Generator/Exponential

Generator/Exponential
You are encouraged to solve this task according to the task description, using any language you may know.

A generator is an executable entity (like a function or procedure) that contains code that yields a sequence of values, one at a time, so that each time you call the generator, the next value in the sequence is provided.

Generators are often built on top of coroutines or objects so that the internal state of the object is handled “naturally”.

Generators are often used in situations where a sequence is potentially infinite, and where it is possible to construct the next value of the sequence with only minimal state.

• Create a function that returns a generation of the m'th powers of the positive integers starting from zero, in order, and without obvious or simple upper limit. (Any upper limit to the generator should not be stated in the source but should be down to factors such as the languages natural integer size limit or computational time/size).
• Use it to create a generator of:
•   Squares.
•   Cubes.
• Create a new generator that filters all cubes from the generator of squares.
• Drop the first 20 values from this last generator of filtered results, and then show the next 10 values.

Note that this task requires the use of generators in the calculation of the result.

Also see

To modify the internal state, the function uses an access parameter. For a different approach, see the Random packages of the Ada compiler, which use the so-called "Rosen trick". With the next release of Ada 2012 functions are allowed to have in-out parameters, which would solve this problem, too. You could also use procedures instead of functions.

`package Generator is    type Generator is tagged private;   procedure Reset (Gen : in out Generator);   function Get_Next (Gen : access Generator) return Natural;    type Generator_Function is access function (X : Natural) return Natural;   procedure Set_Generator_Function (Gen  : in out Generator;                                     Func : Generator_Function);    procedure Skip (Gen : access Generator'Class; Count : Positive := 1); private    function Identity (X : Natural) return Natural;    type Generator is tagged record      Last_Source : Natural := 0;      Last_Value  : Natural := 0;      Gen_Func    : Generator_Function := Identity'Access;   end record; end Generator;`

`package Generator.Filtered is    type Filtered_Generator is new Generator with private;   procedure Reset (Gen : in out Filtered_Generator);   function Get_Next (Gen : access Filtered_Generator) return Natural;    procedure Set_Source (Gen    : in out Filtered_Generator;                         Source : access Generator);   procedure Set_Filter (Gen    : in out Filtered_Generator;                         Filter : access Generator); private    type Filtered_Generator is new Generator with record      Last_Filter : Natural := 0;      Source, Filter : access Generator;   end record; end Generator.Filtered;`

`package body Generator is    --------------   -- Identity --   --------------    function Identity (X : Natural) return Natural is   begin      return X;   end Identity;    ----------   -- Skip --   ----------    procedure Skip (Gen : access Generator'Class; Count : Positive := 1) is      Val : Natural;      pragma Unreferenced (Val);   begin      for I in 1 .. Count loop         Val := Gen.Get_Next;      end loop;   end Skip;    -----------   -- Reset --   -----------    procedure Reset (Gen : in out Generator) is   begin      Gen.Last_Source := 0;      Gen.Last_Value := 0;   end Reset;    --------------   -- Get_Next --   --------------    function Get_Next (Gen : access Generator) return Natural is   begin      Gen.Last_Source := Gen.Last_Source + 1;      Gen.Last_Value := Gen.Gen_Func (Gen.Last_Source);      return Gen.Last_Value;   end Get_Next;    ----------------------------   -- Set_Generator_Function --   ----------------------------    procedure Set_Generator_Function     (Gen  : in out Generator;      Func : Generator_Function)   is   begin      if Func = null then         Gen.Gen_Func := Identity'Access;      else         Gen.Gen_Func := Func;      end if;   end Set_Generator_Function; end Generator;`

`package body Generator.Filtered is    -----------   -- Reset --   -----------    procedure Reset (Gen : in out Filtered_Generator) is   begin      Reset (Generator (Gen));      Gen.Source.Reset;      Gen.Filter.Reset;      Gen.Last_Filter := 0;   end Reset;    --------------   -- Get_Next --   --------------    function Get_Next (Gen : access Filtered_Generator) return Natural is      Next_Source : Natural := Gen.Source.Get_Next;      Next_Filter : Natural := Gen.Last_Filter;   begin      loop         if Next_Source > Next_Filter then            Gen.Last_Filter := Gen.Filter.Get_Next;            Next_Filter := Gen.Last_Filter;         elsif Next_Source = Next_Filter then            Next_Source := Gen.Source.Get_Next;         else            return Next_Source;         end if;      end loop;   end Get_Next;    ----------------   -- Set_Source --   ----------------    procedure Set_Source     (Gen    : in out Filtered_Generator;      Source : access Generator)   is   begin      Gen.Source := Source;   end Set_Source;    ----------------   -- Set_Filter --   ----------------    procedure Set_Filter     (Gen    : in out Filtered_Generator;      Filter : access Generator)   is   begin      Gen.Filter := Filter;   end Set_Filter; end Generator.Filtered;`

example use:

