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digitalmars.D - Scala future, Sing#
As Sing# (http://en.wikipedia.org/wiki/Sing_sharp ) and Chapel, Scala is one of
the languages to be followed more, because they share some of future purposes
of D2/D3.
A small presentation about the close future of Scala (it's not a general
introduction to Scala):
"Scala -- The Next 5 Years" by Martin Odersky:
http://www.scala-lang.org/sites/default/files/odersky/scalaliftoff2009.pdf
Sing# has a complex and advanced core, and I haven't found good tutorials about
it. I have found a confusing document about Spec#, that's a limited father of
Sing#. I think the only significant improvement of Spec# over D2 is that Spec#
contains a kind of inference engine that probably processes/uses contracts and
class invariants quite better than D2 (probably in a similar way to Eiffel):
http://channel9.msdn.com/wiki/specsharp/specsharpobjectprimer
Bye,
bearophile
bearophile wrote:
As Sing# (http://en.wikipedia.org/wiki/Sing_sharp ) and Chapel, Scala is
one of the languages to be followed more, because they share some of
future purposes of D2/D3.
A small presentation about the close future of Scala (it's not a general
introduction to Scala): "Scala -- The Next 5 Years" by Martin Odersky:
http://www.scala-lang.org/sites/default/files/odersky/scalaliftoff2009.pdf
Scala is an impressive language and overall well designed. There are
certainly truckloads of features that could be taken from Scala to D. But
I'm afraid that the desire to have familiarity and compatibility with the
C/C++ family is more important in this community than cool new functional
features. Here's a quick comparison of some factors:
- community: From what I've gathered, the Scala community mostly consists of
much more experienced computer scientists and programmers (I don't mean
industrial boiler-plate experience but experience with different kinds of
languages, PL concepts and e.g. sound argumentation). These programmers
aren't afraid of radical new ideas if it helps every day coding. These guys
hate unorthogonality and love rigorous definition of semantics. They also
want to discuss language issues and unlike Walter, Odersky doesn't lurk
silently when important things are being discussed. This is a huge ++ to the
PR. He also welcomes academics and doesn't ask them to go back to their
ivory tower like most in D's community do. I understand embracing the
industry, too, but it hasn't brought much money to D's development yet.
- bloat: Scala is more lightweight. I've heard Walter say that he doesn't
like e.g. library defined control structures - it's double-edged sword, and
D and Scala have taken different paths here (in D if something is commonly
used and it can be made built-in, it will be added to the compiler, in Scala
it's the opposite). Scala has a very lightweight language core, and many
additional features are defined in libraries. Several optimizations that
improve the performance of HOFs are already known, but the compiler and
virtual machine are not yet as good as they can be. In theory a good
supercompiler can make Scala as fast as D. I personally find it funny that
the meta-programming features in D are perfect for shrinking the language
core, but every year new features still keep creeping it.
- dynamics: Scala is more dynamic (reflection, class loaders etc.) Thanks to
JVM.
- OOP: Scala supports dynamic OOP optimizations unlike D (unless a VM is
used). Thanks to the JIT compiler. The new 2.8 supports new static
optimizations similar to what C++ & D have had.
- syntax: Scala has a consistent and orthogonal syntax. Syntactic sugar is
used sparingly and when it's being used, it shaves off boilerplate quite a
bit.
* e.g. (_._2 * _._1) is something like (tuple a, tuple b) { return a(1) *
b(0); } in D.. I leave the definition of the tuple type as an exercise to
the reader.
* (A => B) => (C => D) vs (B function(A)) function (D function(C))
* case class foo(val a: Int, var b: String) is somewhere between 10-30 LOC
in D
* In D syntactic sugar often saves only a couple of characters (like the
new template T!X syntax)
- modularity & types: Scala supports modularity much better IMO (pure OOP,
self types etc.). The abstractions are well suited for most tasks. But this
is a bit hard to compare objectively.
- high level features: Scala unifies OOP and FP. It also has novel new OOP
concepts.
- low level features: D wins here, OTOH a low level language isn't good for
e.g. sandboxed environments
- memory management: the JVM's GC is pretty mature, but of course manual
memory management isn't as easy as in D
- compatibility: D wins (?) here if C/C++ compatibility is important, but
Scala is compatible with the large existing code base of Java, though
- bugs: IMHO the unspecified parts of D and the huge amount of bugs made it
unusable for me. Luckily I found Scala and have been really happy with it.
I've only found maybe 1-2 bugs in it during the last 1.5 years. I usually
find about 5-10 bugs in DMD in 15 minutes after coming back to D. And I'm
also so happy to find that thanks to authors' knowledge of type systems
(dependent types, HM, System F, etc.) Scala is a genius at inferring types.
D doesn't really have a clue. Especially the array literal type inference is
really naive.
- to summarize: I use Scala for high level tasks, and came back to D when I
need to see the actual machine code and optimize some tight inner loop. D is
sometimes more suitable for this than C/C++ since it has a bit saner syntax
and high level abstractions. But in general I nowadays write 90% of my code
in Scala. I'm much happier and more productive writing Scala. YMMV
Jari-Matti M.:
There are certainly truckloads of features that could be taken from Scala to D.<
But D2 is already quite complex, so it's better to add things carefully. For
example patterm matching is useful, but it adds a lot of complexity too.
But I'm afraid that the desire to have familiarity and compatibility with the
C/C++ family is more important in this community than cool new functional
features.<
And this can be a good thing, because C and C++ are commonly used languages.
- community: From what I've gathered, the Scala community mostly consists of
This is an advantage for D: it can be used by more ignorant people too (or
people more ignorant of functional lanmguages).
- bloat: Scala is more lightweight.<
This is a matter of balance, and there are no 'best' solutions. Moving things
from the library to the language has some advantages.
