=========================
:Authors: Andreas Rumpf :Version: |nimversion|
.. default-role:: code .. include:: rstcommon.rst .. contents::
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.
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
.
define
pragmaAside 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
bool
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.
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])
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.
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.
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.
.. 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:
.
This operator will be matched against both field accesses and method calls.
.()
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.
.=
This operator will be matched against assignments to missing fields.
a.b = c # becomes `.=`(a, b, c)
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)
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 = ...
Templates and macros that take no 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: untyped = foo.bar
assert bar == 10
bar = 15
assert bar == 15
In the future, this may require more specific information on template or macro signatures to be used. Specializations for some applications of this may also be introduced to guarantee consistency and circumvent bugs.
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
.. 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
.
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:
.noSideEffect
proc.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
.. 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:
p
. Note that this does not cover parameters of
inner procs.result
symbol of p
.var
or let
or const
of p
. Note that this does
not cover locals of inner procs.var
or let
.let
or const
.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.e[i]
is a path expression.e[0]
is a path expression.e.field
is a path expression.system.toOpenArray(e, ...)
is a path expression.e[]
is a path expression.addr e
is a path expression.T(e)
is a path 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.
A borrow starts with one of the following:
A borrow operation ends with the last usage of the view variable.
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.
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.
v
must not exceed b
's lifetime. Note: The lifetime of
a parameter is the complete proc body.v
is used for a mutation, b
must be a mutable location too.v
's lifetime, G(b)
can only be modified by v
(and only if
v
is a mutable view).v
is result
then b
has to be a location derived from the first
formal parameter or from a constant location.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.
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.
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
...
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.
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 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.
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""")
The operators *
, **
, |
, ~
have a special meaning in patterns
if they are written in infix notation.
|
operatorThe |
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.
{}
operatorA 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
~
operatorThe ~
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
*
operatorThe *
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")
**
operatorThe **
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 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)
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.
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
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.
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.
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.
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:
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.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.
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
parametersAn 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'
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.
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.
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.