=========================

Nim Experimental Features

:Authors: Andreas Rumpf :Version: |nimversion|

.. default-role:: code .. include:: rstcommon.rst .. contents::

About this document

This document describes features of Nim that are to be considered experimental. Some of these are not covered by the .experimental pragma or --experimental:option: switch because they are already behind a special syntax and one may want to use Nim libraries using these features without using them oneself.

.. note:: Unless otherwise indicated, these features are not to be removed, but refined and overhauled.

Void type

The void type denotes the absence of any type. Parameters of type void are treated as non-existent, void as a return type means that the procedure does not return a value:

  proc nothing(x, y: void): void =
    echo "ha"

  nothing() # writes "ha" to stdout

The void type is particularly useful for generic code:

  proc callProc[T](p: proc (x: T), x: T) =
    when T is void:
      p()
    else:
      p(x)

  proc intProc(x: int) = discard
  proc emptyProc() = discard

  callProc[int](intProc, 12)
  callProc[void](emptyProc)

However, a void type cannot be inferred in generic code:

  callProc(emptyProc)
  # Error: type mismatch: got (proc ())
  # but expected one of:
  # callProc(p: proc (T), x: T)

The void type is only valid for parameters and return types; other symbols cannot have the type void.

Generic `define` pragma

Aside the typed define pragmas for constants, there is a generic {.define.} pragma that interprets the value of the define based on the type of the constant value.

  const foo {.define: "package.foo".} = 123
  const bar {.define: "package.bar".} = false

  nim c -d:package.foo=456 -d:package.bar foobar.nim

The following types are supported:

string and cstring
Signed and unsigned integer types
bool
Enums

Top-down type inference

In expressions such as:

let a: T = ex

Normally, the compiler type checks the expression ex by itself, then attempts to statically convert the type-checked expression to the given type T as much as it can, while making sure it matches the type. The extent of this process is limited however due to the expression usually having an assumed type that might clash with the given type.

With top-down type inference, the expression is type checked with the extra knowledge that it is supposed to be of type T. For example, the following code is does not compile with the former method, but compiles with top-down type inference:

let foo: (float, uint8, cstring) = (1, 2, "abc")

The tuple expression has an expected type of (float, uint8, cstring). Since it is a tuple literal, we can use this information to assume the types of its elements. The expected types for the expressions 1, 2 and "abc" are respectively float, uint8, and cstring; and these expressions can be statically converted to these types.

Without this information, the type of the tuple expression would have been assumed to be (int, int, string). Thus the type of the tuple expression would not match the type of the variable, and an error would be given.

The extent of this varies, but there are some notable special cases.

Sequence literals

Top-down type inference applies to sequence literals.

let x: seq[seq[float]] = @[@[1, 2, 3], @[4, 5, 6]]

This behavior is tied to the @ overloads in the system module, so overloading @ can disable this behavior. This can be circumvented by specifying the system.`@` overload.

proc `@`(x: string): string = "@" & x

# does not compile:
let x: seq[float] = @[1, 2, 3]
# compiles:
let x: seq[float] = system.`@`([1, 2, 3])

Package level objects

Every Nim module resides in a (nimble) package. An object type can be attached to the package it resides in. If that is done, the type can be referenced from other modules as an incomplete:idx: object type. This feature allows to break up recursive type dependencies across module boundaries. Incomplete object types are always passed byref and can only be used in pointer like contexts (var/ref/ptr IncompleteObject) in general, since the compiler does not yet know the size of the object. To complete an incomplete object, the package pragma has to be used. package implies byref.

As long as a type T is incomplete, no runtime type information for T is available.

Example:

  # module A (in an arbitrary package)
  type
    Pack.SomeObject = object # declare as incomplete object of package 'Pack'
    Triple = object
      a, b, c: ref SomeObject # pointers to incomplete objects are allowed

  # Incomplete objects can be used as parameters:
  proc myproc(x: SomeObject) = discard

  # module B (in package "Pack")
  type
    SomeObject* {.package.} = object # Use 'package' to complete the object
      s, t: string
      x, y: int

This feature will likely be superseded in the future by support for recursive module dependencies.

Importing private symbols

In some situations, it may be useful to import all symbols (public or private) from a module. The syntax import foo {.all.} can be used to import all symbols from the module foo. Note that importing private symbols is generally not recommended.

See also the experimental importutils module.

Code reordering

The code reordering feature can implicitly rearrange procedure, template, and macro definitions along with variable declarations and initializations at the top level scope so that, to a large extent, a programmer should not have to worry about ordering definitions correctly or be forced to use forward declarations to preface definitions inside a module.

.. NOTE: The following was documentation for the code reordering precursor, which was {.noForward.}.

In this mode, procedure definitions may appear out of order and the compiler will postpone their semantic analysis and compilation until it actually needs to generate code using the definitions. In this regard, this mode is similar to the modus operandi of dynamic scripting languages, where the function calls are not resolved until the code is executed. Here is the detailed algorithm taken by the compiler:

When a callable symbol is first encountered, the compiler will only note the symbol callable name and it will add it to the appropriate overload set in the current scope. At this step, it won't try to resolve any of the type expressions used in the signature of the symbol (so they can refer to other not yet defined symbols).
When a top level call is encountered (usually at the very end of the module), the compiler will try to determine the actual types of all of the symbols in the matching overload set. This is a potentially recursive process as the signatures of the symbols may include other call expressions, whose types will be resolved at this point too.
Finally, after the best overload is picked, the compiler will start compiling the body of the respective symbol. This in turn will lead the compiler to discover more call expressions that need to be resolved and steps 2 and 3 will be repeated as necessary.

Please note that if a callable symbol is never used in this scenario, its body will never be compiled. This is the default behavior leading to best compilation times, but if exhaustive compilation of all definitions is required, using nim check provides this option as well.

Example:

  {.experimental: "codeReordering".}

  proc foo(x: int) =
    bar(x)

  proc bar(x: int) =
    echo(x)

  foo(10)

Variables can also be reordered as well. Variables that are initialized (i.e. variables that have their declaration and assignment combined in a single statement) can have their entire initialization statement reordered. Be wary of what code is executed at the top level:

  {.experimental: "codeReordering".}

  proc a() =
    echo(foo)

  var foo = 5

  a() # outputs: "5"

.. TODO: Let's table this for now. This is an experimental feature and so the specific manner in which declared operates with it can be decided in eventuality, because right now it works a bit weirdly.

