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{{Short description|Metaprogramming technique}}
{{More footnotes|date=June 2010}}
{{More footnotes needed|date=June 2010}}
{{Programming paradigms}}
 
'''Template metaprogramming''' ('''TMP''') is a [[metaprogramming]] technique in which [[Generic programming|templates]] are used by a [[compiler]] to generate temporary [[source code]], which is merged by the compiler with the rest of the source code and then compiled. The output of these templates can include [[compile time|compile-time]] [[constant (programming)|constant]]s, [[data structure]]s, and complete [[function (computer science)|function]]s. The use of templates can be thought of as [[Compile -time function execution|compile-time executionpolymorphism]]. The technique is used by a number of languages, the best-known being [[C++]], but also [[Curl programming language|Curl]], [[D programming language|D]], [[Nim (programming language)|Nim]], and [[XL Programming Language|XL]].
 
Template metaprogramming was, in a sense, discovered accidentally.<ref name="Meyers2005">{{cite book|author=Scott Meyers|title=Effective C++: 55 Specific Ways to Improve Your Programs and Designs|url=https://books.google.com/books?id=Qx5oyB49poYC&printsec=frontcover#v=onepage&q=%22Template%20metaprogramming+metaprogramming%22&f=false|date=12 May 2005|publisher=Pearson Education|isbn=978-0-13-270206-5}}</ref><ref>See [[wikibooks:C++ Programming/Templates/Template Meta-Programming#History of TMP|History of TMP]] on Wikibooks</ref>
 
Some other languages support similar, if not more powerful, compile-time facilities (such as [[Lisp (programming language)|Lisp]] [[Macro (computer science)#Syntactic macros|macros]]), but those are outside the scope of this article.
 
==Components of template metaprogramming==
The use of templates as a metaprogramming technique requires two distinct operations: a template must be defined, and a defined template must be [[Instance (computer science)|instantiated]]. The template definition describes the generic form of the generated source code, andis thedescribed instantiationin causesthe atemplate specificdefinition, setand ofwhen sourcethe codetemplate tois be generated frominstantiated, the generic form in the template is used to generate a specific set of source code.
 
Template metaprogramming is [[Turing-complete]], meaning that any computation expressible by a computer program can be computed, in some form, by a template metaprogram.<ref name=Veldhuizen2003>{{cite webCiteSeerX|last1=Veldhuizen|first1=Todd L.|title=C++ Templates are Turing Complete|urlyear=http://2003|citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.3670}}</ref>
 
Templates are different from ''[[Macro (computer science)#Programming macros|macros]]''. A macro is a piece of code that executes at compile time and either performs textual manipulation of code to-be compiled (e.g. [[C++]] macros) or manipulates the [[abstract syntax tree]] being produced by the compiler (e.g. [[Rust (programming language)|Rust]] or [[Lisp (programming language)|Lisp]] macros). Textual macros are notably more independent of the syntax of the language being manipulated, as they merely change the in-memory text of the source code right before compilation.
 
Template metaprograms have no [[Immutable object|mutable variables]]&mdash; that is, no variable can change value once it has been initialized, therefore template metaprogramming can be seen as a form of [[functional programming]]. In fact many template implementations implement flow control only through [[Recursion (computer science)|recursion]], as seen in the example below.
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==Compile-time class generation==
What exactly "programming at compile-time" means can be illustrated with an example of a factorial function, which in non-template C++ can be written using recursion as follows:
<sourcesyntaxhighlight lang=cpp>
unsigned int factorial(unsigned int n) {
return n == 0 ? 1 : n * factorial(n - 1);
}
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// factorial(0) would yield 1;
// factorial(4) would yield 24.
</syntaxhighlight>
</source>
The code above will execute at run time to determine the factorial value of the literals 40 and 04.
By using template metaprogramming and template specialization to provide the ending condition for the recursion, the factorials used in the program—ignoring any factorial not used—can be calculated at compile time by this code:
<sourcesyntaxhighlight lang=cpp>
template <unsigned int nN>
struct factorial {
enumstatic {constexpr unsigned value = nN * factorial<nN - 1>::value };
};
 
template <>
struct factorial<0> {
enumstatic {constexpr unsigned value = 1 };
};
 
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// factorial<0>::value would yield 1;
// factorial<4>::value would yield 24.
</syntaxhighlight>
</source>
The code above calculates the factorial value of the literals 40 and 04 at compile time and uses the results as if they were precalculated constants.
To be able to use templates in this manner, the compiler must know the value of its parameters at compile time, which has the natural precondition that factorial<X>::value can only be used if X is known at compile time. In other words, X must be a constant literal or a constant expression.
 
