Discussion of article "Integrating ML models with the Strategy Tester (Part 3): Managing CSV files (II)"
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New article Integrating ML models with the Strategy Tester (Part 3): Managing CSV files (II) has been published:
This material provides a complete guide to creating a class in MQL5 for efficient management of CSV files. We will see the implementation of methods for opening, writing, reading, and transforming data. We will also consider how to use them to store and access information. In addition, we will discuss the limitations and the most important aspects of using such a class. This article ca be a valuable resource for those who want to learn how to process CSV files in MQL5.
The CSV format appeared in the early 1970s and was first used on mainframe systems. CSV cannot be traced to a specific creator since it is a widely used file type.
It is often used to import and export data in various applications such as spreadsheets, databases, data analysis programs, etc. Its popularity is due to both ease of use and understanding, and compatibility with many systems and tools. This is especially useful when we need to share data between different applications, for example to transfer information from one system to another.
So, the key advantages of using CSV are ease of use and compatibility. However, it also has some limitations, such as lack of support for complex data types and reduced ability to handle very large amounts of data. Also, the lack of a universal standard for the CSV format can cause compatibility issues between different applications. In addition, you can accidentally lose or modify data since the format does not provide validation. In general, CSV is a versatile and easy-to-use option for storing and sharing data. Nevertheless, it's important to know and fully understand its limitations and take steps to ensure data accuracy.
Author: Jonathan Pereira