# Data Generators > Introduced in Catch 2.6.0. Data generators (also known as _data driven/parametrized test cases_) let you reuse the same set of assertions across different input values. In Catch2, this means that they respect the ordering and nesting of the `TEST_CASE` and `SECTION` macros, and their nested sections are run once per each value in a generator. This is best explained with an example: ```cpp TEST_CASE("Generators") { auto i = GENERATE(1, 2, 3); SECTION("one") { auto j = GENERATE( -3, -2, -1 ); REQUIRE(j < i); } } ``` The assertion in this test case will be run 9 times, because there are 3 possible values for `i` (1, 2, and 3) and there are 3 possible values for `j` (-3, -2, and -1). There are 2 parts to generators in Catch2, the `GENERATE` macro together with the already provided generators, and the `IGenerator` interface that allows users to implement their own generators. ## Provided generators Catch2's provided generator functionality consists of three parts, * `GENERATE` macro, that serves to integrate generator expression with a test case, * 2 fundamental generators * `SingleValueGenerator` -- contains only single element * `FixedValuesGenerator` -- contains multiple elements * 5 generic generators that modify other generators * `FilterGenerator` -- filters out elements from a generator for which the predicate returns "false" * `TakeGenerator` -- takes first `n` elements from a generator * `RepeatGenerator` -- repeats output from a generator `n` times * `MapGenerator` -- returns the result of applying `Func` on elements from a different generator * `ChunkGenerator` -- returns chunks (inside `std::vector`) of n elements from a generator * 4 specific purpose generators * `RandomIntegerGenerator` -- generates random Integrals from range * `RandomFloatGenerator` -- generates random Floats from range * `RangeGenerator` -- generates all values inside an arithmetic range * `IteratorGenerator` -- copies and returns values from an iterator range > `ChunkGenerator`, `RandomIntegerGenerator`, `RandomFloatGenerator` and `RangeGenerator` were introduced in Catch 2.7.0. > `IteratorGenerator` was introduced in Catch 2.10.0. The generators also have associated helper functions that infer their type, making their usage much nicer. These are * `value(T&&)` for `SingleValueGenerator` * `values(std::initializer_list)` for `FixedValuesGenerator` * `table(std::initializer_list>)` for `FixedValuesGenerator>` * `filter(predicate, GeneratorWrapper&&)` for `FilterGenerator` * `take(count, GeneratorWrapper&&)` for `TakeGenerator` * `repeat(repeats, GeneratorWrapper&&)` for `RepeatGenerator` * `map(func, GeneratorWrapper&&)` for `MapGenerator` (map `U` to `T`, deduced from `Func`) * `map(func, GeneratorWrapper&&)` for `MapGenerator` (map `U` to `T`) * `chunk(chunk-size, GeneratorWrapper&&)` for `ChunkGenerator` * `random(IntegerOrFloat a, IntegerOrFloat b)` for `RandomIntegerGenerator` or `RandomFloatGenerator` * `range(Arithemtic start, Arithmetic end)` for `RangeGenerator` with a step size of `1` * `range(Arithmetic start, Arithmetic end, Arithmetic step)` for `RangeGenerator` with a custom step size * `from_range(InputIterator from, InputIterator to)` for `IteratorGenerator` * `from_range(Container const&)` for `IteratorGenerator` > `chunk()`, `random()` and both `range()` functions were introduced in Catch 2.7.0. > `from_range` has been introduced in Catch 2.10.0 > `range()` for floating point numbers has been introduced in Catch 2.11.0 And can be used as shown in the example below to create a generator that returns 100 odd random number: ```cpp TEST_CASE("Generating random ints", "[example][generator]") { SECTION("Deducing functions") { auto i = GENERATE(take(100, filter([](int i) { return i % 2 == 1; }, random(-100, 100)))); REQUIRE(i > -100); REQUIRE(i < 100); REQUIRE(i % 2 == 1); } } ``` Apart from registering generators with Catch2, the `GENERATE` macro has one more purpose, and that is to provide simple way of generating trivial generators, as seen in the first example on this page, where we used it as `auto i = GENERATE(1, 2, 3);`. This usage converted each of the three literals into a single `SingleValueGenerator` and then placed them all in a special generator that concatenates other generators. It can also be used with other generators as arguments, such as `auto i = GENERATE(0, 2, take(100, random(300, 3000)));`. This is useful e.g. if you know that specific inputs are problematic and want to test them separately/first. **For safety reasons, you cannot use variables inside the `GENERATE` macro. This is done because the generator expression _will_ outlive the outside scope and thus capturing references is dangerous. If you need to use variables inside the generator expression, make sure you thought through the lifetime implications and use `GENERATE_COPY` or `GENERATE_REF`.** > `GENERATE_COPY` and `GENERATE_REF` were introduced in Catch 2.7.1. You can also override the inferred type by using `as` as the first argument to the macro. This can be useful when dealing with string literals, if you want them to come out as `std::string`: ```cpp TEST_CASE("type conversion", "[generators]") { auto str = GENERATE(as{}, "a", "bb", "ccc"); REQUIRE(str.size() > 0); } ``` ## Generator interface You can also implement your own generators, by deriving from the `IGenerator` interface: ```cpp template struct IGenerator : GeneratorUntypedBase { // via GeneratorUntypedBase: // Attempts to move the generator to the next element. // Returns true if successful (and thus has another element that can be read) virtual bool next() = 0; // Precondition: // The generator is either freshly constructed or the last call to next() returned true virtual T const& get() const = 0; }; ``` However, to be able to use your custom generator inside `GENERATE`, it will need to be wrapped inside a `GeneratorWrapper`. `GeneratorWrapper` is a value wrapper around a `std::unique_ptr>`. For full example of implementing your own generator, look into Catch2's examples, specifically [Generators: Create your own generator](../examples/300-Gen-OwnGenerator.cpp).