In [[C++11]] and [[C++20]], [[constexpr]], aand wayconsteval were introduced to let the compiler execute simple constant expressions, was addedcode. Using constexpr and consteval, one can use the usual recursive factorial definition with the non-templated syntax.<ref>http{{Cite web|url=https://www.cprogramming.com/c++11/c++11-compile-time-processing-with-constexpr.html|title=Constexpr - Generalized Constant Expressions in C++11 - Cprogramming.com|website=www.cprogramming.com}}</ref>
 
==Compile-time code optimization==
{{see also|Compile -time function execution}}
The factorial example above is one example of compile-time code optimization in that all factorials used by the program are pre-compiled and injected as numeric constants at compilation, saving both run-time overhead and [[memory footprint]]. It is, however, a relatively minor optimization.
 
As another, more significant, example of compile-time [[loop unrolling]], template metaprogramming can be used to create length-''n'' vector classes (where ''n'' is known at compile time). The benefit over a more traditional length-''n'' vector is that the loops can be unrolled, resulting in very optimized code. As an example, consider the addition operator. A length-''n'' vector addition might be written as
<sourcesyntaxhighlight lang="cpp">
template <int length>
Vector<length>& Vector<length>::operator+=(const Vector<length>& rhs)
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return *this;
}
</syntaxhighlight>
</source>
 
When the compiler instantiates the function template defined above, the following code may be produced:{{citation needed|date=October 2015}}
 
<sourcesyntaxhighlight lang="cpp">
template <>
Vector<2>& Vector<2>::operator+=(const Vector<2>& rhs)
Line 78:
return *this;
}
</syntaxhighlight>
</source>
 
The compiler's optimizer should be able to unroll the <code>for</code> loop because the template parameter <code>length</code> is a constant at compile time.
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==Static polymorphism==
[[Type polymorphism|Polymorphism]] is a common standard programming facility where derived objects can be used as instances of their base object but where the derived objects' methods will be invoked, as in this code
<sourcesyntaxhighlight lang="cpp">
class Base
{
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return 0;
}
</syntaxhighlight>
</source>
where all invocations of <code>virtual</code> methods will be those of the most-derived class. This ''dynamically polymorphic'' behaviour is (typically) obtained by the creation of [[vtable|virtual look-up table]]s for classes with virtual methods, tables that are traversed at run time to identify the method to be invoked. Thus, ''run-time polymorphism'' necessarily entails execution overhead (though on modern architectures the overhead is small).
 
However, in many cases the polymorphic behaviour needed is invariant and can be determined at compile time. Then the [[Curiously Recurring Template Pattern]] (CRTP) can be used to achieve '''static polymorphism''', which is an imitation of polymorphism in programming code but which is resolved at compile time and thus does away with run-time virtual-table lookups. For example:
<sourcesyntaxhighlight lang="cpp">
template <class Derived>
struct base
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}
};
</syntaxhighlight>
</source>
Here the base class template will take advantage of the fact that member function bodies are not instantiated until after their declarations, and it will use members of the derived class within its own member functions, via the use of a <code>static_cast</code>, thus at compilation generating an object composition with polymorphic characteristics. As an example of real-world usage, the CRTP is used in the [[Boost library|Boost]] [[iterator]] library.<ref>{{Cite web|url=http://www.boost.org/libs/iterator/doc/iterator_facade.html|title = Iterator Facade - 1.79.0}}</ref>
 
Another similar use is the "[[Barton–Nackman trick]]", sometimes referred to as "restricted template expansion", where common functionality can be placed in a base class that is used not as a contract but as a necessary component to enforce conformant behaviour while minimising code redundancy.
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== Static Table Generation ==
 
The benefit of static tables is the replacement of "expensive" calculations with a simple array indexing operation (for examples, see [[lookup table]]). In C++, there exists more than one way to generate a static table at compile time. The following listing shows an example of creating a very simple table by using recursive structs and [[variadic templates]].
The table has a size of ten. Each value is the square of the index.
In C++ exists more than one way to generate a static table at compile time.
The following listing shows an example of creating a very simple table by using recursive structs and [[Variadic templates]].
The table has a size of ten and each value is just the index multiplied with itself.
 