`with Ada.Text_IO;with Generator.Filtered; procedure Generator_Test is    function Square (X : Natural) return Natural is   begin      return X * X;   end Square;    function Cube (X : Natural) return Natural is   begin      return X * X * X;   end Cube;    G1, G2 : aliased Generator.Generator;   F : aliased Generator.Filtered.Filtered_Generator; begin    G1.Set_Generator_Function (Func => Square'Unrestricted_Access);   G2.Set_Generator_Function (Func => Cube'Unrestricted_Access);    F.Set_Source (G1'Unrestricted_Access);   F.Set_Filter (G2'Unrestricted_Access);    F.Skip (20);    for I in 1 .. 10 loop      Ada.Text_IO.Put ("I:" & Integer'Image (I));      Ada.Text_IO.Put (", F:" & Integer'Image (F.Get_Next));      Ada.Text_IO.New_Line;   end loop; end Generator_Test;`
Output:
```I: 1, F: 529
I: 2, F: 576
I: 3, F: 625
I: 4, F: 676
I: 5, F: 784
I: 6, F: 841
I: 7, F: 900
I: 8, F: 961
I: 9, F: 1024
I: 10, F: 1089```

AppleScript

Composable generators can be constructed from the methods and persistent properties of script objects:

Translation of: JavaScript
Translation of: Python
`-- powers :: Gen [Int]on powers(n)    script f        on |λ|(x)            x ^ n as integer        end |λ|    end script    fmapGen(f, enumFrom(0))end powers  -- TEST ---------------------------------------------------on run    take(10, ¬        drop(20, ¬            differenceGen(powers(2), powers(3))))     --> {529, 576, 625, 676, 784, 841, 900, 961, 1024, 1089}end run  -- GENERIC ------------------------------------------------ -- Just :: a -> Maybe aon Just(x)    {type:"Maybe", Nothing:false, Just:x}end Just -- Nothing :: Maybe aon Nothing()    {type:"Maybe", Nothing:true}end Nothing -- Tuple (,) :: a -> b -> (a, b)on Tuple(a, b)    {type:"Tuple", |1|:a, |2|:b, length:2}end Tuple  -- differenceGen :: Gen [a] -> Gen [a] -> Gen [a]on differenceGen(ga, gb)    -- All values of ga except any    -- already seen in gb.    script        property g : zipGen(ga, gb)        property bs : {}        property xy : missing value        on |λ|()            set xy to g's |λ|()            if missing value is xy then                xy            else                set x to |1| of xy                set y to |2| of xy                set bs to {y} & bs                if bs contains x then                    |λ|() -- Next in series.                else                    x                end if            end if        end |λ|    end scriptend differenceGen  -- drop :: Int -> [a] -> [a]-- drop :: Int -> String -> Stringon drop(n, xs)    set c to class of xs    if script is not c then        if string is not c then            if n < length of xs then                items (1 + n) thru -1 of xs            else                {}            end if        else            if n < length of xs then                text (1 + n) thru -1 of xs            else                ""            end if        end if    else        take(n, xs) -- consumed        return xs    end ifend drop  -- enumFrom :: Int -> [Int]on enumFrom(x)    script        property v : missing value        on |λ|()            if missing value is not v then                set v to 1 + v            else                set v to x            end if            return v        end |λ|    end scriptend enumFrom  -- fmapGen <\$> :: (a -> b) -> Gen [a] -> Gen [b]on fmapGen(f, gen)    script        property g : mReturn(f)        on |λ|()            set v to gen's |λ|()            if v is missing value then                v            else                g's |λ|(v)            end if        end |λ|    end scriptend fmapGen  -- length :: [a] -> Inton |length|(xs)    set c to class of xs    if list is c or string is c then        length of xs    else        (2 ^ 29 - 1) -- (maxInt - simple proxy for non-finite)    end ifend |length|  -- Lift 2nd class handler function into 1st class script wrapper -- mReturn :: First-class m => (a -> b) -> m (a -> b)on mReturn(f)    if script is class of f then        f    else        script            property |λ| : f        end script    end ifend mReturn  -- take :: Int -> [a] -> [a]-- take :: Int -> String -> Stringon take(n, xs)    set c to class of xs    if list is c then        if 0 < n then            items 1 thru min(n, length of xs) of xs        else            {}        end if    else if string is c then        if 0 < n then            text 1 thru min(n, length of xs) of xs        else            ""        end if    else if script is c then        set ys to {}        repeat with i from 1 to n            set v to xs's |λ|()            if missing value is v then                return ys            else                set end of ys to v            end if        end repeat        return ys    else        missing value    end ifend take  -- uncons :: [a] -> Maybe (a, [a])on uncons(xs)    set lng to |length|(xs)    if 0 = lng then        Nothing()    else        if (2 ^ 29 - 1) as integer > lng then            if class of xs is string then                set cs to text items of xs                Just(Tuple(item 1 of cs, rest of cs))            else                Just(Tuple(item 1 of xs, rest of xs))            end if        else            set nxt to take(1, xs)            if {} is nxt then                Nothing()            else                Just(Tuple(item 1 of nxt, xs))            end if        end if    end ifend uncons  -- zipGen :: Gen [a] -> Gen [b] -> Gen [(a, b)]on zipGen(ga, gb)    script        property ma : missing value        property mb : missing value        on |λ|()            if missing value is ma then                set ma to uncons(ga)                set mb to uncons(gb)            end if            if Nothing of ma or Nothing of mb then                missing value            else                set ta to Just of ma                set tb to Just of mb                set x to Tuple(|1| of ta, |1| of tb)                set ma to uncons(|2| of ta)                set mb to uncons(|2| of tb)                return x            end if        end |λ|    end scriptend zipGen`
Output:
`{529, 576, 625, 676, 784, 841, 900, 961, 1024, 1089}`

ALGOL 68

Translation of: Python
Works with: ALGOL 68 version Revision 1 - with currying of functions and PRAGMA READ extensions
Works with: ALGOL 68G version Any - tested with release algol68g-2.3.5.
File: Template.Generator.a68
`MODE YIELDVALUE = PROC(VALUE)VOID;MODE GENVALUE = PROC(YIELDVALUE)VOID; PROC gen filtered = (GENVALUE gen candidate, gen exclude, YIELDVALUE yield)VOID: (    VALUE candidate; SEMA have next exclude = LEVEL 0;    VALUE exclude;   SEMA get next exclude  = LEVEL 0;    BOOL initialise exclude := TRUE;     PAR ( # run each generator in a different thread ## Thread 1 #      # FOR VALUE next exclude IN # gen exclude( # ) DO #      ##   (VALUE next exclude)VOID: (            DOWN get next exclude; exclude := next exclude;            IF candidate <= exclude THEN                UP have next exclude            ELSE                UP get next exclude            FI      # OD #)),# Thread 2 #      # FOR VALUE next candidate IN # gen candidate( # ) DO #      ##   (VALUE next candidate)VOID: (            candidate := next candidate;            IF initialise exclude ORF candidate > exclude THEN                UP get next exclude;                DOWN have next exclude; # wait for result #                initialise exclude := FALSE            FI;            IF candidate < exclude THEN                yield(candidate)            FI      # OD #))    )); PROC gen slice = (GENVALUE t, VALUE start, stop, YIELDVALUE yield)VOID: (  INT index := 0;  # FOR VALUE i IN # t( # ) DO #  ##   (VALUE i)VOID: (      IF   index >= stop THEN done      ELIF index >= start THEN yield(i) FI;      index +:= 1  # OD # ));    done: SKIP); PROC get list = (GENVALUE gen)[]VALUE: (    INT upb := 0;    INT ups := 2;    FLEX [ups]VALUE out;  # FOR VALUE i IN # gen( # ) DO #  ##   (VALUE i)VOID:(        upb +:= 1;        IF upb > ups THEN # dynamically grow the array 50% #          [ups +:= ups OVER 2]VALUE append; append[:upb-1] := out; out := append        FI;        out[upb] := i  # OD # ))    out[:upb]); PROC powers = (VALUE m, YIELDVALUE yield)VOID:    FOR n FROM 0 DO yield(n ** m) OD;`
File: test.Generator.a68
`#!/usr/local/bin/a68g --script # MODE VALUE = INT;PR READ "Template.Generator.a68" PR GENVALUE squares = powers(2,), cubes = powers(3,);GENVALUE fil = gen filtered(squares, cubes,); printf((\$g(0)x\$, get list(gen slice(fil, 20, 30, )) ))`
Output:
```529 576 625 676 784 841 900 961 1024 1089
```

C

Library: libco

libco is a tiny library that adds cooperative multithreading, also known as coroutines, to the C language. Its co_switch(x) function pauses the current cothread and resumes the other cothread x.

This example provides next64() and yield64(), to generate 64-bit integers. next64() switches to a generator. Then the generator passes some 64-bit integer to yield64(), which switches to the first cothread, where next64() returns this 64-bit integer.

`#include <inttypes.h>	/* int64_t, PRId64 */#include <stdlib.h>	/* exit() */#include <stdio.h>	/* printf() */ #include <libco.h>	/* co_{active,create,delete,switch}() */   /* A generator that yields values of type int64_t. */struct gen64 {	cothread_t giver;	/* this cothread calls yield64() */	cothread_t taker;	/* this cothread calls next64() */	int64_t given;	void (*free)(struct gen64 *);	void *garbage;}; /* Yields a value. */inline voidyield64(struct gen64 *gen, int64_t value){	gen->given = value;	co_switch(gen->taker);} /* Returns the next value that the generator yields. */inline int64_tnext64(struct gen64 *gen){	gen->taker = co_active();	co_switch(gen->giver);	return gen->given;} static voidgen64_free(struct gen64 *gen){	co_delete(gen->giver);} struct gen64 *entry64; /* * Creates a cothread for the generator. The first call to next64(gen) * will enter the cothread; the entry function must copy the pointer * from the global variable struct gen64 *entry64. * * Use gen->free(gen) to free the cothread. */inline voidgen64_init(struct gen64 *gen, void (*entry)(void)){	if ((gen->giver = co_create(4096, entry)) == NULL) {		/* Perhaps malloc() failed */		fputs("co_create: Cannot create cothread\n", stderr);		exit(1);	}	gen->free = gen64_free;	entry64 = gen;}   /* * Generates the powers 0**m, 1**m, 2**m, .... */voidpowers(struct gen64 *gen, int64_t m){	int64_t base, exponent, n, result; 	for (n = 0;; n++) {		/*		 * This computes result = base**exponent, where		 * exponent is a nonnegative integer. The result		 * is the product of repeated squares of base.		 */		base = n;		exponent = m;		for (result = 1; exponent != 0; exponent >>= 1) {			if (exponent & 1) result *= base;			base *= base;		}		yield64(gen, result);	}	/* NOTREACHED */} /* stuff for squares_without_cubes() */#define ENTRY(name, code) static void name(void) { code; }ENTRY(enter_squares, powers(entry64, 2))ENTRY(enter_cubes, powers(entry64, 3)) struct swc {	struct gen64 cubes;	struct gen64 squares;	void (*old_free)(struct gen64 *);}; static voidswc_free(struct gen64 *gen){	struct swc *f = gen->garbage;	f->cubes.free(&f->cubes);	f->squares.free(&f->squares);	f->old_free(gen);} /* * Generates the squares 0**2, 1**2, 2**2, ..., but removes the squares * that equal the cubes 0**3, 1**3, 2**3, .... */voidsquares_without_cubes(struct gen64 *gen){	struct swc f;	int64_t c, s; 	gen64_init(&f.cubes, enter_cubes);	c = next64(&f.cubes); 	gen64_init(&f.squares, enter_squares);	s = next64(&f.squares); 	/* Allow other cothread to free this generator. */	f.old_free = gen->free;	gen->garbage = &f;	gen->free = swc_free; 	for (;;) {		while (c < s)			c = next64(&f.cubes);		if (c != s)			yield64(gen, s);		s = next64(&f.squares);	}	/* NOTREACHED */} ENTRY(enter_squares_without_cubes, squares_without_cubes(entry64)) /* * Look at the sequence of numbers that are squares but not cubes. * Drop the first 20 numbers, then print the next 10 numbers. */intmain(){	struct gen64 gen;	int i; 	gen64_init(&gen, enter_squares_without_cubes); 	for (i = 0; i < 20; i++)		next64(&gen);	for (i = 0; i < 9; i++)		printf("%" PRId64 ", ", next64(&gen));	printf("%" PRId64 "\n", next64(&gen)); 	gen.free(&gen); /* Free memory. */	return 0;}`

```\$ libco=/home/kernigh/park/libco
\$ cc -I\$libco -o main main.c \$libco/libco.c
\$ ./main
529, 576, 625, 676, 784, 841, 900, 961, 1024, 1089```

