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EnTT
3.8.1
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EnTT is a header-only, tiny and easy to use entity-component system (and much more) written in modern C++.
The entity-component-system (also known as ECS) is an architectural pattern used mostly in game development.
EnTT offers a bitset-free entity-component system that doesn't require users to specify the set of components neither at compile-time nor at runtime.
This is why users can instantiate the core class simply like:
In place of its more annoying and error-prone counterpart:
Furthermore, it isn't necessary to announce the existence of a component type. When the time comes, just use it and that's all.
EnTT is designed as a container that can be used at any time just as a vector or any other tool would be used. It doesn't attempt in any way to take over on the user code base, nor to control its main loop or process scheduling.
Unlike other more or less known models, it makes use of independent pools. This has some advantages and disadvantages. The main purpose is to provide a fully customizable tool, where users have the freedom to define pools and opaque proxies for types with specific requirements.
The library provides a default implementation for many things and a mixin model that allows users to completely replace or even just enrich the pool dedicated to one or more components.
The built-in signal support is an example of that: defined as a mixin, it's easily disabled if not needed. Similarly, poly storage is another example of how everything is customizable down to the smallest detail.
EnTT is entirely designed around the principle that users have to pay only for what they want.
When it comes to using an entity-component system, the tradeoff is usually between performance and memory usage. The faster it is, the more memory it uses. Even worse, some approaches tend to heavily affect other functionalities like the construction and destruction of components to favor iterations, even when it isn't strictly required. In fact, slightly worse performance along non-critical paths are the right price to pay to reduce memory usage and have overall better perfomance sometimes and I've always wondered why this kind of tools do not leave me the choice.
EnTT follows a completely different approach. It gets the best out from the basic data structures and gives users the possibility to pay more for higher performance where needed.
So far, this choice has proven to be a good one and I really hope it can be for many others besides me.
EnTT is such that a T** pointer (or whatever a custom pool returns) is always available to directly access all the instances of a given component type T.
I cannot say whether it will be useful or not to the reader, but it's worth to mention it since it's one of the corner stones of this library.
Many of the tools described below give the possibility to get this information and have been designed around this need.
The rest is experimentation and the desire to invent something new, hoping to have succeeded.
The registry to store, the views and the groups to iterate. That's all.
An entity (the E of an ECS) is an opaque identifier that users should use as-is. Inspecting an identifier isn't recommended since its format can change in future and a registry has all the functionalities to query them out-of-the-box. The type entt::entity implements the concept of entity identifier.
Components (the C of an ECS) must be both move constructible and move assignable. They are list initialized by using the parameters provided to construct the component itself. No need to register components or their types neither with the registry nor with the entity-component system at all.
Systems (the S of an ECS) can be plain functions, functors, lambdas and so on. It's not required to announce them in any case and have no requirements.
The following sections explain in short how to use the entity-component system, the core part of the whole library.
The project is composed of many other classes in addition to those describe below. For more details, please refer to the inline documentation.
In EnTT, pools of components are made available through a specialized version of a sparse set.
Each pool contains all the instances of a single component, as well as all the entities to which it's assigned. Sparse arrays are also paged to avoid wasting memory in some cases while packed arrays are not for obvious reasons.
Pools also make available at any time a pointer to the packed lists of entities and components they contain, in addition to the number of elements in use. For this reason, pools can rearrange their items in order to keep the internal arrays tightly packed and maximize performance.
At the moment, it's possible to specialize pools within certain limits, although a more flexible and user-friendly model is under development.
A registry can store and manage entities, as well as create views and groups to iterate the underlying data structures.
The class template basic_registry lets users decide what's the preferred type to represent an entity. Because std::uint32_t is large enough for almost all the cases, there exists also the enum class entt::entity that wraps it and the alias entt::registry for entt::basic_registry<entt::entity>.
Entities are represented by entity identifiers. An entity identifier carries information about the entity itself and its version.
User defined identifiers can be introduced through enum classes and class types that define an entity_type member of type std::uint32_t or std::uint64_t.
A registry is used both to construct and to destroy entities:
The create member function accepts also a hint and has an overload that gets two iterators and can be used to generate multiple entities at once efficiently. Similarly, the destroy member function works also with a range of entities:
In addition to offering an overload to force the version upon destruction. Note that this function removes all components from an entity before releasing its identifier. There exists also a lighter alternative that only releases the elements without poking in any pool, for use with orphaned entities:
As with the destroy function, also in this case entity ranges are supported and it's possible to force the version during release.
In both cases, when an identifier is released, the registry can freely reuse it internally. In particular, the version of an entity is increased (unless the overload that forces a version is used instead of the default one).
Users can probe an identifier to know the information it carries:
Components can be assigned to or removed from entities at any time. As for the entities, the registry offers a set of functions to use to work with components.
The emplace member function template creates, initializes and assigns to an entity the given component. It accepts a variable number of arguments to use to construct the component itself if present:
The default storage detects aggregate types internally and exploits aggregate initialization when possible.
Therefore, it's not strictly necessary to define a constructor for each type, in accordance with the rules of the language.
On the other hand, insert works with ranges and can be used to:
If an entity already has the given component, the replace and patch member function templates can be used to update it:
When it's unknown whether an entity already owns an instance of a component, emplace_or_replace is the function to use instead:
This is a slightly faster alternative for the following snippet:
The all_of and any_of member functions may also be useful if in doubt about whether or not an entity has all the components in a set or any of them:
If the goal is to delete a component from an entity that owns it, the erase member function template is the way to go:
When in doubt whether the entity owns the component, use the remove member function instead. It behaves similarly to erase but it erases the component if and only if it exists, otherwise it returns safely to the caller:
The clear member function works similarly and can be used to either:
Finally, references to components can be retrieved simply as:
The get member function template gives direct access to the component of an entity stored in the underlying data structures of the registry. There exists also an alternative member function named try_get that returns a pointer to the component owned by an entity if any, a null pointer otherwise.
