Raport stocuri marfa 371 pe vechimi (dosar credit banca)

Sectiune dedicata pentru banca cu sumar pe grupe x bucket vechime
(0-6 luni, 6-12 luni, 1-2 ani, 2-3 ani, >3 ani), detaliu articole
si reconciliere contra sold contabil 371 din balanta (vbal).

- queries.py: STOCURI_371_SUMAR (ROLLUP grupa/subgrupa), STOCURI_371_DETALIU,
  STOCURI_371_SOLD_CONTABIL (sold sintetic din vbal, an/luna snapshot).
  Filtru stoc (cants+cant-cante) <> 0 pentru acoperire cu soldul contabil.
- main.py: CLI --aging-dates pentru evolutie multi-data a stocului >3 ani,
  pagina PDF dedicata cu nota metodologica + reconciliere (marker la diff >1%).
- recommendations.py: alerta CONCENTRARE cand stoc 371 >3 ani depaseste prag.
- config.py: threshold aged_stock_371_pct (default 15%).
- run.bat: header documentar cu argumentele disponibile + exemple.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

config.py

@@ -56,6 +56,7 @@ RECOMMENDATION_THRESHOLDS = {
     # Stock indicators
     'stoc_zile_max': 90,          # days - slow stock threshold
     'rotatie_minima': 4,          # minimum annual rotation
+    'aged_stock_371_pct': 0.15,   # prag CONCENTRARE pentru stoc 371 >3 ani
 
     # Receivables aging
     'restante_90_procent': 10,    # % - max receivables > 90 days

main.py

@@ -280,6 +280,25 @@ class PerformanceLogger:
             print(f"\n📝 Log saved to: {log_file}")
 
 
+def parse_aging_dates(raw: str) -> list:
+    """Parse --aging-dates CLI value into sorted list of data_referinta datetimes.
+
+    Accepts 'YYYY-MM,YYYY-MM,...' (end-of-month), returns list of first-day-next-month datetimes.
+    Raises SystemExit on any invalid token so user sees a clear message, not a crash.
+    """
+    dates = []
+    for token in raw.split(','):
+        tok = token.strip()
+        if not tok:
+            continue
+        try:
+            dates.append(compute_data_referinta(tok))
+        except ValueError as e:
+            print(f"❌ --aging-dates: token invalid '{tok}' (astept YYYY-MM). {e}")
+            sys.exit(1)
+    return sorted(set(dates))
+
+
 def compute_data_referinta(end_month_str: str = None) -> datetime:
     """
     Compute reference date (first day of month AFTER the last reporting month).
@@ -389,6 +408,11 @@ def generate_reports(args):
     results = {}
     perf = PerformanceLogger()  # Initialize performance logger
 
+    # Parse multi-date aging request (validation before DB connection)
+    aging_dates_list = []
+    if getattr(args, 'aging_dates', None):
+        aging_dates_list = parse_aging_dates(args.aging_dates)
+
     with OracleConnection() as conn:
         print("\n📥 Extragere date din Oracle:\n")
 
@@ -398,6 +422,37 @@ def generate_reports(args):
             results[query_name] = df
             perf.stop(rows=len(df) if df is not None and not df.empty else 0)
 