Using struct to store state

`#include <stdio.h>#include <stdlib.h>#include <math.h> typedef int (*seq_func)(void *);#define SEQ_BASE seq_func f; int output /* sort of polymorphing data structure */typedef struct { SEQ_BASE; } gen_t; int seq_next(void *state){	return ((gen_t*)state)->output = (*(seq_func*)state)(state);} typedef struct {	SEQ_BASE;	int pos, n;} power_gen_t; int power_next(void *s){	return (int)pow(++((power_gen_t*)s)->pos, ((power_gen_t*)s)->n);} void *power_seq(int n){	power_gen_t *s = malloc(sizeof(power_gen_t));	s->output = -1;	s->f = power_next;	s->n = n;	s->pos = -1;	return s;} typedef struct {	SEQ_BASE;	void *in, *without;} filter_gen_t; int filter_next(void *s){	gen_t *in = ((filter_gen_t*)s)->in, *wo = ((filter_gen_t*)s)->without; 	do{		seq_next(in);		while (wo->output < in->output)			seq_next(wo);	} while(wo->output == in->output); 	return in->output;} void* filter_seq(gen_t *in, gen_t *without){	filter_gen_t *filt = malloc(sizeof(filter_gen_t));	filt->in = in;	filt->without = without;	filt->f = filter_next;	filt->output = -1;	return filt;} int main(){	int i;	void *s = filter_seq(power_seq(2), power_seq(3)); 	for (i = 0; i < 20; i++) seq_next(s);	for (i = 0; i < 10; i++)		printf("%d\n", seq_next(s)); 	return 0;}`
Output:
```529
576
625
676
784
841
900
961
1024

1089```

C++

A templated solution.

`#include <iostream>using namespace std; template<class T>class Generator{public:  virtual T operator()() = 0;}; // Does nothing unspecializedtemplate<class T, T P>class PowersGenerator: Generator<T> {}; // Specialize with other types, or provide a generic version of powtemplate<int P>class PowersGenerator<int, P>: Generator<int>{public:  int i;  PowersGenerator() { i = 1; }  virtual int operator()()   {     int o = 1;     for(int j = 0; j < P; ++j) o *= i;     ++i;    return o;   }}; // Only works with non-decreasing generatorstemplate<class T, class G, class F>class Filter: Generator<T>{public:  G gen;  F filter;  T lastG, lastF;   Filter() { lastG = gen(); lastF = filter(); }   virtual T operator()()   {    while(lastG >= lastF)    {      if(lastG == lastF)        lastG = gen();      lastF = filter();    }     T out = lastG;    lastG = gen();    return out;  }}; int main(){  Filter<int, PowersGenerator<int, 2>, PowersGenerator<int, 3>> gen;   for(int i = 0; i < 20; ++i)    gen();   for(int i = 20; i < 30; ++i)    cout << i << ": " << gen() << endl;}`
Output:
```20: 529
21: 576
22: 625
23: 676
24: 784
25: 841
26: 900
27: 961
28: 1024
29: 1089
```

C#

`using System;using System.Collections.Generic;using System.Linq; static class Program {    static void Main() {        Func<int, IEnumerable<int>> ms = m => Infinite().Select(i => (int)Math.Pow(i, m));        var squares = ms(2);        var cubes = ms(3);        var filtered = squares.Where(square => cubes.First(cube => cube >= square) != square);        var final = filtered.Skip(20).Take(10);        foreach (var i in final) Console.WriteLine(i);    }     static IEnumerable<int> Infinite() {        var i = 0;        while (true) yield return i++;    }}`

Clojure

In Clojure, the role that generator functions take in some other languages is generally filled by sequences. Most of the functions that produce sequences produce lazy sequences, many of the standard functions deal with sequences, and their use in Clojure is extremely idiomatic. Thus we can define squares and cubes as lazy sequences:

`(defn powers [m] (for [n (iterate inc 1)] (reduce * (repeat m n)))))(def squares (powers 2))(take 5 squares) ; => (1 4 9 16 25)`

The definition here of the squares-not-cubes lazy sequence uses the loop/recur construct, which isn't lazy. So we use lazy-seq explicity:

`(defn squares-not-cubes   ([] (squares-not-cubes (powers 2) (powers 3)))  ([squares cubes]     (loop [[p2first & p2rest :as p2s] squares, [p3first & p3rest :as p3s] cubes]      (cond        (= p2first p3first) (recur p2rest p3rest)        (> p2first p3first) (recur p2s p3rest)        :else (cons p2first (lazy-seq (squares-not-cubes p2rest p3s))))))) (->> (squares-not-cubes) (drop 20) (take 10)); => (529 576 625 676 784 841 900 961 1024 1089)`

If we really need a generator function for some reason, any lazy sequence can be turned into a stateful function. (The inverse of seq->fn is the standard function repeatedly.)

`(defn seq->fn [sequence]  (let [state (atom (cons nil sequence))]    (fn [] (first (swap! state rest))) (def f (seq->fn (squares-not-cubes)))[(f) (f) (f)] ; => [4 9 16]`

Common Lisp

`(defun take (seq &optional (n 1))  (values-list (loop repeat n collect (funcall seq)))) (defun power-seq (n)  (let ((x 0))    (lambda () (expt (incf x) n)))) (defun filter-seq (s1 s2) ;; remove s2 from s1  (let ((x1 (take s1)) (x2 (take s2)))    (lambda ()      (tagbody g	(if (= x1 x2)	     (progn (setf x1 (take s1) x2 (take s2)) (go g)))	(if (> x1 x2)	     (progn (setf x2 (take s2)) (go g))))       (prog1 x1 (setf x1 (take s1)))))) (let ((2not3 (filter-seq (power-seq 2) (power-seq 3))))  (take 2not3 20) ;; drop 20  (princ (multiple-value-list (take 2not3 10))))`

D

Efficient Standard Version

`void main() {    import std.stdio, std.bigint, std.range, std.algorithm;     auto squares = 0.sequence!"n".map!(i => i.BigInt ^^ 2);    auto cubes = 0.sequence!"n".map!(i => i.BigInt ^^ 3);     squares.setDifference(cubes).drop(20).take(10).writeln;}`
Output:
`[529, 576, 625, 676, 784, 841, 900, 961, 1024, 1089]`

Simple Ranges-Based Implementation

Translation of: C#
`void main() {    import std.stdio, std.bigint, std.range, std.algorithm;     auto squares = 0.sequence!"n".map!(i => i.BigInt ^^ 2);    auto cubes = 0.sequence!"n".map!(i => i.BigInt ^^ 3);     squares    .filter!(s => cubes.find!(c => c >= s).front != s)    .drop(20)    .take(10)    .writeln;}`

The output is the same.

More Efficient Ranges-Based Version

`import std.stdio, std.bigint, std.range, std.algorithm; struct Filtered(R1, R2) if (is(ElementType!R1 == ElementType!R2)) {    R1 s1;    R2 s2;    alias ElementType!R1 T;    T front, source, filter;     this(R1 r1, R2 r2) {        s1 = r1;        s2 = r2;        source = s1.front;        filter = s2.front;        popFront;    }     static immutable empty = false;     void popFront() {        while (true) {            if (source > filter) {                s2.popFront;                filter = s2.front;                continue;            } else if (source < filter) {                front = source;                s1.popFront;                source = s1.front;                break;            }            s1.popFront;            source = s1.front;        }    }} auto filtered(R1, R2)(R1 r1, R2 r2) // Helper function.if (isInputRange!R1 && isInputRange!R2 &&    is(ElementType!R1 == ElementType!R2)) {    return Filtered!(R1, R2)(r1, r2);} void main() {    auto squares = 0.sequence!"n".map!(i => i.BigInt ^^ 2);    auto cubes = 0.sequence!"n".map!(i => i.BigInt ^^ 3);    filtered(squares, cubes).drop(20).take(10).writeln;}`

The output is the same.

Closures-Based Version

Translation of: Go
`import std.stdio; auto powers(in double e) pure nothrow {    double i = 0;    return () => i++ ^^ e;} auto filter2(D)(D af, D bf) {    double a = af(), b = bf();     return {        double r;        while (true) {            if (a < b) {                r = a;                a = af();                break;            }            if (b == a)                a = af();            b = bf();        }        return r;    };} void main() {    auto fgen = filter2(2.powers, 3.powers);    foreach (immutable i; 0 .. 20)        fgen();    foreach (immutable i; 0 .. 10)        write(fgen(), " ");    writeln;}`
Output:
`529 576 625 676 784 841 900 961 1024 1089 `

Generator Range Version

`import std.stdio, std.range, std.algorithm, std.concurrency, std.bigint; auto powers(in uint m) pure nothrow @safe {    return 0.sequence!"n".map!(i => i.BigInt ^^ m);} auto filtered(R1, R2)(R1 r1, R2 r2) /*@safe*/if (isForwardRange!R1 && isForwardRange!R2 &&    is(ElementType!R1 == ElementType!R2)) {    return new Generator!(ElementType!R1)({        auto v = r1.front; r1.popFront;        auto f = r2.front; r2.popFront;         while (true) {            if (v > f) {                f = r2.front; r2.popFront;                continue;            } else if (v < f)                yield(v);            v = r1.front; r1.popFront;        }    });} void main() {    auto squares = 2.powers, cubes = 3.powers;    filtered(squares, cubes).drop(20).take(10).writeln;}`
Output:
`[529, 576, 625, 676, 784, 841, 900, 961, 1024, 1089]`

E

E does not provide coroutines on the principle that interleaving of execution of code should be explicit to avoid unexpected interactions. However, this problem does not especially require them. Each generator here is simply a function that returns the next value in the sequence when called.

`def genPowers(exponent) {    var i := -1    return def powerGenerator() {        return (i += 1) ** exponent    }} def filtered(source, filter) {    var fval := filter()    return def filterGenerator() {        while (true) {            def sval := source()            while (sval > fval) {                fval := filter()            }            if (sval < fval) {                return sval            }        }    }} def drop(n, gen) {    for _ in 1..n { gen() }}  def squares := genPowers(2)def cubes := genPowers(3)def squaresNotCubes := filtered(squares, cubes)drop(20, squaresNotCubes)for _ in 1..10 {    print(`\${squaresNotCubes()} `)}println()`

EchoLisp

` (lib 'tasks) ;; for make-generator ;; generator of generators(define (gen-power power)	(make-generator		(lambda(n) (yield (expt n power)) (1+ n))  1)) (define powers-2 (gen-power 2))(define powers-3 (gen-power 3)) (take powers-3 10)    → (1 8 27 64 125 216 343 512 729 1000) ;; generators substraction;; input : two generators ga, gb - Sequences must be increasing;; output : new generator  = ga sequence minus gb sequence (define (gen-substract ga gb)	(define (substract b (a))	(set! a (next ga))	(while (>= a b) ; avance b until > a		(when (= a b) (set! a (next ga)))		(set! b (next gb)))	(yield a)	b ) ;; b := next state	(make-generator substract (next gb))) ;; application(define task    (gen-substract (gen-power 2) (gen-power 3))) (drop task 20) (take task 10)    → (529 576 625 676 784 841 900 961 1024 1089) ; inspecttask → #generator:state: 1331 `

Elixir

Translation of: Erlang
