Go is a great language, but it seems terribly suited to data science. The popular data science languages are Python, R, Julia, and to a lesser extent Scala. They’re all extremely flexible languages, where you can easily write high level abstractions/DSLs, and they all have very strong functional programming support, because data science tends to be extremely functional. They also tend to be very concise languages.
Go is at the complete opposite end of the spectrum - not flexible at all, it’s purposefully difficult and awkward to write high level abstractions/DSLs, there’s very poor functional programming support, and it’s very verbose. There are great reasons for these restrictions, they’re intentional design decisions, but they also make it a very poor fit for data science IMO.
Go is at the complete opposite end of the spectrum - not flexible at all, it’s purposefully difficult and awkward to write high level abstractions/DSLs, there’s very poor functional programming support, and it’s very verbose. There are great reasons for these restrictions, they’re intentional design decisions, but they also make it a very poor fit for data science IMO.