<syntaxhighlight lang="cpp">
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*/
template<int INDEX = 0, int ...D>
struct Helper : helperHelper<INDEX + 1, D..., INDEX * INDEX> { };
 
/**
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};
 
constexpr std::array<int, TABLE_SIZE> table = helperHelper<>::table;
 
enum {
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int main() {
for (int i=0; i < TABLE_SIZE; i++) {
std::cout << table[i] << std::endl; // run time use
}
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}
</syntaxhighlight>
The idea behind this is that the struct Helper recursivlyrecursively inherits from a struct with one more template argument (in this example calculated as INDEX * INDEX) until the specialization of the template ends the recursion at a size of 10 elements. The specialization simply uses the variable argument list as elements for the array.
The compiler will produce code similar to the following (taken from clang called with -Xclang -ast-print -fsyntax-only).
<syntaxhighlight lang="cpp">
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</syntaxhighlight>
 
Since C++17 this can be more readablereadably written as:
 
<syntaxhighlight lang="cpp">
Line 226 ⟶ 224:
 
int main() {
for (int i=0; i < TABLE_SIZE; i++) {
std::cout << table[i] << std::endl; // run time use
}
std::cout << "FOUR: " << FOUR << std::endl;
}
</syntaxhighlight>
 
To show a more sophisticated example the code in the following listing has been extended to have a helper for value calculation (in preparation for more complicated computations), a table specific offset and a template argument for the type of the table values (e.g. uint8_t, uint16_t, ...).
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int main() {
for (int i = 0; i < TABLE_SIZE; i++) {
std::cout << table[i] << std::endl;
}
}
</syntaxhighlight>
Which could be written as follows using C++17:
<syntaxhighlight lang="cpp">
#include <iostream>
#include <array>
 
constexpr int TABLE_SIZE = 20;
constexpr int OFFSET = 12;
 
template<typename VALUETYPE, int OFFSET>
constexpr std::array<VALUETYPE, TABLE_SIZE> table = [] { // OR: constexpr auto table
std::array<VALUETYPE, TABLE_SIZE> A = {};
for (unsigned i = 0; i < TABLE_SIZE; i++) {
A[i] = OFFSET + i * i;
}
return A;
}();
 
int main() {
for (int i = 0; i < TABLE_SIZE; i++) {
std::cout << table<uint16_t, OFFSET>[i] << std::endl;
}
}
</syntaxhighlight>
 
==Concepts==
The C++20 standard brought C++ programmers a new tool for meta template programming, concepts.<ref>{{Cite web|url=https://en.cppreference.com/w/cpp/language/constraints|title=Constraints and concepts (since C++20) - cppreference.com|website=en.cppreference.com}}</ref>
 
[[Concepts (C++)|Concepts]] allow programmers to specify requirements for the type, to make instantiation of template possible. The compiler looks for a template with the concept that has the highest requirements.
 
Here is an example of the famous [[Fizz buzz]] problem solved with Template Meta Programming.
 
<syntaxhighlight lang="cpp">
#include <boost/type_index.hpp> // for pretty printing of types
#include <iostream>
#include <tuple>
 
/**
* Type representation of words to print
*/
struct Fizz {};
struct Buzz {};
struct FizzBuzz {};
template<size_t _N> struct number { constexpr static size_t N = _N; };
 
/**
* Concepts used to define condition for specializations
*/
template<typename Any> concept has_N = requires{ requires Any::N - Any::N == 0; };
template<typename A> concept fizz_c = has_N<A> && requires{ requires A::N % 3 == 0; };
template<typename A> concept buzz_c = has_N<A> && requires{ requires A::N % 5 == 0;};
template<typename A> concept fizzbuzz_c = fizz_c<A> && buzz_c<A>;
 
/**
* By specializing `res` structure, with concepts requirements, proper instantiation is performed
*/
template<typename X> struct res;
template<fizzbuzz_c X> struct res<X> { using result = FizzBuzz; };
template<fizz_c X> struct res<X> { using result = Fizz; };
template<buzz_c X> struct res<X> { using result = Buzz; };
template<has_N X> struct res<X> { using result = X; };
 
/**
* Predeclaration of concatenator
*/
template <size_t cnt, typename... Args>
struct concatenator;
 
