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The key to make multiple dispatch work well is that you shouldn't have to think about what method gets called. For this to work out, you need to make sure that
by oscardssmith 5y ago
The key to make multiple dispatch work well is that you shouldn't have to think about what method gets called. For this to work out, you need to make sure that you only add a method to a function if it does the "same thing" (so don't use >> for printing for example). To Dr the benefit of this in action, consider that in Julia 1im+2//3 (the syntax for sqrt(-1)+2 thirds) works and gives you a complex rational number (2//3+1//1 im). To get this behavior in most other languages, you would have to write special code for complex numbers with rational coefficients, but in Julia this just works since complex and rational numbers can be constructed using anything that has arithmetic defined. This goes all the way up the stack in Julia. You can put these numbers in a matrix, and matrix multiplication will just work, you can plot functions using these numbers, you can do gpu computation with them etc. All of this works (and is fast) because multiple dispatch can pick the right method based on all the argument types.
- enriquto 5y ago> make sure that you only add a method to a function if it does the "same thing" But this only concerns when I'm writing the code myself. If I read some code and I see a few nested function calls, there's a combinatorial explosion of possible types that gives me vertigo. > complex and rational numbers can be constructed using anything that has arithmetic defined. seriously? this does not seem right, it cannot be like that. If I build a complex number out of complex numbers, I expect a regular complex number, not a "doubly complex" number with complex coefficients, akin to a quaternion. Or do you? There is surely some hidden dirty magic to avoid that case.
- mbauman 5y agoThere's no hidden dirty magic, but you're right: Complex numbers require `Real` components and Rationals require `Integer` numerators and denominators. Both `Real` and `Integer` are simply abstract types in the numeric type tree, but you're free to make your own. You can see how this works directly in their docstrings — it's that type parameter in curly braces that defines it, and `<:` means subtype: help?> Complex search: Complex complex ComplexF64 ComplexF32 ComplexF16 completecases Complex{T<:Real} <: Number Complex number type with real and imaginary part of type T.
- jpeloquin 5y ago> The key to make multiple dispatch work well is that you shouldn't have to think about what method gets called. For this to work out, you need to make sure that you only add a method to a function if it does the "same thing" (so don't use >> for printing for example). Thanks for writing this. I think it is an important concept for getting started with Julia. When I tried Julia, I was initially confused and concerned about the subtyping hierarchy, which as far as I understand is undocumented. "Apart from a partial description in prose in Bezanson [2015], the only specification of subtyping is 2,800 lines of heavily optimized, undocumented C code." [0]. Assurance that users can safely ignore the subtyping hierarchy if we maintain semantic equivalence between methods, and that this actually works out in practice, makes it easier to commit to using the language. [0] https://dl.acm.org/doi/10.1145/3276483 https://dl.acm.org/doi/10.1145/3276483
- StefanKarpinski 5y agoThis is an important point: abstractions like generic functions are only as good as how much people respect them, and enforcement of that is largely cultural. You can add technological levels of enforcement, but those are limited at best because people are brilliantly devious and can find ways to break any technological enforcement if they set their minds to it; the key to preventing that is convincing them to set their minds to respecting abstractions instead. For a negative example of this, C++ introduced function overloading — which is a static and therefore broken version of multiple dispatch (that calls the wrong “methods” based only on static type information). They then immediately decided to abuse the bitshift operators for I/O — in the standard library, no less. (There are other abuses of overloading but this is the most famous one.) So that didn’t exactly create a culture where people respect the semantic meaning of overloaded functions. As a result, C++ has given function overloading a really horrible reputation. Partly because it is likely to be not actually so what you want because it’s static rather than based on the actual types of arguments, but even more so because there’s no culture of semantic consistency in C++, starting from the standard library itself — you cannot trust anyone to respect the meaning of anything, not even the language authors. In Julia, on the other hand, we’ve always been very strict about this: don’t add a method to a function unless it means the same thing. We would never dream of using bitshift operators to do I/O. Since meaning is the level where human thinking operates, this makes it reasonable to write generic code that works the way you meant it to: you can call `+` on two things and just trust that whoever has implemented `+` for those objects didn’t decide to make it append a value to an array or something wonky like that. Not that people haven’t proposed that kind of thing, but because of the culture, it gets shot down in the standard library and elsewhere in the ecosystem. But yeah, it’s hard to see how this would happen because there is nothing technical preventing the same kinds of abuses that are rampant in C++, it’s just the invisible but extremely force of culture.