How can I increase the length of a tuple in Erlang? For example, suppose Tup={1,2,3}, and now I want to add another element to it. Is there any way to do this?
Tuple is not suppose to be a flexible data structure. If you are resizing it often, then you should consider using other erlang data structures like lists, maps or sets - depends on your expectation. Here is nice introduction to key-value stores.
But if you really have to extend that tuple, then you can use erlang:append_element/2:
{1,2,3,4} = erlang:append_element({1,2,3}, 4).
Tuples aren't mutable so you can't, strictly speaking, increase the length.
Generally, if you want a variable-number-of-things datatype, a tuple will be very inconvenient. For example, iterating over all elements of a list is highly idiomatic, while iterating over all elements of a tuple whose size is unknown at compile-time is a pain.
However, a common pattern is to get a tuple as a result from some function and return elements of that tuple plus additions.
country_coords(Name) ->
{Lat, Lng} = find_address(Name),
{_Street, _City, _Zip, Country} = geocode(Lat, Lng),
{ok, Lat, Lng, Country}.
erlang:append_element(tuple_whose_length_to_increase, element_to_be).This is the inbuilt function but tuples,lists are not meant to be flexible.So avoid using this function unless there is no other way
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What is the idiomatic way of parsing ("5", "6") to (5, 6)? I have already tried calling .map(String::parse::<usize>) but that doesn't work because tuples are not iterators. Nor can I call .into_iter().
Tuples are meant to be heterogeneous collections and as such you can't really iterate over them, as different elements can, in principle, have different types.
So the easiest way is just
let a: usize = my_tuple.0.parse()?;
let b: usize = my_tuple.1.parse()?;
and if you need something more "sophisticated" you'll have to use a macro:
How to iterate or map over tuples?
This might seem unnecessarily cumbersome when you compare it with Python, where tuples are indeed iterable. But that's because you have dynamic and duck typing in Python, so the fact that tuples can be heterogeneous (different datatypes in different positions) isn't that big of a deal.
Think about it. What would even the signature be for the closure to pass to map in a tuple of type, say, (i32, String, Option<f64>)?
I want to model fixed-size arrays that can contain records and other fixed-size arrays. I then want to model store and select accesses to them.
I currently use ArraySorts for the arrays and Datatypes for the records. However, according to this answer (arrays) and this answer (records), these aren't really intended for my usecase. Is there anything else in Z3 I could use instead?
Background: I want to model pointers as they occur in the LLVM IR. For this, each pointer has a data array that represents the memory buffer into which it is pointing and an indices array that represents the indices used in getelementptr calls. Since the memory buffer could contain pointers or structs, I need to be able to nest the arrays (or store the records in arrays).
An example (in z3py) looks like this:
Vec3 = z3.Datatype("Vec3")
Vec3.declare("Vec3__init",
("x", z3.IntSort()),
("y", z3.IntSort()),
("z", z3.IntSort())
)
Vec3 = Vec3.create()
PointerVec3 = z3.Datatype("Pointer__Vec3")
PointerVec3.declare("Pointer__Vec3__init",
("data", z3.ArraySort(z3.BitVecSort(32), Vec3)),
("nindices", z3.IntSort()),
("indices", z3.ArraySort(z3.IntSort(), z3.BitVecSort(32)))
)
PointerVec3 = PointerVec3.create()
Arrays and records are the only way to model these things in z3/SMT-Lib. And they can be nested as you wish.
It is true that SMTLib arrays are not quite like arrays you find in regular programming languages. But it's not true that they are always unbounded. Their size exactly matches the cardinality of their domain. If you want a bounded array, I recommend using an appropriate BitVec type for your source. For an n-bit bit vector, your array will have 2^n elements. You can work with a small enough n, and treat that as your array; which typically matches what you see in practice: Most of such internal arrays will be a power-of-two anyhow. (Moreover, provers usually don't do well with large arrays; so sticking to a small power-of-two is a good idea, at least to start with.)
So, these are your only options. Stack-overflow works the best if you try it out and actually ask about what sort of problems you ran into.
I am wondering what datatype I should be using for my z3 application. My understanding is that the only options for integer-array-like data structures are Array(IntSort(), IntSort()) and IntVector().
Reasons I think Arrays are overkill: Each array element is only written once, I'm not doing anything like Store((Store(X, y, z1)), y, z2). In addition, each array has a predefined length of <= 256 (and each integer in the array is between 0 and 63).
Reasons I think BitVectors won't work: I want to use Int variables to index into the arrays. For instance, I might have z = Int('z'), some clauses constraining z, and then Or(arr[z] == 2, arr[z + 1] == 2). My understanding after playing around with z3 and reading up is that vectors don't support this.
Is there a way I can get the power of variable-indexing without having to use expensive Array operations?