Because of how the registry works internally, it stores a bunch of signal handlers for each pool in order to notify some of its data structures on the construction and destruction of components or when an instance of a component is explicitly replaced by the user.
These signal handlers are also exposed and made available to users. These are the basic bricks to build fancy things like dependencies and reactive systems.
To get a sink to be used to connect and disconnect listeners so as to be notified on the creation of a component, use the on_construct member function:
To be notified when a component is destroyed, use the on_destroy member function instead. Finally, the on_update member function will return a sink to which to connect listeners to observe changes.
In the last case, given the way C++ works, it's also necessary to use specific member functions to allow the signal to be triggered. In particular, listeners attached to on_update will only be invoked following a call to replace or patch.
The function type of a listener should be equivalent to the following:
In all cases, listeners are provided with the registry that triggered the notification and the involved entity.
Note also that:
There are also some limitations on what a listener can and cannot do:
To a certain extent, these limitations don't apply. However, it's risky to try to force them and users should respect the limitations unless they know exactly what they are doing.
Events and therefore listeners must not be used as replacements for systems. They shouldn't contain much logic and interactions with a registry should be kept to a minimum. Moreover, the greater the number of listeners, the greater the performance hit when components are created or destroyed.
Please, refer to the documentation of the signal class to know all the features it offers.
There are many useful but less known functionalities that aren't described here, such as the connection objects or the possibility to attach listeners with a list of parameters that is shorter than that of the signal itself.
Signals are the basic tools to construct reactive systems, even if they aren't enough on their own. EnTT tries to take another step in that direction with the observer class template.
In order to explain what reactive systems are, this is a slightly revised quote from the documentation of the library that first introduced this tool, Entitas:
>Imagine you have 100 fighting units on the battlefield but only 10 of them >changed their positions. Instead of using a normal system and updating all 100 >entities depending on the position, you can use a reactive system which will >only update the 10 changed units. So efficient.
In EnTT, this means to iterating over a reduced set of entities and components with respect to what would otherwise be returned from a view or a group.
On these words, however, the similarities with the proposal of Entitas also end. The rules of the language and the design of the library obviously impose and allow different things.
An observer is initialized with an instance of a registry and a set of rules that describes what are the entities to intercept. As an example:
The class is default constructible and can be reconfigured at any time by means of the connect member function. Moreover, instances can be disconnected from the underlying registries through the disconnect member function.
The observer offers also what is needed to query the internal state and to know if it's empty or how many entities it contains. Moreover, it can return a raw pointer to the list of entities it contains.
However, the most important features of this class are that:
each member function.These aspects make the observer an incredibly powerful tool to know at any time what are the entities that matched the given rules since the last time one asked:
The snippet above is equivalent to the following:
At least as long as the observer isn't const. This means that the non-const overload of each does also reset the underlying data structure before to return to the caller, while the const overload does not for obvious reasons.
The collector is an utility aimed to generate a list of matchers (the actual rules) to use with an observer instead.
There are two types of matchers:
Updated in this case means that all listeners attached to on_update are invoked. In order for this to happen, specific functions such as patch must be used. Refer to the specific documentation for more details.
A grouping matcher supports also exclusion lists as well as single components.
Roughly speaking, an observing matcher intercepts the entities for which the given components are updated while a grouping matcher tracks the entities that have assigned the given components since the last time one asked.
If an entity already has all the components except one and the missing type is assigned to it, the entity is intercepted by a grouping matcher.
In addition, a matcher can be filtered with a where clause:
This clause introduces a way to intercept entities if and only if they are already part of a hypothetical group. If they are not, they aren't returned by the observer, no matter if they matched the given rule.
In the example above, whenever the component sprite of an entity is updated, the observer probes the entity itself to verify that it has at least position and has not velocity before to store it aside. If one of the two conditions of the filter isn't respected, the entity is discared, no matter what.
A where clause accepts a theoretically unlimited number of types as well as multiple elements in the exclusion list. Moreover, every matcher can have its own clause and multiple clauses for the same matcher are combined in a single one.
Sorting entities and components is possible with EnTT. In particular, it's feasible with an in-place algorithm that doesn't require memory allocations nor anything else and is therefore particularly convenient.
With this in mind, there are two functions that respond to slightly different needs:
Or by accessing their entities:
There exists also the possibility to use a custom sort function object for when the usage pattern is known. As an example, in case of an almost sorted pool, quick sort could be much slower than insertion sort.
In this case, instances of movement are arranged in memory so that cache misses are minimized when the two components are iterated together.
As a side note, the use of groups limits the possibility of sorting pools of components. Refer to the specific documentation for more details.
The so called helpers are small classes and functions mainly designed to offer built-in support for the most basic functionalities.
The list of helpers will grow longer as time passes and new ideas come out.
In EnTT, the entt::null variable models the concept of null entity.
The library guarantees that the following expression always returns false:
A registry rejects the null entity in all cases because it isn't considered valid. It also means that the null entity cannot own components.
The type of the null entity is internal and should not be used for any purpose other than defining the null entity itself. However, there exist implicit conversions from the null entity to identifiers of any allowed type:
Similarly, the null entity can be compared to any other identifier:
As for its integral form, the null entity only affects the entity part of an identifier and is instead completely transparent to its version.
Be aware that entt::null and entity 0 aren't the same thing. Likewise, a zero initialized entity isn't the same as entt::null. Therefore, although entt::entity{} is in some sense an alias for entity 0, none of them can be used to create a null entity.
In addition to the null entity, EnTT also models the concept of tombstone with the entt::tombstone variable.
Once created, the integral form of the two values is the same, although they affect different parts of an identifier. In fact, the tombstone uses only the version part and is completely transparent to the entity part.
Also in this case, the following expression always returns false:
Moreover, users cannot set set the tombstone version when releasing an entity:
In this case, a different version number is implicitly generated.
