Collections with C++/WinRT

Internally, a Windows Runtime collection has a lot of complicated moving parts. But when you want to pass a collection object to a Windows Runtime function, or to implement your own collection properties and collection types, there are functions and base classes in C++/WinRT to support you. These features take the complexity out of your hands, and save you a lot of overhead in time and effort.

IVector is the Windows Runtime interface implemented by any random-access collection of elements. If you were to implement IVector yourself, you'd also need to implement IIterable, IVectorView, and IIterator. Even if you need a custom collection type, that's a lot of work. But if you have data in a std::vector (or a std::map, or a std::unordered_map) and all you want to do is pass that to a Windows Runtime API, then you'd want to avoid doing that level of work, if possible. And avoiding it is possible, because C++/WinRT helps you to create collections efficiently and with little effort.

Also see XAML items controls; bind to a C++/WinRT collection.

Note

If you haven't installed the Windows SDK version 10.0.17763.0 (Windows 10, version 1809), or later, then you won't have access to the functions and base classes that are documented in this topic. Instead, see If you have an older version of the Windows SDK for a listing of an observable vector template that you can use instead.

Helper functions for collections

General-purpose collection, empty

This section covers the scenario where you wish to create a collection that's initially empty; and then populate it after creation.

To retrieve a new object of a type that implements a general-purpose collection, you can call the winrt::single_threaded_vector function template. The object is returned as an IVector, and that's the interface via which you call the returned object's functions and properties.

...
#include <winrt/Windows.Foundation.Collections.h>
#include <iostream>
using namespace winrt;
...
int main()
{
    winrt::init_apartment();

    Windows::Foundation::Collections::IVector<int> coll{ winrt::single_threaded_vector<int>() };
    coll.Append(1);
    coll.Append(2);
    coll.Append(3);

    for (auto const& el : coll)
    {
        std::cout << el << std::endl;
    }

    Windows::Foundation::Collections::IVectorView<int> view{ coll.GetView() };
}

As you can see in the code example above, after creating the collection you can append elements, iterate over them, and generally treat the object as you would any Windows Runtime collection object that you might have received from an API. If you need an immutable view over the collection, then you can call IVector::GetView, as shown. The pattern shown above—of creating and consuming a collection—is appropriate for simple scenarios where you want to pass data into, or get data out of, an API. You can pass an IVector, or an IVectorView, anywhere an IIterable is expected.

In the code example above, the call to winrt::init_apartment initializes COM; by default, in a multithreaded apartment.

General-purpose collection, primed from data

This section covers the scenario where you wish to create a collection and populate it at the same time.

You can avoid the overhead of the calls to Append in the previous code example. You may already have the source data, or you may prefer to populate the source data in advance of creating the Windows Runtime collection object. Here's how to do that.

auto coll1{ winrt::single_threaded_vector<int>({ 1,2,3 }) };

std::vector<int> values{ 1,2,3 };
auto coll2{ winrt::single_threaded_vector<int>(std::move(values)) };

for (auto const& el : coll2)
{
    std::cout << el << std::endl;
}

You can pass a temporary object containing your data to winrt::single_threaded_vector, as with coll1, above. Or you can move a std::vector (assuming you won't be accessing it again) into the function. In both cases, you're passing an rvalue into the function. That enables the compiler to be efficient and to avoid copying the data. If you want to know more about rvalues, see Value categories, and references to them.

If you want to bind a XAML items control to your collection, then you can. But be aware that to correctly set the ItemsControl.ItemsSource property, you need to set it to a value of type IVector of IInspectable (or of an interoperability type such as IBindableObservableVector). Here's a code example that produces a collection of a type suitable for binding, and appends an element to it.

auto bookSkus{ winrt::single_threaded_vector<Windows::Foundation::IInspectable>() };
bookSkus.Append(make<Bookstore::implementation::BookSku>(L"Moby Dick"));

You can create a Windows Runtime collection from data, and get a view on it ready to pass to an API, all without copying anything.

std::vector<float> values{ 0.1f, 0.2f, 0.3f };
IVectorView<float> view{ winrt::single_threaded_vector(std::move(values)).GetView() };

In the examples above, the collection we create can be bound to a XAML items control; but the collection isn't observable.

Observable collection

To retrieve a new object of a type that implements an observable collection, call the winrt::single_threaded_observable_vector function template with any element type. But to make an observable collection suitable for binding to a XAML items control, use IInspectable as the element type.

The object is returned as an IObservableVector, and that's the interface via which you (or the control to which it's bound) call the returned object's functions and properties.

auto bookSkus{ winrt::single_threaded_observable_vector<Windows::Foundation::IInspectable>() };

For more details, and code examples, about binding your user interface (UI) controls to an observable collection, see XAML items controls; bind to a C++/WinRT collection.

Associative collection (map)

There are associative collection versions of the two functions that we've looked at.

