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Voltaire Yap, Global Events Manager, Oracle Corp.
AI innovation in the Java ecosystem is accelerating through projects like LangChain4j, Spring AI, and llama3.java, yet Python remains the powerhouse for AI, machine learning, and data science. What if Java developers could use Python’s rich ecosystem directly within their existing Java services, without context switching? This session demonstrates how to do exactly that with GraalPy, a high-performance, embeddable Python 3 runtime for Java.
Attendees will learn how to embed Python in Java applications, install and bundle Python packages using Maven or Gradle plugins, and interact with Python libraries through Java interfaces. The session will feature examples of local inference, data processing, and visualization within Spring Boot and Micronaut applications, and show how to package polyglot Java+Python applications as single deployable JARs. The talk will also explore how to build native executables using GraalVM Native Image to optimize performance and startup time.
What You Will Learn
How to embed Python code in Java using GraalPy
Techniques for integrating Python AI libraries into Spring and Micronaut services
How to package and deploy polyglot Java+Python applications efficiently
Performance optimization using GraalVM Native Image
Who Should Attend
Java developers, software architects, and AI engineers interested in combining Java’s robustness with Python’s AI and data science capabilities in production-ready enterprise applications.
