elab matlab

utils/csv/data_preparation.py

@@ -9,6 +9,16 @@ from itertools import islice
 logger = logging.getLogger(__name__)
 
 async def get_data(cfg: object, id: int, pool) -> tuple:
+    """
+    Retrieves unit name, tool name, and tool data for a given record ID from the database.
+
+    Args:
+        cfg (object): Configuration object containing database table name.
+        id (int): The ID of the record to retrieve.
+        pool: The database connection pool.
+    Returns:
+        tuple: A tuple containing unit_name, tool_name, and tool_data.
+    """
     async with pool.acquire() as conn:
         async with conn.cursor() as cur:
             await cur.execute(f'select unit_name, tool_name, tool_data from {cfg.dbrectable} where id = {id}')
@@ -17,6 +27,16 @@ async def get_data(cfg: object, id: int, pool) -> tuple:
             return unit_name, tool_name, tool_data
 
 async def make_pipe_sep_matrix(cfg: object, id: int, pool) -> list:
+    """
+    Processes pipe-separated data from a CSV record into a structured matrix.
+
+    Args:
+        cfg (object): Configuration object.
+        id (int): The ID of the CSV record.
+        pool: The database connection pool.
+    Returns:
+        list: A list of lists, where each inner list represents a row in the matrix.
+    """
     UnitName, ToolNameID, ToolData = await get_data(cfg, id, pool)
     righe = ToolData.splitlines()
     matrice_valori = []
@@ -39,6 +59,16 @@ async def make_pipe_sep_matrix(cfg: object, id: int, pool) -> list:
     return matrice_valori
 
 async def make_ain_din_matrix(cfg: object, id: int, pool) -> list:
+    """
+    Processes analog and digital input data from a CSV record into a structured matrix.
+
+    Args:
+        cfg (object): Configuration object.
+        id (int): The ID of the CSV record.
+        pool: The database connection pool.
+    Returns:
+        list: A list of lists, where each inner list represents a row in the matrix.
+    """
     UnitName, ToolNameID, ToolData = await get_data(cfg, id, pool)
     node_channels, node_types, node_ains, node_dins = get_nodes_type(cfg, ToolNameID, UnitName)
     righe = ToolData.splitlines()
@@ -63,6 +93,16 @@ async def make_ain_din_matrix(cfg: object, id: int, pool) -> list:
     return matrice_valori
 
 async def make_channels_matrix(cfg: object, id: int, pool) -> list:
+    """
+    Processes channel-based data from a CSV record into a structured matrix.
+
+    Args:
+        cfg (object): Configuration object.
+        id (int): The ID of the CSV record.
+        pool: The database connection pool.
+    Returns:
+        list: A list of lists, where each inner list represents a row in the matrix.
+    """
     UnitName, ToolNameID, ToolData = await get_data(cfg, id, pool)
     node_channels, node_types, node_ains, node_dins = get_nodes_type(cfg, ToolNameID, UnitName)
     righe = ToolData.splitlines()
@@ -81,6 +121,16 @@ async def make_channels_matrix(cfg: object, id: int, pool) -> list:
     return matrice_valori
 
 async def make_musa_matrix(cfg: object, id: int, pool) -> list:
+    """
+    Processes 'Musa' specific data from a CSV record into a structured matrix.
+
+    Args:
+        cfg (object): Configuration object.
+        id (int): The ID of the CSV record.
+        pool: The database connection pool.
+    Returns:
+        list: A list of lists, where each inner list represents a row in the matrix.
+    """
     UnitName, ToolNameID, ToolData = await get_data(cfg, id, pool)
     node_channels, node_types, node_ains, node_dins = get_nodes_type(cfg, ToolNameID, UnitName)
     righe = ToolData.splitlines()
@@ -104,6 +154,16 @@ async def make_musa_matrix(cfg: object, id: int, pool) -> list:
 
 
 async def make_tlp_matrix(cfg: object, id: int, pool) -> list:
+    """
+    Processes 'TLP' specific data from a CSV record into a structured matrix.
+
+    Args:
+        cfg (object): Configuration object.
+        id (int): The ID of the CSV record.
+        pool: The database connection pool.
+    Returns:
+        list: A list of lists, where each inner list represents a row in the matrix.
+    """
     UnitName, ToolNameID, ToolData = await get_data(cfg, id, pool)
     righe = ToolData.splitlines()
     valori_x_nodo = 2
@@ -121,6 +181,16 @@ async def make_tlp_matrix(cfg: object, id: int, pool) -> list:
 
 
 async def make_gd_matrix(cfg: object, id: int, pool) -> list:
+    """
+    Processes 'GD' specific data from a CSV record into a structured matrix.
+
+    Args:
+        cfg (object): Configuration object.
+        id (int): The ID of the CSV record.
+        pool: The database connection pool.
+    Returns:
+        list: A list of lists, where each inner list represents a row in the matrix.
+    """
     UnitName, ToolNameID, ToolData = await get_data(cfg, id, pool)
     righe = ToolData.splitlines()
     matrice_valori = []

utils/csv/loaders.py

@@ -7,6 +7,15 @@ import logging
 logger = logging.getLogger(__name__)
 
 async def main_loader(cfg: object, id: int, pool, action: str) -> None:
+    """
+    Main loader function to process CSV data based on the specified action.
+
+    Args:
+        cfg (object): Configuration object.
+        id (int): The ID of the CSV record to process.
+        pool: The database connection pool.
+        action (str): The type of data processing to perform (e.g., "pipe_separator", "analogic_digital").
+    """
     type_matrix_mapping = {
         "pipe_separator": make_pipe_sep_matrix,
         "analogic_digital": make_ain_din_matrix,
@@ -27,3 +36,39 @@ async def main_loader(cfg: object, id: int, pool, action: str) -> None:
             await unlock(cfg, id, pool)
     else:
         logger.warning(f"Action '{action}' non riconosciuta.")
+
+
+async def get_next_csv_atomic(pool, table_name, status):
+    """Preleva atomicamente il prossimo CSV da elaborare"""
+    async with pool.acquire() as conn:
+        # IMPORTANTE: Disabilita autocommit per questa transazione
+        await conn.begin()
+
+        try:
+            async with conn.cursor() as cur:
+                # Usa SELECT FOR UPDATE per lock atomico
+                await cur.execute(f"""
+                    SELECT id, unit_type, tool_type, unit_name, tool_name
+                    FROM {table_name}
+                    WHERE locked = 0 AND status = %s
+                    ORDER BY id
+                    LIMIT 1
+                    FOR UPDATE SKIP LOCKED
+                """, (status,))
+
+                result = await cur.fetchone()
+                if result:
+                    await cur.execute(f"""
+                        UPDATE {table_name}
+                        SET locked = 1
+                        WHERE id = %s
+                    """, (result[0],))
+
+                # Commit esplicito per rilasciare il lock
+                await conn.commit()
+                return result
+
+        except Exception as e:
+            # Rollback in caso di errore
+            await conn.rollback()
+            raise e