270 lines
12 KiB
Python
270 lines
12 KiB
Python
import pandas as pd
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from datetime import date
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from pathlib import Path
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from openpyxl import load_workbook
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from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
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from openpyxl.utils import get_column_letter
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# STUDY = "42847922MDD3003"
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STUDY = "77242113UCO3001"
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INVENTORY_DIR = Path(f"xls_reports_{STUDY}")
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DESTRUCTION_DIR = Path(f"xls_ip_destruction_{STUDY}")
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OUTPUT_DIR = Path("output")
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OUTPUT_FILE = OUTPUT_DIR / f"{date.today().strftime('%Y-%m-%d')} {STUDY} CZ IWRS overview.xlsx"
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# ── Shared constants ──────────────────────────────────────────────────────────
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COLUMN_RENAMES = {
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"Site": "Site",
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"Medication ID": "Med ID",
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"Packaged Lot number": "Lot No.",
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"Original Expiration Date when Packaged Lot was Added": "Orig Exp Date",
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"Expiration date": "Exp Date",
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"Received Date": "Rcv Date",
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"Shipment Receipt User": "Rcpt User",
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"Subject Identifier": "Subject ID",
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"Quantity Assigned": "Qty Asgn",
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"IRT Transaction": "IRT Tx",
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"Date Assigned": "Date Asgn",
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"Assignment User": "Asgn User",
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"Dispensation Status": "Disp Status",
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"Dispensing Date": "Disp Date",
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"Dispensing date": "Disp Date",
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"Quantity Dispensed": "Qty Disp",
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"Dispensing User": "Disp User",
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"Quantity Returned": "Qty Ret",
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"Date Returned": "Date Ret",
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"Return User": "Ret User",
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"DestroyedOn": "Destroyed",
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"Basket number": "Basket No.",
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}
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DATE_COLUMNS = {
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"Orig Exp Date", "Exp Date", "Rcv Date",
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"Date Asgn", "Disp Date", "Date Ret", "Destroyed", "Max Visit Date",
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}
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COLUMN_WIDTHS = {
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"Site": 14,
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"Med ID": 10,
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"Lot No.": 12,
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"Orig Exp Date": 16,
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"Exp Date": 14,
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"Rcv Date": 14,
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"Rcpt User": 22,
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"Subject ID": 14,
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"Qty Asgn": 9,
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"IRT Tx": 8,
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"Date Asgn": 14,
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"Asgn User": 20,
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"Disp Status": 16,
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"Disp Date": 14,
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"Qty Disp": 9,
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"Disp User": 20,
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"Qty Ret": 10,
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"Date Ret": 14,
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"Ret User": 18,
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"Destroyed": 14,
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"Basket No.": 12,
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"Max Visit Date": 16,
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}
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# ── Helpers ───────────────────────────────────────────────────────────────────
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def read_inventory(path):
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df = pd.read_excel(path, header=None)
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# Support both "Medication ID" (MDD3003) and "Medication" (UCO3001)
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mask = df[0].isin(["Medication ID", "Medication"])
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meta = {}
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for i in range(len(df)):
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val = str(df.iloc[i, 0]) if pd.notna(df.iloc[i, 0]) else ""
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if val.startswith("Site:"):
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meta["site"] = val.replace("Site:", "").strip()
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if not mask.any():
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print(f" {path.name}: no data (skipping)")
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return None, meta
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header_row = df[mask].index[0]
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data = pd.read_excel(path, header=header_row)
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data = data.rename(columns={"Medication": "Medication ID"})
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return data, meta
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def read_destruction_lookup():
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lookup = {}
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for path in DESTRUCTION_DIR.glob("*.xlsx"):
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df = pd.read_excel(path, header=None)
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basket_id = None
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destroyed_on = None
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for i in range(15):
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val = str(df.iloc[i, 0]) if pd.notna(df.iloc[i, 0]) else ""
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if val.startswith("Basket ID:"):
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basket_id = val.replace("Basket ID:", "").strip()
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if val.startswith("Drug Destruction Created Date:"):
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destroyed_on = val.replace("Drug Destruction Created Date:", "").strip()
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header_row = df[df[0] == "Medication ID Description"].index[0]
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data = pd.read_excel(path, header=header_row)
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for med_id in data["Medication ID"].dropna():
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lookup[int(med_id)] = (basket_id, destroyed_on)
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return lookup
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def format_sheet(ws, header_color, highlight_col=None, highlight_color=None):
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thin = Side(style="thin", color="000000")
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border = Border(left=thin, right=thin, top=thin, bottom=thin)
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header_fill = PatternFill("solid", start_color=header_color)
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header_font = Font(bold=True, color="FFFFFF", name="Arial", size=10)
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row_font = Font(name="Arial", size=10)
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hi_fill = PatternFill("solid", start_color=highlight_color) if highlight_color else None
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headers = [cell.value for cell in ws[1]]
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for cell in ws[1]:
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cell.fill = header_fill
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cell.font = header_font
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cell.alignment = Alignment(horizontal="center", vertical="center", wrap_text=False)
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cell.border = border
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for row in ws.iter_rows(min_row=2, max_row=ws.max_row):
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for cell in row:
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col_name = headers[cell.column - 1] if cell.column <= len(headers) else None
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cell.font = row_font
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cell.border = border
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cell.alignment = Alignment(horizontal="center")
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if col_name in DATE_COLUMNS:
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cell.number_format = "DD-MMM-YYYY"
