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