z230

create_accountability_report.py

@@ -1,4 +1,5 @@
 import pandas as pd
+from datetime import date
 from pathlib import Path
 from openpyxl import load_workbook
 from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
@@ -6,8 +7,10 @@ from openpyxl.utils import get_column_letter
 
 INVENTORY_DIR   = Path("xls_reports")
 DESTRUCTION_DIR = Path("xls_ip_destruction")
-OUTPUT_FILE    = "accountability_combined.xlsx"
+OUTPUT_DIR      = Path("output")
-SHEET_NAME     = "CountryMedicationOverview"
+OUTPUT_FILE     = OUTPUT_DIR / f"{date.today().strftime('%Y-%m-%d')} 42847922MDD3003 CZ IWRS overview.xlsx"
+
+# ── Shared constants ──────────────────────────────────────────────────────────
 
 COLUMN_RENAMES = {
     "Site":                                                  "Site",
@@ -35,7 +38,7 @@ COLUMN_RENAMES = {
 
 DATE_COLUMNS = {
     "Orig Exp Date", "Exp Date", "Rcv Date",
-    "Date Asgn", "Disp Date", "Date Ret", "Destroyed",
+    "Date Asgn", "Disp Date", "Date Ret", "Destroyed", "Max Visit Date",
 }
 
 COLUMN_WIDTHS = {
@@ -60,8 +63,10 @@ COLUMN_WIDTHS = {
     "Ret User":       18,
     "Destroyed":      14,
     "Basket No.":     12,
+    "Max Visit Date": 16,
 }
 
+# ── Helpers ───────────────────────────────────────────────────────────────────
 
 def read_inventory(path):
     df = pd.read_excel(path, header=None)
@@ -94,52 +99,15 @@ def read_destruction_lookup():
     return lookup
 
 
-def main():
+def format_sheet(ws, header_color, highlight_col=None, highlight_color=None):
-    lookup = read_destruction_lookup()
-    print(f"Loaded {len(lookup)} kits from destruction reports")
-
-    all_rows = []
-    for path in sorted(INVENTORY_DIR.glob("onsite_inventory_detail_*.xlsx")):
-        df, meta = read_inventory(path)
-        df["DestroyedOn"] = df["Medication ID"].apply(
-            lambda x: lookup.get(int(x), (None, None))[1] if pd.notna(x) else None
-        )
-        df["Basket number"] = df["Medication ID"].apply(
-            lambda x: lookup.get(int(x), (None, None))[0] if pd.notna(x) else None
-        )
-        df.insert(0, "Site", meta.get("site", path.stem))
-        all_rows.append(df)
-        print(f"  {path.name}: {len(df)} kits")
-
-    combined = pd.concat(all_rows, ignore_index=True)
-
-    # Rename columns
-    combined.rename(columns=COLUMN_RENAMES, inplace=True)
-
-    # Convert date columns
-    for col in DATE_COLUMNS:
-        if col in combined.columns:
-            combined[col] = pd.to_datetime(combined[col], dayfirst=True, errors="coerce")
-
-    # Sort
-    combined.sort_values(["Site", "Rcv Date", "Med ID"], inplace=True, ignore_index=True)
-
-    combined.to_excel(OUTPUT_FILE, index=False, sheet_name=SHEET_NAME)
-
-    # ── Formatting ────────────────────────────────────────────────────────────
-    wb = load_workbook(OUTPUT_FILE)
-    ws = wb[SHEET_NAME]
-
-    header_fill = PatternFill("solid", start_color="1F4E79")
-    header_font = Font(bold=True, color="FFFFFF", name="Arial", size=10)
-    new_col_fill = PatternFill("solid", start_color="E2EFDA")
-    row_font     = Font(name="Arial", size=10)
-
     thin        = Side(style="thin", color="000000")
     border      = Border(left=thin, right=thin, top=thin, bottom=thin)
+    header_fill = PatternFill("solid", start_color=header_color)
+    header_font = Font(bold=True, color="FFFFFF", name="Arial", size=10)
+    row_font    = Font(name="Arial", size=10)
+    hi_fill     = PatternFill("solid", start_color=highlight_color) if highlight_color else None
 
     headers = [cell.value for cell in ws[1]]
-    new_cols = {"Destroyed", "Basket No."}
 
     for cell in ws[1]:
         cell.fill      = header_fill
@@ -155,8 +123,8 @@ def main():
             cell.alignment = Alignment(horizontal="center")
             if col_name in DATE_COLUMNS:
                 cell.number_format = "DD-MMM-YYYY"
-            if col_name in new_cols:
+            if hi_fill and col_name == highlight_col:
-                cell.fill = new_col_fill
+                cell.fill = hi_fill
 
     for cell in ws[1]:
         width = COLUMN_WIDTHS.get(cell.value, 14)
@@ -165,8 +133,125 @@ def main():
     ws.auto_filter.ref = ws.dimensions
     ws.freeze_panes    = "A2"
 