The values of expressions involving declared are decided before the code reordering process, and not after. As an example, the output of this code is the same as it would be with code reordering disabled.

 ```nim
 {.experimental: "codeReordering".}

 proc x() =
   echo(declared(foo))

 var foo = 4

 x() # "false"
 ```

It is important to note that reordering only works for symbols at top level scope. Therefore, the following will fail to compile:

  {.experimental: "codeReordering".}

  proc a() =
    b()
    proc b() =
      echo("Hello!")

  a()

This feature will likely be replaced with a better solution to remove the need for forward declarations.

Special Operators

dot operators

.. note:: Dot operators are still experimental and so need to be enabled via {.experimental: "dotOperators".}.

Nim offers a special family of dot operators that can be used to intercept and rewrite proc call and field access attempts, referring to previously undeclared symbol names. They can be used to provide a fluent interface to objects lying outside the static confines of the type system such as values from dynamic scripting languages or dynamic file formats such as JSON or XML.

When Nim encounters an expression that cannot be resolved by the standard overload resolution rules, the current scope will be searched for a dot operator that can be matched against a re-written form of the expression, where the unknown field or proc name is passed to an untyped parameter:

  a.b # becomes `.`(a, b)
  a.b(c, d) # becomes `.`(a, b, c, d)

The matched dot operators can be symbols of any callable kind (procs, templates and macros), depending on the desired effect:

  template `.`(js: PJsonNode, field: untyped): JSON = js[astToStr(field)]

  var js = parseJson("{ x: 1, y: 2}")
  echo js.x # outputs 1
  echo js.y # outputs 2

The following dot operators are available:

operator `.`

This operator will be matched against both field accesses and method calls.

operator `.()`

This operator will be matched exclusively against method calls. It has higher precedence than the . operator and this allows one to handle expressions like x.y and x.y() differently if one is interfacing with a scripting language for example.

operator `.=`

This operator will be matched against assignments to missing fields.

  a.b = c # becomes `.=`(a, b, c)

Call operator

The call operator, (), matches all kinds of unresolved calls and takes precedence over dot operators, however it does not match missing overloads for existing routines. The experimental callOperator switch must be enabled to use this operator.

  {.experimental: "callOperator".}

  template `()`(a: int, b: float): untyped = $(a, b)

  block:
    let a = 1.0
    let b = 2
    doAssert b(a) == `()`(b, a)
    doAssert a.b == `()`(b, a)

  block:
    let a = 1.0
    proc b(): int = 2
    doAssert not compiles(b(a))
    doAssert not compiles(a.b) # `()` not called

  block:
    let a = 1.0
    proc b(x: float): int = int(x + 1)
    let c = 3.0

    doAssert not compiles(a.b(c)) # gives a type mismatch error same as b(a, c)
    doAssert (a.b)(c) == `()`(a.b, c)

Extended macro pragmas

Macro pragmas as described in the manual can also be applied to type, variable and constant declarations.

For types:

  type
    MyObject {.schema: "schema.protobuf".} = object

This is translated to a call to the schema macro with a nnkTypeDef AST node capturing the left-hand side, remaining pragmas and the right-hand side of the definition. The macro can return either a type section or another nnkTypeDef node, both of which will replace the original row in the type section.

In the future, this nnkTypeDef argument may be replaced with a unary type section node containing the type definition, or some other node that may be more convenient to work with. The ability to return nodes other than type definitions may also be supported, however currently this is not convenient when dealing with mutual type recursion. For now, macros can return an unused type definition where the right-hand node is of kind nnkStmtListType. Declarations in this node will be attached to the same scope as the parent scope of the type section.

For variables and constants, it is largely the same, except a unary node with the same kind as the section containing a single definition is passed to macros, and macros can return any expression.

  var
    a = ...
    b {.importc, foo, nodecl.} = ...
    c = ...

Assuming foo is a macro or a template, this is roughly equivalent to:

  var a = ...
  foo:
    var b {.importc, nodecl.} = ...
  var c = ...

Symbols as template/macro calls (alias syntax)

Templates and macros that have no generic parameters and no required arguments can be called as lone symbols, i.e. without parentheses. This is useful for repeated uses of complex expressions that cannot conveniently be represented as runtime values.

  type Foo = object
    bar: int

  var foo = Foo(bar: 10)
  template bar: int = foo.bar
  assert bar == 10
  bar = 15
  assert bar == 15

Not nil annotation

Note: This is an experimental feature. It can be enabled with {.experimental: "notnil".}.

All types for which nil is a valid value can be annotated with the not nil annotation to exclude nil as a valid value:

  {.experimental: "notnil".}

  type
    PObject = ref TObj not nil
    TProc = (proc (x, y: int)) not nil

  proc p(x: PObject) =
    echo "not nil"

  # compiler catches this:
  p(nil)

  # and also this:
  var x: PObject
  p(x)

The compiler ensures that every code path initializes variables which contain non-nilable pointers. The details of this analysis are still to be specified here.

.. include:: manual_experimental_strictnotnil.md

Aliasing restrictions in parameter passing

.. note:: The aliasing restrictions are currently not enforced by the implementation and need to be fleshed out further.

"Aliasing" here means that the underlying storage locations overlap in memory at runtime. An "output parameter" is a parameter of type var T, an input parameter is any parameter that is not of type var.

Two output parameters should never be aliased.
An input and an output parameter should not be aliased.
An output parameter should never be aliased with a global or thread local variable referenced by the called proc.
An input parameter should not be aliased with a global or thread local variable updated by the called proc.

One problem with rules 3 and 4 is that they affect specific global or thread local variables, but Nim's effect tracking only tracks "uses no global variable" via .noSideEffect. The rules 3 and 4 can also be approximated by a different rule:

A global or thread local variable (or a location derived from such a location) can only passed to a parameter of a .noSideEffect proc.

Strict funcs

Since version 1.4, a stricter definition of "side effect" is available. In addition to the existing rule that a side effect is calling a function with side effects, the following rule is also enforced:

A store to the heap via a ref or ptr indirection is not allowed.

