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This article discusses in depth how to use the pyads library to efficiently process PLC real-time data notifications. For high concurrency and large data volume scenarios, we propose and elaborate on class encapsulation-based solutions to avoid global variables and achieve clearer state management and data accumulation. At the same time, the article also introduces key techniques for optimizing data parsing performance, including batch processing using raw byte data and NumPy, aiming to help developers build a robust and high-performance PLC data acquisition system.

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This tutorial explores how to efficiently and Pythonically process real-time, large-scale notification data from PLCs in PyADS applications, avoiding the use of global variables. By introducing a class-based callback function management model, the article elaborates on how to safely integrate callback data into application state and provides strategies to optimize data conversion performance, especially for high-throughput data acquisition scenarios.

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I'm having a tricky problem when developing a PHP project that handles file uploads: How to map the MIME type of a file with its extension exactly? This problem not only affects the identification of files, but also leads to confusion in data processing. After trying multiple methods, I found the fileeye/mimemap library, which not only solved my problem, but also greatly improved the processing efficiency.

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