+
+# ── Build DataFrames ──────────────────────────────────────────────────────────
+
+def build_main(lookup):
+    all_rows = []
+    for path in sorted(INVENTORY_DIR.glob("onsite_inventory_detail_*.xlsx")):
+        df, meta = read_inventory(path)
+        df["DestroyedOn"]   = df["Medication ID"].apply(
+            lambda x: lookup.get(int(x), (None, None))[1] if pd.notna(x) else None)
+        df["Basket number"] = df["Medication ID"].apply(
+            lambda x: lookup.get(int(x), (None, None))[0] if pd.notna(x) else None)
+        df.insert(0, "Site", meta.get("site", path.stem))
+        all_rows.append(df)
+        print(f"  {path.name}: {len(df)} kits")
+
+    combined = pd.concat(all_rows, ignore_index=True)
+    combined.rename(columns=COLUMN_RENAMES, inplace=True)
+    for col in DATE_COLUMNS:
+        if col in combined.columns:
+            combined[col] = pd.to_datetime(combined[col], dayfirst=True, errors="coerce")
+    combined.sort_values(["Site", "Rcv Date", "Med ID"], inplace=True, ignore_index=True)
+    return combined
+
+
+def build_expired(df):
+    today = date.today()
+    mask = (
+        df["Basket No."].isna() &
+        df["Subject ID"].isna() &
+        (df["Exp Date"] < pd.Timestamp(today))
+    )
+    filtered = df[mask].copy().reset_index(drop=True)
+    sheet_name = f"Expired as of {today.strftime('%d-%b-%Y')}"
+    print(f"  Expired: {len(filtered)}")
+    return filtered, sheet_name
+
+
+def build_assigned_not_dispensed(df):
+    mask = df["Subject ID"].notna() & df["Disp Date"].isna()
+    filtered = df[mask].copy().reset_index(drop=True)
+    print(f"  Assigned not dispensed: {len(filtered)}")
+    return filtered
+
+
+def build_not_returned(df):
+    no_ret = df[
+        df["Date Ret"].isna() &
+        df["Subject ID"].notna() &
+        (df["Disp Status"].str.upper() != "NOT DISPENSED")
+    ].copy()
+    max_asgn = df.groupby("Subject ID")["Date Asgn"].max().rename("Max Visit Date")
+    no_ret = no_ret.join(max_asgn, on="Subject ID")
+    filtered = no_ret[no_ret["Date Asgn"] < no_ret["Max Visit Date"]].copy()
+    filtered = filtered.drop(columns=["Qty Ret", "Date Ret", "Ret User", "Destroyed", "Basket No."])
+    filtered = filtered.reset_index(drop=True)
+    print(f"  Not returned: {len(filtered)}")
+    return filtered
+
+
+def build_kits_for_destruction(df):
+    mask = (
+        df["Basket No."].isna() &
+        (df["Date Ret"].notna() | (df["Disp Status"].str.upper() == "NOT DISPENSED"))
+    )
+    filtered = df[mask].copy().sort_values(["Site", "Date Ret"], ascending=[True, True])
+    filtered = filtered.drop(columns=["Destroyed", "Basket No."]).reset_index(drop=True)
+    print(f"  Kits for destruction: {len(filtered)}")
+    return filtered
+
+
+# ── Main ──────────────────────────────────────────────────────────────────────
+
+def main():
+    # Prepare output dir, remove any previous overview file
+    OUTPUT_DIR.mkdir(exist_ok=True)
+    for old in OUTPUT_DIR.glob("*42847922MDD3003 CZ IWRS overview.xlsx"):
+        old.unlink()
+        print(f"Removed old file: {old.name}")
+
+    lookup = read_destruction_lookup()
+    print(f"Loaded {len(lookup)} kits from destruction reports")
+
+    df = build_main(lookup)
+
+    expired_df, expired_sheet = build_expired(df)
+    assigned_df               = build_assigned_not_dispensed(df)
+    not_returned_df           = build_not_returned(df)
+    destruction_df            = build_kits_for_destruction(df)
+
+    # Write all sheets
+    with pd.ExcelWriter(OUTPUT_FILE, engine="openpyxl") as writer:
+        df.to_excel(             writer, index=False, sheet_name="CountryMedicationOverview")
+        expired_df.to_excel(     writer, index=False, sheet_name=expired_sheet)
+        assigned_df.to_excel(    writer, index=False, sheet_name="Assigned not dispensed")
+        not_returned_df.to_excel(writer, index=False, sheet_name="Not returned")
+        destruction_df.to_excel( writer, index=False, sheet_name="Kits for destruction")
+
+    # Format all sheets
+    wb = load_workbook(OUTPUT_FILE)
+
+    # Main sheet — dark blue, green highlight for Destroyed/Basket No.
+    ws_main = wb["CountryMedicationOverview"]
+    format_sheet(ws_main, header_color="1F4E79")
+    # Extra: green fill for Destroyed and Basket No. columns
+    new_col_fill = PatternFill("solid", start_color="E2EFDA")
+    headers_main = [c.value for c in ws_main[1]]
+    for row in ws_main.iter_rows(min_row=2, max_row=ws_main.max_row):
+        for cell in row:
+            col_name = headers_main[cell.column - 1] if cell.column <= len(headers_main) else None
+            if col_name in ("Destroyed", "Basket No."):
+                cell.fill = new_col_fill
+
+    format_sheet(wb[expired_sheet],              header_color="C00000", highlight_col="Exp Date",       highlight_color="FFE0E0")
+    format_sheet(wb["Assigned not dispensed"],   header_color="833C00", highlight_col="Subject ID",     highlight_color="FFF2CC")
+    format_sheet(wb["Not returned"],             header_color="375623", highlight_col="Max Visit Date",  highlight_color="E2EFDA")
+    format_sheet(wb["Kits for destruction"],     header_color="595959")
+
     wb.save(OUTPUT_FILE)
-    print(f"\nSaved: {OUTPUT_FILE} ({len(combined)} rows, sheet '{SHEET_NAME}')")
+    print(f"\nSaved: {OUTPUT_FILE}  ({len(df)} rows on main sheet, {wb.sheetnames})")
 
