Using CSS Selectors to Extract Trading Data from HTML
Summary
This article explains how an MQL5 program can turn HTML pages into structured data using a document object model and CSS selectors. A parser reads tags, attributes, text, and nesting, then selector queries can locate items such as table rows and specific cells. The described selectors cover tag, class, identifier, attribute, child-position, and relationship-based matching. The article also notes that real web pages may contain malformed or inconsistent markup, so a practical parser needs to tolerate variations.
Examples show how extracted data can support tasks such as reading economic calendar information or processing third-party trading reports, with results exported or used in an Expert Advisor. The approach is useful when a service lacks a suitable API, but it depends on the target page’s structure and selector settings, which may need revision as pages change. The material describes data extraction infrastructure rather than a trading signal or evidence of strategy performance.
Key ideas
- An HTML parser can build a DOM tree that preserves tag hierarchy and attributes.
- CSS selectors provide a query language for finding page elements by properties and relationships.
- Selector queries can isolate table rows and cells for structured data extraction.
- Real-world markup can be malformed or inconsistent, so parsers must handle variations.
- Extracted data can feed files, chart displays, or Expert Advisor calculations.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.