Several optimizations that improve the performance of HOFs are already known,
but the compiler and virtual machine are not yet as good as they can be. In
theory a good supercompiler can make Scala as fast as D.<
HotSpot Java GC is much more efficient than the current D GC, and HotSpot is
often able to inline virtual methods. D has the advantage of having a simpler
core. Creating a Scala compiler on LLVM may be hard, running D1 on LLVM was
easy enough. Simpler systems have some advantages. Scala type inference is much
more powerful but it's also harder to use (if you want to do complex things),
and requires a more complex compiler.
In practice supercompilers are very hard to create, while D1 code running on
the LLVM is already very efficient.
Simpler systems also have the advantahe of being more transparent:
understanding why some D1 code is fast or slow is probably simpler than doing
the same thing with a piece of Scala code.
I personally find it funny that the meta-programming features in D are perfect
for shrinking the language core, but every year new features still keep
creeping it.<
They are not perfect, they have limits, and the ersults aren't always nice, see
the struct bitfields.
- dynamics: Scala is more dynamic (reflection, class loaders etc.) Thanks to
JVM.<
Some of such things can be added/improved in D too.
- syntax: Scala has a consistent and orthogonal syntax.<
Too much orthogonality is bad, it produces the LEGO disease. A compromise is
better.
Syntactic sugar is used sparingly and when it's being used, it shaves off
boilerplate quite a bit. * e.g. (_._2 * _._1)<
Here there are risks too. I have seen a syntax for a fold (reduce) in Scala
that's horribly unreadable. Python3 has even removed reduce() from the core
language because folds aren't easy to understand and I agree with their
decision. Keeping the language easy is more important. Too much boilerplate is
boring, but the boilerplate is better than hard to understand code.
* In D syntactic sugar often saves only a couple of characters (like the new
template T!X syntax)<
I agree that was a silly idea, that I may even like to remove from D2. I want
eager/lazy sequence comphrensions :-)
- memory management: the JVM's GC is pretty mature, but of course manual memory
management isn't as easy as in D<
Some forms of memory usage that I use in D are impossible on the JavaVM.
- compatibility: D wins (?) here if C/C++ compatibility is important, but Scala
is compatible with the large existing code base of Java, though<
D refuses to be compatible with C++. There's just partial compatibility (and
this is probably good).
the huge amount of bugs made it unusable for me.<
There are many bugs in D, but D is slowly opening a bit more and more toward
the community, for example see the recent lot of bug fixes by Don. If more
people will work like Don, lot of bugs will be removed. Walter is slowly
understanding what open source development means. So I have hope still.
And I'm also so happy to find that thanks to authors' knowledge of type systems
(dependent types, HM, System F, etc.) Scala is a genius at inferring types. D
doesn't really have a clue.<
Scala uses a totally different type system. I think it uses an Hindley–Milner
type inference algorithm. Walter is probably not expert on such thing. A single
person can't be expert on everything. Today designing concurrency, type
inference or garbage collectors requires lot of specialized and even some
academic knowledge. Scala author has used the JavaVM to avoid doing lot of
low-level work. D type system isn't so bad. It has limits, and some of such
limits may be lifted a little, but you can do lot of things with the D language
anyway, see some of the things I've done in my dlibs. Keeping the type system
simpler has some advantages too, for example compilation speed.
Especially the array literal type inference is really naive.<
I'm sure it's not hard to fix the array literal type inference that currently
is not good; it's just that Walter isn't interested in doing it, or he thinks
things are good like this, like for the half-unfinished module system.
- to summarize: I use Scala for high level tasks, and came back to D when I
need to see the actual machine code and optimize some tight inner loop. D is
sometimes more suitable for this than C/C++ since it has a bit saner syntax and
high level abstractions.<
Today when you need hi-performance you need the GPU or to use SSE registers
very well.
An usage usample of the GPU:
http://www.smartwikisearch.com/algorithm.html
In the end if you need really fast programs that have to perform heavy
numerical computations you need languages like Python (plus the right libs,
like CorePy), D (and Scala) isn't up to the task yet:
http://www.corepy.org/
http://mathema.tician.de/software/pycuda
http://python.sys-con.com/node/926439
http://pypi.python.org/pypi/python-opencl/0.2
Bye,
bearophile
Jari-Matti Mäkelä wrote:
bearophile wrote:
As Sing# (http://en.wikipedia.org/wiki/Sing_sharp ) and Chapel, Scala is
one of the languages to be followed more, because they share some of
future purposes of D2/D3.
A small presentation about the close future of Scala (it's not a general
introduction to Scala): "Scala -- The Next 5 Years" by Martin Odersky:
http://www.scala-lang.org/sites/default/files/odersky/scalaliftoff2009.pdf
Scala is an impressive language and overall well designed. There are
certainly truckloads of features that could be taken from Scala to D. But
I'm afraid that the desire to have familiarity and compatibility with the
C/C++ family is more important in this community than cool new functional
features. Here's a quick comparison of some factors:
- community: From what I've gathered, the Scala community mostly consists of
much more experienced computer scientists and programmers (I don't mean
industrial boiler-plate experience but experience with different kinds of
languages, PL concepts and e.g. sound argumentation). These programmers
aren't afraid of radical new ideas if it helps every day coding. These guys
hate unorthogonality and love rigorous definition of semantics. They also
want to discuss language issues and unlike Walter, Odersky doesn't lurk
silently when important things are being discussed. This is a huge ++ to the
PR. He also welcomes academics and doesn't ask them to go back to their
ivory tower like most in D's community do. I understand embracing the
industry, too, but it hasn't brought much money to D's development yet.
- bloat: Scala is more lightweight. I've heard Walter say that he doesn't
like e.g. library defined control structures -
Actually, you can do them with "lazy" function arguments. There was an
example somewhere of doing control structures with it.
it's double-edged sword, and
D and Scala have taken different paths here (in D if something is commonly
used and it can be made built-in, it will be added to the compiler, in Scala
it's the opposite).