For example:

  {.experimental: "strictFuncs".}

  type
    Node = ref object
      le, ri: Node
      data: string

  func len(n: Node): int =
    # valid: len does not have side effects
    var it = n
    while it != nil:
      inc result
      it = it.ri

  func mut(n: Node) =
    var it = n
    while it != nil:
      it.data = "yeah" # forbidden mutation
      it = it.ri

View types

.. tip:: --experimental:views:option: is more effective with --experimental:strictFuncs:option:.

A view type is a type that is or contains one of the following types:

lent T (view into T)
openArray[T] (pair of (pointer to array of T, size))

For example:

  type
    View1 = openArray[byte]
    View2 = lent string
    View3 = Table[openArray[char], int]

Exceptions to this rule are types constructed via ptr or proc. For example, the following types are not view types:

  type
    NotView1 = proc (x: openArray[int])
    NotView2 = ptr openArray[char]
    NotView3 = ptr array[4, lent int]

The mutability aspect of a view type is not part of the type but part of the locations it's derived from. More on this later.

A view is a symbol (a let, var, const, etc.) that has a view type.

Since version 1.4, Nim allows view types to be used as local variables. This feature needs to be enabled via {.experimental: "views".}.

A local variable of a view type borrows from the locations and it is statically enforced that the view does not outlive the location it was borrowed from.

For example:

  {.experimental: "views".}

  proc take(a: openArray[int]) =
    echo a.len

  proc main(s: seq[int]) =
    var x: openArray[int] = s # 'x' is a view into 's'
    # it is checked that 'x' does not outlive 's' and
    # that 's' is not mutated.
    for i in 0 .. high(x):
      echo x[i]
    take(x)

    take(x.toOpenArray(0, 1)) # slicing remains possible
    let y = x  # create a view from a view
    take y
    # it is checked that 'y' does not outlive 'x' and
    # that 'x' is not mutated as long as 'y' lives.


  main(@[11, 22, 33])

A local variable of a view type can borrow from a location derived from a parameter, another local variable, a global const or let symbol or a thread-local var or let.

Let p the proc that is analysed for the correctness of the borrow operation.

Let source be one of:

A formal parameter of p. Note that this does not cover parameters of inner procs.
The result symbol of p.
A local var or let or const of p. Note that this does not cover locals of inner procs.
A thread-local var or let.
A global let or const.
A constant array/seq/object/tuple constructor.

Path expressions

A location derived from source is then defined as a path expression that has source as the owner. A path expression e is defined recursively:

source itself is a path expression.
Container access like e[i] is a path expression.
Tuple access e[0] is a path expression.
Object field access e.field is a path expression.
system.toOpenArray(e, ...) is a path expression.
Pointer dereference e[] is a path expression.
An address addr e is a path expression.
A type conversion T(e) is a path expression.
A cast expression cast[T](e) is a path expression.
f(e, ...) is a path expression if f's return type is a view type. Because the view can only have been borrowed from e, we then know that the owner of f(e, ...) is e.

If a view type is used as a return type, the location must borrow from a location that is derived from the first parameter that is passed to the proc. See the manual for details about how this is done for var T.

A mutable view can borrow from a mutable location, an immutable view can borrow from both a mutable or an immutable location.

If a view borrows from a mutable location, the view can be used to update the location. Otherwise it cannot be used for mutations.

The duration of a borrow is the span of commands beginning from the assignment to the view and ending with the last usage of the view.

For the duration of the borrow operation, no mutations to the borrowed locations may be performed except via the view that borrowed from the location. The borrowed location is said to be sealed during the borrow.

  {.experimental: "views".}

  type
    Obj = object
      field: string

  proc dangerous(s: var seq[Obj]) =
    let v: lent Obj = s[0] # seal 's'
    s.setLen 0  # prevented at compile-time because 's' is sealed.
    echo v.field

The scope of the view does not matter:

  proc valid(s: var seq[Obj]) =
    let v: lent Obj = s[0]  # begin of borrow
    echo v.field            # end of borrow
    s.setLen 0  # valid because 'v' isn't used afterwards

The analysis requires as much precision about mutations as is reasonably obtainable, so it is more effective with the experimental [strict funcs] feature. In other words --experimental:views:option: works better with --experimental:strictFuncs:option:.

The analysis is currently control flow insensitive:

  proc invalid(s: var seq[Obj]) =
    let v: lent Obj = s[0]
    if false:
      s.setLen 0
    echo v.field

In this example, the compiler assumes that s.setLen 0 invalidates the borrow operation of v even though a human being can easily see that it will never do that at runtime.

Start of a borrow

A borrow starts with one of the following:

The assignment of a non-view-type to a view-type.
The assignment of a location that is derived from a local parameter to a view-type.

End of a borrow

A borrow operation ends with the last usage of the view variable.

Reborrows

A view v can borrow from multiple different locations. However, the borrow is always the full span of v's lifetime and every location that is borrowed from is sealed during v's lifetime.

Algorithm

The following section is an outline of the algorithm that the current implementation uses. The algorithm performs two traversals over the AST of the procedure or global section of code that uses a view variable. No fixpoint iterations are performed, the complexity of the analysis is O(N) where N is the number of nodes of the AST.

The first pass over the AST computes the lifetime of each local variable based on a notion of an "abstract time", in the implementation it's a simple integer that is incremented for every visited node.

In the second pass, information about the underlying object "graphs" is computed. Let v be a parameter or a local variable. Let G(v) be the graph that v belongs to. A graph is defined by the set of variables that belong to the graph. Initially for all v: G(v) = {v}. Every variable can only be part of a single graph.

Assignments like a = b "connect" two variables, both variables end up in the same graph {a, b} = G(a) = G(b). Unfortunately, the pattern to look for is much more complex than that and can involve multiple assignment targets and sources:

f(x, y) = g(a, b)

connects x and y to a and b: G(x) = G(y) = G(a) = G(b) = {x, y, a, b}. A type based alias analysis rules out some of these combinations, for example a string value cannot possibly be connected to a seq[int].

A pattern like v[] = value or v.field = value marks G(v) as mutated. After the second pass a set of disjoint graphs was computed.

For strict functions it is then enforced that there is no graph that is both mutated and has an element that is an immutable parameter (that is a parameter that is not of type var T).

For borrow checking, a different set of checks is performed. Let v be the view and b the location that is borrowed from.