+        # --- Evolutie multi-data stoc 371 >3 ani (optional) ---
+        if aging_dates_list:
+            print(f"\n📥 Extragere evolutie stoc 371 pe {len(aging_dates_list)} date:")
+            evolutie_rows = []
+            sumar_info = QUERIES['stocuri_371_sumar']
+            original_param = sumar_info['params'].get('data_referinta')
+            for dref in aging_dates_list:
+                perf.start(f"QUERY: stocuri_371_sumar@{dref.strftime('%Y-%m-%d')}")
+                sumar_info['params']['data_referinta'] = dref
+                df_e = execute_query(conn, f"stocuri_371_sumar@{dref.strftime('%Y-%m')}", sumar_info)
+                perf.stop(rows=len(df_e) if df_e is not None else 0)
+                if df_e is None or df_e.empty:
+                    continue
+                grand = df_e[df_e['GROUPING_LEVEL'] == 3]
+                if grand.empty:
+                    continue
+                row = grand.iloc[0]
+                val_total = float(row.get('VALOARE_TOTAL', 0) or 0)
+                val_3 = float(row.get('VAL_PESTE_3_ANI', 0) or 0)
+                evolutie_rows.append({
+                    'DATA_REFERINTA': (dref - timedelta(days=1)).strftime('%Y-%m-%d'),
+                    'VALOARE_TOTAL': round(val_total, 2),
+                    'VALOARE_PESTE_3_ANI': round(val_3, 2),
+                    'PROCENT_PESTE_3_ANI': round(val_3 / val_total * 100, 2) if val_total > 0 else 0.0
+                })
+            # restore original data_referinta for downstream consumers
+            sumar_info['params']['data_referinta'] = original_param
+            results['stocuri_371_evolutie'] = pd.DataFrame(evolutie_rows)
+        else:
+            results['stocuri_371_evolutie'] = pd.DataFrame()
+
     # Generate Excel Report
     print("\n📝 Generare raport Excel...")
     excel_gen = ExcelReportGenerator(excel_path)
@@ -537,6 +592,9 @@ def generate_reports(args):
         # STOC
         'stoc_curent',
         'stoc_lent',
+        'stocuri_371_sumar',
+        'stocuri_371_detaliu',
+        'stocuri_371_evolutie',
         'rotatie_stocuri',
 
         # PRODUCTIE
@@ -576,6 +634,28 @@ def generate_reports(args):
             'VALOARE': 'Cantitate × preț achiziție',
             'ZILE_FARA_MISCARE': 'Zile de la ultima ieșire (dataout) sau intrare'
         },
+        'stocuri_371_sumar': {
+            'GROUPING_LEVEL': '0 = detaliu subgrupa, 1 = subtotal per grupa, 3 = grand total (ROLLUP)',
+            'VALOARE_TOTAL': 'Total valoare stoc cont 371 la data de referinta (cost achizitie fara TVA)',
+            'VAL_0_6_LUNI': 'Valoare articole cu vechime 0-180 zile',
+            'VAL_6_12_LUNI': 'Valoare articole cu vechime 181-365 zile',
+            'VAL_1_2_ANI': 'Valoare articole cu vechime 366-730 zile',
+            'VAL_2_3_ANI': 'Valoare articole cu vechime 731-1095 zile',
+            'VAL_PESTE_3_ANI': 'Valoare articole cu vechime peste 1095 zile (risc haircut bancar)'
+        },
+        'stocuri_371_detaliu': {
+            'CANTITATE': 'Stoc final = cants + cant - cante',
+            'VALOARE': 'Cantitate × pret achizitie (cost, fara TVA)',
+            'ZILE_VECHIME': '(data_referinta - 1) - NVL(dataout, datain)',
+            'ANI_VECHIME': 'zile_vechime / 365',
+            'BUCKET_VECHIME': 'Grupare: 0-6 luni / 6-12 luni / 1-2 ani / 2-3 ani / >3 ani'
+        },
+        'stocuri_371_evolutie': {
+            'DATA_REFERINTA': 'End-of-month pentru care s-a calculat snapshot-ul',
+            'VALOARE_TOTAL': 'Total stoc 371 la acea data',
+            'VALOARE_PESTE_3_ANI': 'Portiunea cu vechime >3 ani (trend an-la-an pentru banca)',
+            'PROCENT_PESTE_3_ANI': '% din total care depaseste 3 ani'
+        },
         'rotatie_stocuri': {
             'VALOARE_STOC': 'Stoc curent (cants+cant-cante) × preț achiziție',
             'VANZARI_12_LUNI': 'Doar vânzări (nu transferuri/consumuri) din ultimele 12 luni',
@@ -916,24 +996,37 @@ def generate_reports(args):
         'grad_acoperire_datorii', 'proiectie_lichiditate'
     }
 
+    # Metadata pentru sheet-uri sintetice (nu sunt in QUERIES dar sunt randate)
+    synthetic_sheets = {
+        'stocuri_371_evolutie': {
+            'title': 'Stocuri Marfa 371 - Evolutie >3 ani',
+            'description': 'Valoare totala 371 si portiune >3 ani la mai multe end-of-month (trend)'
+        }
+    }
+
     for query_name in sheet_order:
         # Skip consolidated sheets and their source sheets
         if query_name in consolidated_sheets:
             continue
 
