In many cx_Oracle applications, executing SQL and PL/SQL statements using the method cursor.execute() is perfect. This article shows how batch statement execution in the Python cx_Oracle interface for Oracle Database can significantly improve performance and make working with large data sets easy.
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You learn a common Batch application workflow and how to interact programmatically with Batch and Storage resources. This tutorial walks through a Python example of running a parallel workload using Batch. import os, re for root, dir, file in os.walk(/path/to/files): for f in file: if re.match('.*\.dat$', f): run_existing_script1 root + / file run_existing_script2 root + / fil Use Azure Batch to run large-scale parallel and high-performance computing (HPC) batch jobs efficiently in Azure. You may then open Notepad and copy the code below You can write a batch script in python using os.walk() to generate a list of the files and then process them one by one with your existing python programs. For demonstration purposes, I created a simple batch file that would produce The Matrix effect, but the method described here would work for any batch file that you'd like to run from Python. Steps to Create a Batch File to Run Python Script Step 1: Create the Python Script Step 2: Save your Script Step 3: Create the Batch File Step 4: Run the Batch Fil Steps to Run a Batch File from Python Step 1: Create the batch file.