The lifetime of v must not exceed b's lifetime. Note: The lifetime of a parameter is the complete proc body.
If v is used for a mutation, b must be a mutable location too.
During v's lifetime, G(b) can only be modified by v (and only if v is a mutable view).
If v is result then b has to be a location derived from the first formal parameter or from a constant location.
A view cannot be used for a read or a write access before it was assigned to.

Concepts

Concepts, also known as "user-defined type classes", are used to specify an arbitrary set of requirements that the matched type must satisfy.

Concepts are written in the following form:

  type
    Comparable = concept x, y
      (x < y) is bool

    Stack[T] = concept s, var v
      s.pop() is T
      v.push(T)

      s.len is Ordinal

      for value in s:
        value is T

The concept matches if:

a) all expressions within the body can be compiled for the tested type b) all statically evaluable boolean expressions in the body are true

The identifiers following the concept keyword represent instances of the currently matched type. You can apply any of the standard type modifiers such as var, ref, ptr and static to denote a more specific type of instance. You can also apply the type modifier to create a named instance of the type itself:

  type
    MyConcept = concept x, var v, ref r, ptr p, static s, type T
      ...

Within the concept body, types can appear in positions where ordinary values and parameters are expected. This provides a more convenient way to check for the presence of callable symbols with specific signatures:

  type
    OutputStream = concept var s
      s.write(string)

In order to check for symbols accepting type params, you must prefix the type with the explicit type modifier. The named instance of the type, following the concept keyword is also considered to have the explicit modifier and will be matched only as a type.

  type
    # Let's imagine a user-defined casting framework with operators
    # such as `val.to(string)` and `val.to(JSonValue)`. We can test
    # for these with the following concept:
    MyCastables = concept x
      x.to(type string)
      x.to(type JSonValue)

    # Let's define a couple of concepts, known from Algebra:
    AdditiveMonoid* = concept x, y, type T
      x + y is T
      T.zero is T # require a proc such as `int.zero` or 'Position.zero'

    AdditiveGroup* = concept x, y, type T
      x is AdditiveMonoid
      -x is T
      x - y is T

Please note that the is operator allows one to easily verify the precise type signatures of the required operations, but since type inference and default parameters are still applied in the concept body, it's also possible to describe usage protocols that do not reveal implementation details.

Much like generics, concepts are instantiated exactly once for each tested type and any static code included within the body is executed only once.

Concept diagnostics

By default, the compiler will report the matching errors in concepts only when no other overload can be selected and a normal compilation error is produced. When you need to understand why the compiler is not matching a particular concept and, as a result, a wrong overload is selected, you can apply the explain pragma to either the concept body or a particular call-site.

  type
    MyConcept {.explain.} = concept ...

  overloadedProc(x, y, z) {.explain.}

This will provide Hints in the compiler output either every time the concept is not matched or only on the particular call-site.

Generic concepts and type binding rules

The concept types can be parametric just like the regular generic types:

  ### matrixalgo.nim

  import std/typetraits

  type
    AnyMatrix*[R, C: static int; T] = concept m, var mvar, type M
      M.ValueType is T
      M.Rows == R
      M.Cols == C

      m[int, int] is T
      mvar[int, int] = T

      type TransposedType = stripGenericParams(M)[C, R, T]

    AnySquareMatrix*[N: static int, T] = AnyMatrix[N, N, T]

    AnyTransform3D* = AnyMatrix[4, 4, float]

  proc transposed*(m: AnyMatrix): m.TransposedType =
    for r in 0 ..< m.R:
      for c in 0 ..< m.C:
        result[r, c] = m[c, r]

  proc determinant*(m: AnySquareMatrix): int =
    ...

  proc setPerspectiveProjection*(m: AnyTransform3D) =
    ...

  --------------
  ### matrix.nim

  type
    Matrix*[M, N: static int; T] = object
      data: array[M*N, T]

  proc `[]`*(M: Matrix; m, n: int): M.T =
    M.data[m * M.N + n]

  proc `[]=`*(M: var Matrix; m, n: int; v: M.T) =
    M.data[m * M.N + n] = v

  # Adapt the Matrix type to the concept's requirements
  template Rows*(M: typedesc[Matrix]): int = M.M
  template Cols*(M: typedesc[Matrix]): int = M.N
  template ValueType*(M: typedesc[Matrix]): typedesc = M.T

  -------------
  ### usage.nim

  import matrix, matrixalgo

  var
    m: Matrix[3, 3, int]
    projectionMatrix: Matrix[4, 4, float]

  echo m.transposed.determinant
  setPerspectiveProjection projectionMatrix

When the concept type is matched against a concrete type, the unbound type parameters are inferred from the body of the concept in a way that closely resembles the way generic parameters of callable symbols are inferred on call sites.

Unbound types can appear both as params to calls such as s.push(T) and on the right-hand side of the is operator in cases such as x.pop is T and x.data is seq[T].

Unbound static params will be inferred from expressions involving the == operator and also when types dependent on them are being matched:

  type
    MatrixReducer[M, N: static int; T] = concept x
      x.reduce(SquareMatrix[N, T]) is array[M, int]

The Nim compiler includes a simple linear equation solver, allowing it to infer static params in some situations where integer arithmetic is involved.

Just like in regular type classes, Nim discriminates between bind once and bind many types when matching the concept. You can add the distinct modifier to any of the otherwise inferable types to get a type that will be matched without permanently inferring it. This may be useful when you need to match several procs accepting the same wide class of types:

  type
    Enumerable[T] = concept e
      for v in e:
        v is T

  type
    MyConcept = concept o
      # this could be inferred to a type such as Enumerable[int]
      o.foo is distinct Enumerable

      # this could be inferred to a different type such as Enumerable[float]
      o.bar is distinct Enumerable

      # it's also possible to give an alias name to a `bind many` type class
      type Enum = distinct Enumerable
      o.baz is Enum

On the other hand, using bind once types allows you to test for equivalent types used in multiple signatures, without actually requiring any concrete types, thus allowing you to encode implementation-defined types:

  type
    MyConcept = concept x
      type T1 = auto
      x.foo(T1)
      x.bar(T1) # both procs must accept the same type

      type T2 = seq[SomeNumber]
      x.alpha(T2)
      x.omega(T2) # both procs must accept the same type
                  # and it must be a numeric sequence

As seen in the previous examples, you can refer to generic concepts such as Enumerable[T] just by their short name. Much like the regular generic types, the concept will be automatically instantiated with the bind once auto type in the place of each missing generic param.