-        if query_name in results and query_name in QUERIES:
-            query_info = QUERIES[query_name]
-            # Create short sheet name from query name
+        if query_name in results and (query_name in QUERIES or query_name in synthetic_sheets):
+            df_sheet = results[query_name]
+            if df_sheet is None or df_sheet.empty:
+                continue
+            if query_name in QUERIES:
+                meta = QUERIES[query_name]
+            else:
+                meta = synthetic_sheets[query_name]
             sheet_name = query_name.replace('_', ' ').title()[:31]
             perf.start(f"EXCEL: {query_name} detail sheet")
             excel_gen.add_sheet(
                 name=sheet_name,
-                df=results[query_name],
-                title=query_info.get('title', query_name),
-                description=query_info.get('description', ''),
+                df=df_sheet,
+                title=meta.get('title', query_name),
+                description=meta.get('description', ''),
                 legend=legends.get(query_name)
             )
-            df_rows = len(results[query_name]) if results[query_name] is not None else 0
+            df_rows = len(df_sheet)
             perf.stop(rows=df_rows)
 
     perf.start("EXCEL: Save workbook")
@@ -1087,6 +1180,94 @@ def generate_reports(args):
             max_rows=20
         )
 
+    # =========================================================================
+    # Pagina dedicata BANCA: Stocuri Marfa 371 pe Vechimi + reconciliere
+    # =========================================================================
+    df_sumar_371 = results.get('stocuri_371_sumar')
+    if df_sumar_371 is not None and not df_sumar_371.empty:
+        perf.start("PDF: Stocuri 371 bank page")
+        pdf_gen.add_page_break()
+
+        nota_metodologica = (
+            "METODOLOGIE: Vechimea este calculata ca numar de zile intre data de referinta "
+            f"({end_date.strftime('%d.%m.%Y')}) si ultima miscare a articolului in stoc "
+            "(iesire, sau intrare daca nu a existat nicio iesire). Valoarea este costul de "
+            "achizitie fara TVA (cant × pret din vstoc). Se includ toate pozitiile cu stoc "
+            "nenul (<> 0), inclusiv cele negative (corectii / erori de inventar), ca sa se "
+            "reconcilieze corect cu soldul contabil 371 din balanta (vbal, cont sintetic)."
+        )
+        pdf_gen.add_explanation(nota_metodologica)
+
+        pdf_gen.add_table_section(
+            "Raport Stocuri Marfa 371 - Sumar Vechimi (pentru banca)",
+            df_sumar_371,
+            columns=['GRUPA', 'SUBGRUPA', 'VALOARE_TOTAL', 'VAL_0_6_LUNI',
+                     'VAL_6_12_LUNI', 'VAL_1_2_ANI', 'VAL_2_3_ANI', 'VAL_PESTE_3_ANI'],
+            max_rows=30
+        )
+
+        df_evolutie_371 = results.get('stocuri_371_evolutie')
+        if df_evolutie_371 is not None and not df_evolutie_371.empty:
+            pdf_gen.add_table_section(
+                "Evolutie stoc 371 >3 ani (multi-data)",
+                df_evolutie_371,
+                columns=['DATA_REFERINTA', 'VALOARE_TOTAL', 'VALOARE_PESTE_3_ANI', 'PROCENT_PESTE_3_ANI'],
+                max_rows=20
+            )
+
+        df_detaliu_371 = results.get('stocuri_371_detaliu')
+        if df_detaliu_371 is not None and not df_detaliu_371.empty:
+            pdf_gen.add_table_section(
+                "Top 25 articole dupa vechime (detaliu 371)",
+                df_detaliu_371,
+                columns=['COD_ARTICOL', 'DENUMIRE', 'CANTITATE', 'VALOARE',
+                         'ZILE_VECHIME', 'BUCKET_VECHIME'],
+                max_rows=25
+            )
+
+        # Reconciliere contabila
+        df_sold = results.get('stocuri_371_sold_contabil')
+        grand_total_row = df_sumar_371[df_sumar_371['GROUPING_LEVEL'] == 3]
+        total_raport = float(grand_total_row['VALOARE_TOTAL'].iloc[0]) if not grand_total_row.empty else 0.0
+
+        sold_contabil = None
+        if df_sold is not None and not df_sold.empty:
+            val = df_sold['SOLD_371'].iloc[0]
+            if val is not None:
+                sold_contabil = float(val)
+
+        if sold_contabil is None:
+            recon_rows = [
+                {'INDICATOR': 'Total valoare stoc 371 (raport)', 'VALOARE_RON': f'{total_raport:,.2f}'},
+                {'INDICATOR': 'Sold contabil 371 (vbal)', 'VALOARE_RON': 'INDISPONIBIL (verifica balanta vbal pe luna ref)'},
+                {'INDICATOR': 'Diferenta', 'VALOARE_RON': 'N/A'}
+            ]
+        else:
+            diferenta = total_raport - sold_contabil
+            pct = (diferenta / sold_contabil * 100) if sold_contabil else 0.0
+            marker = ' ⚠' if abs(pct) > 1.0 else ''
+            recon_rows = [
+                {'INDICATOR': 'Total valoare stoc 371 (raport)', 'VALOARE_RON': f'{total_raport:,.2f}'},
+                {'INDICATOR': 'Sold contabil 371 (vbal, la data ref)', 'VALOARE_RON': f'{sold_contabil:,.2f}'},
+                {'INDICATOR': f'Diferenta{marker}', 'VALOARE_RON': f'{diferenta:,.2f} ({pct:+.2f}%)'}
+            ]
+
+        df_recon = pd.DataFrame(recon_rows)
+        pdf_gen.add_table_section(
+            "RECONCILIERE CONTABILA",
+            df_recon,
+            columns=['INDICATOR', 'VALOARE_RON'],
+            max_rows=5
+        )
+
+        if sold_contabil is not None and abs((total_raport - sold_contabil) / sold_contabil * 100) > 1.0:
+            pdf_gen.add_explanation(
+                "Diferenta >1% intre raport si soldul contabil. Cauze uzuale: evaluare "
+                "pret mediu vs FIFO, inregistrari contabile ulterioare snapshot-ului vstoc, "
+                "sau cont 371 analitic (371.1, 371.2) netotalizat in vbal."
+            )
+        perf.stop()
+
     perf.start("PDF: Save document")
     pdf_gen.save()
     perf.stop()
@@ -1132,6 +1313,13 @@ Exemple:
         help='Luna finala de raportare YYYY-MM (default: luna completa anterioara). Ex: 2026-01'
     )
 