That's not quite right. I'll add things to the core if there is a good
reason to - the compiler can do things a library cannot. For example,
string literals.
Scala has a very lightweight language core, and many
additional features are defined in libraries. Several optimizations that
improve the performance of HOFs are already known, but the compiler and
virtual machine are not yet as good as they can be. In theory a good
supercompiler can make Scala as fast as D.
I've been hearing that (about Java, same problem) for as long as Java
has been around. It might get there yet, but that won't be in the near
future.
I personally find it funny that
the meta-programming features in D are perfect for shrinking the language
core, but every year new features still keep creeping it.
Actually, some features are being removed. Imaginary and complex
variables, for one. There's some work being done to rewrite D forms into
simpler D forms, saving hundreds of lines of code in the compiler.
- dynamics: Scala is more dynamic (reflection, class loaders etc.) Thanks to
JVM.
Yes, but an interpreter or JIT is required to make that work. That makes
the language binary not lightweight.
- OOP: Scala supports dynamic OOP optimizations unlike D (unless a VM is
used).
Do you mean knowing a class or virtual method has no descendants? Sure,
you need to know the whole program to do that, or just declare it as final.
Thanks to the JIT compiler. The new 2.8 supports new static
optimizations similar to what C++ & D have had.
- syntax: Scala has a consistent and orthogonal syntax. Syntactic sugar is
used sparingly and when it's being used, it shaves off boilerplate quite a
bit.
* e.g. (_._2 * _._1) is something like (tuple a, tuple b) { return a(1) *
b(0); } in D.. I leave the definition of the tuple type as an exercise to
the reader.
* (A => B) => (C => D) vs (B function(A)) function (D function(C))
* case class foo(val a: Int, var b: String) is somewhere between 10-30 LOC
in D
* In D syntactic sugar often saves only a couple of characters (like the
new template T!X syntax)
- modularity & types: Scala supports modularity much better IMO (pure OOP,
self types etc.). The abstractions are well suited for most tasks. But this
is a bit hard to compare objectively.
- high level features: Scala unifies OOP and FP. It also has novel new OOP
concepts.
- low level features: D wins here, OTOH a low level language isn't good for
e.g. sandboxed environments
Sure, but there's the Safe D subset, and also D isn't intended for
non-programmers to download untrusted source code from the internet and run.
- memory management: the JVM's GC is pretty mature, but of course manual
memory management isn't as easy as in D
- compatibility: D wins (?) here if C/C++ compatibility is important, but
Scala is compatible with the large existing code base of Java, though
You can mechanically translate Java to D, but it still requires some
manual touch-up.
- bugs: IMHO the unspecified parts of D and the huge amount of bugs made it
unusable for me. Luckily I found Scala and have been really happy with it.
I've only found maybe 1-2 bugs in it during the last 1.5 years. I usually
find about 5-10 bugs in DMD in 15 minutes after coming back to D.
I couldn't find any bugs you've submitted to the D bugzilla. If you
don't submit them, they won't get fixed <g>.
And I'm
also so happy to find that thanks to authors' knowledge of type systems
(dependent types, HM, System F, etc.) Scala is a genius at inferring types.
D doesn't really have a clue.
Can you give an example?
Especially the array literal type inference is really naive.
How should it be done?
- to summarize: I use Scala for high level tasks, and came back to D when I
need to see the actual machine code and optimize some tight inner loop. D is
sometimes more suitable for this than C/C++ since it has a bit saner syntax
and high level abstractions. But in general I nowadays write 90% of my code
in Scala. I'm much happier and more productive writing Scala. YMMV
I appreciate you taking the time to tell us your impressions on this.
Walter Bright escribió:
Jari-Matti Mäkelä wrote:
bearophile wrote:
- OOP: Scala supports dynamic OOP optimizations unlike D (unless a VM
is used).
Do you mean knowing a class or virtual method has no descendants? Sure,
you need to know the whole program to do that, or just declare it as final.
I think the standard name is "adaptive optimization":
http://en.wikipedia.org/wiki/Adaptive_optimization
"Adaptive optimization is a technique in computer science that performs
dynamic recompilation of portions of a program based on the current
execution profile."
"Consider a hypothetical banking application that handles transactions
one after another. These transactions may be checks, deposits, and a
large number of more obscure transactions. When the program executes,
the actual data may consist of clearing tens of thousands of checks
without processing a single deposit and without processing a single
check with a fraudulent account number. An adaptive optimizer would
compile assembly code to optimize for this common case. If the system
then started processing tens of thousands of deposits instead, the
adaptive optimizer would recompile the assembly code to optimize the new
common case. This optimization may include inlining code or moving error
processing code to secondary cache."
Ary Borenszweig wrote:
Walter Bright escribió:
Jari-Matti Mäkelä wrote:
bearophile wrote:
- OOP: Scala supports dynamic OOP optimizations unlike D (unless a VM
is used).
Do you mean knowing a class or virtual method has no descendants?
Sure, you need to know the whole program to do that, or just declare
it as final.
I think the standard name is "adaptive optimization":
http://en.wikipedia.org/wiki/Adaptive_optimization
"Adaptive optimization is a technique in computer science that performs
dynamic recompilation of portions of a program based on the current
execution profile."
"Consider a hypothetical banking application that handles transactions
one after another. These transactions may be checks, deposits, and a
large number of more obscure transactions. When the program executes,
the actual data may consist of clearing tens of thousands of checks
without processing a single deposit and without processing a single
check with a fraudulent account number. An adaptive optimizer would
compile assembly code to optimize for this common case. If the system
then started processing tens of thousands of deposits instead, the
adaptive optimizer would recompile the assembly code to optimize the new
common case. This optimization may include inlining code or moving error
processing code to secondary cache."