Please note that generic concepts such as Enumerable[T] can be matched against concrete types such as string. Nim doesn't require the concept type to have the same number of parameters as the type being matched. If you wish to express a requirement towards the generic parameters of the matched type, you can use a type mapping operator such as genericHead or stripGenericParams within the body of the concept to obtain the uninstantiated version of the type, which you can then try to instantiate in any required way. For example, here is how one might define the classic Functor concept from Haskell and then demonstrate that Nim's Option[T] type is an instance of it:

```nim test = "nim c $1" import std/[sugar, typetraits]

type

Functor[A] = concept f
  type MatchedGenericType = genericHead(typeof(f))
    # `f` will be a value of a type such as `Option[T]`
    # `MatchedGenericType` will become the `Option` type

  f.val is A
    # The Functor should provide a way to obtain
    # a value stored inside it

  type T = auto
  map(f, A -> T) is MatchedGenericType[T]
    # And it should provide a way to map one instance of
    # the Functor to a instance of a different type, given
    # a suitable `map` operation for the enclosed values

import std/options echo Option[int] is Functor # prints true



Concept derived values
----------------------

All top level constants or types appearing within the concept body are
accessible through the dot operator in procs where the concept was successfully
matched to a concrete type:

  ```nim
  type
    DateTime = concept t1, t2, type T
      const Min = T.MinDate
      T.Now is T

      t1 < t2 is bool

      type TimeSpan = typeof(t1 - t2)
      TimeSpan * int is TimeSpan
      TimeSpan + TimeSpan is TimeSpan

      t1 + TimeSpan is T

  proc eventsJitter(events: Enumerable[DateTime]): float =
    var
      # this variable will have the inferred TimeSpan type for
      # the concrete Date-like value the proc was called with:
      averageInterval: DateTime.TimeSpan

      deviation: float
    ...

Concept refinement

When the matched type within a concept is directly tested against a different concept, we say that the outer concept is a refinement of the inner concept and thus it is more-specific. When both concepts are matched in a call during overload resolution, Nim will assign a higher precedence to the most specific one. As an alternative way of defining concept refinements, you can use the object inheritance syntax involving the of keyword:

  type
    Graph = concept g, type G of EquallyComparable, Copyable
      type
        VertexType = G.VertexType
        EdgeType = G.EdgeType

      VertexType is Copyable
      EdgeType is Copyable

      var
        v: VertexType
        e: EdgeType

    IncidendeGraph = concept of Graph
      # symbols such as variables and types from the refined
      # concept are automatically in scope:

      g.source(e) is VertexType
      g.target(e) is VertexType

      g.outgoingEdges(v) is Enumerable[EdgeType]

    BidirectionalGraph = concept g, type G
      # The following will also turn the concept into a refinement when it
      # comes to overload resolution, but it doesn't provide the convenient
      # symbol inheritance
      g is IncidendeGraph

      g.incomingEdges(G.VertexType) is Enumerable[G.EdgeType]

  proc f(g: IncidendeGraph)
  proc f(g: BidirectionalGraph) # this one will be preferred if we pass a type
                                # matching the BidirectionalGraph concept

.. Converter type classes

Concepts can also be used to convert a whole range of types to a single type or a small set of simpler types. This is achieved with a return statement within the concept body:

```nim
type
  Stringable = concept x
    $x is string
    return $x

  StringRefValue[CharType] = object
    base: ptr CharType
    len: int

  StringRef = concept x
    # the following would be an overloaded proc for cstring, string, seq and
    # other user-defined types, returning either a StringRefValue[char] or
    # StringRefValue[wchar]
    return makeStringRefValue(x)

# the varargs param will here be converted to an array of StringRefValues
# the proc will have only two instantiations for the two character types
proc log(format: static string, varargs[StringRef])

# this proc will allow char and wchar values to be mixed in
# the same call at the cost of additional instantiations
# the varargs param will be converted to a tuple
proc log(format: static string, varargs[distinct StringRef])
```

.. VTable types

Concepts allow Nim to define a great number of algorithms, using only static polymorphism and without erasing any type information or sacrificing any execution speed. But when polymorphic collections of objects are required, the user must use one of the provided type erasure techniques - either common base types or VTable types.

VTable types are represented as "fat pointers" storing a reference to an object together with a reference to a table of procs implementing a set of required operations (the so called vtable).

In contrast to other programming languages, the vtable in Nim is stored externally to the object, allowing you to create multiple different vtable views for the same object. Thus, the polymorphism in Nim is unbounded - any type can implement an unlimited number of protocols or interfaces not originally envisioned by the type's author.

Any concept type can be turned into a VTable type by using the vtref or the vtptr compiler magics. Under the hood, these magics generate a converter type class, which converts the regular instances of the matching types to the corresponding VTable type.

```nim
type
  IntEnumerable = vtref Enumerable[int]

  MyObject = object
    enumerables: seq[IntEnumerable]
    streams: seq[OutputStream.vtref]

proc addEnumerable(o: var MyObject, e: IntEnumerable) =
  o.enumerables.add e

proc addStream(o: var MyObject, e: OutputStream.vtref) =
  o.streams.add e
```

The procs that will be included in the vtable are derived from the concept body and include all proc calls for which all param types were specified as concrete types. All such calls should include exactly one param of the type matched against the concept (not necessarily in the first position), which will be considered the value bound to the vtable.

Overloads will be created for all captured procs, accepting the vtable type in the position of the captured underlying object.

Under these rules, it's possible to obtain a vtable type for a concept with unbound type parameters or one instantiated with metatypes (type classes), but it will include a smaller number of captured procs. A completely empty vtable will be reported as an error.

The vtref magic produces types which can be bound to ref types and the vtptr magic produced types bound to ptr types.

.. deepCopy

=deepCopy is a builtin that is invoked whenever data is passed to a spawn'ed proc to ensure memory safety. The programmer can override its behaviour for a specific ref or ptr type T. (Later versions of the language may weaken this restriction.)