If you have small arrays of fixed-length with no symbolic index access, then I'd strongly recommend using an IntVector (See https://z3prover.github.io/api/html/namespacez3py.html#a7e166f891df8f17fd23290bec963b03c)
Note the important thing here is whether you need access with a symbolic index. (That is, do you always address your array with known constant indices, or do you need the ability to read/write to a symbolically addressed location.) From your description, it appears you always statically know the address, so IntVector is your best choice. If addresses can be symbolic, then you have to use good old SMTLib arrays, which are more costly.
According to F#'s list documentation:
"A list in F# is an ordered, immutable series of elements of the same type"
"Lists in F# are implemented as singly linked lists"
Why not implement it contiguously in memory since it immutable and thus has a fixed size? Why ever use an F# list instead of an F# array?
They serve different purposes, for instance:
You use an Array in F# to store big amounts of data that needs to be accessed randomly with relative low overhead.
A List in F# is useful when you need to accumulate something over iterations of a recursive function. Arrays don't play well here, since they have a fixed size.
With a list, you can prepend all elements of ListM (size M) to ListN (size N) in O(M) time. Similarly, you can prepend a single Element to any list in O(1) time.
Seq.windowed in F# returns a sequence where each window within is an array. Is there a reason why each window is returned as an array (a very concrete type) as opposed to say, another sequence or IList<'T>? An IList<'T>, for example, would be sufficient if the purpose was to communicate that the items of the window can be randomly accessed but an array says two things: elements are mutable and randomly accessible. If you can rationalise the choice of array, how is windowed different from Seq.groupBy? Why does that latter (or operators in the same vein) not also return the members of a group as an array?
I'm wondering if this is simply a design oversight or is there a deeper, contractual reason for an array?
I do not know what is the design principle behind this. I suppose it might just be an accidental aspect of the implementation - Seq.windowed can be quite easily implemented by storing items in arrays, while Seq.groupBy probably needs to use some more complicated structure.
In general, I think that F# APIs either use 'T[] if using array is the natural efficient implementation, or return seq<'T> when the data source may be infinite, lazy, or when the implementation would have to convert the data to an array explicitly (then this can be left to the caller).
For Seq.windowed, I think that array makes a good sense, because you know the length of the array and so you are likely to use indexing. For example, assuming that prices is a sequence of date-price tuples (seq<DateTime * float>) you can write:
prices
|> Seq.windowed 5
|> Seq.map (fun win -> fst (win.[2]), Seq.averageBy snd win)
The sample calculates floating average and uses indexing to get the date in the middle.
In summary, I do not really have a good explanation for the design rationale, but I'm quite happy with the choices made - they seem to work really well with the usual use cases for the functions.
A couple of thoughts.
First, know that in their current version, both Seq.windowed and Seq.groupBy use non-lazy collections in their implementation. windowed uses arrays and returns you arrays. groupBy builds up a Dictionary<'tkey, ResizeArray<'tvalue>>, but keeps that a secret and returns the group values back as a seq instead of ResizeArray.
Returning ResizeArrays from groupBy wouldn't fit with anything else, so that obviously needs to be hidden. The other alternative is to give back the ToArray() of the data. This would require another copy of the data to be created, which is a downside. And there isn't really much upside, since you don't know ahead of time how big your group will be anyways, so you aren't expecting to do random access or any of the other special stuff arrays enable. So simply wrapping in a seq seems like a good option.
For windowed, it's a different story. You want an array back in this case. Why? Because you already know how big that array is going to be, so you can safely do random access or, better yet, pattern matching. That's a big upside. The downside remains, though - the data needs to be re-copied into a newly-allocated array for every window.
seq{1 .. 100} |> Seq.windowed 3 |> Seq.map (fun [|x; _; y|] -> x + y)
There is still the open question - "but couldn't we avoid the array allocation/copy downside by internally only using true lazy seqs, and returning them as such? Isn't that more in the 'spirit of the seq'?" It would be kind of tricky (would need some fancy cloning of enumerators?), but sure, probably with some careful coding. There's a huge downside to this, though. You'd need to cache the entire unspooled seq in memory to make it work, which kind of negates the whole goal of doing things lazily. Unlike lists or arrays, enumerating a seq multiple times is not guaranteed to yield the same results (e.g. a seq that returns random numbers), so the backing data for these seq windows you are returning needs to be cached somewhere. When that window is eventually accessed, you can't just tap in and re-enumerate through the original source seq - you might get back different data, or the seq might end at a different place. This points to the other upside of using arrays in Seq.windowed - only windowSize elements need to be kept in memory at once.
This is of course pure guess. I think this is related to the way both functions are implemented.
As already mentioned, in Seq.groupBy the groups are of variable length and in Seq.windowed they are of a fixed size.
So in the implementation from Seq.windowed it makes more sense to use a fixed size array, as opposed to the Generic.List used in Seq.groupBy, which btw in F# is called ResizeArray.
Now to the outside world, an Array though mutable is widely used in F# code and libraries and F# provides syntactic support for creating, initializing and manipulating arrays, whereas the ResizeArray is not that widely used in F# code and the language provides no syntactic support apart from the type alias, so I think that's why they decided to expose it as a Seq.