The rdfpro-core library provides the RDFProcessor abstraction, the implementation of processors for common tasks and the logic required for composing processors in a pipeline. This library represent the basis of the rdfpro command line tool and can be embedded in applications to perform rdfpro tasks via Java code.

In order to use the rdfpro-core library you have to include the following dependency in your pom.xml:

<dependency>
  <groupId>eu.fbk.rdfpro</groupId>
  <artifactId>rdfpro-core</artifactId>
  <version>0.6</version>
</dependency>

If you don’t use Maven, you have to download and include the following mandatory JARs in the classpath:

Note that the three Sesame JARs are not necessary in case the openrdf-sesame-2.8.6-onejar.jar file is already included. The SLF4J API is used by Sesame for logging. You need to include also an implementation (e.g., Logback) for logging to work.

In case you want to use the @groovy processor, you also have to include the following dependency in your pom.xml:

<dependency>
  <groupId>eu.fbk.rdfpro</groupId>
  <artifactId>rdfpro-groovy</artifactId>
  <version>0.6</version>
</dependency>

If you don’t use Maven, ensure to download and include the additional JARs in the classpath:

The library main abstraction is the interface RDFProcessor. You can obtain RDFProcessor implementation for common processing tasks and you can apply sequential and parallel composition using the static factory methods in the companion class RDFProcessors. You can also implement interface RDFProcessor to build your own processor, which can then be used and composed in pipelines as done with builtin processors. See the Javadoc for further details.

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Last Published: 2016/07/22.

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