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Update documentation and examples for generators
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<a id="top"></a>
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# Data Generators
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# Data Generators
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_Generators are currently considered an experimental feature and their
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API can change between versions freely._
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Data generators (also known as _data driven/parametrized test cases_)
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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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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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In Catch2, this means that they respect the ordering and nesting
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of the `TEST_CASE` and `SECTION` macros.
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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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How does combining generators and test cases work might be better
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explained by an example:
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This is best explained with an example:
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```cpp
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```cpp
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TEST_CASE("Generators") {
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TEST_CASE("Generators") {
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auto i = GENERATE( range(1, 11) );
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auto i = GENERATE(1, 2, 3);
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SECTION("one") {
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SECTION( "Some section" ) {
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auto j = GENERATE( -3, -2, -1 );
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auto j = GENERATE( range( 11, 21 ) );
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REQUIRE(j < i);
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REQUIRE(i < j);
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}
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}
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}
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}
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```
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```
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the assertion will be checked 100 times, because there are 10 possible
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The assertion in this test case will be run 9 times, because there
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values for `i` (1, 2, ..., 10) and for each of them, there are 10 possible
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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` (11, 12, ..., 20).
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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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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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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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You can also combine multiple generators by concatenation:
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```cpp
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```cpp
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static int square(int x) { return x * x; }
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TEST_CASE("Generating random ints", "[example][generator]") {
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TEST_CASE("Generators 2") {
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SECTION("Deducing functions") {
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auto i = GENERATE(0, 1, -1, range(-20, -10), range(10, 20));
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auto i = GENERATE(take(100, filter([](int i) { return i % 2 == 1; }, random(-100, 100))));
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CAPTURE(i);
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REQUIRE(i > -100);
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REQUIRE(square(i) >= 0);
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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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```
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```
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This will call `square` with arguments `0`, `1`, `-1`, `-20`, ..., `-11`,
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_Note that `random` is currently not a part of the first-party generators_.
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`10`, ..., `19`.
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----------
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Because of the experimental nature of the current Generator implementation,
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Apart from registering generators with Catch2, the `GENERATE` macro has
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we won't list all of the first-party generators in Catch2. Instead you
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one more purpose, and that is to provide simple way of generating trivial
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should look at our current usage tests in
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generators, as seen in the first example on this page, where we used it
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[projects/SelfTest/UsageTests/Generators.tests.cpp](/projects/SelfTest/UsageTests/Generators.tests.cpp).
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as `auto i = GENERATE(1, 2, 3);`. This usage converted each of the three
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For implementing your own generators, you can look at their implementation in
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literals into a single `ValueGenerator<int>` and then placed them all in
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[include/internal/catch_generators.hpp](/include/internal/catch_generators.hpp).
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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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@ -14,6 +14,9 @@
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- Report: [TeamCity reporter](../examples/207-Rpt-TeamCityReporter.cpp)
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- Report: [TeamCity reporter](../examples/207-Rpt-TeamCityReporter.cpp)
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- Listener: [Listeners](../examples/210-Evt-EventListeners.cpp)
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- Listener: [Listeners](../examples/210-Evt-EventListeners.cpp)
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- Configuration: [Provide your own output streams](../examples/231-Cfg-OutputStreams.cpp)
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- Configuration: [Provide your own output streams](../examples/231-Cfg-OutputStreams.cpp)
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- Generators: [Create your own generator](../examples/300-Gen-OwnGenerator.cpp)
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- Generators: [Use variables in generator expressions](../examples/310-Gen-VariablesInGenerators.cpp)
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## Planned
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## Planned
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59
examples/300-Gen-OwnGenerator.cpp
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examples/300-Gen-OwnGenerator.cpp
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// 300-Gen-OwnGenerator.cpp
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// Shows how to define a custom generator.
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// Specifically we will implement a random number generator for integers
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// It will have infinite capacity and settable lower/upper bound
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#include <catch2/catch.hpp>
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#include <random>
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// This class shows how to implement a simple generator for Catch tests
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class RandomIntGenerator : public Catch::Generators::IGenerator<int> {
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std::minstd_rand m_rand;
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std::uniform_int_distribution<> m_dist;
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int current_number;
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public:
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RandomIntGenerator(int low, int high):
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m_rand(std::random_device{}()),
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m_dist(low, high)
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{
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static_cast<void>(next());
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}
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int const& get() const override;
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bool next() override {
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current_number = m_dist(m_rand);
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return true;
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}
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};
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// Avoids -Wweak-vtables
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int const& RandomIntGenerator::get() const {
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return current_number;
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}
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// This helper function provides a nicer UX when instantiating the generator
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// Notice that it returns an instance of GeneratorWrapper<int>, which
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// is a value-wrapper around std::unique_ptr<IGenerator<int>>.