 
 main()

sheet_assigned_not_dispensed.py

@@ -0,0 +1,92 @@
+import pandas as pd
+from openpyxl import load_workbook
+from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
+from openpyxl.utils import get_column_letter
+
+SOURCE_FILE = "accountability_combined.xlsx"
+OUTPUT_FILE = "sheet_assigned_not_dispensed.xlsx"
+SHEET_NAME  = "Assigned not dispensed"
+
+DATE_COLUMNS = {
+    "Orig Exp Date", "Exp Date", "Rcv Date",
+    "Date Asgn", "Disp Date", "Date Ret", "Destroyed",
+}
+
+COLUMN_WIDTHS = {
+    "Site":          14,
+    "Med ID":        10,
+    "Lot No.":       12,
+    "Orig Exp Date": 16,
+    "Exp Date":      14,
+    "Rcv Date":      14,
+    "Rcpt User":     22,
+    "Subject ID":    14,
+    "Qty Asgn":       9,
+    "IRT Tx":         8,
+    "Date Asgn":     14,
+    "Asgn User":     20,
+    "Disp Status":   16,
+    "Disp Date":     14,
+    "Qty Disp":       9,
+    "Disp User":     20,
+    "Qty Ret":       10,
+    "Date Ret":      14,
+    "Ret User":      18,
+    "Destroyed":     14,
+    "Basket No.":    12,
+}
+
+df = pd.read_excel(SOURCE_FILE)
+
+for col in DATE_COLUMNS:
+    if col in df.columns:
+        df[col] = pd.to_datetime(df[col], errors="coerce")
+
+# Filter: Subject ID present AND Disp Date missing
+mask = df["Subject ID"].notna() & df["Disp Date"].isna()
+filtered = df[mask].copy().reset_index(drop=True)
+
+print(f"Assigned not dispensed: {len(filtered)}")
+
+filtered.to_excel(OUTPUT_FILE, index=False, sheet_name=SHEET_NAME)
+
+# Formatting
+wb = load_workbook(OUTPUT_FILE)
+ws = wb[SHEET_NAME]
+
+header_fill  = PatternFill("solid", start_color="833C00")   # dark orange
+header_font  = Font(bold=True, color="FFFFFF", name="Arial", size=10)
+row_font     = Font(name="Arial", size=10)
+subj_fill    = PatternFill("solid", start_color="FFF2CC")   # light yellow highlight for Subject ID
+
+thin   = Side(style="thin", color="000000")
+border = Border(left=thin, right=thin, top=thin, bottom=thin)
+
+headers = [cell.value for cell in ws[1]]
+
+for cell in ws[1]:
+    cell.fill      = header_fill
+    cell.font      = header_font
+    cell.alignment = Alignment(horizontal="center", vertical="center", wrap_text=False)
+    cell.border    = border
+
+for row in ws.iter_rows(min_row=2, max_row=ws.max_row):
+    for cell in row:
+        col_name = headers[cell.column - 1] if cell.column <= len(headers) else None
+        cell.font      = row_font
+        cell.border    = border
+        cell.alignment = Alignment(horizontal="center")
+        if col_name in DATE_COLUMNS:
+            cell.number_format = "DD-MMM-YYYY"
+        if col_name == "Subject ID":
+            cell.fill = subj_fill
+
+for cell in ws[1]:
+    width = COLUMN_WIDTHS.get(cell.value, 14)
+    ws.column_dimensions[get_column_letter(cell.column)].width = width
+
+ws.auto_filter.ref = ws.dimensions
+ws.freeze_panes    = "A2"
+
+wb.save(OUTPUT_FILE)
+print(f"Saved: {OUTPUT_FILE}  (sheet: '{SHEET_NAME}')")

