commit abfe04716562316223be065edb63c9f9cef24902
Author: admin <l.barontini@open-squared.ch>
Date:   Tue Feb 10 19:11:45 2026 +0000

    Add faircot_automation.py

diff --git a/faircot_automation.py b/faircot_automation.py
new file mode 100644
index 0000000..f7825c9
--- /dev/null
+++ b/faircot_automation.py
@@ -0,0 +1,167 @@
+import pandas as pd
+import pyodbc
+from sqlalchemy import create_engine, text, inspect
+from sqlalchemy.types import Date, VARCHAR
+
+# =========================
+# Connexion SQL Server
+# =========================
+sql_server_conn_str = (
+    "DRIVER={ODBC Driver 18 for SQL Server};"
+    "SERVER=VPS88.DATACENTER.CSTI;"
+    "DATABASE=FAIRCOT-Test;"
+    "UID=SINGA_META;"
+    "PWD=Start.123;"
+    "TrustServerCertificate=yes;"
+)
+
+sql_conn = pyodbc.connect(sql_server_conn_str)
+
+# =========================
+# Lecture de la vue
+# =========================
+query = "SELECT * FROM [SINGA_VW_FREIGHT_BOOKING_INFO]"
+df = pd.read_sql(query, sql_conn)
+
+print("Colonnes chargées depuis la vue :")
+print(df.columns.tolist())
+print(f"{len(df)} lignes chargées")
+
+# =========================
+# Conversion des dates
+# =========================
+df["BL_Date"] = pd.to_datetime(
+    df["BL_Date"].astype(str),
+    format="%Y%m%d",
+    errors="coerce"
+)
+
+df["ETD_Date"] = pd.to_datetime(
+    df["ETD_Date"].astype(str),
+    format="%Y%m%d",
+    errors="coerce"
+)
+
+query2 = "SELECT * FROM [SINGA_VW_LOTS_SHIPPED_BY_BOOKING]"
+df2 = pd.read_sql(query2, sql_conn)
+
+df2["BOOKING_DATE"] = pd.to_datetime(df2["BOOKING_DATE"].astype(str), format="%Y%m%d", errors="coerce")
+df2["LOT_CREATION_DATE"] = pd.to_datetime(df2["LOT_CREATION_DATE"].astype(str), format="%Y%m%d", errors="coerce")
+df2["LOT_UPDATE_DATE"] = pd.to_datetime(df2["LOT_UPDATE_DATE"].astype(str), format="%Y%m%d", errors="coerce")
+df2["LOGDOC_DATE"] = pd.to_datetime(df2["LOGDOC_DATE"].astype(str), format="%Y%m%d", errors="coerce")
+df2["SALE_INVOICE_DATE"] = pd.to_datetime(df2["SALE_INVOICE_DATE"].astype(str), format="%Y%m%d", errors="coerce")
+
+# =========================
+# Diagnostic
+# =========================
+print("\n🔎 DIAGNOSTIC BL_Date")
+print("BL_Date type :", df["BL_Date"].dtype)
+print("BL_Date min :", df["BL_Date"].min())
+print("BL_Date max :", df["BL_Date"].max())
+
+# =========================
+# Filtre
+# =========================
+df = df[df["BL_Date"] > pd.Timestamp("2025-09-01")]
+print(f"{len(df)} lignes après filtre BL_Date > 2025-09-01")
+
+# =========================
+# Sécurisation colonnes texte
+# =========================
+if "ShippingInstructionNumber" in df.columns:
+    df["ShippingInstructionNumber"] = df["ShippingInstructionNumber"].astype(str)
+
+df3 = pd.read_sql("SELECT * FROM [ALF]", sql_conn)
+df4 = pd.read_sql("SELECT * FROM [PLACES]", sql_conn)
+
+# =========================
+# Connexion PostgreSQL
+# =========================
+pg_engine = create_engine(
+    "postgresql://postgres:dsproject@localhost:5433/tradon"
+)
+
+inspector = inspect(pg_engine)
+
+table_name = "freight_booking_info"
+table_name2 = "freight_booking_lots"
+table_name3 = "alf"
+table_name4 = "places"
+
+dtype_mapping = {
+    "ETD_Date": Date(),
+    "BL_Date": Date(),
+    "ShippingInstructionNumber": VARCHAR(255),
+}
+
+dtype_mapping2 = {
+    "BOOKING_DATE": Date(),
+    "LOT_CREATION_DATE": Date(),
+    "LOT_UPDATE_DATE": Date(),
+    "LOGDOC_DATE": Date(),
+    "SALE_INVOICE_DATE": Date(),
+}
+
+# =========================
+# Synchronisation PostgreSQL
+# =========================
+
+# ---- freight_booking_info
+with pg_engine.begin() as conn:
+    if table_name in inspector.get_table_names():
+        conn.execute(text(f'TRUNCATE TABLE "{table_name}"'))
+
+    df.to_sql(
+        table_name,
+        conn,
+        if_exists="append",
+        index=False,
+        dtype=dtype_mapping,
+    )
+
+print(f"♻️ Table mise à jour : {table_name} ({len(df)} lignes)")
+
+# ---- freight_booking_lots
+with pg_engine.begin() as conn:
+    if table_name2 in inspector.get_table_names():
+        conn.execute(text(f'TRUNCATE TABLE "{table_name2}"'))
+
+    df2.to_sql(
+        table_name2,
+        conn,
+        if_exists="append",
+        index=False,
+        dtype=dtype_mapping2,
+    )
+
+print(f"♻️ Table mise à jour : {table_name2} ({len(df2)} lignes)")
+
+# ---- alf
+with pg_engine.begin() as conn:
+    if table_name3 in inspector.get_table_names():
+        conn.execute(text(f'TRUNCATE TABLE "{table_name3}"'))
+
+    df3.to_sql(
+        table_name3,
+        conn,
+        if_exists="append",
+        index=False,
+    )
+
+print(f"♻️ Table mise à jour : {table_name3} ({len(df3)} lignes)")
+
+# ---- places
+with pg_engine.begin() as conn:
+    if table_name4 in inspector.get_table_names():
+        conn.execute(text(f'TRUNCATE TABLE "{table_name4}"'))
+
+    df4.to_sql(
+        table_name4,
+        conn,
+        if_exists="append",
+        index=False,
+    )
+
+print(f"♻️ Table mise à jour : {table_name4} ({len(df4)} lignes)")
+
+print("\n🎉 Synchronisation terminée : table filtrée sur BL_Date > 01/09/2025")