`defmodule Generator do  def filter( source_pid, remove_pid ) do    first_remove = next( remove_pid )    spawn( fn -> filter_loop(source_pid, remove_pid, first_remove) end )  end   def next( pid ) do    send(pid, {:next, self})    receive do      x -> x    end  end   def power( m ), do: spawn( fn -> power_loop(m, 0) end )   def task do    squares_pid = power( 2 )    cubes_pid = power( 3 )    filter_pid = filter( squares_pid, cubes_pid )    for _x <- 1..20, do: next(filter_pid)    for _x <- 1..10, do: next(filter_pid)  end   defp filter_loop( pid1, pid2, n2 ) do    receive do      {:next, pid} ->        {n, new_n2} = filter_loop_next( next(pid1), n2, pid1, pid2 )        send( pid, n )        filter_loop( pid1, pid2, new_n2 )    end  end   defp filter_loop_next( n1, n2, pid1, pid2 ) when n1 > n2, do:       filter_loop_next( n1, next(pid2), pid1, pid2 )  defp filter_loop_next( n, n, pid1, pid2 ), do:       filter_loop_next( next(pid1), next(pid2), pid1, pid2 )  defp filter_loop_next( n1, n2, _pid1, _pid2 ), do: {n1, n2}   defp power_loop( m, n ) do    receive do      {:next, pid} -> send( pid, round(:math.pow(n, m) ) )    end    power_loop( m, n + 1 )  endend IO.inspect Generator.task`
Output:
```[529, 576, 625, 676, 784, 841, 900, 961, 1024, 1089]
```

Emacs Lisp

This code requires generator library which was introduced in Emacs 25.2

` (require 'generator)(setq lexical-binding t) (iter-defun exp-gen (pow)  (let ((i -1))    (while      (setq i (1+ i))      (iter-yield (expt i pow))))) (iter-defun flt-gen ()  (let* ((g (exp-gen 2))	 (f (exp-gen 3))	 (i (iter-next g))	 (j (iter-next f)))    (while      (setq i (iter-next g))      (while (> i j)	(setq j (iter-next f)))      (unless (= i j)	(iter-yield i)))))  (let ((g (flt-gen))      (o 'nil))  (dotimes (i 29)    (setq o (iter-next g))    (when (>= i 20)      (print o))))`

Erlang

` -module( generator ). -export( [filter/2, next/1, power/1, task/0] ). filter(	Source_pid, Remove_pid ) ->	First_remove = next( Remove_pid	),        erlang:spawn( fun() -> filter_loop(Source_pid, Remove_pid, First_remove) end ). next( Pid ) ->    Pid ! {next, erlang:self()},    receive X -> X end. power( M ) -> erlang:spawn( fun() -> power_loop(M, 0) end ). task() ->    Squares_pid = power( 2 ),    Cubes_pid = power( 3 ),    Filter_pid = filter( Squares_pid, Cubes_pid ),    [next(Filter_pid) || _X <- lists:seq(1, 20)],    [next(Filter_pid) || _X <- lists:seq(1, 10)].  filter_loop( Pid1, Pid2, N2 ) ->        receive        {next, Pid} ->	       {N, New_N2} = filter_loop_next( next(Pid1), N2, Pid1, Pid2 ),               Pid ! N        end,        filter_loop( Pid1, Pid2, New_N2 ). filter_loop_next( N1, N2, Pid1, Pid2 ) when N1 > N2 -> filter_loop_next( N1, next(Pid2), Pid1, Pid2 );filter_loop_next( N, N, Pid1, Pid2 ) -> filter_loop_next( next(Pid1), next(Pid2), Pid1, Pid2 );filter_loop_next( N1, N2, _Pid1, _Pid2 ) -> {N1, N2}. power_loop( M, N ) ->        receive	{next, Pid} -> Pid ! erlang:round(math:pow(N, M) ) end,	power_loop( M, N + 1 ). `
Output:
```31> generator:task().
[529,576,625,676,784,841,900,961,1024,1089]
```

F#

Translation of: C#
`let m n = Seq.unfold(fun i -> Some(bigint.Pow(i, n), i + 1I)) 0I let squares = m 2let cubes = m 3 let (--) orig veto = Seq.where(fun n -> n <> (Seq.find(fun m -> m >= n) veto)) orig let ``squares without cubes`` = squares -- cubes Seq.take 10 (Seq.skip 20 (``squares without cubes``))|> Seq.toList |> printfn "%A"`
Output:
`[529; 576; 625; 676; 784; 841; 900; 961; 1024; 1089]`

Factor

Using lazy lists for our generators:

`USING: fry kernel lists lists.lazy math math.functionsprettyprint ;IN: rosetta-code.generator-exponential : mth-powers-generator ( m -- lazy-list )    [ 0 lfrom ] dip [ ^ ] curry lmap-lazy ; : lmember? ( elt list -- ? )    over '[ unswons dup _ >= ] [ drop ] until nip = ; : 2-not-3-generator ( -- lazy-list )    2 mth-powers-generator    [ 3 mth-powers-generator lmember? not ] <lazy-filter> ; 10 2-not-3-generator 20 [ unswons drop ] times ltake list>array.`
Output:
```{ 529 576 625 676 784 841 900 961 1024 1089 }
```

Fantom

Using closures to implement generators.

` class Main{  // Create and return a function which generates mth powers when called  |->Int| make_generator (Int m)  {    current := 0    return |->Int|    {      current += 1      return (current-1).pow (m)    }  }   |->Int| squares_without_cubes ()  {    squares := make_generator (2)    cubes := make_generator (3)    c := cubes.call    return |->Int|    {      while (true)      {        s := squares.call        while (c < s) { c = cubes.call }        if (c != s) return s      }      return 0    }  }   Void main ()  {    swc := squares_without_cubes ()    20.times { swc.call } // drop 20 values    10.times // display the next 10    {      echo (swc.call)    }  }} `
Output:
```529
576
625
676
784
841
900
961
1024
1089
```

Forth

` \ genexp-rcode.fs   Generator/Exponential for RosettaCode.org \ Generator/filter implementation using return stack as continuations stack: ENTER         ( cont.addr --  ;borrowed from M.L.Gasanenko papers)        >R;: |             ( f --  ;true->go ahead, false->return into generator )        IF EXIT THEN R> DROP;: GEN           ( --  ;generate forever what is between 'GEN' and ';' )        BEGIN [email protected] ENTER AGAIN;: STOP          ( f --  ;return to caller of word that contain 'GEN' )        IF R> DROP R> DROP R> DROP THEN; \ Problem at hand: square        ( n -- n^2 )    dup * ;: cube          ( n -- n^3 )    dup square * ; \ Faster tests using info that tested numbers are monotonic growing        VARIABLE Sqroot         \ last square root        VARIABLE Cbroot         \ last cubic  root: square?       ( u -- f  ;test U for square number)        BEGIN                Sqroot @ square over <         WHILE                1 Sqroot +!         REPEAT         Sqroot @ square =;: cube?         ( u -- f  ;test U for cubic  number)        BEGIN                Cbroot @ cube over <        WHILE                1 Cbroot +!        REPEAT        Cbroot @ cube =;        VARIABLE Counter: (go)  ( u -- u' )        GEN 1+ Counter @ 30 >= STOP        dup square? | dup cube? 0= | Counter @ 20 >= 1 Counter +! | dup . ;:noname 0 Counter ! 1 Sqroot ! 1 Cbroot ! 0 (go) drop ;execute cr bye `
Output:
```\$ gforth -e "include genexp-rcode.fs"
529 576 625 676 784 841 900 961 1024 1089
\$
```

FunL

(for the powers function)
Translation of: Scala
(for the filter)
`def powers( m ) = map( (^ m), 0.. ) def  filtered( [email protected]:_, ch:ct ) | sh > ch = filtered( s, ct )  filtered( sh:st, [email protected]:_ ) | sh < ch = sh # filtered( st, c )  filtered( _:st, c ) = filtered( st, c ) println( filtered(powers(2), powers(3)).drop(20).take(10) )`
Output:
```[529, 576, 625, 676, 784, 841, 900, 961, 1024, 1089]
```

Go

Most direct and most efficient on a single core is implementing generators with closures.

`package main import (    "fmt"    "math") // note: exponent not limited to intsfunc newPowGen(e float64) func() float64 {    var i float64    return func() (r float64) {        r = math.Pow(i, e)        i++        return    }} // given two functions af, bf, both monotonically increasing, return a// new function that returns values of af not returned by bf.func newMonoIncA_NotMonoIncB_Gen(af, bf func() float64) func() float64 {    a, b := af(), bf()    return func() (r float64) {        for {            if a < b {                r = a                a = af()                break            }            if b == a {                a = af()            }            b = bf()        }        return    }} func main() {    fGen := newMonoIncA_NotMonoIncB_Gen(newPowGen(2), newPowGen(3))    for i := 0; i < 20; i++ {        fGen()    }    for i := 0; i < 10; i++ {        fmt.Print(fGen(), " ")    }    fmt.Println()}`
Output:
```529 576 625 676 784 841 900 961 1024 1089
```

Alternatively, generators can be implemented in Go with goroutines and channels. There are tradeoffs however, and often one technique is a significantly better choice.

Goroutines can run concurrently, but there is overhead associated with thread scheduling and channel communication. Flow control is also different. A generator implemented as a closure is a function with a single entry point fixed at the beginning. On repeated calls, execution always starts over at the beginning and ends when a value is returned. A generator implemented as a goroutine, on the other hand, "returns" a value by sending it on a channel, and then the goroutine continues execution from that point. This allows more flexibility in structuring code.

`package main import (    "fmt"    "math") func newPowGen(e float64) chan float64 {    ch := make(chan float64)    go func() {        for i := 0.; ; i++ {            ch <- math.Pow(i, e)        }    }()    return ch} // given two input channels, a and b, both known to return monotonically// increasing values, supply on channel c values of a not returned by b.func newMonoIncA_NotMonoIncB_Gen(a, b chan float64) chan float64 {    ch := make(chan float64)    go func() {        for va, vb := <-a, <-b; ; {            switch {            case va < vb:                ch <- va                fallthrough            case va == vb:                va = <-a            default:                vb = <-b             }        }    }()    return ch} func main() {    ch := newMonoIncA_NotMonoIncB_Gen(newPowGen(2), newPowGen(3))    for i := 0; i < 20; i++ {        <-ch    }    for i := 0; i < 10; i++ {        fmt.Print(<-ch, " ")    }    fmt.Println()}`

Generators in most cases can be implemented using infinite lists in Haskell. Because Haskell is lazy, only as many elements as needed is computed from the infinite list:

`import Data.List.Ordered powers :: Int -> [Int]powers m = map (^ m) [0..] squares :: [Int]squares = powers 2 cubes :: [Int]cubes = powers 3 foo :: [Int]foo = filter (not . has cubes) squares main :: IO ()main = print \$ take 10 \$ drop 20 foo`
Output:
`[529,576,625,676,784,841,900,961,1024,1089]`

Icon and Unicon

Generators are close to the heart and soul of Icon/Unicon. Co-expressions let us circumvent the normal backtracking mechanism and get results where we need them.

`procedure main() write("Non-cube Squares (21st to 30th):") every (k := 0, s := noncubesquares()) do    if(k +:= 1) > 30 then break   else write(20 < k," : ",s)  end procedure mthpower(m)   #: generate i^m for i = 0,1,...while (/i := 0) | (i +:= 1) do suspend i^mend procedure noncubesquares()  #: filter for squares that aren't cubescu := create mthpower(3)    # co-expressions so that we can sq := create mthpower(2)    # ... get our results where we need repeat {   if c === s then  ( c := @cu , s := @sq )    else if s > c then c := @cu   else {      suspend s      s := @sq       }   }end`

Note: The task could be written without co-expressions but would be likely be ugly. If there is an elegant non-co-expression version please add it as an alternate example.

Output:
```Non-cube Squares (21st to 30th):
21 : 529
22 : 576
23 : 625
24 : 676
25 : 784
26 : 841
27 : 900
28 : 961
29 : 1024
30 : 1089```

