Experiments with Go generics


Quick experiments with Go generics

  • algebra, a generic square root function for float, complex and and rational.
  • future, a concurrent cache ("future cache").
  • mapreduce, parallel Map, Reduce, and ForEach utilities
  • maps, a map with sorted keys based on a binary tree.
  • metric, a streamz-style multidimensional variable for production monitoring.
  • number, generic functions related to numbers (min, max, abs) and a user-defined complex type.
  • oddities, bugs and quirks.
  • pq, a priority queue
  • slices, generic slice utilities, and a user-defined Slice type.
  • stream, a streams library.
  • striped, a concurrency-safe map using lock striping, and also a custom hash/eq relation.

First impression:

This is really nice. It addresses the main things I miss about generics, namely

  • being able to change the equivalence relation of map;
  • better APIs for data structures like trees, graphs, and priority queues; and
  • the ability to generate efficient specialized code for a range of data types (though I understand that's not guaranteed);

and does so without overwhelming complexity.

By comparison, C++'s templates are extremely powerful, but syntactically and semantically quite complex, and historically the error messages have been both confusing and too late. (Templates also lead to considerable bloat in the text segment, but that may be a risk of the Go approach too.) Java's generics are limited to reference types, and thus are no use for efficient algorithms on (say) arrays of integers. Somehow the Go approach seems to do most of what I need while still feeling simple and easy to use.


  • Slices can now be implemented in the language, but not without unsafe pointer arithmetic. The generic slice algorithms work nicely. So does sorting with a custom order.

  • unsafe.Sizeof is disallowed on type parameters, yet it can be simulated using pointer arithmetic (though not as a constant expression). Why?

  • I often need a hash table with an alternative hash function, for

    • comparing non-canonical pointers (e.g. *big.Int, go/types.Type) by their referent;
    • comparing non-comparable values (such as slices) under the obvious relation;
    • using an alternative comparator (e.g. case insensitive, absolute value) for simple types. However, the custom hash function often wants to be at least partly defined in terms of the standard hash function, so the latter needs to be exposed somehow; see hacks.RuntimeHash. I imagine that could be problematic.
  • min, max, abs work nicely.

  • Go's built-in complex numbers could be satisfactorily replaced by a library.

  • The abstract algebraic ring generates pretty good code. One can imagine writing some numerical analysis routines this way when the algorithm is sufficiently complex that it is best not duplicated.

  • I couldn't find a way to achieve ad-hoc polymorphism, that is, defining a generic function by cases specialized to each possible type. For example, I don't know how to write a generic version of all the math/bits.OnesCount functions that uses the most efficient implementation. (Typeswitch doesn't handle named variants of built-in types; and using reflect is cheating.)

  • In practice I suspect concurrent loop abstractions will nearly always want additional parameters such as: a limit on parallelism; a context; cancellation; control over errors (e.g. ignore, choose first, choose arbitrarily, or combine all).

Users will no doubt build generic libraries of collections, of stream processing functions, and of numeric analysis routines. The design space for each is large, and I imagine arriving at simple, efficient, and coherent APIs worthy of the standard library will be an arduous task. But there is no need to hurry.

My experiments have tended to parameterize over built-in types, or "any". I should probably spend more time investigating interface-constrained types.

Alan Donovan
Software engineer at GitHub; ex-Googler; co-author of https://gopl.io.
Alan Donovan
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