It's also called profile guided optimization, but Jari-Matti said it was
"OOP" related, so I wondered how that fit in.
Walter Bright wrote:
Ary Borenszweig wrote:
Walter Bright escribió:
Jari-Matti Mäkelä wrote:
bearophile wrote:
- OOP: Scala supports dynamic OOP optimizations unlike D (unless a VM
is used).
Do you mean knowing a class or virtual method has no descendants?
Sure, you need to know the whole program to do that, or just declare
it as final.
I think the standard name is "adaptive optimization":
http://en.wikipedia.org/wiki/Adaptive_optimization
"Adaptive optimization is a technique in computer science that performs
dynamic recompilation of portions of a program based on the current
execution profile."
"Consider a hypothetical banking application that handles transactions
one after another. These transactions may be checks, deposits, and a
large number of more obscure transactions. When the program executes,
the actual data may consist of clearing tens of thousands of checks
without processing a single deposit and without processing a single
check with a fraudulent account number. An adaptive optimizer would
compile assembly code to optimize for this common case. If the system
then started processing tens of thousands of deposits instead, the
adaptive optimizer would recompile the assembly code to optimize the new
common case. This optimization may include inlining code or moving error
processing code to secondary cache."
It's also called profile guided optimization, but Jari-Matti said it was
"OOP" related, so I wondered how that fit in.
I meant this
"Another important example of this kind of optimization is class-hierarchy-
based optimization. A virtual method invocation, for example, involves
looking at the class of the receiver object for the call to discover which
actual target implements the virtual method for the receiver object.
Research has shown that most virtual invocations have only a single target
for all receiver objects, and JIT compilers can generate more-efficient code
for a direct call than for a virtual invocation. By analyzing the class
hierarchy's state when the code is compiled, the JIT compiler can find the
single target method for a virtual invocation and generate code that
directly calls the target method rather than performing the slower virtual
invocation. Of course, if the class hierarchy changes and a second target
method becomes possible, then the JIT compiler can correct the originally
generated code so that the virtual invocation is performed. In practice,
these corrections are rarely required. Again, the potential need to make
such corrections makes performing this optimization statically troublesome."
http://www.ibm.com/developerworks/java/library/j-rtj2/index.html
Jari-Matti Mäkelä wrote:
I meant this
"Another important example of this kind of optimization is class-hierarchy-
based optimization. A virtual method invocation, for example, involves
looking at the class of the receiver object for the call to discover which
actual target implements the virtual method for the receiver object.
Research has shown that most virtual invocations have only a single target
for all receiver objects, and JIT compilers can generate more-efficient code
for a direct call than for a virtual invocation. By analyzing the class
hierarchy's state when the code is compiled, the JIT compiler can find the
single target method for a virtual invocation and generate code that
directly calls the target method rather than performing the slower virtual
invocation. Of course, if the class hierarchy changes and a second target
method becomes possible, then the JIT compiler can correct the originally
generated code so that the virtual invocation is performed. In practice,
these corrections are rarely required. Again, the potential need to make
such corrections makes performing this optimization statically troublesome."
http://www.ibm.com/developerworks/java/library/j-rtj2/index.html
I'm not quite sure what that means, but I think it means nothing more
than noting that a method is not overridden, and so can be called directly.
Currently, this optimization happens in D if a method or class is
annotated with 'final'. It is possible for the compiler to do this if
flow analysis can prove the direct type of a class reference, but the
optimizer currently does not do that. It is also possible for the
compiler to determine that methods are final automatically if it knows
about all the modules that import a particular class.
Walter Bright wrote:
Jari-Matti Mäkelä wrote:
- bloat: Scala is more lightweight. I've heard Walter say that he doesn't
like e.g. library defined control structures -
Actually, you can do them with "lazy" function arguments. There was an
example somewhere of doing control structures with it.
Agreed, you /can/ do something similar. But in Scala it's the standard way
of doing things. If you compare the grammars of both languages, you'll see
that Scala is a bit lighter than D (see http://www.scala-
lang.org/sites/default/files/linuxsoft_archives/docu/files/ScalaReference.pdf)
it's double-edged sword, and
D and Scala have taken different paths here (in D if something is
commonly used and it can be made built-in, it will be added to the
compiler, in Scala it's the opposite).
That's not quite right. I'll add things to the core if there is a good
reason to - the compiler can do things a library cannot. For example,
string literals.
I exaggerated a bit. But there are some constructs that some think should
not be there, e.g. foreach_reverse.
- bugs: IMHO the unspecified parts of D and the huge amount of bugs made
it unusable for me. Luckily I found Scala and have been really happy with
it. I've only found maybe 1-2 bugs in it during the last 1.5 years. I
usually find about 5-10 bugs in DMD in 15 minutes after coming back to D.
I couldn't find any bugs you've submitted to the D bugzilla. If you
don't submit them, they won't get fixed <g>.
I've submitted couple of reports years ago and luckily some of them have
already been fixed. Maybe the search is broken.
And I'm
also so happy to find that thanks to authors' knowledge of type systems
(dependent types, HM, System F, etc.) Scala is a genius at inferring
types. D doesn't really have a clue.
Can you give an example?
http://d.puremagic.com/issues/show_bug.cgi?id=3042
auto foo = [ 1, 2L ]; // typeof == int[2u]
auto foo = [ 2L, 1 ]; // typeof == long[2u]
auto foo = [ "a", "abcdefgh" ]; // typeof == char[1u][2u] in D1
auto foo = [ [], [1,2,3] ]; // doesn't even compile
Especially the array literal type inference is really naive.
How should it be done?