J

Generators are not very natural, in J, because they avoid the use of arrays and instead rely on sequential processing.

Here is a generator for mth powers of a number:

`coclass 'mthPower'  N=: 0  create=: 3 :0    M=: y  )  next=: 3 :0    n=. N    N=: N+1    n^M  )`

And, here are corresponding square and cube generators

`stateySquare=: 2 conew 'mthPower'stateyCube=: 3 conew 'mthPower'`

Here is a generator for squares which are not cubes:

`coclass 'uncubicalSquares'  N=: 0  next=: 3 :0"0    while. (-: <.) 3 %: *: n=. N do. N=: N+1 end. N=: N+1    *: n  )`

And here is an example of its use:

`   next__g i.10 [ next__g i.20 [ g=: conew 'uncubicalSquares'529 576 625 676 784 841 900 961 1024 1089`

That said, here is a more natural approach, for J.

`mthPower=: 1 :'^&[email protected]'squares=: 2 mthPowercubes=: 3 mthPoweruncubicalSquares=: squares -. cubes`

The downside of this approach is that it is computing independent sequences. And for the "uncubicalSquares" verb, it is removing some elements from that sequence. So you must estimate how many values to generate. However, this can be made transparent to the user with a simplistic estimator:

`uncubicalSquares=: {. [email protected]<[email protected]~&3 1.1 -. cubes`

Example use:

`20 }. uncubicalSquares 30 NB. the 21st through 30th uncubical square529 576 625 676 784 841 900 961 1024 1089`

Java

Works with: java version 8
`import java.util.function.LongSupplier;import static java.util.stream.LongStream.generate; public class GeneratorExponential implements LongSupplier {    private LongSupplier source, filter;    private long s, f;     public GeneratorExponential(LongSupplier source, LongSupplier filter) {        this.source = source;        this.filter = filter;        f = filter.getAsLong();    }     @Override    public long getAsLong() {        s = source.getAsLong();         while (s == f) {            s = source.getAsLong();            f = filter.getAsLong();        }         while (s > f) {            f = filter.getAsLong();        }         return s;    }     public static void main(String[] args) {        generate(new GeneratorExponential(new SquaresGen(), new CubesGen()))                .skip(20).limit(10)                .forEach(n -> System.out.printf("%d ", n));    }} class SquaresGen implements LongSupplier {    private long n;     @Override    public long getAsLong() {        return n * n++;    }} class CubesGen implements LongSupplier {    private long n;     @Override    public long getAsLong() {        return n * n * n++;    }}`
`529 576 625 676 784 841 900 961 1024 1089`

JavaScript

Procedural

` function PowersGenerator(m) {	var n=0;	while(1) {		yield Math.pow(n, m);		n += 1;		}} function FilteredGenerator(g, f){	var value = g.next();	var filter = f.next(); 	while(1) {		if( value < filter ) {			yield value;			value = g.next();		} else if ( value > filter ) {			filter = f.next();		} else {			value = g.next();			filter = f.next();		}	}	}   var squares = PowersGenerator(2);var cubes = PowersGenerator(3); var filtered = FilteredGenerator(squares, cubes);   for( var x = 0; x < 20; x++ ) filtered.next()for( var x = 20; x < 30; x++ ) console.logfiltered.next());  `

ES6

`function* nPowerGen(n) {  let e = 0;  while (1) { e++ && (yield Math.pow(e, n)); }} function* filterGen(gS, gC, skip=0) {  let s = 0; // The square value  let c = 0; // The cube value  let n = 0; // A skip counter   while(1) {    s = gS.next().value;    s > c && (c = gC.next().value);    s == c ?      c = gC.next().value :      n++ && n > skip && (yield s);  }} const filtered = filterGen(nPowerGen(2), nPowerGen(3), skip=20);`
`// Generate the first 10 valuesfor (let n = 0; n < 10; n++) {  console.log(filtered.next().value)}`
```529
576
625
676
784
841
900
961
1024
1089```

Functional

ES6

Compositional derivation of custom generators:

Translation of: Python
`(() => {    'use strict';     // main :: IO()    const main = () => {         // powers :: Gen [Int]        const powers = n =>            fmapGen(                x => Math.pow(x, n),                enumFrom(0)            );         // xs :: [Int]        const xs = take(10, drop(20,            differenceGen(                powers(2),                powers(3)            )        ));         console.log(xs);        // -> [529,576,625,676,784,841,900,961,1024,1089]    };      // GENERIC FUNCTIONS ----------------------------------     // Just :: a -> Maybe a    const Just = x => ({        type: 'Maybe',        Nothing: false,        Just: x    });     // Nothing :: Maybe a    const Nothing = () => ({        type: 'Maybe',        Nothing: true,    });     // Tuple (,) :: a -> b -> (a, b)    const Tuple = (a, b) => ({        type: 'Tuple',        '0': a,        '1': b,        length: 2    });     // differenceGen :: Gen [a] -> Gen [a] -> Gen [a]    function* differenceGen(ga, gb) {        // All values of generator stream a except any        // already seen in generator stream b.        const            stream = zipGen(ga, gb),            sb = new Set([]);        let xy = take(1, stream);        while (0 < xy.length) {            const [x, y] = Array.from(xy[0]);            sb.add(y);            if (!sb.has(x)) yield x;            xy = take(1, stream);        }    };     // drop :: Int -> [a] -> [a]    // drop :: Int -> Generator [a] -> Generator [a]    // drop :: Int -> String -> String    const drop = (n, xs) =>        Infinity > length(xs) ? (            xs.slice(n)        ) : (take(n, xs), xs);     // enumFrom :: Enum a => a -> [a]    function* enumFrom(x) {        let v = x;        while (true) {            yield v;            v = 1 + v;        }    }     // fmapGen <\$> :: (a -> b) -> Gen [a] -> Gen [b]    function* fmapGen(f, gen) {        let v = take(1, gen);        while (0 < v.length) {            yield(f(v[0]))            v = take(1, gen)        }    }     // fst :: (a, b) -> a    const fst = tpl => tpl[0];     // Returns Infinity over objects without finite length.    // This enables zip and zipWith to choose the shorter    // argument when one is non-finite, like cycle, repeat etc     // length :: [a] -> Int    const length = xs =>        (Array.isArray(xs) || 'string' === typeof xs) ? (            xs.length        ) : Infinity;     // snd :: (a, b) -> b    const snd = tpl => tpl[1];     // take :: Int -> [a] -> [a]    // take :: Int -> String -> String    const take = (n, xs) =>        'GeneratorFunction' !== xs.constructor.constructor.name ? (            xs.slice(0, n)        ) : [].concat.apply([], Array.from({            length: n        }, () => {            const x = xs.next();            return x.done ? [] : [x.value];        }));     // uncons :: [a] -> Maybe (a, [a])    const uncons = xs => {        const lng = length(xs);        return (0 < lng) ? (            lng < Infinity ? (                Just(Tuple(xs[0], xs.slice(1))) // Finite list            ) : (() => {                const nxt = take(1, xs);                return 0 < nxt.length ? (                    Just(Tuple(nxt[0], xs))                ) : Nothing();            })() // Lazy generator        ) : Nothing();    };     // zipGen :: Gen [a] -> Gen [b] -> Gen [(a, b)]    const zipGen = (ga, gb) => {        function* go(ma, mb) {            let                a = ma,                b = mb;            while (!a.Nothing && !b.Nothing) {                let                    ta = a.Just,                    tb = b.Just                yield(Tuple(fst(ta), fst(tb)));                a = uncons(snd(ta));                b = uncons(snd(tb));            }        }        return go(uncons(ga), uncons(gb));    };     // MAIN ---    return main();})();`
Output:
`[529,576,625,676,784,841,900,961,1024,1089]`

jq

Works with: jq version 1.4

Part 1: i^m, 2^m and 3^m

jq is a purely functional language and so does not have generators with state. To generate a sequence of values one-by-one therefore requires a "next-value" function, the input of which must include relevant state information. For convenience, a counter is usually included. For generating i^m, therefore, we would have:

`# Compute self^m where m is a non-negative integer:def pow(m): . as \$in | reduce range(0;m) as \$i (1; .*\$in); # state: [i, i^m]def next_power(m): .[0] + 1 | [., pow(m) ];`

To make such generators easier to use, we shall define filters to skip and to emit a specified number of items:

`# skip m states, and return the next statedef skip(m; next):  if m <= 0 then . else next | skip(m-1; next) end; # emit m states including the initial statedef emit(m; next):  if m <= 0 then empty else ., (next | emit(m-1; next)) end;`

Examples:

`# Generate the first 4 values in the sequence i^2:[0,0] | emit(4; next_power(2)) | .[1] # Generate all the values in the sequence i^3 less than 100:[0,0] | recurse(next_power(3) | if .[1] < 100 then . else empty end) | .[1]`

An aside on streams

Since the release of version jq 1.4, enhancements for processing streams of values have been added, notably "foreach" and "limit". If your version of jq has these enhancements, then it is often preferable to use them in conjunction with functions that emit streams of values rather than the "next-value" functions that are the focus of this page.

Part 2: selection from 2 ^ m

`# Infrastructure:def last(f): reduce f as \$i (null; \$i); # emit the last value that satisfies condition, or nulldef while(condition; next):  def w: if condition then ., (next|w) else empty end;  last(w); # Powers of m1 that are not also powers of m2.# filtered_next_power(m1;m2) produces [[i, i^m1], [j, j^m1]] where i^m1# is not a power of m2 and j^m2 < i^m1#def filtered_next_power(m1; m2):  if . then . else [[0,0],[0,0]] end  | (.[0] | next_power(m1)) as \$next1  | (.[1] | while( .[1] <= \$next1[1]; next_power(m2))) as \$next2  | if \$next1[1] == \$next2[1]    then [\$next1, \$next2] | filtered_next_power(m1;m2)    else [\$next1, \$next2]    end ; # Emit ten powers of 2 that are NOT powers of 3,# skipping the first 20 integers satisfying the condition, including 0.filtered_next_power(2;3)  | skip(20; filtered_next_power(2;3))  | emit(10; filtered_next_power(2;3))  | .[0][1]`
Output:
`\$ jq -n -f generators.jq52957662567678484190096110241089`

Julia

The task can be achieved by using closures, iterators or tasks. Here is a solution using anonymous functions and closures.

`drop(gen::Function, n::Integer) = (for _ in 1:n gen() end; gen)take(gen::Function, n::Integer) = collect(gen() for _ in 1:n) function pgen(n::Number)    x = 0    return () -> (x += 1) ^ nend function genfilter(g1::Function, g2::Function)    local r1    local r2 = g2()    return () -> begin        r1 = g1()        while r2 <  r1 r2 = g2() end        while r1 == r2 r1 = g1() end        return r1    endend @show take(drop(genfilter(pgen(2), pgen(3)), 20), 10)`
Output:
`take(drop(genfilter(pgen(2), pgen(3)), 20), 10) = [529, 576, 625, 676, 784, 841, 900, 961, 1024, 1089]`

Kotlin

Coroutines were introduced in version 1.1 of Kotlin but, as yet, are an experimental feature:

`// version 1.1.0// compiled with flag -Xcoroutines=enable to suppress 'experimental' warning import kotlin.coroutines.experimental.buildSequence fun generatePowers(m: Int) =    buildSequence {        var n = 0        val mm = m.toDouble()        while (true) yield(Math.pow((n++).toDouble(), mm).toLong())    } fun generateNonCubicSquares(squares: Sequence<Long>, cubes: Sequence<Long>) =    buildSequence {        val iter2 = squares.iterator()        val iter3 = cubes.iterator()        var square = iter2.next()        var cube = iter3.next()        while (true) {            if (square > cube) {                cube = iter3.next()                continue            } else if (square < cube) {                yield(square)            }            square = iter2.next()        }    } fun main(args: Array<String>) {    val squares = generatePowers(2)    val cubes = generatePowers(3)    val ncs = generateNonCubicSquares(squares, cubes)    print("Non-cubic squares (21st to 30th) : ")    ncs.drop(20).take(10).forEach { print("\$it ") } // print 21st to 30th items    println()}`
Output:
```Non-cubic squares (21st to 30th) : 529 576 625 676 784 841 900 961 1024 1089
```

M2000 Interpreter

` Module Generator {      PowGen = Lambda (e)-> {            =lambda i=0, e -> {                  i++                              =i**e            }      }       Squares=lambda PowGen=PowGen(2) ->{            =PowGen()      }       Cubes=Lambda PowGen=PowGen(3) -> {            =PowGen()      }       Filter=Lambda  z=Squares(), Squares, m, Cubes->{            while m<Z {m=cubes()}            if z=m then z=Squares()            =z            z=Squares()      }       For i=1 to 20 : dropit=Filter() :Next i       Document doc\$="Non-cubic squares (21st to 30th)"      Print doc\$      \\ a new line to doc\$      doc\$={      }      For i=1 to  10 {            f=Filter()            Print Format\$("I: {0::-2}, F: {1}",i+20, f)            doc\$=Format\$("I: {0::-2}, F: {1}",i+20, f)+{              }      }      Clipboard doc\$}Generator `
Output:
```Non-cubic squares (21st to 30th)
I: 21, F: 529
I: 22, F: 576
I: 23, F: 625
I: 24, F: 676
I: 25, F: 784
I: 26, F: 841
I: 27, F: 900
I: 28, F: 961
I: 29, F: 1024
I: 30, F: 1089
```

Lingo

Lingo neither supports coroutines nor first-class functions, and also misses syntactic sugar for implementing real generators. But in the context of for or while loops, simple pseudo-generator objects that store states internally and manipulate data passed by reference can be used to implement generator-like behavior and solve the given task.

`squares = script("generator.power").new(2)cubes   = script("generator.power").new(3)filter  = script("generator.filter").new(squares, cubes)filter.skip(20)res = []i = 0repeat while filter.exec(res)    i = i + 1    if i>10 then exit repeat    put res[1]end repeat`
Output:
```-- 529
-- 576
-- 625
-- 676
-- 784
-- 841
-- 900
-- 961
-- 1024
-- 1089
```

Parent script "generator.power"

`property _expproperty _index -- @constructoron new (me, e)    me._exp = e    me._index = 0    return meend on exec (me, input)    me._index = me._index+1    input[1] = integer(power(me._index, me._exp))    return TRUEend on skip (me, steps)    me._index = me._index + stepsend on reset (me)    me._index = 0end`

Parent script "generator.filter"

`property _genvproperty _genf -- @constructoron new (me, genv, genf)    me._genv = genv    me._genf = genf    return meend on exec (me, input)    repeat while TRUE        me._genv.exec(input)        v = input[1]        ok = TRUE        me._genf.reset() -- reset filter generator        repeat while TRUE            me._genf.exec(input)            f = input[1]            if f>v then exit repeat            if f=v then                ok=FALSE                exit repeat            end if        end repeat        if ok then            input[1] = v            exit repeat        end if    end repeat    return TRUEend on skip (me, steps)    repeat with i = 1 to steps        me.exec([])    end repeatend on reset (me)    me._genv.reset()    me._genf.reset()end`

Lua

Generators can be implemented both as closures and as coroutines. The following example demonstrates both.

` --could be done with a coroutine, but a simple closure works just as well.local function powgen(m)  local count = 0  return function()    count = count + 1    return count^m  endend local squares = powgen(2)local cubes = powgen(3) local cowrap,coyield = coroutine.wrap, coroutine.yield local function filter(f,g)  return cowrap(function()    local ff,gg = f(), g()    while true do      if ff == gg then        ff,gg = f(), g()      elseif ff < gg then        coyield(ff)        ff = f()      else        gg = g()      end    end  end)end filter = filter(squares,cubes) for i = 1,30 do  local result = filter()  if i > 20 then    print(result)  endend `

Nim

`proc `^`*(base: int, exp: int): int =  var (base, exp) = (base, exp)  result = 1   while exp != 0:    if (exp and 1) != 0:      result *= base    exp = exp shr 1    base *= base proc next(s): int =  for n in s(): return n proc powers(m): auto =  iterator it(): int{.closure.} =    for n in 0 .. <int.high:      yield n ^ m  return it iterator filtered(s1, s2): int =  var v = next(s1)  var f = next(s2)  while true:    if v > f:      f = next(s2)      continue    elif v < f:      yield v    v = next(s1) var  squares = powers(2)  cubes = powers(3)  i = 1for x in filtered(squares, cubes):  if i > 20:    echo x  if i >= 30:    break  inc i`
Output:
```529
576
625
676
784
841
900
961
1024
1089```