+    parser.add_argument(
+        '--aging-dates',
+        type=str,
+        default=None,
+        help='Lista YYYY-MM separata prin virgula pentru sectiunea evolutie stoc 371 >3 ani. Ex: 2022-12,2023-12,2024-12,2025-12'
+    )
+
     parser.add_argument(
         '--output-dir', '-o',
         type=Path,

queries.py

@@ -440,6 +440,96 @@ ORDER BY zile_fara_miscare DESC NULLS FIRST
 FETCH FIRST 100 ROWS ONLY
 """
 
+# =============================================================================
+# 12b. STOCURI MARFĂ 371 — SUMAR PE VECHIMI (pentru dosar credit bancă)
+# =============================================================================
+STOCURI_371_SUMAR = """
+-- NOTĂ: :data_referinta = prima zi a lunii URMĂTOARE end-month (convenție proiect).
+-- (:data_referinta - 1) = ultima zi a lunii de raport — folosit pentru:
+--   (a) filtru snapshot vstoc: an=YEAR(data_ref-1), luna=MONTH(data_ref-1)
+--   (b) calcul vechime: (data_ref - 1) - NVL(dataout, datain)
+WITH s AS (
+    SELECT
+        s.id_grupa, s.grupa, s.id_subgrupa, s.subgrupa,
+        (s.cants + s.cant - s.cante) * s.pret AS val,
+        ROUND((:data_referinta - 1) - NVL(s.dataout, s.datain)) AS zile
+    FROM vstoc s
+    WHERE s.an = EXTRACT(YEAR FROM (:data_referinta - 1))
+      AND s.luna = EXTRACT(MONTH FROM (:data_referinta - 1))
+      AND s.cont = '371'
+      AND (s.cants + s.cant - s.cante) <> 0
+)
+SELECT
+    NVL(grupa, 'NECLASIFICAT') AS grupa,
+    NVL(subgrupa, '-') AS subgrupa,
+    GROUPING_ID(grupa, subgrupa) AS grouping_level,
+    ROUND(SUM(val), 2) AS valoare_total,
+    ROUND(SUM(CASE WHEN zile <= 180 THEN val ELSE 0 END), 2) AS val_0_6_luni,
+    ROUND(SUM(CASE WHEN zile > 180 AND zile <= 365 THEN val ELSE 0 END), 2) AS val_6_12_luni,
+    ROUND(SUM(CASE WHEN zile > 365 AND zile <= 730 THEN val ELSE 0 END), 2) AS val_1_2_ani,
+    ROUND(SUM(CASE WHEN zile > 730 AND zile <= 1095 THEN val ELSE 0 END), 2) AS val_2_3_ani,
+    ROUND(SUM(CASE WHEN zile > 1095 THEN val ELSE 0 END), 2) AS val_peste_3_ani
+FROM s
+GROUP BY ROLLUP(grupa, subgrupa)
+ORDER BY GROUPING_ID(grupa, subgrupa), grupa, subgrupa
+"""
+
+# =============================================================================
+# 12c. STOCURI MARFĂ 371 — DETALIU ARTICOLE
+# =============================================================================
+STOCURI_371_DETALIU = """
+-- Vezi NOTA de la STOCURI_371_SUMAR.
+SELECT
+    s.codmat AS cod_articol,
+    s.denumire,
+    s.nume_gestiune,
+    NVL(s.grupa, 'NECLASIFICAT') AS grupa,
+    NVL(s.subgrupa, '-') AS subgrupa,
+    s.um,
+    (s.cants + s.cant - s.cante) AS cantitate,
+    ROUND(s.pret, 4) AS pret_unitar,
+    ROUND((s.cants + s.cant - s.cante) * s.pret, 2) AS valoare,
+    s.datain AS data_intrare,
+    s.dataout AS data_ultima_iesire,
+    ROUND((:data_referinta - 1) - NVL(s.dataout, s.datain)) AS zile_vechime,
+    ROUND(((:data_referinta - 1) - NVL(s.dataout, s.datain)) / 365, 2) AS ani_vechime,