The type of a tombstone is internal and can change at any time. However, there exist implicit conversions from a tombstone to identifiers of any allowed type:
Similarly, the tombstone can be compared to any other identifier:
Be aware that entt::tombstone and entity 0 aren't the same thing. Likewise, a zero initialized entity isn't the same as entt::tombstone. Therefore, although entt::entity{} is in some sense an alias for entity 0, none of them can be used to create tombstones.
Sometimes it's useful to get the entity from a component instance.
This is what the entt::to_entity helper does. It accepts a registry and an instance of a component and returns the entity associated with the latter:
A null entity is returned in case the component doesn't belong to the registry.
The registry class is designed to be able to create short circuits between its functions. This simplifies the definition of dependencies between different operations.
For example, the following adds (or replaces) the component a_type whenever my_type is assigned to an entity:
Similarly, the code shown below removes a_type from an entity whenever my_type is assigned to it:
A dependency can also be easily broken as follows:
There are many other types of dependencies. In general, most of the functions that accept an entity as the first argument are good candidates for this purpose.
Sometimes it's useful to be able to directly invoke a member function of a component as a callback. It's already possible in practice but requires users to extend their classes and this may not always be possible.
The invoke helper allows to propagate the signal in these cases:
All it does is pick up the right component for the received entity and invoke the requested method, passing on the arguments if necessary.
A handle is a thin wrapper around an entity and a registry. It provides the same functions that the registry offers for working with components, such as emplace, get, patch, remove and so on. The difference being that the entity is implicitly passed to the registry.
It's default constructible as an invalid handle that contains a null registry and a null entity. When it contains a null registry, calling functions that delegate execution to the registry will cause an undefined behavior, so it's recommended to check the validity of the handle with implicit cast to bool when in doubt.
A handle is also non-owning, meaning that it can be freely copied and moved around without affecting its entity (in fact, handles happen to be trivially copyable). An implication of this is that mutability becomes part of the type.
There are two aliases that use entt::entity as their default entity: entt::handle and entt::const_handle.
Users can also easily create their own aliases for custom identifiers as:
Handles are also implicitly convertible to const handles out of the box but not the other way around.
A handle stores a non-const pointer to a registry and therefore it can do all the things that can be done with a non-const registry. On the other hand, a const handles store const pointers to registries and offer a restricted set of functionalities.
This class is intended to simplify function signatures. In case of functions that take a registry and an entity and do most of their work on that entity, users might want to consider using handles, either const or non-const.
The organizer class template offers minimal support (but sufficient in many cases) for creating an execution graph from functions and their requirements on resources.
The resulting tasks aren't executed in any case. This isn't the goal of this tool. Instead, they are returned to the user in the form of a graph that allows for safe execution.
The functions are added in order of execution to the organizer. Free functions and member functions are supported as template parameters, however there is also the possibility to pass pointers to free functions or decayed lambdas as parameters to the emplace member function:
As for free functions and member functions, these are the parameters that can be presented by their function types and that will be correctly handled:
entt::view with any possible combination of types. It will be created from the registry passed to the task and supplied directly to the function.T. It will be interpreted as context variable, which will be created within the registry and passed to the function.The function type for free functions and decayed lambdas passed as parameters to emplace is void(const void *, entt::registry &) instead. The registry is the same as provided to the task. The first parameter is an optional pointer to user defined data to provide upon registration:
In all cases, it's also possible to associate a name with the task when creating it. For example:
When a function of any type is registered with the organizer, everything it accesses is considered a resource (views are unpacked and their types are treated as resources). The constness of the type also dictates its access mode (RO/RW). In turn, this affects the resulting graph, since it influences the possibility of launching tasks in parallel.
As for the registry, if a function doesn't explicitly request it or requires a constant reference to it, it's considered a read-only access. Otherwise, it's considered as read-write access. All functions will still have the registry among their resources.
When registering a function, users can also require resources that aren't in the list of parameters of the function itself. These are declared as template parameters:
Similarly, users can override the access mode of a type again via template parameters:
In this case, even if renderable appears among the parameters of the function as not constant, it will be treated as constant as regards the generation of the task graph.
To generate the task graph, the organizer offers the graph member function:
The graph is returned in the form of an adjacency list. Each vertex offers the following features:
ro_count and rw_count: they return the number of resources accessed in read-only or read-write mode.ro_dependency and rw_dependency: useful for retrieving the type info objects associated with the parameters of the underlying function.top_level: indicates whether a node is a top level one, that is, it has no entering edges.info: returns the type info object associated with the underlying function.name: returns the name associated with the given vertex if any, a null pointer otherwise.callback: a pointer to the function to execute and whose function type is void(const void *, entt::registry &).data: optional data to provide to the callback.children: the vertices reachable from the given node, in the form of indices within the adjacency list.Since the creation of pools and resources within the registry isn't necessarily thread safe, each vertex also offers a prepare function which can be called to setup a registry for execution with the created graph:
The actual scheduling of the tasks is the responsibility of the user, who can use the preferred tool.
It is often convenient to assign context variables to a registry, so as to make it the only source of truth of an application.
This is possible by means of a member function named set to use to create a context variable from a given type. Either ctx or try_ctx can be used to retrieve the newly created instance, while unset is meant to clear the variable if needed:
The type of a context variable must be such that it's default constructible and can be moved. The set member function either creates a new instance of the context variable or overwrites an already existing one if any.
The try_ctx member function returns a pointer to the context variable if it exists, otherwise it returns a null pointer. As ctx, it supports both const and non-const types and requires a const one when used on a const registry:
Context variables can also be used to create aliases for existing variables that aren't directly managed by the registry. In this case, it's also possible to make them read-only.
To do that, the type used upon construction must be a reference type and an lvalue is necessarily provided as an argument:
Read-only aliased properties are created using const types instead:
From the point of view of the user, there are no differences between a variable that is managed by the registry and an aliased property. However, read-only variables aren't accesible as non-const references:
Aliased properties can be unset and are overwritten when set is invoked, as it happens with standard variables.
By default, EnTT keeps all pools compact when a component is removed. This is done through a swap-and-pop between the removed item and the one occupying the last position in the storage.