PARI/GP

Define two generator functions genpow() and genpow2().

`g = List(1);		\\ generator stack genpow(p) = my(a=g[1]++);listput(g,[0,p]);()->g[a][1]++^g[a][2]; genpowf(p,f) = my(a=g[1]++);listput(g,[0,p]);(s=0)->my(q);while(ispower(p=g[a][1]++^g[a][2],f)||(s&&q++<=s),);p;`

genpow(power) returns a function that returns a simple power generator.
genpowf(power,filter) returns a function thats returns a filtered power generator. This generator accepts an optional skip-parameter.

Create simple power generators:

```gp > squares = genpow(2);
gp > cubes = genpow(3);
gp > cubes()
1
gp > cubes()
8
gp > squares()
1
gp > squares()
4
gp > cubes()
27
gp > squares()
9```

Create filtered power generator, skip first 20 results and print next 10 values:

```gp > powf2 = genpowf(2,3);
gp > print(powf2(20)); for(i=1,9,print(powf2()))
529
576
625
676
784
841
900
961
1024
1089```

Perl

These generators are anonymous subroutines, which are closures.

`# gen_pow(\$m) creates and returns an anonymous subroutine that will# generate and return the powers 0**m, 1**m, 2**m, ...sub gen_pow {    my \$m = shift;    my \$e = 0;    return sub { return \$e++ ** \$m; };} # gen_filter(\$g1, \$g2) generates everything returned from \$g1 that# is not also returned from \$g2. Both \$g1 and \$g2 must be references# to subroutines that generate numbers in increasing order. gen_filter# creates and returns an anonymous subroutine.sub gen_filter {    my(\$g1, \$g2) = @_;    my \$v1;    my \$v2 = \$g2->();    return sub {        for (;;) {            \$v1 = \$g1->();            \$v2 = \$g2->() while \$v1 > \$v2;            return \$v1 unless \$v1 == \$v2;        }    };} # Create generators.my \$squares = gen_pow(2);my \$cubes = gen_pow(3);my \$squares_without_cubes = gen_filter(\$squares, \$cubes); # Drop 20 values.\$squares_without_cubes->() for (1..20); # Print 10 values.my @answer;push @answer, \$squares_without_cubes->() for (1..10);print "[", join(", ", @answer), "]\n";`
Output:
`[529, 576, 625, 676, 784, 841, 900, 961, 1024, 1089]`

Perl 6

Works with: rakudo version 2015.12

As with Haskell, generators are disguised as lazy lists in Perl 6.

`sub powers(\$m) { \$m XR** 0..* } my @squares = powers(2);my @cubes   = powers(3); sub infix:<with-out> (@orig,@veto) {    gather for @veto -> \$veto {        take @orig.shift while @orig[0] before \$veto;        @orig.shift if @orig[0] eqv \$veto;    }} say (@squares with-out @cubes)[20 ..^ 20+10].join(', ');`
Output:
`529, 576, 625, 676, 784, 841, 900, 961, 1024, 1089`

Phix

`---- demo\rosetta\Generator_Exponential.exw-- ======================================--bool terminate = false atom res procedure powers(integer p)integer i=0    while not terminate do        res = power(i,p)        task_suspend(task_self())        task_yield()        i += 1    end whileend procedure constant squares = task_create(routine_id("powers"),{2}),         cubes   = task_create(routine_id("powers"),{3}) atom square, cubetask_schedule(cubes,1)task_yield()cube = resfor i=1 to 30 do    while 1 do        task_schedule(squares,1)        task_yield()        square = res        while cube<square do            task_schedule(cubes,1)            task_yield()            cube = res        end while        if square!=cube then exit end if    end while    if i>20 then        ?square    end ifend forterminate = 1`
Output:
```529
576
625
676
784
841
900
961
1024
1089
```

PHP

Translation of: Python
Works with: PHP version 5.5+
`<?phpfunction powers(\$m) {    for (\$n = 0; ; \$n++) {        yield pow(\$n, \$m);    }} function filtered(\$s1, \$s2) {    while (true) {        list(\$v, \$f) = [\$s1->current(), \$s2->current()];        if (\$v > \$f) {            \$s2->next();            continue;        } else if (\$v < \$f) {            yield \$v;        }        \$s1->next();    }} list(\$squares, \$cubes) = [powers(2), powers(3)];\$f = filtered(\$squares, \$cubes);foreach (range(0, 19) as \$i) {    \$f->next();}foreach (range(20, 29) as \$i) {    echo \$i, "\t", \$f->current(), "\n";    \$f->next();}?>`
Output:
```20	529
21	576
22	625
23	676
24	784
25	841
26	900
27	961
28	1024
29	1089
```

PicoLisp

Coroutines are available only in the 64-bit version.

