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+# Data Generators
+
+> Introduced in Catch2 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, 3, 5);
+    REQUIRE(is_odd(i));
+}
+```
+
+The "Generators" `TEST_CASE` will be entered 3 times, and the value of
+`i` will be 1, 3, and 5 in turn. `GENERATE`s can also be used multiple
+times at the same scope, in which case the result will be a cartesian
+product of all elements in the generators. This means that in the snippet
+below, the test case will be run 6 (2\*3) times.
+
+```cpp
+TEST_CASE("Generators") {
+    auto i = GENERATE(1, 2);
+    auto j = GENERATE(3, 4, 5);
+}
+```
+
+There are 2 parts to generators in Catch2, the `GENERATE` macro together
+with the already provided generators, and the `IGenerator<T>` interface
+that allows users to implement their own generators.
+
+
+## Combining `GENERATE` and `SECTION`.
+
+`GENERATE` can be seen as an implicit `SECTION`, that goes from the place
+`GENERATE` is used, to the end of the scope. This can be used for various
+effects. The simplest usage is shown below, where the `SECTION` "one"
+runs 4 (2\*2) times, and `SECTION` "two" is run 6 times (2\*3).
+
+```cpp
+TEST_CASE("Generators") {
+    auto i = GENERATE(1, 2);
+    SECTION("one") {
+        auto j = GENERATE(-3, -2);
+        REQUIRE(j < i);
+    }
+    SECTION("two") {
+        auto k = GENERATE(4, 5, 6);
+        REQUIRE(i != k);
+    }
+}
+```
+
+The specific order of the `SECTION`s will be "one", "one", "two", "two",
+"two", "one"...
+
+
+The fact that `GENERATE` introduces a virtual `SECTION` can also be used
+to make a generator replay only some `SECTION`s, without having to
+explicitly add a `SECTION`. As an example, the code below reports 3
+assertions, because the "first" section is run once, but the "second"
+section is run twice.
+
+```cpp
+TEST_CASE("GENERATE between SECTIONs") {
+    SECTION("first") { REQUIRE(true); }
+    auto _ = GENERATE(1, 2);
+    SECTION("second") { REQUIRE(true); }
+}
+```
+
+This can lead to surprisingly complex test flows. As an example, the test
+below will report 14 assertions:
+
+```cpp
+TEST_CASE("Complex mix of sections and generates") {
+    auto i = GENERATE(1, 2);
+    SECTION("A") {
+        SUCCEED("A");
+    }
+    auto j = GENERATE(3, 4);
+    SECTION("B") {
+        SUCCEED("B");
+    }
+    auto k = GENERATE(5, 6);
+    SUCCEED();
+}
+```
+
+> The ability to place `GENERATE` between two `SECTION`s was [introduced](https://github.com/catchorg/Catch2/issues/1938) in Catch2 2.13.0.
+
+## 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<T>` -- contains only single element
+  * `FixedValuesGenerator<T>` -- contains multiple elements
+* 5 generic generators that modify other generators
+  * `FilterGenerator<T, Predicate>` -- filters out elements from a generator
+  for which the predicate returns "false"
+  * `TakeGenerator<T>` -- takes first `n` elements from a generator
+  * `RepeatGenerator<T>` -- repeats output from a generator `n` times
+  * `MapGenerator<T, U, Func>` -- returns the result of applying `Func`
+  on elements from a different generator
+  * `ChunkGenerator<T>` -- returns chunks (inside `std::vector`) of n elements from a generator
+* 4 specific purpose generators
+  * `RandomIntegerGenerator<Integral>` -- generates random Integrals from range
+  * `RandomFloatGenerator<Float>` -- generates random Floats from range
+  * `RangeGenerator<T>(first, last)` -- generates all values inside a `[first, last)` arithmetic range
+  * `IteratorGenerator<T>` -- copies and returns values from an iterator range
+
+> `ChunkGenerator<T>`, `RandomIntegerGenerator<Integral>`, `RandomFloatGenerator<Float>` and `RangeGenerator<T>` were introduced in Catch2 2.7.0.