Unfortunately, this also inevitably leads the components to change position within the storage, making direct access almost impossible (be it via pointer or index).
However, the underlying model with its independent pools helps introduce storage with different deletion policies, so that users can best choose type by type.
In particular, the library offers out of the box support for in-place deletion, thus offering storage with completely stable pointers. To do so, it's required to specialize the component_traits class.
The definition common to all components is the following:
Where in_place_delete instructs the library on the deletion policy for a given type while ignore_if_empty selectively disables empty type optimization.
The component_traits class template is sfinae-friendly, it supports single- and multi-type specializations as well as feature-based ones:
This will ensure in-place deletion for the position component without further user intervention.
Pools, views and groups will adapt accordingly when they detect a storage with a different deletion policy than the default. No specific action is required from the user once in-place deletion is enabled.
The ability to achieve pointer stability for one, several or all components is a direct consequence of the design of EnTT and of its default storage.
In fact, although it contains what is commonly referred to as a packed array, the default storage is paged and doesn't suffer from invalidation of references when it runs out of space and has to reallocate.
However, this isn't enough to ensure pointer stability in case of deletion. For this reason, a stable deletion method is also offered. This one is such that the position of the elements is preserved by creating tombstones upon deletion rather than trying to fill the holes that are created.
For performance reasons, EnTT will also favor storage compaction in all cases, although often accessing a component occurs mostly randomly or traversing pools in a non-linear order on the user side (as in the case of a hierarchy).
In other words, pointer stability is not automatic but is enabled on request. To have it at the project level and for all components, it's required to partially specialize the component_traits class for all possible types:
Because of how C++ works, this specialization will obviously have to be visible every time operations are performed on a storage.
EnTT doesn't attempt in any way to offer built-in methods with hidden or unclear costs to facilitate the creation of hierarchies.
There are various solutions to the problem, such as using the following class:
However, it should be pointed out that the possibility of having stable pointers for one, many or all types solves the problem of hierarchies at the root in many cases.
In fact, if a certain type of component is visited mainly in random order or according to hierarchical relationships, using direct pointers has many advantages:
Furthermore, it's quite common for a group of elements to be created close in time and therefore fallback into adjacent positions, thus favoring locality even on random accesses. Locality that won't be sacrificed over time given the stability of storage positions, with undoubted performance advantages.
Of course, the cost moves to linear iterations, where views and groups will have to identify (and discard) all tombstones. However, once considered the benefits, from performance to ease of use, and given the many optimizations that make this cost negligible, this is configured as one of the most convenient solutions and certainly something to take into consideration.
The range-destroy functionality offers an improved path under the hood. To understand it, let's try to describe what problem it tries to solve.
This function accepts two iterators that point to the beginning and end of a range of entities. If the iterators are those returned from a view, this pair cannot be passed to the first storage asking to remove all entities and then to all other storage. This is because the range may be empty when passed to the second pool, as not all of those entities still own all the components iterated from the view itself.
As a result, only one component is removed and no entities are destroyed.
To avoid this, in many cases the registry doesn't pass the range to all pools. Instead, it iterates the range and passes an entity at a time to all pools.
It goes without saying that the latter is slightly slower than the former.
On the other side, the destroy function also uses is_iterator_type under the hood to detect dangerous iterators. Whenever possible, it still chooses the fastest path.
This means that performance will improve if, for example, two iterators returned from an std::vector are used or, more in general, with all iterators that are not part of EnTT.
Unfortunately, this risks falling into the error described above in some corner cases. In particular, where an iterator is used that is not defined by EnTT but which uses one of the latter within it.
It's quite unlikely to happen even in large software. However, the library offers a solution also in this case, so as to allow for custom iterators and better performance at the same time.
In particular, it's necessary to either expose the member type iterator_type and declare that an iterator from EnTT is used internally or specialize the is_iterator_type class to drive the choice of the destroy function.
In both cases, the aim is to not choose the optimized route if it can cause problems.
With a good chance, the last note can be ignored and there will never be a need to do the above even after writing millions of lines of code.
However, it's good to know how to exploit the destroy function to get the best out of it.
EnTT takes full advantage of what the language offers at compile-time.
However, by combining these feature with a tool for static polymorphism, it's also possible to have opaque proxies to work with type-less pools at runtime.
These objects are returned by the storage member function, which accepts a type_info object as an argument rather than a compile-time type (the same returned by the visit member function):
By default and to stay true with the philosophy of the library, the API of a proxy is minimal and doesn't allow users to do much.
However, it's also completely customizable in a generic way and with the possibility of defining specific behaviors for given types.
This section won't go into detail on how to define a poly storage to get all the possible functionalities out of it. EnTT already contains enough snippets to get inspiration from, both in the test suite and in the example folder.
In short, users will have to define their own concepts (see the entt::poly documentation for this) and register them via the poly_storage_traits class template, which has been designed as sfinae-friendly for the purpose.
Once the concept that a poly storage must adhere to has been properly defined, copying an entity will be as easy as:
Where other is the entity to which the elements should be replicated.
Similarly, copying entire pools between different registries can look like this:
Where this time other represents the destination registry.
So, all in all, EnTT shifts the complexity to the one-time definition of a concept that reflects the user's needs, and then leaves room for ease of use within the codebase.
The possibility of extreme customization is the icing on the cake in this sense, allowing users to design this tool around their own requirements.
The registry class offers basic support to serialization.
It doesn't convert components to bytes directly, there wasn't the need of another tool for serialization out there. Instead, it accepts an opaque object with a suitable interface (namely an archive) to serialize its internal data structures and restore them later. The way types and instances are converted to a bunch of bytes is completely in charge to the archive and thus to final users.
The goal of the serialization part is to allow users to make both a dump of the entire registry or a narrower snapshot, that is to select only the components in which they are interested.
Intuitively, the use cases are different. As an example, the first approach is suitable for local save/restore functionalities while the latter is suitable for creating client-server applications and for transferring somehow parts of the representation side to side.