sheet_expired.py

@@ -0,0 +1,97 @@
+import pandas as pd
+from datetime import date
+from openpyxl import load_workbook
+from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
+from openpyxl.utils import get_column_letter
+
+SOURCE_FILE = "accountability_combined.xlsx"
+OUTPUT_FILE = "sheet_expired.xlsx"
+
+DATE_COLUMNS = {
+    "Orig Exp Date", "Exp Date", "Rcv Date",
+    "Date Asgn", "Disp Date", "Date Ret", "Destroyed",
+}
+
+COLUMN_WIDTHS = {
+    "Site":          14,
+    "Med ID":        10,
+    "Lot No.":       12,
+    "Orig Exp Date": 16,
+    "Exp Date":      14,
+    "Rcv Date":      14,
+    "Rcpt User":     22,
+    "Subject ID":    14,
+    "Qty Asgn":       9,
+    "IRT Tx":         8,
+    "Date Asgn":     14,
+    "Asgn User":     20,
+    "Disp Status":   16,
+    "Disp Date":     14,
+    "Qty Disp":       9,
+    "Disp User":     20,
+    "Qty Ret":       10,
+    "Date Ret":      14,
+    "Ret User":      18,
+    "Destroyed":     14,
+    "Basket No.":    12,
+}
+
+today = date.today()
+sheet_name = f"Expired as of {today.strftime('%d-%b-%Y')}"
+
+# Load source
+df = pd.read_excel(SOURCE_FILE)
+
+# Convert date columns
+for col in DATE_COLUMNS:
+    if col in df.columns:
+        df[col] = pd.to_datetime(df[col], errors="coerce")
+
+# Filter: not in basket AND not assigned to patient AND Exp Date < today
+mask = df["Basket No."].isna() & df["Subject ID"].isna() & (df["Exp Date"] < pd.Timestamp(today))
+filtered = df[mask].copy().reset_index(drop=True)
+
+print(f"Expired kits not in basket: {len(filtered)}")
+
+filtered.to_excel(OUTPUT_FILE, index=False, sheet_name=sheet_name)
+
+# Formatting
+wb = load_workbook(OUTPUT_FILE)
+ws = wb[sheet_name]
+
+header_fill = PatternFill("solid", start_color="C00000")   # dark red
+header_font = Font(bold=True, color="FFFFFF", name="Arial", size=10)
+row_font    = Font(name="Arial", size=10)
+exp_fill    = PatternFill("solid", start_color="FFE0E0")   # light red highlight for Exp Date
+
+thin   = Side(style="thin", color="000000")
+border = Border(left=thin, right=thin, top=thin, bottom=thin)
+
+headers = [cell.value for cell in ws[1]]
+
+for cell in ws[1]:
+    cell.fill      = header_fill
+    cell.font      = header_font
+    cell.alignment = Alignment(horizontal="center", vertical="center", wrap_text=False)
+    cell.border    = border
+
+for row in ws.iter_rows(min_row=2, max_row=ws.max_row):
+    for cell in row:
+        col_name = headers[cell.column - 1] if cell.column <= len(headers) else None
+        cell.font      = row_font
+        cell.border    = border
+        cell.alignment = Alignment(horizontal="center")
+        if col_name in DATE_COLUMNS:
+            cell.number_format = "DD-MMM-YYYY"
+        if col_name == "Exp Date":
+            cell.fill = exp_fill
+
+for cell in ws[1]:
+    width = COLUMN_WIDTHS.get(cell.value, 14)
+    ws.column_dimensions[get_column_letter(cell.column)].width = width
+
+ws.auto_filter.ref = ws.dimensions
+ws.freeze_panes    = "A2"
+
+wb.save(OUTPUT_FILE)
+print(f"Saved: {OUTPUT_FILE}  (sheet: '{sheet_name}')")

