A one-stop solution for generating, inserting, and verifying quick response codes in scientific journals based on Python

Background: This study aims to make quick response (QR) code processing operable, reliable, and efficient. It discusses the exploration and practice of QR code processing in Computer Systems & Applications, providing a useful reference for editors. Methods: Common problems encountered when manually handling QR codes are summarized and analyzed. A QR code-integrated tool is designed using Python language to propose an integrated solution for QR codes, and the tool is compared with manual solutions. Results: The self-developed QR code-integrated tool can realize the automatic processing of tasks, such as generating, inserting, and verifying QR codes, thereby achieving high efficiency and reliability. For example, it takes about 2 hours to handle 45 papers by hand, whereas automated operations require only about 30 seconds, without any errors. The use of tools to automatically verify QR codes no longer relies on uniform resource locator (URL) activation, achieving perfect integration between QR code processing flow and the traditional editorial publishing process. Conclusion: Using Python, this study demonstrates that high-quality QR code settings can be achieved efficiently in single articles in scientific journals. Computer automation operations have high efficiency and strong reliability in dealing with repetitive work. Scientific journal editors should think creatively and continuously improve their work efficiency by adopting computer technology to refine workflow.