+
+> `IteratorGenerator<T>` was introduced in Catch2 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<T>`
+* `values(std::initializer_list<T>)` for `FixedValuesGenerator<T>`
+* `table<Ts...>(std::initializer_list<std::tuple<Ts...>>)` for `FixedValuesGenerator<std::tuple<Ts...>>`
+* `filter(predicate, GeneratorWrapper<T>&&)` for `FilterGenerator<T, Predicate>`
+* `take(count, GeneratorWrapper<T>&&)` for `TakeGenerator<T>`
+* `repeat(repeats, GeneratorWrapper<T>&&)` for `RepeatGenerator<T>`
+* `map(func, GeneratorWrapper<T>&&)` for `MapGenerator<T, U, Func>` (map `U` to `T`, deduced from `Func`)
+* `map<T>(func, GeneratorWrapper<U>&&)` for `MapGenerator<T, U, Func>` (map `U` to `T`)
+* `chunk(chunk-size, GeneratorWrapper<T>&&)` for `ChunkGenerator<T>`
+* `random(IntegerOrFloat a, IntegerOrFloat b)` for `RandomIntegerGenerator` or `RandomFloatGenerator`
+* `range(Arithmetic start, Arithmetic end)` for `RangeGenerator<Arithmetic>` with a step size of `1`
+* `range(Arithmetic start, Arithmetic end, Arithmetic step)` for `RangeGenerator<Arithmetic>` with a custom step size
+* `from_range(InputIterator from, InputIterator to)` for `IteratorGenerator<T>`
+* `from_range(Container const&)` for `IteratorGenerator<T>`
+
+> `chunk()`, `random()` and both `range()` functions were introduced in Catch2 2.7.0.
+
+> `from_range` has been introduced in Catch2 2.10.0
+
+> `range()` for floating point numbers has been introduced in Catch2 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<int>` 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 Catch2 2.7.1.
+
+You can also override the inferred type by using `as<type>` 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<std::string>{}, "a", "bb", "ccc");
+    REQUIRE(str.size() > 0);
+}
+```
+
+
+### Random number generators: details
+
+> This section applies from Catch2 3.5.0. Before that, random generators
+> were a thin wrapper around distributions from `<random>`.
+
+All of the `random(a, b)` generators in Catch2 currently generate uniformly
+distributed number in closed interval \[a; b\]. This  is different from
+`std::uniform_real_distribution`, which should return numbers in interval
+\[a; b) (but due to rounding can end up returning b anyway), but the
+difference is intentional, so that `random(a, a)` makes sense. If there is
+enough interest from users, we can provide API to pick any of CC, CO, OC,
+or OO ranges.
+
+Unlike `std::uniform_int_distribution`, Catch2's generators also support
+various single-byte integral types, such as `char` or `bool`.
+
+
+#### Reproducibility
+
+Given the same seed, the output from the integral generators is fully
+reproducible across different platforms.
+
+For floating point generators, the situation is much more complex.
+Generally Catch2 only promises reproducibility (or even just correctness!)
+on platforms that obey the IEEE-754 standard. Furthermore, reproducibility
+only applies between binaries that perform floating point math in the
+same way, e.g. if you compile a binary targetting the x87 FPU and another
+one targetting SSE2 for floating point math, their results will vary.
+Similarly, binaries compiled with compiler flags that relax the IEEE-754
+adherence, e.g. `-ffast-math`, might provide different results than those
+compiled for strict IEEE-754 adherence.
+
+Finally, we provide zero guarantees on the reproducibility of generating
+`long double`s, as the internals of `long double` varies across different
+platforms.
+
+
+
+## Generator interface
+
+You can also implement your own generators, by deriving from the
+`IGenerator<T>` interface:
+
+```cpp
+template<typename T>
+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;
+
+    // Returns user-friendly string showing the current generator element
+    // Does not have to be overridden, IGenerator provides default implementation
+    virtual std::string stringifyImpl() const;
+};
+```
+
+However, to be able to use your custom generator inside `GENERATE`, it
+will need to be wrapped inside a `GeneratorWrapper<T>`.
+`GeneratorWrapper<T>` is a value wrapper around a
+`Catch::Detail::unique_ptr<IGenerator<T>>`.
+
+For full example of implementing your own generator, look into Catch2's
+examples, specifically
+[Generators: Create your own generator](../examples/300-Gen-OwnGenerator.cpp).
+
+
+### Handling empty generators
+
+The generator interface assumes that a generator always has at least one
+element. This is not always true, e.g. if the generator depends on an external
+datafile, the file might be missing.
+
+There are two ways to handle this, depending on whether you want this
+to be an error or not.
+
+ * If empty generator **is** an error, throw an exception in constructor.
+ * If empty generator **is not** an error, use the [`SKIP`](skipping-passing-failing.md#skipping-test-cases-at-runtime) in constructor.
+
+
+
+---
+
+[Home](Readme.md#top)