/**
* Recursive way of concatenating next types
*/
template <size_t cnt, typename ... Args>
struct concatenator<cnt, std::tuple<Args...>>
{ using type = typename concatenator<cnt - 1, std::tuple< typename res< number<cnt> >::result, Args... >>::type;};
 
/**
* Base case
*/
template <typename... Args> struct concatenator<0, std::tuple<Args...>> { using type = std::tuple<Args...>;};
 
/**
* Final result getter
*/
template<size_t Amount>
using fizz_buzz_full_template = typename concatenator<Amount - 1, std::tuple<typename res<number<Amount>>::result>>::type;
 
int main()
{
// printing result with boost, so it's clear
std::cout << boost::typeindex::type_id<fizz_buzz_full_template<100>>().pretty_name() << std::endl;
/*
Result:
std::tuple<number<1ul>, number<2ul>, Fizz, number<4ul>, Buzz, Fizz, number<7ul>, number<8ul>, Fizz, Buzz, number<11ul>, Fizz, number<13ul>, number<14ul>, FizzBuzz, number<16ul>, number<17ul>, Fizz, number<19ul>, Buzz, Fizz, number<22ul>, number<23ul>, Fizz, Buzz, number<26ul>, Fizz, number<28ul>, number<29ul>, FizzBuzz, number<31ul>, number<32ul>, Fizz, number<34ul>, Buzz, Fizz, number<37ul>, number<38ul>, Fizz, Buzz, number<41ul>, Fizz, number<43ul>, number<44ul>, FizzBuzz, number<46ul>, number<47ul>, Fizz, number<49ul>, Buzz, Fizz, number<52ul>, number<53ul>, Fizz, Buzz, number<56ul>, Fizz, number<58ul>, number<59ul>, FizzBuzz, number<61ul>, number<62ul>, Fizz, number<64ul>, Buzz, Fizz, number<67ul>, number<68ul>, Fizz, Buzz, number<71ul>, Fizz, number<73ul>, number<74ul>, FizzBuzz, number<76ul>, number<77ul>, Fizz, number<79ul>, Buzz, Fizz, number<82ul>, number<83ul>, Fizz, Buzz, number<86ul>, Fizz, number<88ul>, number<89ul>, FizzBuzz, number<91ul>, number<92ul>, Fizz, number<94ul>, Buzz, Fizz, number<97ul>, number<98ul>, Fizz, Buzz>
*/
}
</syntaxhighlight>
 
==Benefits and drawbacks of template metaprogramming==
Compile-time versus execution-time tradeoffs get visible if a great deal of template metaprogramming is used.
; Compile-time versus execution-time tradeoff : If a great deal of template metaprogramming is used, compilation may become slow; section 14.7.1 [temp.inst] of the current standard defines the circumstances under which templates are implicitly instantiated. Defining a template does not imply that it will be instantiated, and instantiating a class template does not cause its member definitions to be instantiated. Depending on the style of use, templates may compile either faster or slower than hand-rolled code.
;* [[Generic programming]] : Template metaprogramming allows the programmer to focus on architecture and delegate to the compiler the generation of any implementation required by client code. Thus, template metaprogramming can accomplish truly [[Generic programming|generic code]], facilitating code minimization and better maintainability{{Citation needed|date=June 2014}}.
; Readability :* With respect to C++ prior to version ''C++11'', the syntax and idioms of template metaprogramming arewere esoteric compared to conventional C++ programming, and template metaprograms cancould be very difficult to understand.<ref>{{cite paperweb
| first1 = K.
| last1 = Czarnecki
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|quote=''C++ Template Metaprogramming suffers from a number of limitations, including portability problems due to compiler limitations (although this has significantly improved in the last few years), lack of debugging support or IO during template instantiation, long compilation times, long and incomprehensible errors, poor readability of the code, and poor error reporting.''
| ref = Czarnecki, O’Donnell, Striegnitz, Taha - DSL implementation in metaocaml, template haskell, and C++
}}</ref><ref>{{cite paperweb
| first1 = Tim
| last1 = Sheard
Line 303 ⟶ 396:
| quote = ''Robinson’s provocative paper identifies C++ templates as a major, albeit accidental, success of the C++ language design. Despite the extremely baroque nature of template meta-programming, templates are used in fascinating ways that extend beyond the wildest dreams of the language designers. Perhaps surprisingly, in view of the fact that templates are functional programs, functional programmers have been slow to capitalize on C++’s success''
| ref = Sheard, S.P.Jones - Template Meta-programming for Haskell
}}</ref> But from C++11 onward the syntax for value computation metaprogramming becomes more and more akin to "normal" C++, with less and less readability penalty.
}}</ref>
 