You shouldn't use the type of the first given element when constructing the
type of the array. If you have [ e_1, ..., e_n ], the type of the literal is
unify(type_of_e_1, ..., type_of_e_n) + "[]". For instance:
=> typeof([ [], [1,2,3] ])
=> unify( typeof([]), typeof([1,2,3]) ) + "[]"
=> unify( "a[]", unify(typeof(1),typeof(2),typeof(3)) + "[]" ) + "[]"
=> unify( "a[]", unify("int","int","int") + "[]" ) + "[]"
=> unify( "a[]", "int" + "[]" ) + "[]"
=> unify( "a[]", "int[]" ) + "[]" // a is a local type var, subst = { a ->
int }
=> "int[]" + "[]"
=> "int[][]"
Jari-Matti Mäkelä wrote:
Agreed, you /can/ do something similar. But in Scala it's the standard way
of doing things. If you compare the grammars of both languages, you'll see
that Scala is a bit lighter than D (see http://www.scala-
lang.org/sites/default/files/linuxsoft_archives/docu/files/ScalaReference.pdf)
Yes, it's a bit different philosophy. I like the advantage of built in
control structures, because that leads to commonality between code
bases. I wished to avoid things like C++ string, where everyone invents
their own string class that's incompatible with everyone elses'. Whether
that latter effect occurs in Scala or not, I don't know.
I exaggerated a bit. But there are some constructs that some think should
not be there, e.g. foreach_reverse.
Perhaps, but you can just ignore it.
I've submitted couple of reports years ago and luckily some of them have
already been fixed. Maybe the search is broken.
Can you provide bug numbers?
Scala is a genius at inferring
types. D doesn't really have a clue.
http://d.puremagic.com/issues/show_bug.cgi?id=3042
auto foo = [ 1, 2L ]; // typeof == int[2u]
auto foo = [ 2L, 1 ]; // typeof == long[2u]
auto foo = [ "a", "abcdefgh" ]; // typeof == char[1u][2u] in D1
auto foo = [ [], [1,2,3] ]; // doesn't even compile
Especially the array literal type inference is really naive.
You shouldn't use the type of the first given element when constructing the
type of the array. If you have [ e_1, ..., e_n ], the type of the literal is
unify(type_of_e_1, ..., type_of_e_n) + "[]". For instance:
=> typeof([ [], [1,2,3] ])
=> unify( typeof([]), typeof([1,2,3]) ) + "[]"
=> unify( "a[]", unify(typeof(1),typeof(2),typeof(3)) + "[]" ) + "[]"
=> unify( "a[]", unify("int","int","int") + "[]" ) + "[]"
=> unify( "a[]", "int" + "[]" ) + "[]"
=> unify( "a[]", "int[]" ) + "[]" // a is a local type var, subst = { a ->
int }
=> "int[]" + "[]"
=> "int[][]"
Ok.
Walter Bright wrote:
Especially the array literal type inference is really naive.
You shouldn't use the type of the first given element when
constructing the type of the array. If you have [ e_1, ..., e_n ], the
type of the literal is
unify(type_of_e_1, ..., type_of_e_n) + "[]". For instance:
=> typeof([ [], [1,2,3] ])
=> unify( typeof([]), typeof([1,2,3]) ) + "[]"
=> unify( "a[]", unify(typeof(1),typeof(2),typeof(3)) + "[]" ) + "[]"
=> unify( "a[]", unify("int","int","int") + "[]" ) + "[]"
=> unify( "a[]", "int" + "[]" ) + "[]"
=> unify( "a[]", "int[]" ) + "[]" // a is a local type var, subst =
{ a -> int }
=> "int[]" + "[]"
=> "int[][]"
Ok.
Walter: I told you :o).
I'd already defined the unify meta-function, it's called CommonType, see
http://www.digitalmars.com/d/2.0/phobos/std_traits.html#CommonType
You pass any number of types and it will figure out the type that all
types can be converted to. Using that, it is trivial to define functions
that infer array types properly. At a point I had an array() function
that took any number of arguments and returned a correctly-typed array.
Then I dropped that and defined array() in std with a different meaning
(transform a range into an array).
Andrei
Walter Bright:
Actually, you can do them with "lazy" function arguments. There was an example
somewhere of doing control structures with it.<
There are some problems with this:
- Are current (especially LDC) compilers able to inline those lazy delegates?
Scala compiler contains some parts to do that at compile-time (so it's not done
at runtime by the JavaVM).
- I have put inside my dlibs a select() (adapting code written by another
person) that uses lazy arguments to implement an eager (it can't be lazy,
unfortunately) array comphrension. I'ver tried to see how the LDC compiles it
and people there have shown me distaste for that code of mine, even just for a
benchmark. So it seems the D community doesn't like to use lazy arguments to
create control structures.
- Andrei has shown so much distate for such things that the Phobos2 doesn't
ususually even use normal delegates, and you have even added a "typeless" way
to give a delegate to a template in D2. This shows there's little interest
among D developers to go the way of Scala. Scala uses delegates for those
purposes, and then inlines them.
I've been hearing that (about Java, same problem) for as long as Java has been
around. It might get there yet, but that won't be in the near future.<
Today Java is very fast, especially for very OOP-style code. Sometimes programs
in C++ can be a little faster, but generally no more than 2 times. C# on dotnet
too is fast, for example its GC and associative arrays are much faster.
Yes, but an interpreter or JIT is required to make that work. That makes the
language binary not lightweight.<
D can be improved/debugged in several ways in this regard, even if keeps not
using a VM.
Do you mean knowing a class or virtual method has no descendants? Sure, you
need to know the whole program to do that, or just declare it as final.<
I can see there's lot of confusion about such matters.
Experience has shown that class-hierarchy-based optimization isn't much
effective, because in most practical programs lot of virtual calls are bi- or
multi- morphic. Other strategies like "Type feedback" work better.
