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import cx_Oracle import threading pool = cx_Oracle.SessionPool(db_config.user, db_config.pw, db_config.dsn + ":pooled", min = 2, max = 5, increment = 1, threaded = True, getmode = cx_Oracle.SPOOL_ATTRVAL_WAIT) def Query(): con = pool.acquire(cclass = "PYTHONHOL", purity = cx_Oracle.ATTR_PURITY_SELF) cur = conn.cursor() for i in range(4): cur ...
in this tutorial, you will learn how to select data from Oracle Database using fetchone(), fetchmany(), and fetchall() methods.
30 Αυγ 2018 · When you decide to create pandas dataframes from data coming from Oracle (or another database, CSV file, JSON etc.), you have to use pandas function written specifically for this purpose. And in the case of an Oracle database, you have a function read_sql () that can be executed with a sql statement given in parameter.
14 Φεβ 2023 · Each Oracle connection can only do one database operation at a time, so there would be no parallelization. Here’s a demo I threw together that actually does use multiple connections:
26 Μαΐ 2021 · The answer supplied by Joe Thor will work well so long as the values in the SOUTHERN_STATE variable are well-known and cannot result in SQL injection. If the values are not well-known, this solution can be used instead: SOUTHERN_STATE = ["AL", "GA", "TN", ....] bind_names = ",".join(":" + str(i + 1) for i in range(len(SOUTHERN_STATE))) sql = f""".
31 Ιαν 2023 · For example, to execute a SELECT statement, you can use the following code: # Execute a SELECT statement. cursor.execute('SELECT * FROM table_name') # Fetch the results. results = cursor.fetchall() # Loop through the results. for row in results: print(row)
20 Αυγ 2024 · Pipelining is simple in python-oracledb: you add operations such as INSERT and SELECT statements to a “pipeline” object, send that object to the database which processes the statements, and...