The signature has to be:

```nim
proc `=deepCopy`(x: T): T
```

This mechanism will be used by most data structures that support shared memory, like channels, to implement thread safe automatic memory management.

The builtin deepCopy can even clone closures and their environments. See the documentation of [spawn][spawn statement] for details.

Dynamic arguments for bindSym

This experimental feature allows the symbol name argument of macros.bindSym to be computed dynamically.

  {.experimental: "dynamicBindSym".}

  import macros

  macro callOp(opName, arg1, arg2): untyped =
    result = newCall(bindSym($opName), arg1, arg2)

  echo callOp("+", 1, 2)
  echo callOp("-", 5, 4)

Term rewriting macros

Term rewriting macros are macros or templates that have not only a name but also a pattern that is searched for after the semantic checking phase of the compiler: This means they provide an easy way to enhance the compilation pipeline with user defined optimizations:

  template optMul{`*`(a, 2)}(a: int): int = a + a

  let x = 3
  echo x * 2

The compiler now rewrites x * 2 as x + x. The code inside the curly brackets is the pattern to match against. The operators *, **, |, ~ have a special meaning in patterns if they are written in infix notation, so to match verbatim against * the ordinary function call syntax needs to be used.

Term rewriting macros are applied recursively, up to a limit. This means that if the result of a term rewriting macro is eligible for another rewriting, the compiler will try to perform it, and so on, until no more optimizations are applicable. To avoid putting the compiler into an infinite loop, there is a hard limit on how many times a single term rewriting macro can be applied. Once this limit has been passed, the term rewriting macro will be ignored.

Unfortunately optimizations are hard to get right and even this tiny example is wrong:

  template optMul{`*`(a, 2)}(a: int): int = a + a

  proc f(): int =
    echo "side effect!"
    result = 55

  echo f() * 2

We cannot duplicate 'a' if it denotes an expression that has a side effect! Fortunately Nim supports side effect analysis:

  template optMul{`*`(a, 2)}(a: int{noSideEffect}): int = a + a

  proc f(): int =
    echo "side effect!"
    result = 55

  echo f() * 2 # not optimized ;-)

You can make one overload matching with a constraint and one without, and the one with a constraint will have precedence, and so you can handle both cases differently.

So what about 2 * a? We should tell the compiler * is commutative. We cannot really do that however as the following code only swaps arguments blindly:

  template mulIsCommutative{`*`(a, b)}(a, b: int): int = b * a

What optimizers really need to do is a canonicalization:

  template canonMul{`*`(a, b)}(a: int{lit}, b: int): int = b * a

The int{lit} parameter pattern matches against an expression of type int, but only if it's a literal.

Parameter constraints

The parameter constraint:idx: expression can use the operators | (or), & (and) and ~ (not) and the following predicates:

=================== ===================================================== Predicate Meaning =================== ===================================================== atom The matching node has no children. lit The matching node is a literal like "abc", 12. sym The matching node must be a symbol (a bound

                     identifier).

ident The matching node must be an identifier (an unbound

                     identifier).

call The matching AST must be a call/apply expression. lvalue The matching AST must be an lvalue. sideeffect The matching AST must have a side effect. nosideeffect The matching AST must have no side effect. param A symbol which is a parameter. genericparam A symbol which is a generic parameter. module A symbol which is a module. type A symbol which is a type. var A symbol which is a variable. let A symbol which is a let variable. const A symbol which is a constant. result The special result variable. proc A symbol which is a proc. method A symbol which is a method. iterator A symbol which is an iterator. converter A symbol which is a converter. macro A symbol which is a macro. template A symbol which is a template. field A symbol which is a field in a tuple or an object. enumfield A symbol which is a field in an enumeration. forvar A for loop variable. label A label (used in block statements). nk* The matching AST must have the specified kind.

                     (Example: `nkIfStmt` denotes an `if` statement.)

alias States that the marked parameter needs to alias

                     with *some* other parameter.

noalias States that every other parameter must not alias

                     with the marked parameter.

=================== =====================================================

Predicates that share their name with a keyword have to be escaped with backticks. The alias and noalias predicates refer not only to the matching AST, but also to every other bound parameter; syntactically they need to occur after the ordinary AST predicates:

  template ex{a = b + c}(a: int{noalias}, b, c: int) =
    # this transformation is only valid if 'b' and 'c' do not alias 'a':
    a = b
    inc a, c

Another example:

  proc somefunc(s: string)                 = assert s == "variable"
  proc somefunc(s: string{nkStrLit})       = assert s == "literal"
  proc somefunc(s: string{nkRStrLit})      = assert s == r"raw"
  proc somefunc(s: string{nkTripleStrLit}) = assert s == """triple"""
  proc somefunc(s: static[string])         = assert s == "constant"

  # Use parameter constraints to provide overloads based on both the input parameter type and form.
  var variable = "variable"
  somefunc(variable)
  const constant = "constant"
  somefunc(constant)
  somefunc("literal")
  somefunc(r"raw")
  somefunc("""triple""")

Pattern operators

The operators *, **, |, ~ have a special meaning in patterns if they are written in infix notation.

The `|` operator

The | operator if used as infix operator creates an ordered choice:

  template t{0|1}(): untyped = 3
  let a = 1
  # outputs 3:
  echo a

The matching is performed after the compiler performed some optimizations like constant folding, so the following does not work:

  template t{0|1}(): untyped = 3
  # outputs 1:
  echo 1

The reason is that the compiler already transformed the 1 into "1" for the echo statement. However, a term rewriting macro should not change the semantics anyway. In fact, they can be deactivated with the --patterns:off:option: command line option or temporarily with the patterns pragma.

