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import gradio as gr | |
import pandas as pd | |
import gspread | |
from gspread_dataframe import set_with_dataframe | |
from oauth2client.service_account import ServiceAccountCredentials | |
from datetime import datetime, timedelta | |
# -------------------- 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(CREDS_JSON, scope) | |
client = gspread.authorize(creds) | |
# -------------------- SHEET LOAD / UTILS -------------------- | |
def normalize_columns(df): | |
df.columns = df.columns.str.strip().str.title() | |
return df | |
def load_sheet_df(sheet_name): | |
try: | |
ws = client.open_by_url(SHEET_URL).worksheet(sheet_name) | |
df = pd.DataFrame(ws.get_all_records()) | |
return normalize_columns(df) | |
except Exception as e: | |
return pd.DataFrame([{"Error": str(e)}]) | |
def rep_options(sheet_name, rep_col="Rep"): | |
df = load_sheet_df(sheet_name) | |
if rep_col in df.columns: | |
return sorted(df[rep_col].dropna().unique().tolist()) | |
return [] | |
# -------------------- DATE FILTERS -------------------- | |
def get_current_week_range(): | |
today = datetime.now() | |
start = today - timedelta(days=today.weekday()) | |
return start.date(), (start + timedelta(days=6)).date() | |
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 and rep_col in out.columns: | |
out = out[out[rep_col] == rep] | |
return out | |
def filter_date(df, date_col, rep_col, 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 and rep_col in out.columns: | |
out = out[out[rep_col] == rep] | |
return out | |
# -------------------- REPORT FUNCTIONS -------------------- | |
def get_calls(rep=None): | |
df = load_sheet_df("Calls") | |
if "Call Date" not in df.columns: | |
return pd.DataFrame([{"Error":"Missing 'Call Date'"}]) | |
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") | |
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'"}]) | |
return filter_date(df, "Call Date", "Rep", y,m,d, rep) | |
def get_appointments(rep=None): | |
df = load_sheet_df("Appointments") | |
if "Appointment Date" not in df.columns: | |
return pd.DataFrame([{"Error":"Missing 'Appointment Date'"}]) | |
return filter_week(df, "Appointment Date", "Rep", 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") | |
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'"}]) | |
return filter_date(df, "Appointment Date", "Rep", y,m,d, rep) | |
def get_leads_detail(): | |
df = load_sheet_df("AllocatedLeads") | |
if "Assigned Rep" not in df.columns: | |
return pd.DataFrame([{"Error":"Missing 'Assigned Rep'"}]) | |
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") | |
# -------------------- INSIGHTS -------------------- | |
def compute_insights(): | |
def top_rep(df, col): | |
if "Error" in df.columns or df.empty: | |
return "N/A" | |
counts = df.groupby(col).size() | |
return counts.idxmax() if not counts.empty else "N/A" | |
calls = get_calls() | |
appts = get_appointments() | |
leads = get_leads_detail().rename(columns={"Assigned Rep":"Rep"}) | |
return pd.DataFrame([ | |
{"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, "Rep")}, | |
]) | |
# -------------------- USER MANAGEMENT -------------------- | |
def load_users(): | |
df = load_sheet_df("Users") # your sheet tab is named "Users" | |
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" | |
] | |
cols = [c for c in wanted if c in df.columns] | |
return df[cols] | |
def save_users(df): | |
ws = client.open_by_url(SHEET_URL).worksheet("Users") | |
ws.clear() | |
set_with_dataframe(ws, df) | |
return "β Users saved!" | |
# -------------------- GRADIO UI -------------------- | |
with gr.Blocks(title="Graffiti Admin Dashboard") as app: | |
gr.Markdown("# π Graffiti Admin Dashboard") | |
# βββ Calls Report βββββββββββββββββββ | |
with gr.Tab("Calls Report"): | |
rep_calls = gr.Dropdown("Optional Rep Filter", choices=rep_options("Calls"), allow_custom_value=True) | |
calls_btn = gr.Button("Load Current Week Calls") | |
calls_sum = gr.Dataframe(label="π Calls by Rep") | |
calls_det = gr.Dataframe(label="π Detailed Calls") | |
calls_btn.click(fn=lambda r: (get_calls_summary(r), get_calls(r)), | |
inputs=rep_calls, outputs=[calls_sum, calls_det]) | |
gr.Markdown("### π Search Calls by Date") | |
y1,m1,d1 = gr.Textbox("Year"), gr.Textbox("Month"), gr.Textbox("Day") | |
rep1 = gr.Dropdown("Optional Rep Filter", choices=rep_options("Calls"), allow_custom_value=True) | |
calls_dt_btn = gr.Button("Search") | |
calls_dt_tbl = gr.Dataframe() | |
calls_dt_btn.click(fn=search_calls_by_date, | |
inputs=[y1,m1,d1,rep1], | |
outputs=calls_dt_tbl) | |
# βββ Appointments Report ββββββββββββ | |
with gr.Tab("Appointments Report"): | |
rep_appt = gr.Dropdown("Optional Rep Filter", choices=rep_options("Appointments"), allow_custom_value=True) | |
appt_btn = gr.Button("Load Current Week Appts") | |
appt_sum = gr.Dataframe(label="π Appts by Rep") | |
appt_det = gr.Dataframe(label="π Detailed Appts") | |
appt_btn.click(fn=lambda r: (get_appointments_summary(r), get_appointments(r)), | |
inputs=rep_appt, outputs=[appt_sum, appt_det]) | |
gr.Markdown("### π Search Appts by Date") | |
y2,m2,d2 = gr.Textbox("Year"), gr.Textbox("Month"), gr.Textbox("Day") | |
rep2 = gr.Dropdown("Optional Rep Filter", choices=rep_options("Appointments"), allow_custom_value=True) | |
appt_dt_btn = gr.Button("Search") | |
appt_dt_sum = gr.Dataframe(label="π Appts Summary by Rep") | |
appt_dt_det = gr.Dataframe(label="π Detailed Appts") | |
appt_dt_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_dt_sum, appt_dt_det] | |
) | |
# βββ Appointed Leads ββββββββββββββββ | |
with gr.Tab("Appointed Leads"): | |
leads_btn = gr.Button("View Appointed Leads") | |
leads_sum = gr.Dataframe(label="π Leads Count by Rep") | |
leads_det = gr.Dataframe(label="π Detailed Leads") | |
leads_btn.click(fn=lambda: (get_leads_summary(), get_leads_detail()), | |
outputs=[leads_sum, leads_det]) | |
# βββ Insights βββββββββββββββββββββββ | |
with gr.Tab("Insights"): | |
ins_btn = gr.Button("Generate Insights") | |
ins_tbl = gr.Dataframe() | |
ins_btn.click(fn=compute_insights, outputs=ins_tbl) | |
# βββ User Management ββββββββββββββββ | |
with gr.Tab("User Management"): | |
gr.Markdown("## π€ Manage Users\nEdit/add/remove rows, then click **Save Users**.") | |
users_df = gr.Dataframe(load_users(), interactive=True) | |
save_btn = gr.Button("Save Users") | |
save_stat = gr.Textbox() | |
save_btn.click(fn=save_users, inputs=users_df, outputs=save_stat) | |
app.launch() | |