sheet_kits_for_destruction.py

@@ -0,0 +1,99 @@
+import pandas as pd
+from openpyxl import load_workbook
+from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
+from openpyxl.utils import get_column_letter
+
+SOURCE_FILE = "accountability_combined.xlsx"
+OUTPUT_FILE = "sheet_kits_for_destruction.xlsx"
+SHEET_NAME  = "Kits for destruction"
+
+DATE_COLUMNS = {
+    "Orig Exp Date", "Exp Date", "Rcv Date",
+    "Date Asgn", "Disp Date", "Date Ret", "Destroyed",
+}
+
+COLUMN_WIDTHS = {
+    "Site":          14,
+    "Med ID":        10,
+    "Lot No.":       12,
+    "Orig Exp Date": 16,
+    "Exp Date":      14,
+    "Rcv Date":      14,
+    "Rcpt User":     22,
+    "Subject ID":    14,
+    "Qty Asgn":       9,
+    "IRT Tx":         8,
+    "Date Asgn":     14,
+    "Asgn User":     20,
+    "Disp Status":   16,
+    "Disp Date":     14,
+    "Qty Disp":       9,
+    "Disp User":     20,
+    "Qty Ret":       10,
+    "Date Ret":      14,
+    "Ret User":      18,
+    "Destroyed":     14,
+    "Basket No.":    12,
+}
+
+df = pd.read_excel(SOURCE_FILE)
+
+for col in DATE_COLUMNS:
+    if col in df.columns:
+        df[col] = pd.to_datetime(df[col], errors="coerce")
+
+# Filter: no basket AND (Date Ret filled OR Disp Status == NOT DISPENSED)
+mask = (
+    df["Basket No."].isna() &
+    (
+        df["Date Ret"].notna() |
+        (df["Disp Status"].str.upper() == "NOT DISPENSED")
+    )
+)
+filtered = df[mask].copy().sort_values(["Site", "Date Ret"], ascending=[True, True])
+filtered = filtered.drop(columns=["Destroyed", "Basket No."]).reset_index(drop=True)
+
+print(f"Kits for destruction: {len(filtered)}")
+
+filtered.to_excel(OUTPUT_FILE, index=False, sheet_name=SHEET_NAME)
+
+# Formatting
+wb = load_workbook(OUTPUT_FILE)
+ws = wb[SHEET_NAME]
+
+header_fill  = PatternFill("solid", start_color="595959")   # dark grey
+header_font  = Font(bold=True, color="FFFFFF", name="Arial", size=10)
+row_font     = Font(name="Arial", size=10)
+basket_fill  = PatternFill("solid", start_color="FFE0E0")   # light red for empty Basket No.
+
+thin   = Side(style="thin", color="000000")
+border = Border(left=thin, right=thin, top=thin, bottom=thin)
+
+headers = [cell.value for cell in ws[1]]
+
+for cell in ws[1]:
+    cell.fill      = header_fill
+    cell.font      = header_font
+    cell.alignment = Alignment(horizontal="center", vertical="center", wrap_text=False)
+    cell.border    = border
+
+for row in ws.iter_rows(min_row=2, max_row=ws.max_row):
+    for cell in row:
+        col_name = headers[cell.column - 1] if cell.column <= len(headers) else None
+        cell.font      = row_font
+        cell.border    = border
+        cell.alignment = Alignment(horizontal="center")
+        if col_name in DATE_COLUMNS:
+            cell.number_format = "DD-MMM-YYYY"
+        if col_name == "Basket No.":
+            cell.fill = basket_fill
+
+for cell in ws[1]:
+    width = COLUMN_WIDTHS.get(cell.value, 14)
+    ws.column_dimensions[get_column_letter(cell.column)].width = width
+
+ws.auto_filter.ref = ws.dimensions
+ws.freeze_panes    = "A2"
+
+wb.save(OUTPUT_FILE)
+print(f"Saved: {OUTPUT_FILE}  (sheet: '{SHEET_NAME}')")