The `{}` operator

A pattern expression can be bound to a pattern parameter via the expr{param} notation:

  template t{(0|1|2){x}}(x: untyped): untyped = x + 1
  let a = 1
  # outputs 2:
  echo a

The `~` operator

The ~ operator is the 'not' operator in patterns:

  template t{x = (~x){y} and (~x){z}}(x, y, z: bool) =
    x = y
    if x: x = z

  var
    a = false
    b = true
    c = false
  a = b and c
  echo a

The `*` operator

The * operator can flatten a nested binary expression like a & b & c to &(a, b, c):

  var
    calls = 0

  proc `&&`(s: varargs[string]): string =
    result = s[0]
    for i in 1..len(s)-1: result.add s[i]
    inc calls

  template optConc{ `&&` * a }(a: string): untyped = &&a

  let space = " "
  echo "my" && (space & "awe" && "some " ) && "concat"

  # check that it's been optimized properly:
  doAssert calls == 1

The second operator of * must be a parameter; it is used to gather all the arguments. The expression "my" && (space & "awe" && "some " ) && "concat" is passed to optConc in a as a special list (of kind nkArgList) which is flattened into a call expression; thus the invocation of optConc produces:

  `&&`("my", space & "awe", "some ", "concat")

The `**` operator

The ** is much like the * operator, except that it gathers not only all the arguments, but also the matched operators in reverse polish notation:

  import std/macros

  type
    Matrix = object
      dummy: int

  proc `*`(a, b: Matrix): Matrix = discard
  proc `+`(a, b: Matrix): Matrix = discard
  proc `-`(a, b: Matrix): Matrix = discard
  proc `$`(a: Matrix): string = result = $a.dummy
  proc mat21(): Matrix =
    result.dummy = 21

  macro optM{ (`+`|`-`|`*`) ** a }(a: Matrix): untyped =
    echo treeRepr(a)
    result = newCall(bindSym"mat21")

  var x, y, z: Matrix

  echo x + y * z - x

This passes the expression x + y * z - x to the optM macro as an nnkArgList node containing:

Arglist
  Sym "x"
  Sym "y"
  Sym "z"
  Sym "*"
  Sym "+"
  Sym "x"
  Sym "-"

(This is the reverse polish notation of x + y * z - x.)

Parameters

Parameters in a pattern are type checked in the matching process. If a parameter is of the type varargs, it is treated specially and can match 0 or more arguments in the AST to be matched against:

  template optWrite{
    write(f, x)
    ((write|writeLine){w})(f, y)
  }(x, y: varargs[untyped], f: File, w: untyped) =
    w(f, x, y)

noRewrite pragma

Term rewriting macros and templates are currently greedy and they will rewrite as long as there is a match. There was no way to ensure some rewrite happens only once, e.g. when rewriting term to same term plus extra content.

noRewrite pragma can actually prevent further rewriting on marked code, e.g. with given example echo("ab") will be rewritten just once:

  template pwnEcho{echo(x)}(x: untyped) =
    {.noRewrite.}: echo("pwned!")

  echo "ab"

noRewrite pragma can be useful to control term-rewriting macros recursion.

Example: Partial evaluation

The following example shows how some simple partial evaluation can be implemented with term rewriting:

  proc p(x, y: int; cond: bool): int =
    result = if cond: x + y else: x - y

  template optP1{p(x, y, true)}(x, y: untyped): untyped = x + y
  template optP2{p(x, y, false)}(x, y: untyped): untyped = x - y

Example: Hoisting

The following example shows how some form of hoisting can be implemented:

  import std/pegs

  template optPeg{peg(pattern)}(pattern: string{lit}): Peg =
    var gl {.global, gensym.} = peg(pattern)
    gl

  for i in 0 .. 3:
    echo match("(a b c)", peg"'(' @ ')'")
    echo match("W_HI_Le", peg"\y 'while'")

The optPeg template optimizes the case of a peg constructor with a string literal, so that the pattern will only be parsed once at program startup and stored in a global gl which is then re-used. This optimization is called hoisting because it is comparable to classical loop hoisting.

AST based overloading

Parameter constraints can also be used for ordinary routine parameters; these constraints then affect ordinary overloading resolution:

  proc optLit(a: string{lit|`const`}) =
    echo "string literal"
  proc optLit(a: string) =
    echo "no string literal"

  const
    constant = "abc"

  var
    variable = "xyz"

  optLit("literal")
  optLit(constant)
  optLit(variable)

However, the constraints alias and noalias are not available in ordinary routines.

Parallel & Spawn

Nim has two flavors of parallelism: 1) Structured:idx: parallelism via the parallel statement. 2) Unstructured:idx: parallelism via the standalone spawn statement.

Nim has a builtin thread pool that can be used for CPU intensive tasks. For IO intensive tasks the async and await features should be used instead. Both parallel and spawn need the threadpool module to work.

Somewhat confusingly, spawn is also used in the parallel statement with slightly different semantics. spawn always takes a call expression of the form f(a, ...). Let T be f's return type. If T is void, then spawn's return type is also void, otherwise it is FlowVar[T].

Within a parallel section, the FlowVar[T] is sometimes eliminated to T. This happens when T does not contain any GC'ed memory. The compiler can ensure the location in location = spawn f(...) is not read prematurely within a parallel section and so there is no need for the overhead of an indirection via FlowVar[T] to ensure correctness.

.. note:: Currently exceptions are not propagated between spawn'ed tasks!

This feature is likely to be removed in the future as external packages can have better solutions.

Spawn statement

The spawn:idx: statement can be used to pass a task to the thread pool:

  import std/threadpool

  proc processLine(line: string) =
    discard "do some heavy lifting here"

  for x in lines("myinput.txt"):
    spawn processLine(x)
  sync()

For reasons of type safety and implementation simplicity the expression that spawn takes is restricted:

It must be a call expression f(a, ...).
f must be gcsafe.
f must not have the calling convention closure.
f's parameters may not be of type var. This means one has to use raw ptr's for data passing reminding the programmer to be careful.
ref parameters are deeply copied, which is a subtle semantic change and can cause performance problems, but ensures memory safety. This deep copy is performed via system.deepCopy, so it can be overridden.
For safe data exchange between f and the caller, a global Channel needs to be used. However, since spawn can return a result, often no further communication is required.

spawn executes the passed expression on the thread pool and returns a data flow variable:idx: FlowVar[T] that can be read from. The reading with the ^ operator is blocking. However, one can use blockUntilAny to wait on multiple flow variables at the same time:

  import std/threadpool, ...

  # wait until 2 out of 3 servers received the update:
  proc main =
    var responses = newSeq[FlowVarBase](3)
    for i in 0..2:
      responses[i] = spawn tellServer(Update, "key", "value")
    var index = blockUntilAny(responses)
    assert index >= 0
    responses.del(index)
    discard blockUntilAny(responses)

Data flow variables ensure that no data races are possible. Due to technical limitations, not every type T can be used in a data flow variable: T has to be a ref, string, seq or of a type that doesn't contain any GC'd type. This restriction is not hard to work-around in practice.