+    CASE
+        WHEN ROUND((:data_referinta - 1) - NVL(s.dataout, s.datain)) <= 180 THEN '0-6 luni'
+        WHEN ROUND((:data_referinta - 1) - NVL(s.dataout, s.datain)) <= 365 THEN '6-12 luni'
+        WHEN ROUND((:data_referinta - 1) - NVL(s.dataout, s.datain)) <= 730 THEN '1-2 ani'
+        WHEN ROUND((:data_referinta - 1) - NVL(s.dataout, s.datain)) <= 1095 THEN '2-3 ani'
+        ELSE '>3 ani'
+    END AS bucket_vechime,
+    s.lot,
+    s.adata_expirare AS data_expirare,
+    s.furnizor
+FROM vstoc s
+WHERE s.an = EXTRACT(YEAR FROM (:data_referinta - 1))
+  AND s.luna = EXTRACT(MONTH FROM (:data_referinta - 1))
+  AND s.cont = '371'
+  AND (s.cants + s.cant - s.cante) <> 0
+ORDER BY zile_vechime DESC, valoare DESC
+"""
+
+# =============================================================================
+# 12d. SOLD CONTABIL 371 (reconciliere cu raport)
+# =============================================================================
+STOCURI_371_SOLD_CONTABIL = """
+-- Sold contabil 371 la finalul lunii de raportare, din balanta de verificare (vbal).
+-- Filtrul (an, luna) = ultima luna raportata, identic cu vstoc:
+--   an  = EXTRACT(YEAR  FROM (:data_referinta - 1))
+--   luna= EXTRACT(MONTH FROM (:data_referinta - 1))
+-- 371 este cont de activ => sold debitor. Folosim (solddeb - soldcred) ca sa fie
+-- robust daca exista inregistrari cu sold credit (corectii). Se aduna pe toate
+-- sucursalele (id_sucursala), pentru ca raportul vstoc acopera toate gestiunile.
+SELECT
+    ROUND(SUM(NVL(b.solddeb, 0) - NVL(b.soldcred, 0)), 2) AS sold_371
+FROM vbal b
+WHERE b.cont = '371'
+  AND b.an = EXTRACT(YEAR FROM (:data_referinta - 1))
+  AND b.luna = EXTRACT(MONTH FROM (:data_referinta - 1))
+"""
+
 # =============================================================================
 # 13. ROTAȚIE STOCURI
 # =============================================================================
@@ -2496,6 +2586,24 @@ QUERIES = {
         'title': '⚠️ Stoc Lent (>90 zile)',
         'description': 'Produse fără mișcare de peste 90 de zile'
     },
+    'stocuri_371_sumar': {
+        'sql': STOCURI_371_SUMAR,
+        'params': {},
+        'title': 'Stocuri Marfă 371 — Sumar Vechimi (pentru bancă)',
+        'description': 'Valoarea stocului cont 371 pe grupe și buckets de vechime la data de referință'
+    },
+    'stocuri_371_detaliu': {
+        'sql': STOCURI_371_DETALIU,
+        'params': {},
+        'title': 'Stocuri Marfă 371 — Detaliu Articole',
+        'description': 'Lista completă articole cont 371 cu vechime și valoare'
+    },
+    'stocuri_371_sold_contabil': {
+        'sql': STOCURI_371_SOLD_CONTABIL,
+        'params': {},
+        'title': 'Stocuri Marfă 371 — Sold Contabil (reconciliere)',
+        'description': 'Sold 371 din rulaje la data ref pentru cross-check'
+    },
     'rotatie_stocuri': {
         'sql': ROTATIE_STOCURI,
         'params': {},