I have already discussed this topic a little, but it was on the D.learn
newsgroup, so you have missed it.
A good old paper about this topic:
"Eliminating Virtual Function Calls in C++ Programs" (1996), by Gerald Aigner,
Urs Hölzle:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.7.7766
There are other papers written on this topic, and some of such papers are more
modern/updated too (this is about 13 years old), but it's a good starting
point. If yoy want more papers please ask.
Note that the LDC compiler has Link-Time Optimization too, and LTO can also be
done when you "know the whole program". If the front-end gives some semantic
annotations to LDC, it can do powerful things during LTO.
Can you give an example?<
I don't know Scala enough to give you examples, so I leave this to Jari-Matti.
But I think Scala uses an Hindley-Milner type inference algorithm, it's another
class of type inferencing. I am not asking you to put Hindley-Milner inside D.
[array literal type inference] How should it be done?<
Silently dropping information is bad. So cutting strings according to the
length of the first one as in D1 is bad.
The type of an array literal has to be determined by the type specified by the
programmer on the right. If such annotation is absent (because there's an auto,
or because the array is inside an expression) the type has to be the most tight
able to represent all the types contained in the array literal (or raise an
error if no one can be found).
By default array literals have to produce dynamic arrays, unless the
programmers specifies that he/she/shi wants a fixed-size one.
(People are asking for similar things for years, it's not a new topic invented
by Jari-Matti M. or by me).
Bye,
bearophile
bearophile wrote:
Walter Bright:
Actually, you can do them with "lazy" function arguments. There was
an example somewhere of doing control structures with it.<
There are some problems with this: - Are current (especially LDC)
compilers able to inline those lazy delegates?
No, but it's not a technical issue, just more of no demand for it. But
this would not be a reason to use Scala, as one doesn't use Scala for
performance oriented programs.
I'ver tried to see how the LDC compiles it and people
there have shown me distaste for that code of mine, even just for a
benchmark. So it seems the D community doesn't like to use lazy
arguments to create control structures. - Andrei has shown so much
distate for such things that the Phobos2 doesn't ususually even use
normal delegates, and you have even added a "typeless" way to give a
delegate to a template in D2. This shows there's little interest
among D developers to go the way of Scala. Scala uses delegates for
those purposes, and then inlines them.
D supports many styles of programming. Whether a particular style is
popular or not is not really the issue - if someone wants to use that
style, it is available. If someone builds a compelling case for the
advantages of such a style, it can catch on.
We can see this in C++ over time, where different styles have gained
ascendancy and then were replaced by new styles.
I've been hearing that (about Java, same problem) for as long as
Java has been around. It might get there yet, but that won't be in
the near future.<
Today Java is very fast, especially for very OOP-style code.
Sometimes programs in C++ can be a little faster, but generally no
more than 2 times. C# on dotnet too is fast, for example its GC and
associative arrays are much faster.
A factor of 2 is a big deal.
Yes, but an interpreter or JIT is required to make that work. That
makes the language binary not lightweight.<
keeps not using a VM.
Sure, but there's still a huge difference.
Do you mean knowing a class or virtual method has no descendants?
Sure, you need to know the whole program to do that, or just
declare it as final.<
I can see there's lot of confusion about such matters. Experience has
shown that class-hierarchy-based optimization isn't much effective,
because in most practical programs lot of virtual calls are bi- or
multi- morphic. Other strategies like "Type feedback" work better. I
have already discussed this topic a little, but it was on the D.learn
newsgroup, so you have missed it.
A good old paper about this topic: "Eliminating Virtual Function
Calls in C++ Programs" (1996), by Gerald Aigner, Urs Hölzle:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.7.7766
Thanks for the reference. DMC++ does a good job of eliminating many
virtual calls.
There are other papers written on this topic, and some of such papers
are more modern/updated too (this is about 13 years old), but it's a
good starting point. If yoy want more papers please ask.
Note that the LDC compiler has Link-Time Optimization too, and LTO
can also be done when you "know the whole program". If the front-end
gives some semantic annotations to LDC, it can do powerful things
during LTO.
I didn't know that.
Walter Bright:
No, but it's not a technical issue, just more of no demand for it. But this
would not be a reason to use Scala, as one doesn't use Scala for performance
oriented programs.<
The usage of higher-order functions is pervasive in Scala, and they use
delegates. So optimiizing those delegates was quite high on the priority list
of optimization to perform.
In functional-style programming people use first-class functions all the time,
so they have to be optimized. That's why D2 may need to do the same if it wants
people to use functional-style programming :-)
DMC++ does a good job of eliminating many virtual calls.<
I have not found much of such capability in DMD. If DMD too performs that, then
can you show me 1 example when it's performed? :-)
[LTO in LDC] I didn't know that.<
Note: LTO isn't done automatically yet by LDC, so to do it you have to input 3
different commands.
Ask (to me, for example) if you want to know them.
Bye,
bearophile
bearophile wrote:
Walter Bright:
No, but it's not a technical issue, just more of no demand for it.
But this would not be a reason to use Scala, as one doesn't use
Scala for performance oriented programs.<
The usage of higher-order functions is pervasive in Scala, and they
use delegates. So optimiizing those delegates was quite high on the
priority list of optimization to perform. In functional-style
programming people use first-class functions all the time, so they
have to be optimized. That's why D2 may need to do the same if it
wants people to use functional-style programming :-)
There's quite a lot of D specific optimizations that are not done at the
moment, simply because of other more pressing issues.
DMC++ does a good job of eliminating many virtual calls.<
I have not found much of such capability in DMD. If DMD too performs
that, then can you show me 1 example when it's performed? :-)
DMC++, not DMD. I haven't done the effort yet to do it in DMD.
bearophile Wrote:
Walter Bright:
Actually, you can do them with "lazy" function arguments. There was an example
somewhere of doing control structures with it.<
There are some problems with this:
- Are current (especially LDC) compilers able to inline those lazy delegates?