You can optionally prime these collections with data by passing to the function an rvalue of type std::map or std::unordered_map.

auto coll1{
    winrt::single_threaded_map<winrt::hstring, int>(std::map<winrt::hstring, int>{
        { L"AliceBlue", 0xfff0f8ff }, { L"AntiqueWhite", 0xfffaebd7 }
    })
};

std::map<winrt::hstring, int> values{
    { L"AliceBlue", 0xfff0f8ff }, { L"AntiqueWhite", 0xfffaebd7 }
};
auto coll2{ winrt::single_threaded_map<winrt::hstring, int>(std::move(values)) };

Single-threaded

The "single-threaded" in the names of these functions indicates that they don't provide any concurrency—in other words, they're not thread-safe. The mention of threads is unrelated to apartments, because the objects returned from these functions are all agile (see Agile objects in C++/WinRT). It's just that the objects are single-threaded. And that's entirely appropriate if you just want to pass data one way or the other across the application binary interface (ABI).

Base classes for collections

If, for complete flexibility, you want to implement your own custom collection, then you'll want to avoid doing that the hard way. For example, this is what a custom vector view would look like without the assistance of C++/WinRT's base classes.

...
using namespace winrt;
using namespace Windows::Foundation::Collections;
...
struct MyVectorView :
    implements<MyVectorView, IVectorView<float>, IIterable<float>>
{
    // IVectorView
    float GetAt(uint32_t const) { ... };
    uint32_t GetMany(uint32_t, winrt::array_view<float>) const { ... };
    bool IndexOf(float, uint32_t&) { ... };
    uint32_t Size() { ... };

    // IIterable
    IIterator<float> First() const { ... };
};
...
IVectorView<float> view{ winrt::make<MyVectorView>() };

Instead, it's much easier to derive your custom vector view from the winrt::vector_view_base struct template, and just implement the get_container function to expose the container holding your data.

struct MyVectorView2 :
    implements<MyVectorView2, IVectorView<float>, IIterable<float>>,
    winrt::vector_view_base<MyVectorView2, float>
{
    auto& get_container() const noexcept
    {
        return m_values;
    }

private:
    std::vector<float> m_values{ 0.1f, 0.2f, 0.3f };
};

The container returned by get_container must provide the begin and end interface that winrt::vector_view_base expects. As shown in the example above, std::vector provides that. But you can return any container that fulfils the same contract, including your own custom container.

struct MyVectorView3 :
    implements<MyVectorView3, IVectorView<float>, IIterable<float>>,
    winrt::vector_view_base<MyVectorView3, float>
{
    auto get_container() const noexcept
    {
        struct container
        {
            float const* const first;
            float const* const last;

            auto begin() const noexcept
            {
                return first;
            }

            auto end() const noexcept
            {
                return last;
            }
        };

        return container{ m_values.data(), m_values.data() + m_values.size() };
    }

private:
    std::array<float, 3> m_values{ 0.2f, 0.3f, 0.4f };
};

These are the base classes that C++/WinRT provides to help you implement custom collections.

winrt::vector_view_base

See the code examples above.

winrt::vector_base

struct MyVector :
    implements<MyVector, IVector<float>, IVectorView<float>, IIterable<float>>,
    winrt::vector_base<MyVector, float>
{
    auto& get_container() const noexcept
    {
        return m_values;
    }

    auto& get_container() noexcept
    {
        return m_values;
    }

private:
    std::vector<float> m_values{ 0.1f, 0.2f, 0.3f };
};

winrt::observable_vector_base

struct MyObservableVector :
    implements<MyObservableVector, IObservableVector<float>, IVector<float>, IVectorView<float>, IIterable<float>>,
    winrt::observable_vector_base<MyObservableVector, float>
{
    auto& get_container() const noexcept
    {
        return m_values;
    }

    auto& get_container() noexcept
    {
        return m_values;
    }

private:
    std::vector<float> m_values{ 0.1f, 0.2f, 0.3f };
};

winrt::map_view_base

struct MyMapView :
    implements<MyMapView, IMapView<winrt::hstring, int>, IIterable<IKeyValuePair<winrt::hstring, int>>>,
    winrt::map_view_base<MyMapView, winrt::hstring, int>
{
    auto& get_container() const noexcept
    {
        return m_values;
    }

private:
    std::map<winrt::hstring, int> m_values{
        { L"AliceBlue", 0xfff0f8ff }, { L"AntiqueWhite", 0xfffaebd7 }
    };
};

winrt::map_base

struct MyMap :
    implements<MyMap, IMap<winrt::hstring, int>, IMapView<winrt::hstring, int>, IIterable<IKeyValuePair<winrt::hstring, int>>>,
    winrt::map_base<MyMap, winrt::hstring, int>
{
    auto& get_container() const noexcept
    {
        return m_values;
    }

    auto& get_container() noexcept
    {
        return m_values;
    }

private:
    std::map<winrt::hstring, int> m_values{
        { L"AliceBlue", 0xfff0f8ff }, { L"AntiqueWhite", 0xfffaebd7 }
    };
};

winrt::observable_map_base

struct MyObservableMap :
    implements<MyObservableMap, IObservableMap<winrt::hstring, int>, IMap<winrt::hstring, int>, IMapView<winrt::hstring, int>, IIterable<IKeyValuePair<winrt::hstring, int>>>,
    winrt::observable_map_base<MyObservableMap, winrt::hstring, int>
{
    auto& get_container() const noexcept
    {
        return m_values;
    }

    auto& get_container() noexcept
    {
        return m_values;
    }

private:
    std::map<winrt::hstring, int> m_values{
        { L"AliceBlue", 0xfff0f8ff }, { L"AntiqueWhite", 0xfffaebd7 }
    };
};

Important APIs