Parallel statement

Example:

```nim test = "nim c --threads:on $1" # Compute pi in an inefficient way import std/[strutils, math, threadpool] {.experimental: "parallel".}

proc term(k: float): float = 4 * math.pow(-1, k) / (2*k + 1)

proc pi(n: int): float =

var ch = newSeq[float](n + 1)
parallel:
  for k in 0..ch.high:
    ch[k] = spawn term(float(k))
for k in 0..ch.high:
  result += ch[k]

echo formatFloat(pi(5000))



The parallel statement is the preferred mechanism to introduce parallelism in a
Nim program. Only a subset of the Nim language is valid within a `parallel`
section. This subset is checked during semantic analysis to be free of data
races. A sophisticated `disjoint checker`:idx: ensures that no data races are
possible, even though shared memory is extensively supported!

The subset is in fact the full language with the following
restrictions / changes:

* `spawn` within a `parallel` section has special semantics.
* Every location of the form `a[i]`, `a[i..j]` and `dest` where
  `dest` is part of the pattern `dest = spawn f(...)` has to be
  provably disjoint. This is called the *disjoint check*.
* Every other complex location `loc` that is used in a spawned
  proc (`spawn f(loc)`) has to be immutable for the duration of
  the `parallel` section. This is called the *immutability check*. Currently
  it is not specified what exactly "complex location" means. We need to make
  this an optimization!
* Every array access has to be provably within bounds. This is called
  the *bounds check*.
* Slices are optimized so that no copy is performed. This optimization is not
  yet performed for ordinary slices outside of a `parallel` section.


Strict definitions and `out` parameters
=======================================

With `experimental: "strictDefs"` *every* local variable must be initialized explicitly before it can be used:

  ```nim
  {.experimental: "strictDefs".}

  proc test =
    var s: seq[string]
    s.add "abc" # invalid!

Needs to be written as:

  {.experimental: "strictDefs".}

  proc test =
    var s: seq[string] = @[]
    s.add "abc" # valid!

A control flow analysis is performed in order to prove that a variable has been written to before it is used. Thus the following is valid:

  {.experimental: "strictDefs".}

  proc test(cond: bool) =
    var s: seq[string]
    if cond:
      s = @["y"]
    else:
      s = @[]
    s.add "abc" # valid!

In this example every path does set s to a value before it is used.

  {.experimental: "strictDefs".}

  proc test(cond: bool) =
    let s: seq[string]
    if cond:
      s = @["y"]
    else:
      s = @[]

With experimental: "strictDefs", let statements are allowed to not have an initial value, but every path should set s to a value before it is used.

`out` parameters

An out parameter is like a var parameter but it must be written to before it can be used:


  proc myopen(f: out File; name: string): bool =
    f = default(File)
    result = open(f, name)

While it is usually the better style to use the return type in order to return results API and ABI considerations might make this infeasible. Like for var T Nim maps out T to a hidden pointer. For example POSIX's stat routine can be wrapped as:


  proc stat*(a1: cstring, a2: out Stat): cint {.importc, header: "<sys/stat.h>".}

When the implementation of a routine with output parameters is analysed, the compiler checks that every path before the (implicit or explicit) return does set every output parameter:


  proc p(x: out int; y: out string; cond: bool) =
    x = 4
    if cond:
      y = "abc"
    # error: not every path initializes 'y'

Out parameters and exception handling

The analysis should take exceptions into account (but currently does not):


  proc p(x: out int; y: out string; cond: bool) =
    x = canRaise(45)
    y = "abc" # <-- error: not every path initializes 'y'

Once the implementation takes exceptions into account it is easy enough to use outParam = default(typeof(outParam)) in the beginning of the proc body.

Out parameters and inheritance

It is not valid to pass an lvalue of a supertype to an out T parameter:


  type
    Superclass = object of RootObj
      a: int
    Subclass = object of Superclass
      s: string

  proc init(x: out Superclass) =
    x = Superclass(a: 8)

  var v: Subclass
  init v
  use v.s # the 's' field was never initialized!

However, in the future this could be allowed and provide a better way to write object constructors that take inheritance into account.

Note: The implementation of "strict definitions" and "out parameters" is experimental but the concept is solid and it is expected that eventually this mode becomes the default in later versions.

Strict case objects

With experimental: "strictCaseObjects" every field access is checked to be valid at compile-time. The field is within a case section of an object.

  {.experimental: "strictCaseObjects".}

  type
    Foo = object
      case b: bool
      of false:
        s: string
      of true:
        x: int

  var x = Foo(b: true, x: 4)
  case x.b
  of true:
    echo x.x # valid
  of false:
    echo "no"

  case x.b
  of false:
    echo x.x # error: field access outside of valid case branch: x.x
  of true:
    echo "no"

Note: The implementation of "strict case objects" is experimental but the concept is solid and it is expected that eventually this mode becomes the default in later versions.

manual_experimental.md 59 KB Permalink History Raw

Nim Experimental Features

About this document

Void type

Generic define pragma

Top-down type inference

Sequence literals

Package level objects

Importing private symbols

Code reordering

Special Operators

dot operators

operator .

operator .()

operator .=

Call operator

Extended macro pragmas

Symbols as template/macro calls (alias syntax)

Not nil annotation

Aliasing restrictions in parameter passing

Strict funcs

View types

Path expressions

Start of a borrow

End of a borrow

Reborrows

Algorithm

Concepts

Concept diagnostics

Generic concepts and type binding rules

Concept refinement

Dynamic arguments for bindSym

Term rewriting macros

Parameter constraints

Pattern operators

The | operator

The {} operator

The ~ operator

The * operator

The ** operator

Parameters

noRewrite pragma

Example: Partial evaluation

Example: Hoisting

AST based overloading

Parallel & Spawn

Spawn statement

Parallel statement

out parameters

Out parameters and exception handling

Out parameters and inheritance

Strict case objects

manual_experimental.md 59 KB

Permalink History Raw

Generic `define` pragma

operator `.`

operator `.()`

operator `.=`

The `|` operator

The `{}` operator

The `~` operator

The `*` operator

The `**` operator

`out` parameters