Scala compiler contains some parts to do that at compile-time (so it's not done
at runtime by the JavaVM).
- I have put inside my dlibs a select() (adapting code written by another
person) that uses lazy arguments to implement an eager (it can't be lazy,
unfortunately) array comphrension. I'ver tried to see how the LDC compiles it
and people there have shown me distaste for that code of mine, even just for a
benchmark. So it seems the D community doesn't like to use lazy arguments to
create control structures.
- Andrei has shown so much distate for such things that the Phobos2 doesn't
ususually even use normal delegates, and you have even added a "typeless" way
to give a delegate to a template in D2. This shows there's little interest
among D developers to go the way of Scala. Scala uses delegates for those
purposes, and then inlines them.
The call-by-name trailing block syntax is also more uniform with the built-ins
in scala, e.g.:
scala> object Helpers { def run_twice[T](block: => T) = { block; block } }
defined module Helpers
scala> import Helpers._
import Helpers._
scala> var i = 1
i: Int = 1
scala> run_twice { i += 1; i }
res5: Int = 3
scala> run_twice { print("foo\n") }
foo
foo
I've been hearing that (about Java, same problem) for as long as Java has been
around. It might get there yet, but that won't be in the near future.<
Today Java is very fast, especially for very OOP-style code. Sometimes
programs in C++ can be a little faster, but generally no more than 2 times. C#
on dotnet too is fast, for example its GC and associative arrays are much
faster.
Java is /fast enough/ for many (if not most) purposes. People even use
languages with slower implementations like php or javascript these days (ever
heard of web 2.0?). Often the other aspects of the language have a larger
impact on real world projects than raw execution speed.
[array literal type inference] How should it be done?<
Silently dropping information is bad. So cutting strings according to the
length of the first one as in D1 is bad.
Since now I've mostly been experimenting with D1. But this seems to be fixed in
D2.
The type of an array literal has to be determined by the type specified by the
programmer on the right. If such annotation is absent (because there's an auto,
or because the array is inside an expression) the type has to be the most tight
able to represent all the types contained in the array literal (or raise an
error if no one can be found).
By default array literals have to produce dynamic arrays, unless the
programmers specifies that he/she/shi wants a fixed-size one.
The literals should also handle cases like [[],[],[1,2]], not only the string
case. What makes this frustating is that one can assume that since the generic
type inference engine isn't used consistently in all cases, there isn't one in
dmd. This might result in more corner cases in other parts of the language.
Jari-Matti Mäkelä wrote:
bearophile wrote:
As Sing# (http://en.wikipedia.org/wiki/Sing_sharp ) and Chapel, Scala is
one of the languages to be followed more, because they share some of
future purposes of D2/D3.
A small presentation about the close future of Scala (it's not a general
introduction to Scala): "Scala -- The Next 5 Years" by Martin Odersky:
http://www.scala-lang.org/sites/default/files/odersky/scalaliftoff2009.pdf
Scala is an impressive language and overall well designed. There are
certainly truckloads of features that could be taken from Scala to D. But
I'm afraid that the desire to have familiarity and compatibility with the
C/C++ family is more important in this community than cool new functional
features. Here's a quick comparison of some factors:
You are making very good points, thanks for an insightful post. A few of
them are slightly inaccurate, but those were discussed by Walter
already. I'd like to make a few high-level comments.
I find the lack of rigor in certain parts of D as damaging as you do.
Fortunately, that has improved by leaps and bounds and is still
improving. When I joined Walter with working on D back in 2006, D was
quite a lot less theoretically-motivated - it was all greasy nuts and
bolts and pegs hammered in place. There was a tacit agreement between
Walter and me that D will improve the rigor of its ways, and indeed we
have made strides in that respect. If things work out properly, we'll be
able to define SafeD - a proper, checkable safe subset of the language.
It would be great if there were more PL heavyweights in the D community
(as you mention there are in Scala), but D's community is in large part
young and enthusiastic, and that's an asset. Possibly some of the young
students using D will become PL experts themselves and help improve it.
(Unlike you, I think that by and large there is no hatred or shunning of
the ivory tower.) Among other things, it would be great if you yourself
hung out more around here. It's a risky proposition, but I guess it's a
simple fact that you have a better chance at making a vital contribution
to D than to Scala.
About unifying FP and OOP, I hope you can educate me a bit. My
understanding from a cursory search is that Scala does not have true
immutability and purity, only Java-style by-convention immutability a la
String class. Is that correct? If that's the case, I think Scala got the
syntactic sugar part of FP right (pattern matching) but not the purity
and immutability aspects, which I believe are much more important. These
aspects are related to concurrency as well, where I think Scala has a
distinctly underwhelming lineup. Even with what we know we can implement
now in D concurrency-wise, we'll be in better shape than many (most?
all?) other languages. Stay tuned.
I agree that D could improve its type deduction - it doesn't even do
Hindley-Milner. (Incidentally, you chose a particularly poor example
regarding the type of array literals - those are very easy to type
properly (and in fact I do so with a library function), but Walter
insisted that typing by the first member is simple enough for people to
understand and remember.) I'm afraid D's type deduction abilities will
stay at about this level at least for D2. The good news is that, due to
templates' deferred typechecking, I haven't found that to be a huge
problem in practice.
Andrei
Andrei Alexandrescu Wrote:
Jari-Matti Mäkelä wrote:
bearophile wrote:
As Sing# (http://en.wikipedia.org/wiki/Sing_sharp ) and Chapel, Scala is
one of the languages to be followed more, because they share some of
future purposes of D2/D3.