`(de powers (M)   (co (intern (pack 'powers M))      (for (I 0 (inc 'I))         (yield (** I M)) ) ) ) (de filtered (N M)   (co 'filtered      (let (V (powers N)  F (powers M))         (loop            (if (> V F)               (setq F (powers M))               (and (> F V) (yield V))               (setq V (powers N)) ) ) ) ) ) (do 20 (filtered 2 3))(do 10 (println (filtered 2 3)))`
Output:
```529
576
625
676
784
841
900
961
1024
1089```

PL/I

` Generate: procedure options (main);   /* 27 October 2013 */        declare j fixed binary;        declare r fixed binary;         /* Ignore the first 20 values */        do j = 1 to 20;           /* put edit (filter() ) (f(6)); */           r = filter ();        end;        put skip;        do j = 1 to 10;           put edit (filter() ) (f(6));        end; /* filters out cubes from the result of the square generator. */filter: procedure returns (fixed binary);   declare n fixed binary static initial (-0);   declare (i, j, m) fixed binary;    do while ('1'b);      m = squares();      r = 0;      do j = 1 to m;         if m = cubes() then go to ignore;      end;      return (m);ignore:   end;end filter; squares: procedure returns (fixed binary);        declare i fixed binary static initial (-0);         i = i + 1;        return (i**2);end squares; cubes: procedure returns (fixed binary);         r = r + 1;        return (r**3);end cubes; end Generate; `
```20 dropped values:
4     9    16    25    36    49    81   100   121   144   169   196   225
256   289   324   361   400   441   484

Next 10 values:
529   576   625   676   784   841   900   961  1024  1089
```

Python

In Python, any function that contains a yield statement becomes a generator. The standard libraries itertools module provides the following functions used in the solution: count, that will count up from zero; and islice, which will take a slice from an iterator/generator.

Works with: Python version 2.6+ and 3.x
(in versions prior to 2.6, replace `next(something)` with `something.next()`)
`from itertools import islice, count def powers(m):    for n in count():        yield n ** m def filtered(s1, s2):    v, f = next(s1), next(s2)    while True:        if v > f:            f = next(s2)            continue        elif v < f:            yield v        v = next(s1) squares, cubes = powers(2), powers(3)f = filtered(squares, cubes)print(list(islice(f, 20, 30)))`
Output:
`[529, 576, 625, 676, 784, 841, 900, 961, 1024, 1089]`

Or, deriving custom generators compositionally:

Works with: Python version 3.7
`'''Exponentials as generators''' from itertools import count, islice  # powers :: Gen [Int]def powers(n):    '''A non-finite succession of integers,       starting at zero,       raised to the nth power.'''     def f(x):        return pow(x, n)     return map(f, count(0))  # main :: IO ()def main():    '''Taking the difference between two derived generators.'''    print(        take(10)(            drop(20)(                differenceGen(powers(2))(                    powers(3)                )            )        )    )  # GENERIC -------------------------------------------------  # differenceGen :: Gen [a] -> Gen [a] -> Gen [a]def differenceGen(ga):    '''All values of ga except any       already seen in gb.'''    def go(a, b):        stream = zip(a, b)        bs = set([])        while True:            xy = next(stream, None)            if None is not xy:                x, y = xy                bs.add(y)                if x not in bs:                    yield x            else:                return    return lambda gb: go(ga, gb)  # drop :: Int -> [a] -> [a]# drop :: Int -> String -> Stringdef drop(n):    '''The sublist of xs beginning at       (zero-based) index n.'''    def go(xs):        if isinstance(xs, list):            return xs[n:]        else:            take(n)(xs)            return xs    return lambda xs: go(xs)  # take :: Int -> [a] -> [a]# take :: Int -> String -> Stringdef take(n):    '''The prefix of xs of length n,       or xs itself if n > length xs.'''    return lambda xs: (        xs[0:n]        if isinstance(xs, list)        else list(islice(xs, n))    )  # MAIN ---if __name__ == '__main__':    main()`
Output:
`[529, 576, 625, 676, 784, 841, 900, 961, 1024, 1089]`

R

`powers = function(m)   {n = -1    function()       {n <<- n + 1        n^m}} noncubic.squares = local(   {squares = powers(2)    cubes = powers(3)    cube = cubes()    function()       {square = squares()        while (1)           {if (square > cube)               {cube <<- cubes()                next}            else if (square < cube)               {return(square)}            else               {square = squares()}}}}) for (i in 1:20)    noncubic.squares()for (i in 1:10)    message(noncubic.squares())`

Racket

` #lang racket (require racket/generator) ;; this is a function that returns a powers generator, not a generator(define (powers m)  (generator ()    (for ([n (in-naturals)]) (yield (expt n m))))) (define squares (powers 2))(define cubes   (powers 3)) ;; same here(define (filtered g1 g2)  (generator ()    (let loop ([n1 (g1)] [n2 (g2)])      (cond [(< n1 n2) (yield n1) (loop (g1) n2)]            [(> n1 n2) (loop n1 (g2))]            [else (loop (g1) (g2))])))) (for/list ([x (in-producer (filtered squares cubes) (lambda (_) #f))]           [i 30] #:when (>= i 20))  x) `
Output:
```'(529 576 625 676 784 841 900 961 1024 1089)
```

REXX

The generators   (below, the   Gxxxxx   functions)   lie dormant until a request is made for a specific generator index.

`/*REXX program demonstrates how to use a  generator  (also known as an  iterator).      */parse arg N .;   if N=='' |  N==","  then N=20   /*N  not specified?   Then use default.*/@.=                                              /* [↓]  calculate squares,cubes,pureSq.*/         do i=1  for N;   call Gsquare     i                          call Gcube       i                          call GpureSquare i     /*these are  cube─free  square numbers.*/         end   /*i*/      do k=1  for N;  @.pureSquare.k=;  end /*k*/ /*this is used to drop  1st  N  values.*/ w=length(N+10);               ps= 'pure square'  /*the width of the numbers;  a literal.*/      do m=N+1  for 10;    say ps   right(m, w)":"     right(GpureSquare(m), 3*w)     end       /*m*/exit                                             /*stick a fork in it,  we're all done. *//*──────────────────────────────────────────────────────────────────────────────────────*/Gpower:      procedure expose @.;       parse arg x,p;   [email protected].pow.x.p             if q\==''  then return q;  _=x**p;          @.pow.x.p=_             return _/*──────────────────────────────────────────────────────────────────────────────────────*/Gsquare:     procedure expose @.;       parse arg x;     [email protected].square.x             if q==''  then @.square.x=Gpower(x, 2)             return @.square.x/*──────────────────────────────────────────────────────────────────────────────────────*/Gcube:       procedure expose @.;       parse arg x;     [email protected].cube.x             if q==''  then @.cube.x=Gpower(x, 3)        [email protected].cube.x;     @.3pow._=1             return @.cube.x/*──────────────────────────────────────────────────────────────────────────────────────*/GpureSquare: procedure expose @.;       parse arg x;     [email protected].pureSquare.x             if q\==''  then return q             #=0                   do j=1  until #==x;  ?=Gpower(j, 2)        /*search for pure square. */                   if @.3pow.?==1  then iterate               /*is it a power of three? */                   #=#+1;               @.pureSquare.#=?      /*assign next pureSquare. */                   end   /*j*/             return @.pureSquare.x`

output   when using the default value:

```pure square 21:    529
pure square 22:    576
pure square 23:    625
pure square 24:    676
pure square 25:    784
pure square 26:    841
pure square 27:    900
pure square 28:    961
pure square 29:   1024
pure square 30:   1089
```

Ruby

This first solution cheats and uses only one generator! It has three iterators powers(2), powers(3) and squares_without_cubes, but the only generator runs powers(3).

An iterator is a Ruby method that takes a block parameter, and loops the block for each element. So powers(2) { |i| puts "Got #{i}" } would loop forever and print Got 0, Got 1, Got 4, Got 9 and so on. Starting with Ruby 1.8.7, one can use Object#enum_for to convert an iterator method to an Enumerator object. The Enumerator#next method is a generator that runs the iterator method on a separate coroutine. Here cubes.next generates the next cube number.

`# This solution cheats and uses only one generator! def powers(m)  return enum_for(__method__, m) unless block_given?  0.step{|n| yield n**m}end def squares_without_cubes  return enum_for(__method__) unless block_given?   cubes = powers(3)  c = cubes.next  powers(2) do |s|    c = cubes.next while c < s    yield s unless c == s  endend p squares_without_cubes.take(30).drop(20)# p squares_without_cubes.lazy.drop(20).first(10)   # Ruby 2.0+`
Output:
```[529, 576, 625, 676, 784, 841, 900, 961, 1024, 1089]
```

Here is the correct solution, which obeys the requirement of three generators.

`# This solution uses three generators. def powers(m)  return enum_for(__method__, m) unless block_given?  0.step{|n| yield n**m}end def squares_without_cubes  return enum_for(__method__) unless block_given?   cubes = powers(3) #no block, so this is the first generator  c = cubes.next  squares = powers(2) # second generator  loop do    s = squares.next    c = cubes.next while c < s    yield s unless c == s  endend answer = squares_without_cubes # third generator20.times { answer.next }p 10.times.map { answer.next }`
Output:
```[529, 576, 625, 676, 784, 841, 900, 961, 1024, 1089]
```

If we change both programs to drop the first 1_000_020 values (output: [1000242014641, 1000244014884, 1000246015129, 1000248015376, 1000250015625, 1000252015876, 1000254016129, 1000256016384, 1000258016641, 1000260016900]), then the one-generator solution runs much faster than the three-generator solution on a machine with MRI 1.9.2.

The other way. Powers method is the same as the above.

Translation of: Python
`def filtered(s1, s2)  return enum_for(__method__, s1, s2) unless block_given?  v, f = s1.next, s2.next  loop do    v > f and f = s2.next and next    v < f and yield v    v = s1.next  endend squares, cubes = powers(2), powers(3)f = filtered(squares, cubes)p f.take(30).last(10)# p f.lazy.drop(20).first(10)   # Ruby 2.0+`

Output is the same as the above.

Scala

`object Generators {   def main(args: Array[String]): Unit = {      def squares(n:Int=0):Stream[Int]=(n*n) #:: squares(n+1)      def cubes(n:Int=0):Stream[Int]=(n*n*n) #:: cubes(n+1)       def filtered(s:Stream[Int], c:Stream[Int]):Stream[Int]={         if(s.head>c.head) filtered(s, c.tail)         else if(s.head<c.head) Stream.cons(s.head, filtered(s.tail, c))         else filtered(s.tail, c)      }       filtered(squares(), cubes()) drop 20 take 10 print   }}`

Here is an alternative filter implementation using pattern matching.

`def filtered2(s:Stream[Int], c:Stream[Int]):Stream[Int]=(s, c) match {   case (sh#::_, ch#::ct) if (sh>ch) => filtered2(s, ct)   case (sh#::st, ch#::_) if (sh<ch) => sh #:: filtered2(st, c)   case (_#::st, _) => filtered2(st, c)}`
Output:
`529, 576, 625, 676, 784, 841, 900, 961, 1024, 1089, empty`

Rust

`use std::cmp::Ordering;use std::iter::Peekable; fn powers(m: u32) -> impl Iterator<Item = u64> {    (0u64..).map(move |x| x.pow(m))} fn noncubic_squares() -> impl Iterator<Item = u64> {    NoncubicSquares {        squares: powers(2).peekable(),        cubes: powers(3).peekable(),    }} struct NoncubicSquares<T: Iterator<Item = u64>, U: Iterator<Item = u64>> {    squares: Peekable<T>,    cubes: Peekable<U>,} impl<T: Iterator<Item = u64>, U: Iterator<Item = u64>> Iterator for NoncubicSquares<T, U> {    type Item = u64;    fn next(&mut self) -> Option<u64> {        loop {            match self.squares.peek()?.cmp(self.cubes.peek()?) {                Ordering::Equal => self.squares.next(),                Ordering::Greater => self.cubes.next(),                Ordering::Less => return self.squares.next(),            };        }    }} fn main() {    noncubic_squares()        .skip(20)        .take(10)        .for_each(|x| print!("{} ", x));    println!();}`
Output:
`529 576 625 676 784 841 900 961 1024 1089 `

Scheme

`(define (power-seq n)  (let ((i 0))    (lambda ()      (set! i (+ 1 i))      (expt i n)))) (define (filter-seq m n)  (let* ((s1 (power-seq m)) (s2 (power-seq n))			    (a 0) (b 0))    (lambda ()      (set! a (s1))      (let loop ()	(if (>= a b) (begin		       (cond ((> a b) (set! b (s2)))			     ((= a b) (set! a (s1))))		       (loop))))      a))) (let loop ((seq (filter-seq 2 3)) (i 0))  (if (< i 30)    (begin      (if (> i 20)	(begin	  (display (seq))	  (newline))	(seq))      (loop seq (+ 1 i)))))`
Output:
```576
625
676
784
841
900
961
1024
1089```

Sidef

Translation of: Perl
`func gen_pow(m) {    var e = 0;    func { e++ ** m };} func gen_filter(g1, g2) {    var v2 = g2.run;    func {        loop {            var v1 = g1.run;            while (v1 > v2) { v2 = g2.run };            v1 == v2 || return v1;        }    }} # Create generators.var squares = gen_pow(2);var cubes = gen_pow(3);var squares_without_cubes = gen_filter(squares, cubes); # Drop 20 values.20.times { squares_without_cubes() }; # Print 10 values.var answer = [];10.times { answer.append(squares_without_cubes()) };say answer;`
Output:
```[529, 576, 625, 676, 784, 841, 900, 961, 1024, 1089]
```

Swift

`func powGen(m: Int) -> GeneratorOf<Int> {  let power = Double(m)  var cur: Double = 0  return GeneratorOf { Int(pow(cur++, power)) }} var squares = powGen(2)var cubes = powGen(3) var nCube = cubes.next() var filteredSqs = GeneratorOf<Int> {  for var nSq = squares.next() ;; nCube = cubes.next() {    if nCube > nSq {      return nSq    } else if nCube == nSq {      nSq = squares.next()    }  }} extension GeneratorOf {  func drop(n: Int) -> GeneratorOf<T> {    var g = self    for _ in 0..<n {g.next()}    return GeneratorOf{g.next()}  }  func take(n: Int) -> GeneratorOf<T> {    var (i, g) = (0, self)    return GeneratorOf{++i > n ? nil : g.next()}  }} for num in filteredSqs.drop(20).take(10) {  print(num)} //529//576//625//676//784//841//900//961//1024//1089`

SuperCollider

` f = { |m| {:x, x<-(0..) } ** m };g = f.(2);g.nextN(10); // answers  [ 0, 1, 4, 9, 16, 25, 36, 49, 64, 81 ] `

patterns are stream generators:

`(f = Pseries(0, 1)g = f ** 2;g.asStream.nextN(10); // answers  [ 0, 1, 4, 9, 16, 25, 36, 49, 64, 81 ]) `

supercollider has no "without" stream function, this builds one:

`(var filter = { |a, b, func| // both streams are assumed to be ordered	Prout {		var astr, bstr;		var aval, bval;		astr = a.asStream;		bstr = b.asStream;		bval = bstr.next;		while {			aval = astr.next;			aval.notNil		} {			while {				bval.notNil and: { bval < aval }			} {				bval = bstr.next;			};			if(func.value(aval, bval)) { aval.yield };		}	}};var without = filter.(_, _, { |a, b|  a != b }); // partially apply function f = Pseries(0, 1); g = without.(f ** 2, f ** 3);h = g.drop(20);h.asStream.nextN(10);) answers: [ 529, 576, 625, 676, 784, 841, 900, 961, 1024, 1089 ] `

Tcl

Works with: Tcl version 8.6

Tcl implements generators in terms of coroutines. If these generators were terminating, they would finish by doing `return -code break` so as to terminate the calling loop context that is doing the extraction of the values from the generator.

`package require Tcl 8.6 proc powers m {    yield    for {set n 0} true {incr n} {	yield [expr {\$n ** \$m}]    }}coroutine squares powers 2coroutine cubes powers 3coroutine filtered apply {{s1 s2} {    yield    set f [\$s2]    set v [\$s1]    while true {	if {\$v > \$f} {	    set f [\$s2]	    continue	} elseif {\$v < \$f} {	    yield \$v	}	set v [\$s1]    }}} squares cubes # Drop 20for {set i 0} {\$i<20} {incr i} {filtered}# Take/print 10for {} {\$i<30} {incr i} {    puts [filtered]}`
Output:
```529
576
625
676
784
841
900
961
1024
1089
```

VBA

`Public lastsquare As LongPublic nextsquare As LongPublic lastcube As LongPublic midcube As LongPublic nextcube As LongPrivate Sub init()    lastsquare = 1    nextsquare = -1    lastcube = -1    midcube = 0    nextcube = 1End Sub Private Function squares() As Long    lastsquare = lastsquare + nextsquare    nextsquare = nextsquare + 2    squares = lastsquareEnd Function Private Function cubes() As Long    lastcube = lastcube + nextcube    nextcube = nextcube + midcube    midcube = midcube + 6    cubes = lastcubeEnd Function Public Sub main()    init    cube = cubes    For i = 1 To 30        Do While True            square = squares            Do While cube < square                cube = cubes            Loop            If square <> cube Then                Exit Do            End If        Loop        If i > 20 Then            Debug.Print square;        End If    Next iEnd Sub`
Output:
` 529  576  625  676  784  841  900  961  1024  1089 `

XPL0

`code ChOut=8, IntOut=11; func Gen(M);            \Generate Mth powers of positive integersint  M;int  N, R, I;[N:= [0, 0, 0, 0];      \provides own/static variablesR:= 1;for I:= 1 to M do R:= R*N(M);N(M):= N(M)+1;return R;]; func Filter;            \Generate squares of positive integers that aren't cubesint  S, C;[C:= [0];               \static variable = smallest cube > current squarerepeat  S:= Gen(2);        while S > C(0) do C(0):= Gen(3);until   S # C(0);return S;]; int  I;[for I:= 1 to 20 do Filter;                             \drop first 20 values for I:= 1 to 10 do [IntOut(0, Filter);  ChOut(0, ^ )]; \show next 10 values]`
Output:
```529 576 625 676 784 841 900 961 1024 1089
```

zkl

Translation of: Python

Generators are implemented with fibers (aka VMs) and return [lazy] iterators.

`fcn powers(m){ n:=0.0; while(1){vm.yield(n.pow(m).toInt()); n+=1} }var squared=Utils.Generator(powers,2), cubed=Utils.Generator(powers,3); fcn filtered(sg,cg){s:=sg.next(); c:=cg.next();   while(1){      if(s>c){c=cg.next(); continue;}       else if(s<c) vm.yield(s);       s=sg.next()   }}var f=Utils.Generator(filtered,squared,cubed);f.drop(20);f.walk(10).println();`
Output:
`L(529,576,625,676,784,841,900,961,1024,1089)`

For this task, generators are overkill and overweight, and lazy infinite squences can be used. There is no real change to the algorithms (since generators are lazy sequences), it just has been rewritten in a more functional style.

Translation of: Clojure
`fcn powers(m){[0.0..].tweak(fcn(n,m){a:=n; do(m-1){a*=n} a}.fp1(m))}var squared=powers(2), cubed=powers(3); fcn filtered(sg,cg){s:=sg.peek(); c:=cg.peek();   if(s==c){ cg.next(); sg.next(); return(self.fcn(sg,cg)) }    if(s>c) { cg.next(); return(self.fcn(sg,cg)); }   sg.next(); return(s);}var f=[0..].tweak(filtered.fp(squared,cubed))f.drop(20).walk(10).println();`