sheet_not_returned.py

@@ -0,0 +1,102 @@
+import pandas as pd
+from openpyxl import load_workbook
+from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
+from openpyxl.utils import get_column_letter
+
+SOURCE_FILE = "accountability_combined.xlsx"
+OUTPUT_FILE = "sheet_not_returned.xlsx"
+SHEET_NAME  = "Not returned"
+
+DATE_COLUMNS = {
+    "Orig Exp Date", "Exp Date", "Rcv Date",
+    "Date Asgn", "Disp Date", "Max Visit Date",
+}
+
+COLUMN_WIDTHS = {
+    "Site":           14,
+    "Med ID":         10,
+    "Lot No.":        12,
+    "Orig Exp Date":  16,
+    "Exp Date":       14,
+    "Rcv Date":       14,
+    "Rcpt User":      22,
+    "Subject ID":     14,
+    "Qty Asgn":        9,
+    "IRT Tx":          8,
+    "Date Asgn":      14,
+    "Asgn User":      20,
+    "Disp Status":    16,
+    "Disp Date":      14,
+    "Qty Disp":        9,
+    "Disp User":      20,
+    "Max Visit Date": 16,
+}
+
+df = pd.read_excel(SOURCE_FILE)
+
+for col in DATE_COLUMNS:
+    if col in df.columns:
+        df[col] = pd.to_datetime(df[col], errors="coerce")
+
+# Kits with no return date, assigned to a patient, and not "NOT DISPENSED"
+no_ret = df[
+    df["Date Ret"].isna() &
+    df["Subject ID"].notna() &
+    (df["Disp Status"].str.upper() != "NOT DISPENSED")
+].copy()
+
+# Max Date Asgn per patient (from full dataset)
+max_asgn = df.groupby("Subject ID")["Date Asgn"].max().rename("Max Visit Date")
+no_ret = no_ret.join(max_asgn, on="Subject ID")
+
+# Keep only kits where Date Asgn is NOT the latest for that patient
+filtered = no_ret[no_ret["Date Asgn"] < no_ret["Max Visit Date"]].copy()
+
+# Drop columns Q-U and keep Max Visit Date
+filtered = filtered.drop(columns=["Qty Ret", "Date Ret", "Ret User", "Destroyed", "Basket No."])
+filtered = filtered.reset_index(drop=True)
+
+print(f"Not returned kits: {len(filtered)}")
+
+filtered.to_excel(OUTPUT_FILE, index=False, sheet_name=SHEET_NAME)
+
+# Formatting
+wb = load_workbook(OUTPUT_FILE)
+ws = wb[SHEET_NAME]
+
+header_fill = PatternFill("solid", start_color="375623")   # dark green
+header_font = Font(bold=True, color="FFFFFF", name="Arial", size=10)
+row_font    = Font(name="Arial", size=10)
+ret_fill    = PatternFill("solid", start_color="E2EFDA")   # light green highlight for Date Ret
+
+thin   = Side(style="thin", color="000000")
+border = Border(left=thin, right=thin, top=thin, bottom=thin)
+
+headers = [cell.value for cell in ws[1]]
+
+for cell in ws[1]:
+    cell.fill      = header_fill
+    cell.font      = header_font
+    cell.alignment = Alignment(horizontal="center", vertical="center", wrap_text=False)
+    cell.border    = border
+
+for row in ws.iter_rows(min_row=2, max_row=ws.max_row):
+    for cell in row:
+        col_name = headers[cell.column - 1] if cell.column <= len(headers) else None
+        cell.font      = row_font
+        cell.border    = border
+        cell.alignment = Alignment(horizontal="center")
+        if col_name in DATE_COLUMNS:
+            cell.number_format = "DD-MMM-YYYY"
+        if col_name == "Max Visit Date":
+            cell.fill = ret_fill
+
+for cell in ws[1]:
+    width = COLUMN_WIDTHS.get(cell.value, 14)
+    ws.column_dimensions[get_column_letter(cell.column)].width = width
+
+ws.auto_filter.ref = ws.dimensions
+ws.freeze_panes    = "A2"
+
+wb.save(OUTPUT_FILE)
+print(f"Saved: {OUTPUT_FILE}  (sheet: '{SHEET_NAME}')")