Go is an open source programming language that makes it easy to build simple, reliable, and efficient software. It provides an expressive syntax with its lightweight type system and comes with concurrency as a built-in feature at the language level.
In this post, we’ll look at how to build Go programs – such as compilers and static analysis tools – that interact with the LLVM compiler framework using the LLVM IR assembly language.
Today we will see how Apache Arrow could be useful for data science, or – really – a lot of analysis workloads.
Lingua franca In Data Science and in many scientific fields, the lingua franca is Python.
Overview Apache Beam (batch and stream) is a powerful tool for handling embarrassingly parallel workloads. It is a evolution of Google’s Flume, which provides batch and streaming data processing based on the MapReduce concepts.
Interfaces are one of the fundamental tools for abstraction in Go. Interfaces store type information when assigned a value. Reflection is a method of examining type and value information at runtime.
Debuggers. Traditionally they are used to find complex bugs and reason about how they happen. But what if you cannot explain why some changes happen between steps?