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if hi_fill and col_name == highlight_col:
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cell.fill = hi_fill
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for cell in ws[1]:
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width = COLUMN_WIDTHS.get(cell.value, 14)
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ws.column_dimensions[get_column_letter(cell.column)].width = width
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ws.auto_filter.ref = ws.dimensions
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ws.freeze_panes = "A2"
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# ── Build DataFrames ──────────────────────────────────────────────────────────
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def build_main(lookup):
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all_rows = []
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for path in sorted(INVENTORY_DIR.glob("onsite_inventory_detail_*.xlsx")):
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df, meta = read_inventory(path)
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if df is None:
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continue
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df["DestroyedOn"] = df["Medication ID"].apply(
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lambda x: lookup.get(int(x), (None, None))[1] if pd.notna(x) else None)
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df["Basket number"] = df["Medication ID"].apply(
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lambda x: lookup.get(int(x), (None, None))[0] if pd.notna(x) else None)
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df.insert(0, "Site", meta.get("site", path.stem))
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all_rows.append(df)
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print(f" {path.name}: {len(df)} kits")
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combined = pd.concat(all_rows, ignore_index=True)
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combined.rename(columns=COLUMN_RENAMES, inplace=True)
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for col in DATE_COLUMNS:
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if col in combined.columns:
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combined[col] = pd.to_datetime(combined[col], dayfirst=True, errors="coerce")
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combined.sort_values(["Site", "Rcv Date", "Med ID"], inplace=True, ignore_index=True)
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return combined
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def build_expired(df):
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today = date.today()
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mask = (
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df["Basket No."].isna() &
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df["Subject ID"].isna() &
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(df["Exp Date"] < pd.Timestamp(today))
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)
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filtered = df[mask].copy().reset_index(drop=True)
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sheet_name = f"Expired as of {today.strftime('%d-%b-%Y')}"
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print(f" Expired: {len(filtered)}")
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return filtered, sheet_name
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def build_assigned_not_dispensed(df):
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mask = df["Subject ID"].notna() & df["Disp Date"].isna()
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filtered = df[mask].copy().reset_index(drop=True)
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print(f" Assigned not dispensed: {len(filtered)}")
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return filtered
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def build_not_returned(df):
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no_ret = df[
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df["Date Ret"].isna() &
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df["Subject ID"].notna() &
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(df["Disp Status"].str.upper() != "NOT DISPENSED")
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].copy()
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max_asgn = df.groupby("Subject ID")["Date Asgn"].max().rename("Max Visit Date")
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no_ret = no_ret.join(max_asgn, on="Subject ID")
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filtered = no_ret[no_ret["Date Asgn"] < no_ret["Max Visit Date"]].copy()
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filtered = filtered.drop(columns=["Qty Ret", "Date Ret", "Ret User", "Destroyed", "Basket No."])
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filtered = filtered.reset_index(drop=True)
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print(f" Not returned: {len(filtered)}")
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return filtered
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def build_kits_for_destruction(df):
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mask = (
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df["Basket No."].isna() &
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(df["Date Ret"].notna() | (df["Disp Status"].str.upper() == "NOT DISPENSED"))
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)
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filtered = df[mask].copy().sort_values(["Site", "Date Ret"], ascending=[True, True])
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filtered = filtered.drop(columns=["Destroyed", "Basket No."]).reset_index(drop=True)
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print(f" Kits for destruction: {len(filtered)}")
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return filtered
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# ── Main ──────────────────────────────────────────────────────────────────────
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def main():
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# Prepare output dir, remove any previous overview file
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OUTPUT_DIR.mkdir(exist_ok=True)
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for old in OUTPUT_DIR.glob(f"*{STUDY} CZ IWRS overview.xlsx"):
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old.unlink()
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print(f"Removed old file: {old.name}")
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lookup = read_destruction_lookup()
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print(f"Loaded {len(lookup)} kits from destruction reports")
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df = build_main(lookup)
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expired_df, expired_sheet = build_expired(df)
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assigned_df = build_assigned_not_dispensed(df)
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not_returned_df = build_not_returned(df)
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destruction_df = build_kits_for_destruction(df)
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# Write all sheets
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with pd.ExcelWriter(OUTPUT_FILE, engine="openpyxl") as writer:
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df.to_excel( writer, index=False, sheet_name="CountryMedicationOverview")
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expired_df.to_excel( writer, index=False, sheet_name=expired_sheet)
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assigned_df.to_excel( writer, index=False, sheet_name="Assigned not dispensed")
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not_returned_df.to_excel(writer, index=False, sheet_name="Not returned")
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destruction_df.to_excel( writer, index=False, sheet_name="Kits for destruction")
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# Format all sheets
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wb = load_workbook(OUTPUT_FILE)
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# Main sheet — dark blue, green highlight for Destroyed/Basket No.
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ws_main = wb["CountryMedicationOverview"]
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format_sheet(ws_main, header_color="1F4E79")
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# Extra: green fill for Destroyed and Basket No. columns
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new_col_fill = PatternFill("solid", start_color="E2EFDA")
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headers_main = [c.value for c in ws_main[1]]
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for row in ws_main.iter_rows(min_row=2, max_row=ws_main.max_row):
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for cell in row:
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col_name = headers_main[cell.column - 1] if cell.column <= len(headers_main) else None
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if col_name in ("Destroyed", "Basket No."):
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cell.fill = new_col_fill
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format_sheet(wb[expired_sheet], header_color="C00000", highlight_col="Exp Date", highlight_color="FFE0E0")
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format_sheet(wb["Assigned not dispensed"], header_color="833C00", highlight_col="Subject ID", highlight_color="FFF2CC")
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format_sheet(wb["Not returned"], header_color="375623", highlight_col="Max Visit Date", highlight_color="E2EFDA")
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format_sheet(wb["Kits for destruction"], header_color="595959")
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wb.save(OUTPUT_FILE)
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print(f"\nSaved: {OUTPUT_FILE} ({len(df)} rows on main sheet, {wb.sheetnames})")
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main()
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