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Analysis

Similar to how much of the crawling code is modular and configurable to a particular interface and/or crawling context, so is the analysis of the graph (that is produced by crawling an application).

To analyze a graph produced by any interface and/or crawling context, use the demodocusfw.analysis.BaseAnalyzer. By default, it will compare the graph of each crawl UserModel to that of the build UserModel, both with network metrics and optimal paths. A report is printed to the output directory called analysis_report.md. An analyzed .gml file is also outputted, which can be read into the graph application for visualization.

Implementing a new Analyzer

The accessibility context required more analysis than what is generic to all applications, and is a good example on how to implement other Analyzers. See demodocusfw/web/accessibility/analysis.py for more details. When building a new Analyzer, you may want to perform analysis on the fully built graph (not specific to any UserModel), and/or you may want to perform analysis for each of the UserModels that crawled the graph. To do this, you will need to override the following fields and methods in BaseAnalyzer.

NOTE: If you only need to make changes to just the build analysis, you do not need to change Fields and Methods associated with the crawl_users, and vice versa.

If a new Analyzer needs access to other data, simply put that data in your crawler configuration file. All analyzers have full access to the data in the config using their Analyzer.config instance getter method.

There are many other methods that can be updated, and many that probably won’t need to be updated. For more of those details, see the high-level comments in demodocusfw/analyis.py::BaseAnalyzer.