To take a snapshot of a registry, use the snapshot class:
It isn't necessary to invoke all functions each and every time. What functions to use in which case mostly depends on the goal and there is not a golden rule for that.
The entities member function makes the snapshot serialize all entities (both those still alive and those released) along with their versions.
On the other hand, the component member function is a function template the aim of which is to store aside components. The presence of a template parameter list is a consequence of a couple of design choices from the past and in the present:
There exists also another version of the component member function that accepts a range of entities to serialize. This version is a bit slower than the other one, mainly because it iterates the range of entities more than once for internal purposes. However, it can be used to filter out those entities that shouldn't be serialized for some reasons.
As an example:
Note that component stores items along with entities. It means that it works properly without a call to the entities member function.
Once a snapshot is created, there exist mainly two ways to load it: as a whole and in a kind of continuous mode.
The following sections describe both loaders and archives in details.
A snapshot loader requires that the destination registry be empty and loads all the data at once while keeping intact the identifiers that the entities originally had.
To use it, just pass to the constructor a valid registry:
It isn't necessary to invoke all functions each and every time. What functions to use in which case mostly depends on the goal and there is not a golden rule for that. For obvious reasons, what is important is that the data are restored in exactly the same order in which they were serialized.
The entities member function restores the sets of entities and the versions that they originally had at the source.
The component member function restores all and only the components specified and assigns them to the right entities. Note that the template parameter list must be exactly the same used during the serialization.
The orphans member function literally releases those entities that have no components attached. It's usually useless if the snapshot is a full dump of the source. However, in case all the entities are serialized but only few components are saved, it could happen that some of the entities have no components once restored. The best the users can do to deal with them is to release those entities and thus update their versions.
A continuous loader is designed to load data from a source registry to a (possibly) non-empty destination. The loader can accommodate in a registry more than one snapshot in a sort of continuous loading that updates the destination one step at a time.
Identifiers that entities originally had are not transferred to the target. Instead, the loader maps remote identifiers to local ones while restoring a snapshot. Because of that, this kind of loader offers a way to update automatically identifiers that are part of components (as an example, as data members or gathered in a container).
Another difference with the snapshot loader is that the continuous loader has an internal state that must persist over time. Therefore, there is no reason to limit its lifetime to that of a temporary object.
Example of use:
It isn't necessary to invoke all functions each and every time. What functions to use in which case mostly depends on the goal and there is not a golden rule for that. For obvious reasons, what is important is that the data are restored in exactly the same order in which they were serialized.
The entities member function restores groups of entities and maps each entity to a local counterpart when required. In other terms, for each remote entity identifier not yet registered by the loader, it creates a local identifier so that it can keep the local entity in sync with the remote one.
The component member function restores all and only the components specified and assigns them to the right entities.
In case the component contains entities itself (either as data members of type entt::entity or as containers of entities), the loader can update them automatically. To do that, it's enough to specify the data members to update as shown in the example.
The orphans member function literally releases those entities that have no components after a restore. It has exactly the same purpose described in the previous section and works the same way.
Finally, shrink helps to purge local entities that no longer have a remote conterpart. Users should invoke this member function after restoring each snapshot, unless they know exactly what they are doing.
Archives must publicly expose a predefined set of member functions. The API is straightforward and consists only of a group of function call operators that are invoked by the snapshot class and the loaders.
In particular:
Where entt::entity is the type of the entities used by the registry.
Note that all member functions of the snapshot class make also an initial call to store aside the size of the set they are going to store. In this case, the expected function type for the function call operator is:
In addition, an archive must accept a pair of entity and component for each type to be serialized. Therefore, given a type T, the archive must contain a function call operator with the following signature:
The output archive can freely decide how to serialize the data. The register is not affected at all by the decision.
Where entt::entity is the type of the entities used by the registry. Each time the function is invoked, the archive must read the next element from the underlying storage and copy it in the given variable.
Note that all member functions of a loader class make also an initial call to read the size of the set they are going to load. In this case, the expected function type for the function call operator is:
In addition, the archive must accept a pair of references to an entity and its component for each type to be restored. Therefore, given a type T, the archive must contain a function call operator with the following signature:
Every time such an operator is invoked, the archive must read the next elements from the underlying storage and copy them in the given variables.
EnTT comes with some examples (actually some tests) that show how to integrate a well known library for serialization as an archive. It uses Cereal C++ under the hood, mainly because I wanted to learn how it works at the time I was writing the code.
The code is not production-ready and it isn't neither the only nor (probably) the best way to do it. However, feel free to use it at your own risk.
The basic idea is to store everything in a group of queues in memory, then bring everything back to the registry with different loaders.
First of all, it's worth answering a question: why views and groups?
Briefly, they're a good tool to enforce single responsibility. A system that has access to a registry can create and destroy entities, as well as assign and remove components. On the other side, a system that has access to a view or a group can only iterate, read and update entities and components.
It is a subtle difference that can help designing a better software sometimes.
More in details:
There are mainly two kinds of views: compile-time (also known as view) and runtime (also known as runtime_view).
The former requires a compile-time list of component types and can make several optimizations because of that. The latter can be constructed at runtime instead using numerical type identifiers and are a bit slower to iterate.
In both cases, creating and destroying a view isn't expensive at all since they don't have any type of initialization.
Groups come in three different flavors: full-owning groups, partial-owning groups and non-owning groups. The main difference between them is in terms of performance.
Groups can literally own one or more component types. They are allowed to rearrange pools so as to speed up iterations. Roughly speaking: the more components a group owns, the faster it is to iterate them.
A given component can belong to multiple groups only if they are nested, so users have to define groups carefully to get the best out of them.
A view behaves differently if it's constructed for a single component or if it has been created to iterate multiple components. Even the API is slightly different in the two cases.
Single component views are specialized in order to give a boost in terms of performance in all the situations. This kind of views can access the underlying data structures directly and avoid superfluous checks. There is nothing as fast as a single component view. In fact, they walk through a packed (actually paged) array of components and return them one at a time.
