Preface
Every one of us who works with technology knows the feeling of finding a tool that perfectly fits the need for which it was designed. Jython is one of those perfect fits, combining the ease of Python scripting with the ubiquity and power of the Java libraries and Java Virtual Machine. Each of the book’s two authors had an “Aha!” experience discovering the power of Jython.
Samuele Pedroni’s moment came when a friend got him involved in a project about machine learning and artificial life. They originally planned to implement the project in Java. Java’s garbage collection and rich libraries meant that they could focus just on their ideas. The system needed to be portable, and had to allow for the distribution of the computational load over many machines, when necessary.
At the same time, Samuele was reading O’Reilly’s Learning Python and discovered what was then called JPython. The first thing he did with JPython was embed it in a CORBA server to manage startup configuration on his artificial life project. Samuele discovered that mixing Java and JPython gave him and his friend even more freedom to express their ideas.
Over time, they wrote a constellation of tools for their simulations in Jython. In the meantime, Samuele got involved in JPython development while it was transitioning from Jim Hugunin’s original JPython project to the “truly” open source Jython project.
Noel Rappin’s case is similar. He was working on a short program and wanted the flexibility and development speed ...
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