==See also==
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* [[Parametric polymorphism]]
* [[Expression templates]]
* [[Variadic Templatestemplate]]
* [[Compile -time function execution]]
 
==References==
{{Reflist}}
* {{cite book | authorlink = Ulrich W. Eisenecker | first = Ulrich W. | last = Eisenecker | title = Generative Programming: Methods, Tools, and Applications | publisher = Addison-Wesley | isbn = 0-201-30977-7 | year = 2000 }}
* {{cite book | authorlink = Andrei Alexandrescu | first = Andrei | last = Alexandrescu | title = [[Modern C++ Design]]: Generic Programming and Design Patterns Applied | publisher = Addison-Wesley | isbn = 3-8266-1347-3 | year = 2003 }}
* {{cite book | authorlink1 = David Abrahams (computer programmer) | firstfirst1 = David | lastlast1 = Abrahams | authorlink2 = Aleksey Gurtovoy | first2 = Aleksey | last2 = Gurtovoy | title = C++ Template Metaprogramming: Concepts, Tools, and Techniques from Boost and Beyond | publisher = Addison-Wesley | isbn = 0-321-22725-5 | date = January 2005 }}
* {{cite book | authorlink1 = David VandervoordeVandevoorde | first1 = David | last1 = VandervoordeVandevoorde | authorlink2 = Nicolai M. Josuttis | first2 = Nicolai M. | last2 = Josuttis | title = C++ Templates: The Complete Guide | publisher = Addison-Wesley | isbn = 0-201-73484-2 | year = 2003 }}
* {{cite book | authorlink = Manuel Clavel | first = Manuel | last = Clavel | title = Reflection in Rewriting Logic: Metalogical Foundations and Metaprogramming Applications | isbn = 1-57586-238-7 | date = 2000-10-16 | publisher = Cambridge University Press }}
 
==External links==
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* {{cite web | url = https://wiki.haskell.org/Template_Haskell | title = Template Haskell }} (type-safe metaprogramming in Haskell)
* {{cite web | authorlink = Walter Bright | first = Walter | last = Bright | url = http://www.digitalmars.com/d/templates-revisited.html | title = Templates Revisited }} (template metaprogramming in the [[D programming language]])
* {{cite web | url = http://staff.ustc.edu.cn/~xyfeng/teaching/FOPL/lectureNotes/MetaprogrammingCpp.pdf | title = Metaprogramming in C++ | authorlink = Johannes Koskinen | first = Johannes | last = Koskinen | access-date = 2014-06-20 | archive-date = 2014-08-28 | archive-url = https://web.archive.org/web/20140828190250/http://staff.ustc.edu.cn/~xyfeng/teaching/FOPL/lectureNotes/MetaprogrammingCpp.pdf | url-status = dead }}
* {{cite web | url = http://lcgapp.cern.ch/project/architecture/ReflectionPaper.pdf | title = Reflection support by means of template metaprogramming | first1 = Giuseppe | last1 = Attardi | first2 = Antonio | last2 = Cisternino | access-date = 2008-10-24 | archive-date = 2016-03-03 | archive-url = https://web.archive.org/web/20160303183212/http://lcgapp.cern.ch/project/architecture/ReflectionPaper.pdf | url-status = dead }}
* {{cite paperCiteSeerX | citeseerx = 10.1.1.14.5881 | title = Static data structures | first1 = Michael C. | last1 = Burton | first2 = William G. | last2 = Griswold | first3 = Andrew D. | last3 = McCulloch | first4 = Gary A. | last4 = Huber | year = 2002 }}
* {{cite web | url = http://www.codeproject.com/Articles/19989/Template-Meta-Programming-and-Number-Theory | title = Template Meta Programming and Number Theory | first = Zeeshan | last = Amjad | date = 13 August 2007 }}
* {{cite web | url = http://www.codeproject.com/Articles/20180/Template-Meta-Programming-and-Number-Theory-Part | title = Template Meta Programming and Number Theory: Part 2 | first = Zeeshan | last = Amjad | date = 24 August 2007 }}
* {{cite web | url = http://www.intelib.org/intro.html | title = A library for LISP-style programming in C++ }}
 
{{Programming paradigms navbox}}
 
[[Category:Metaprogramming]]