Single component views also offer a bunch of functionalities to get the number of entities they are going to return and a raw access to the entity list as well as to the component list. It's also possible to ask a view if it contains a given entity.
Refer to the inline documentation for all the details.
Multi component views iterate entities that have at least all the given components in their bags. During construction, these views look at the number of entities available for each component and pick up a reference to the smallest set of candidates in order to speed up iterations.
They offer fewer functionalities than single component views. In particular, a multi component view exposes utility functions to get the estimated number of entities it is going to return and to know if it contains a given entity.
Refer to the inline documentation for all the details.
There is no need to store views aside for they are extremely cheap to construct, even though valid views can be copied without problems and reused freely.
Views also return newly created and correctly initialized iterators whenever begin or end are invoked.
Views share the way they are created by means of a registry:
Filtering entities by components is also supported:
To iterate a view, either use it in a range-for loop:
Or rely on the each member functions to iterate both entities and components at once:
Note that entities can also be excluded from the parameter list when received through a callback and this can improve even further the performance during iterations.
Since they aren't explicitly instantiated, empty components aren't returned in any case.
As a side note, in the case of single component views, get accepts but doesn't strictly require a template parameter, since the type is implicitly defined. However, when the type isn't specified, for consistency with the multi component view, the instance will be returned using a tuple:
Note: prefer the get member function of a view instead of that of a registry during iterations to get the types iterated by the view itself.
Views are combined with each other to create new and more specific types.
The type returned when combining multiple views together is itself a view, more in general a multi component one.
Combining different views tries to mimic C++20 ranges:
The constness of the types is preserved and their order depends on the order in which the views are combined. Therefore, the pack in the example above will return an instance of position first and then one of velocity.
Since combining views generates views, a chain can be of arbitrary length and the above type order rules apply sequentially.
Runtime views iterate entities that have at least all the given components in their bags. During construction, these views look at the number of entities available for each component and pick up a reference to the smallest set of candidates in order to speed up iterations.
They offer more or less the same functionalities of a multi component view. However, they don't expose a get member function and users should refer to the registry that generated the view to access components. In particular, a runtime view exposes utility functions to get the estimated number of entities it is going to return and to know whether it's empty or not. It's also possible to ask a runtime view if it contains a given entity.
Refer to the inline documentation for all the details.
Runtime views are pretty cheap to construct and should not be stored aside in any case. They should be used immediately after creation and then they should be thrown away. The reasons for this go far beyond the scope of this document.
To iterate a runtime view, either use it in a range-for loop:
Or rely on the each member function to iterate entities:
Performance are exactly the same in both cases.
Filtering entities by components is also supported for this kind of views:
Note: runtime views are meant for all those cases where users don't know at compile-time what components to use to iterate entities. If possible, don't use runtime views as their performance are inferior to those of the other views.
Groups are meant to iterate multiple components at once and to offer a faster alternative to multi component views.
Groups overcome the performance of the other tools available but require to get the ownership of components and this sets some constraints on pools. On the other side, groups aren't an automatism that increases memory consumption, affects functionalities and tries to optimize iterations for all the possible combinations of components. Users can decide when to pay for groups and to what extent.
The most interesting aspect of groups is that they fit usage patterns. Other solutions around usually try to optimize everything, because it is known that somewhere within the everything there are also our usage patterns. However this has a cost that isn't negligible, both in terms of performance and memory usage. Ironically, users pay the price also for things they don't want and this isn't something I like much. Even worse, one cannot easily disable such a behavior. Groups work differently instead and are designed to optimize only the real use cases when users find they need to.
Another nice-to-have feature of groups is that they have no impact on memory consumption, put aside full non-owning groups that are pretty rare and should be avoided as long as possible.
All groups affect to an extent the creation and destruction of their components. This is due to the fact that they must observe changes in the pools of interest and arrange data correctly when needed for the types they own.
That being said, the way groups operate is beyond the scope of this document. However, it's unlikely that users will be able to appreciate the impact of groups on the other functionalities of a registry.
Groups offer a bunch of functionalities to get the number of entities they are going to return and a raw access to the entity list as well as to the component list for owned components. It's also possible to ask a group if it contains a given entity.
Refer to the inline documentation for all the details.
There is no need to store groups aside for they are extremely cheap to construct, even though valid groups can be copied without problems and reused freely.
A group performs an initialization step the very first time it's requested and this could be quite costly. To avoid it, consider creating the group when no components have been assigned yet. If the registry is empty, preparation is extremely fast. Groups also return newly created and correctly initialized iterators whenever begin or end are invoked.
To iterate groups, either use them in a range-for loop:
Or rely on the each member functions to iterate both entities and components at once:
Note that entities can also be excluded from the parameter list when received through a callback and this can improve even further the performance during iterations.
Since they aren't explicitly instantiated, empty components aren't returned in any case.
Note: prefer the get member function of a group instead of that of a registry during iterations to get the types iterated by the group itself.
A full-owning group is the fastest tool an user can expect to use to iterate multiple components at once. It iterates all the components directly, no indirection required. This type of groups performs more or less as if users are accessing sequentially a bunch of packed arrays of components all sorted identically, with no jumps nor branches.
A full-owning group is created as:
Filtering entities by components is also supported:
Once created, the group gets the ownership of all the components specified in the template parameter list and arranges their pools as needed.
Sorting owned components is no longer allowed once the group has been created. However, full-owning groups can be sorted by means of their sort member functions. Sorting a full-owning group affects all its instances.
A partial-owning group works similarly to a full-owning group for the components it owns, but relies on indirection to get components owned by other groups. This isn't as fast as a full-owning group, but it's already much faster than views when there are only one or two free components to retrieve (the most common cases likely). In the worst case, it's not slower than views anyway.
A partial-owning group is created as:
Filtering entities by components is also supported:
Once created, the group gets the ownership of all the components specified in the template parameter list and arranges their pools as needed. The ownership of the types provided via entt::get doesn't pass to the group instead.
