr.Button("Generate Insights")
         tbl_ins = gr.Dataframe()
         btn_ins.click(fn=compute_insights, outputs=tbl_ins)
 
+    # User Management Tab
+    with gr.Tab("User Management"):
+        gr.Markdown("### 🧑‍💼 Manage Users\nEdit, add, or remove rows, then click **Save Users**.")
+        users_df = gr.Dataframe(
+            value=load_users(),
+            label="Users",
+            interactive=True
+        )
+        save_btn = gr.Button("Save Users")
+        save_status = gr.Markdown()
+
+        def on_save(df):
+            saved = save_users(pd.DataFrame(df))
+            return "✅ Users saved!", saved
+
+        save_btn.click(
+            fn=on_save,
+            inputs=users_df,
+            outputs=[save_status, users_df]
+        )
+
 app.launch()