A small presentation about the close future of Scala (it's not a general
introduction to Scala): "Scala -- The Next 5 Years" by Martin Odersky:
http://www.scala-lang.org/sites/default/files/odersky/scalaliftoff2009.pdf
Scala is an impressive language and overall well designed. There are
certainly truckloads of features that could be taken from Scala to D. But
I'm afraid that the desire to have familiarity and compatibility with the
C/C++ family is more important in this community than cool new functional
features. Here's a quick comparison of some factors:
You are making very good points, thanks for an insightful post. A few of
them are slightly inaccurate, but those were discussed by Walter
already. I'd like to make a few high-level comments.
I find the lack of rigor in certain parts of D as damaging as you do.
Fortunately, that has improved by leaps and bounds and is still
improving. When I joined Walter with working on D back in 2006, D was
quite a lot less theoretically-motivated - it was all greasy nuts and
bolts and pegs hammered in place. There was a tacit agreement between
Walter and me that D will improve the rigor of its ways, and indeed we
have made strides in that respect. If things work out properly, we'll be
able to define SafeD - a proper, checkable safe subset of the language.
That's great to hear.
It would be great if there were more PL heavyweights in the D community
(as you mention there are in Scala), but D's community is in large part
young and enthusiastic, and that's an asset. Possibly some of the young
students using D will become PL experts themselves and help improve it.
That's more likely. I can see why the approach doesn't attract PL post-grad
students, but that's not necessarily a huge problem.
(Unlike you, I think that by and large there is no hatred or shunning of
the ivory tower.)
I've experienced this kind of attitude in the D's irc channel and sometimes
here on the newsgroup. It's quite understandable that since D consists of so
many heterogenic features, different kinds of aspects motivate us. To me the
coherent "user interface" of the language and its semantics are one of the
appealing sides, but for some other people things like backend optimizations
and compatibility with existing C/C++ libraries matters more and e.g. rigorous
language semantics are just bikeshedding.
I have little problem reading or writing code written in a cryptic unorthogonal
language - on the contrary I sometimes find it an exciting way of spending
time. But when I sometimes suggest some feature or change in semantics, my goal
is to make the language easier to use for all of us.
Among other things, it would be great if you yourself
hung out more around here. It's a risky proposition, but I guess it's a
simple fact that you have a better chance at making a vital contribution
to D than to Scala.
I do hang out here, have done so since 2003. And I have some hopes that D
becomes useful for me again. I've liked the direction D2 is heading towards,
and once the largest problems have been ironed out, I might actually start
using it (or D3), and I'm sure there are others who will do the same.
About unifying FP and OOP, I hope you can educate me a bit. My
understanding from a cursory search is that Scala does not have true
immutability and purity, only Java-style by-convention immutability a la
String class.
It doesn't have a system similar to what D2 has, but the Java-style
immutability is used to provide e.g. immutable collections. I'm expecting a
change here later when the concurrency becomes a larger issue (it should be
already, but you only have so much time!). I've done some research on
concurrency issues lately and it seems to me that there are so many
computational models to choose from that in some sense it might be too early to
stick with one.
Is that correct? If that's the case, I think Scala got the
syntactic sugar part of FP right (pattern matching) but not the purity
and immutability aspects, which I believe are much more important.
Agreed, it's not a pure functional language. In fact the functional feel is
quite different from the old school functional languages.
I agree that D could improve its type deduction - it doesn't even do
Hindley-Milner. (Incidentally, you chose a particularly poor example
regarding the type of array literals - those are very easy to type
properly (and in fact I do so with a library function), but Walter
insisted that typing by the first member is simple enough for people to
understand and remember.) I'm afraid D's type deduction abilities will
stay at about this level at least for D2. The good news is that, due to
templates' deferred typechecking, I haven't found that to be a huge
problem in practice.
Yea, I did some other tests and it really seems the type inference has gotten
much better. It just felt dishonest to claim something without providing
examples. I expected more problems, but was happy to see that many cases indeed
worked now.
On Tue, Aug 25, 2009 at 11:47 AM, Andrei
Alexandrescu<SeeWebsiteForEmail erdani.org> wrote:
Walter Bright wrote:
Especially the array literal type inference is really naive.
How should it be done?
You shouldn't use the type of the first given element when constructing
the type of the array. If you have [ e_1, ..., e_n ], the type of the
literal is
unify(type_of_e_1, ..., type_of_e_n) + "[]". For instance:
=3D> typeof([ [], [1,2,3] ])
=3D> unify( typeof([]), typeof([1,2,3]) ) + "[]"
=3D> unify( "a[]", unify(typeof(1),typeof(2),typeof(3)) + "[]" ) + "[]"
=3D> unify( "a[]", unify("int","int","int") + "[]" ) + "[]"
=3D> unify( "a[]", "int" + "[]" ) + "[]"
=3D> unify( "a[]", "int[]" ) + "[]" =A0 // a is a local type var, subst=
-> int }
=3D> "int[]" + "[]"
=3D> "int[][]"
Ok.
Walter: I told you :o).
I'd already defined the unify meta-function, it's called CommonType, see
http://www.digitalmars.com/d/2.0/phobos/std_traits.html#CommonType
You pass any number of types and it will figure out the type that all typ=
can be converted to. Using that, it is trivial to define functions that
infer array types properly. At a point I had an array() function that too=
any number of arguments and returned a correctly-typed array. Then I drop=
that and defined array() in std with a different meaning (transform a ran=
into an array).
That's also the rule used by NumPy. I found D's array behavior very surpri=
sing.
--bb
Op Wed, 26 Aug 2009 02:04:18 +0200 schreef bearophile
<bearophileHUGS lycos.com>:
Note: LTO isn't done automatically yet by LDC, so to do it you have to
input 3 different commands.
Ask (to me, for example) if you want to know them.
Well I do :-)
|
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C & C++
DMDScript
bearophile <bearophileHUGS lycos.com> 