Sorting owned components is no longer allowed once the group has been created. However, partial-owning groups can be sorted by means of their sort member functions. Sorting a partial-owning group affects all its instances.
Non-owning groups are usually fast enough, for sure faster than views and well suited for most of the cases. However, they require custom data structures to work properly and they increase memory consumption. As a rule of thumb, users should avoid using non-owning groups, if possible.
A non-owning group is created as:
Filtering entities by components is also supported:
The group doesn't receive the ownership of any type of component in this case. This type of groups is therefore the least performing in general, but also the only one that can be used in any situation to slightly improve performance.
Non-owning groups can be sorted by means of their sort member functions. Sorting a non-owning group affects all its instances.
A type of component cannot be owned by two or more conflicting groups such as:
registry.group<transform, sprite>().registry.group<transform, rotation>().However, the same type can be owned by groups belonging to the same family, also called nested groups, such as:
registry.group<sprite, transform>().registry.group<sprite, transform, rotation>().Fortunately, these are also very common cases if not the most common ones.
It allows to increase performance on a greater number of component combinations.
Two nested groups are such that they own at least one componet type and the list of component types involved by one of them is contained entirely in that of the other. More specifically, this applies independently to all component lists used to define a group.
Therefore, the rules for defining whether two or more groups are nested can be summarized as:
It means that nested groups extend their parents by adding more conditions in the form of new components.
As mentioned, the components don't necessarily have to be all owned so that two groups can be considered nested. The following definitions are fully valid:
registry.group<sprite>(entt::get<renderable>).registry.group<sprite, transform>(entt::get<renderable>).registry.group<sprite, transform>(entt::get<renderable, rotation>).Exclusion lists also play their part in this respect. When it comes to defining nested groups, an excluded component type T is treated as being an observed type not_T. Therefore, consider these two definitions:
registry.group<sprite, transform>().registry.group<sprite, transform>(entt::exclude<rotation>).They are treated as if users were defining the following groups:
group<sprite, transform>().group<sprite, transform>(entt::get<not_rotation>).Where not_rotation is an empty tag present only when rotation is not.
Because of this, to define a new group that is more restrictive than an existing one, it's enough to take the list of component types of the latter and extend it by adding new component types either owned, observed or excluded, without any precautions depending on the case.
The opposite is also true. To define a larger group, it will be enough to take an existing one and remove constraints from it, in whatever form they are expressed.
Note that the greater the number of component types involved by a group, the more restrictive it is.
Despite the extreme flexibility of nested groups which allow to independently use component types either owned, observed or excluded, the real strength of this tool lies in the possibility of defining a greater number of groups that own the same components, thus offering the best performance in more cases.
In fact, given a list of component types involved by a group, the greater the number of those owned, the greater the performance of the group itself.
As a side note, it's no longer possible to sort all groups when defining nested ones. This is because the most restrictive group shares its elements with the less restrictive ones and ordering the latter would invalidate the former.
However, given a family of nested groups, it's still possible to sort the most restrictive of them. To prevent users from having to remember which of their groups is the most restrictive, the registry class offers the sortable member function to know if a group can be sorted or not.
The registry class offers two overloads when it comes to constructing views and groups: a const version and a non-const one. The former accepts only const types as template parameters, the latter accepts both const and non-const types instead.
It means that views and groups can be constructed from a const registry and they propagate the constness of the registry to the types involved. As an example:
Consider the following definition for a non-const view instead:
In the example above, view can be used to access either read-only or writable position components while velocity components are read-only in all cases.
Similarly, these statements are all valid:
It's not possible to get non-const references to velocity components from the same view instead and these will result in compilation errors:
The each member functions also propagates constness to its return values:
A caller can still refer to the position components through a const reference because of the rules of the language that fortunately already allow it.
The same concepts apply to groups as well.
Views and groups are narrow windows on the entire list of entities. They work by filtering entities according to their components.
In some cases there may be the need to iterate all the entities still in use regardless of their components. The registry offers a specific member function to do that:
It returns to the caller all the entities that are still in use.
As a rule of thumb, consider using a view or a group if the goal is to iterate entities that have a determinate set of components. These tools are usually much faster than combining this function with a bunch of custom tests.
In all the other cases, this is the way to go.
There exists also another member function to use to retrieve orphans. An orphan is an entity that is still in use and has no assigned components.
The signature of the function is the same of each:
To test the orphanity of a single entity, use the member function orphan instead. It accepts a valid entity identifer as an argument and returns true in case the entity is an orphan, false otherwise.
In general, all these functions can result in poor performance.
each is fairly slow because of some checks it performs on each and every entity. For similar reasons, orphans can be even slower. Both functions should not be used frequently to avoid the risk of a performance hit.
Since it's possible to have completely stable storage in EnTT, it's also required that all views behave accordingly.
In general, this aspect is quite transparent to the user who doesn't have to do anything in the vast majority of cases. In particular:
The policy adopted doesn't emerge from the view type, although it's available through the storage_policy alias.
However, this can affect the feature set offered by the view itself. In the case of storage that also support tombstones, all views (even single-component ones) will always behave as a multi-type views. Therefore, for example, it won't be possible to directly access the raw representation of entities and components.
In other words, the more generic version of a view will be provided in case of stable storage, even for single components, always supported by an appropriate iteration policy.
The latter will be such that in no case will a tombstone be returned from the view itself, regardless of the iteration method. Similarly, no non-existent components will be accessed, which could result in an UB otherwise.
Most of the ECS available out there don't allow to create and destroy entities and components during iterations, nor to have pointer stability.
EnTT partially solves the problem with a few limitations:
In other terms, iterators are never invalidated. Also, component references aren't invalidated when a new element is added while they could be invalidated upon destruction due to the swap-and-pop policy, unless the type leading the iteration undergoes in-place deletion.
Consider the following example:
The each member function won't break (because iterators remain valid) nor will any reference be invalidated. Instead, more attention should be paid to the destruction of entities or the removal of components.