recommendations.py

@@ -297,7 +297,26 @@ class RecommendationsEngine:
                     vezi_detalii='Sheet: Rotatie Stocuri'
                 )
 
-        # 3. Check cash conversion cycle
+        # 3. Check aged stock 371 (bank collateral haircut risk)
+        stocuri_371 = results.get('stocuri_371_detaliu')
+        if stocuri_371 is not None and not stocuri_371.empty and 'VALOARE' in stocuri_371.columns:
+            valoare_total = stocuri_371['VALOARE'].sum()
+            if valoare_total > 0 and 'BUCKET_VECHIME' in stocuri_371.columns:
+                peste_3 = stocuri_371[stocuri_371['BUCKET_VECHIME'] == '>3 ani']['VALOARE'].sum()
+                procent = peste_3 / valoare_total
+                prag = self.thresholds.get('aged_stock_371_pct', 0.15)
+                if procent > prag:
+                    self._add_recommendation(
+                        categorie='Stoc 371',
+                        indicator='Marfa invechita cont 371',
+                        valoare=f'{procent*100:.1f}%',
+                        status='CONCENTRARE',
+                        explicatie=f'{procent*100:.1f}% din valoarea stocului 371 are >3 ani ({peste_3:,.0f} RON). Banca aplica haircut la evaluare colateral.',
+                        recomandare='Lichidare / provizionare recomandata inainte de depunere dosar credit.',
+                        vezi_detalii='Sheet: stocuri_371_detaliu'
+                    )
+
+        # 4. Check cash conversion cycle
         ciclu = results.get('ciclu_conversie_cash')
         if ciclu is not None and not ciclu.empty:
             dio_row = ciclu[ciclu['INDICATOR'].str.contains('stoc|DIO', case=False, na=False)]

run.bat

@@ -1,5 +1,22 @@
 @echo off
-REM Run Data Intelligence Report Generator (Windows)
+REM =============================================================================
+REM Data Intelligence Report Generator - ROMFAST
+REM =============================================================================
+REM
+REM Argumente disponibile:
+REM   --months N              Numar luni pentru analiza (default: 12)
+REM   --end-month YYYY-MM     Luna finala de raportare (default: luna precedenta)
+REM                           Ex: --end-month 2025-12
+REM   --aging-dates LIST      Lista YYYY-MM pentru evolutie stoc 371 >3 ani
+REM                           Ex: --aging-dates 2022-12,2023-12,2024-12,2025-12
+REM   --output-dir PATH       Director output (default: ./output)
+REM
+REM Exemple:
+REM   run.bat                                          (raport standard)
+REM   run.bat --end-month 2025-12                      (raport dosar banca)
+REM   run.bat --end-month 2025-12 --aging-dates 2022-12,2023-12,2024-12,2025-12
+REM                                                    (raport dosar banca + trend)
+REM =============================================================================
 
 cd /d "%~dp0"
 call .venv\Scripts\activate.bat