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Catch::Generators::GeneratorWrapper<int> random(int low, int high) {
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return Catch::Generators::GeneratorWrapper<int>(std::unique_ptr<Catch::Generators::IGenerator<int>>(new RandomIntGenerator(low, high)));
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}
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// The two sections in this test case are equivalent, but the first one
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// is much more readable/nicer to use
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TEST_CASE("Generating random ints", "[example][generator]") {
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SECTION("Nice UX") {
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auto i = GENERATE(take(100, random(-100, 100)));
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REQUIRE(i >= -100);
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REQUIRE(i <= 100);
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}
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SECTION("Creating the random generator directly") {
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auto i = GENERATE(take(100, GeneratorWrapper<int>(std::unique_ptr<IGenerator<int>>(new RandomIntGenerator(-100, 100)))));
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REQUIRE(i >= -100);
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REQUIRE(i <= 100);
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}
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}
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// Compiling and running this file will result in 400 successful assertions
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72
examples/310-Gen-VariablesInGenerators.cpp
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72
examples/310-Gen-VariablesInGenerators.cpp
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// 310-Gen-VariablesInGenerator.cpp
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// Shows how to use variables when creating generators.
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// Note that using variables inside generators is dangerous and should
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// be done only if you know what you are doing, because the generators
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// _WILL_ outlive the variables -- thus they should be either captured
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// by value directly, or copied by the generators during construction.
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#include <catch2/catch.hpp>
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#include <random>
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// Lets start by implementing a parametrizable double generator
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class RandomDoubleGenerator : public Catch::Generators::IGenerator<double> {
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std::minstd_rand m_rand;
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std::uniform_real_distribution<> m_dist;
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double current_number;
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public:
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RandomDoubleGenerator(double low, double high):
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m_rand(std::random_device{}()),
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m_dist(low, high)
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{
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static_cast<void>(next());
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}
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double const& get() const override;
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bool next() override {
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current_number = m_dist(m_rand);
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return true;
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}
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};
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// Avoids -Wweak-vtables
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double const& RandomDoubleGenerator::get() const {
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return current_number;
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}
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// Also provide a nice shortcut for creating the generator
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Catch::Generators::GeneratorWrapper<double> random(double low, double high) {
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return Catch::Generators::GeneratorWrapper<double>(std::unique_ptr<Catch::Generators::IGenerator<double>>(new RandomDoubleGenerator(low, high)));
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}
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TEST_CASE("Generate random doubles across different ranges",
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"[generator][example][advanced]") {
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// Workaround for old libstdc++
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using record = std::tuple<double, double>;
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// Set up 3 ranges to generate numbers from
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auto r = GENERATE(table<double, double>({
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record{3, 4},
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record{-4, -3},
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record{10, 1000}
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}));
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// This will not compile (intentionally), because it accesses a variable
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// auto number = GENERATE(take(50, random(r.first, r.second)));
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// We have to manually register the generators instead
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// Notice that we are using value capture in the lambda, to avoid lifetime issues
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auto number = Catch::Generators::generate( CATCH_INTERNAL_LINEINFO,
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[=]{
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using namespace Catch::Generators;
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return makeGenerators(take(50, random(std::get<0>(r), std::get<1>(r))));
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}
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);
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REQUIRE(std::abs(number) > 0);
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}
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// Compiling and running this file will result in 150 successful assertions
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@ -44,6 +44,8 @@ set( SOURCES_IDIOMATIC_TESTS
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110-Fix-ClassFixture.cpp
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110-Fix-ClassFixture.cpp
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120-Bdd-ScenarioGivenWhenThen.cpp
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120-Bdd-ScenarioGivenWhenThen.cpp
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210-Evt-EventListeners.cpp
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210-Evt-EventListeners.cpp
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300-Gen-OwnGenerator.cpp
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310-Gen-VariablesInGenerators.cpp
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)
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)
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# main-s for reporter-specific test sources:
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# main-s for reporter-specific test sources:
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