Use a common range-for loop and get components directly from the view or move the deletion of entities and components at the end of the function to avoid dangling pointers.
For all types that don't offer stable pointers, iterators are also invalidated and the behavior is undefined if an entity is modified or destroyed and it's not the one currently returned by the iterator nor a newly created one.
To work around it, possible approaches are:
A notable side effect of this feature is that the number of required allocations is further reduced in most of the cases.
Groups are a (much) faster alternative to views. However, the higher the performance, the greater the constraints on what is allowed and what is not.
In particular, groups add in some rare cases a limitation on the creation of components during iterations. It happens in quite particular cases. Given the nature and the scope of the groups, it isn't something in which it will happen to come across probably, but it's good to know it anyway.
First of all, it must be said that creating components while iterating a group isn't a problem at all and can be done freely as it happens with the views. The same applies to the destruction of components and entities, for which the rules mentioned above apply.
The additional limitation pops out instead when a given component that is owned by a group is iterated outside of it. In this case, adding components that are part of the group itself may invalidate the iterators. There are no further limitations to the destruction of components and entities.
Fortunately, this isn't always true. In fact, it almost never is and this happens only under certain conditions. In particular:
In other words, the limitation doesn't exist as long as a type is treated as a free type (as an example with multi component views and partial- or non-owning groups) or iterated with its own group, but it can occur if the type is used as a main type to rule on an iteration.
This happens because groups own the pools of their components and organize the data internally to maximize performance. Because of that, full consistency for owned components is guaranteed only when they are iterated as part of their groups or as free types with multi component views and groups in general.
An empty type T is such that std::is_empty_v<T> returns true. They are also the same types for which empty base optimization (EBO) is possibile.
EnTT handles these types in a special way, optimizing both in terms of performance and memory usage. However, this also has consequences that are worth mentioning.
When an empty type is detected, it's not instantiated in any case. Therefore, only the entities to which it's assigned are made available.
There doesn't exist a way to get empty types from a registry, views and groups will never return instances for them (for example, during a call to each) and some functions such as try_get or the raw access to the list of components aren't available for empty types. Finally, the sort functionality will only accepts callbacks that require to return entities rather than components:
On the other hand, iterations are faster because only the entities to which the type is assigned are considered. Moreover, less memory is used, mainly because there doesn't exist any instance of the component, no matter how many entities it is assigned to.
More in general, none of the features offered by the library is affected, but for the ones that require to return actual instances.
This optimization can be disabled for the whole application by defining the ENTT_NO_ETO macro. In this case, empty types will be treated like all other types, no matter what.
Otherwise, users can specialize the component_traits template class and in particular the ignore_if_empty alias, disabling this optimization for some types only.
In general, the entire registry isn't thread safe as it is. Thread safety isn't something that users should want out of the box for several reasons. Just to mention one of them: performance.
Views, groups and consequently the approach adopted by EnTT are the great exception to the rule. It's true that views, groups and iterators in general aren't thread safe by themselves. Because of this users shouldn't try to iterate a set of components and modify the same set concurrently. However:
X or assign and removes that component from a set of entities, another thread can safely do the same with components Y and Z and everything will work like a charm. As a trivial example, users can freely execute the rendering system and iterate the renderable entities while updating a physic component concurrently on a separate thread.This kind of entity-component systems can be used in single threaded applications as well as along with async stuff or multiple threads. Moreover, typical thread based models for ECS don't require a fully thread safe registry to work. Actually, users can reach the goal with the registry as it is while working with most of the common models.
Because of the few reasons mentioned above and many others not mentioned, users are completely responsible for synchronization whether required. On the other hand, they could get away with it without having to resort to particular expedients.
Finally, EnTT can be configured via a few compile-time definitions to make some of its parts implicitly thread-safe, roughly speaking only the ones that really make sense and can't be turned around.
In particular, when multiple instances of objects referencing the type index generator (such as the registry class) are used in different threads, then it might be useful to define ENTT_USE_ATOMIC.
See the relevant documentation for more information.
A special mention is needed for the iterators returned by views and groups. Most of the times they meet the requirements of random access iterators, in all cases they meet at least the requirements of bidirectional iterators.
In other terms, they are suitable for use with the parallel algorithms of the standard library. If it's not clear, this is a great thing.
As an example, this kind of iterators can be used in combination with std::for_each and std::execution::par to parallelize the visit and therefore the update of the components returned by a view or a group, as long as the constraints previously discussed are respected:
This can increase the throughput considerably, even without resorting to who knows what artifacts that are difficult to maintain over time.
Unfortunately, because of the limitations of the current revision of the standard, the parallel std::for_each accepts only forward iterators. This means that the default iterators provided by the library cannot return proxy objects as references and must return actual reference types instead.
This may change in the future and the iterators will almost certainly return both the entities and a list of references to their components by default sooner or later. Multi-pass guarantee won't break in any case and the performance should even benefit from it further.
Contrary to what the standard library containers offer, a const registry is generally but not completely thread safe.
In particular, one (and only one) of its const member functions isn't fully thread safe. That is the view method.
The reason for this is easy to explain. To avoid requiring types to be announced in advance, the registry lazily initializes the storage objects for the different components.
In most cases, this isn't even necessary. The absence of a storage is itself the required information. However, when building a view, all pools must necessarily exist. This makes the view member function not thread safe even in its const overload, unless all pools already exist.
Fortunately, there is also a way to instantiate storage classes early when in doubt or when there are special requirements.
Calling the prepare method is equivalent to announcing the existence of a particular storage, to avoid running into problems. For those interested, there are also alternative approaches, such as a single threaded tick for the registry warm-up, but these are not always applicable.
There are many other features and functions not listed in this document.
EnTT and in particular its ECS part is in continuous development and some things could be forgotten, others could have been omitted on purpose to reduce the size of this file. Unfortunately, some parts may even be outdated and still to be updated.
For further information, it's recommended to refer to the documentation included in the code itself or join the official channels to ask a question.
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