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In this talk, I will show how you can use ScalaPy to leverage an excellent NLP library like Spacy, minimizing your discomfort of using Python, and enhancing your comfort with Scala 3 for the remaining parts of your application.
In many domains of computer science, state-of-the-art frameworks are written in Python. Natural Language Processing (NLP) is such a domain, and if you want to use cutting-edge approaches, you have to resort to Python libraries. In this talk, I will show how you can use ScalaPy to leverage an excellent NLP library like Spacy, minimizing your discomfort of using Python, and enhancing your comfort with Scala 3 for the remaining parts of your application. I will show everything from configuring your (minimal) environment to interacting with Python, defining facades, and controlling memory usage.
In this talk, we will start with the basics, understanding what build caching is and why it can be a bit tricky to handle in real projects.
I propose that we can extend Mirrors to operations, and use the most natural DSL of all - plain trait definitions.
In this talk, I will cover three key concepts that emerged from reflecting on this past year of learning: making mistakes, helping others to help you and finding community.
