DataManipulators の実装
This is a guide for contributors who want to help with Data API implementation by creating DataManipulators. An updated list of DataManipulators to be implemented can be found at SpongeCommon Issue #8.
To fully implement a DataManipulator
these steps must be followed:
Implement the
DataManipulator
itselfImplement the
ImmutableDataManipulator
When these steps are complete, the following must also be done:
Register the
Key
in theKeyRegistry
Implement the
DataProcessor
Implement the
ValueProcessor
for each value being represented by theDataManipulator
Register everything in the
SpongeSerializationRegistry
If the data applies to a block, several methods must also be mixed in to the block.
注釈
Make sure you follow our コントリビューション ガイドライン.
1. DataManipulator の実装
The naming convention for DataManipulator
implementations is the name of the interface prefixed with 「Sponge」.
So to implement the HealthData
interface, we create a class named SpongeHealthData
in the appropriate package.
For implementing the DataManipulator
first have it extend an appropriate abstract class from the
org.spongepowered.common.data.manipulator.mutable.common
package. The most generic there is AbstractData
but there are also abstractions that reduce boilerplate code even more for some special cases like
DataManipulator
s only containing a single value.
public class SpongeHealthData extends AbstractData<HealthData, ImmutableHealthData> implements HealthData {
[...]
}
There are two type arguments to the AbstractData class. The first is the interface implemented by this class, the
second is the interface implemented by the corresponding ImmutableDataManipulator
.
コンストラクタ
In most cases while implementing an abstract DataManipulator
you need to have two constructors:
One without arguments (no-args) which calls the second constructor with 「default」 values
The second constructor that takes all the values it supports.
The second constructor must
make a call to the
AbstractData
constructor, passing the class reference for the implemented interface.make sure the values passed are valid
call the
registerGettersAndSetters()
method
import static com.google.common.base.Preconditions.checkArgument;
public class SpongeHealthData {
public SpongeHealthData() {
this(DataConstants.DEFAULT_HEALTH, DataConstants.DEFAULT_HEALTH);
}
public SpongeHealthData(double currentHealth, double maxHealth) {
super(HealthData.class);
checkArgument(currentHealth >= DataConstants.MINIMUM_HEALTH && currentHealth <= (double) Float.MAX_VALUE);
checkArgument(maxHealth >= DataConstants.MINIMUM_HEALTH && maxHealth <= (double) Float.MAX_VALUE);
this.currentHealth = currentHealth;
this.maximumHealth = maxHealth;
this.registerGettersAndSetters();
}
...
}
Since we know that both current health and maximum health are bounded values, we need to make sure no values
outside of these bounds can be passed. To achieve this we use guava’s Preconditions
of which we import the
required methods statically.
注釈
Never use so-called magic values (arbitrary numbers, booleans etc) in your code. Instead, locate the
org.spongepowered.common.data.util.DataConstants
class and use a fitting constant - or create one, if
necessary.
Accessors defined by the Interface
The interface we implement specifies some methods to access Value
objects. For HealthData
, those are
health()
and maxHealth()
. Every call to those should yield a new Value
.
public MutableBoundedValue<Double> health() {
return SpongeValueFactory.boundedBuilder(Keys.HEALTH)
.minimum(DataConstants.MINIMUM_HEALTH)
.maximum(this.maximumHealth)
.defaultValue(this.maximumHealth)
.actualValue(this.currentHealth)
.build();
}
ちなみに
Since Double
is a Comparable
, we do not need to explicitly specify a comparator.
If no current value is specified, calling get()
on the Value
returns the default value.
Copying and Serialization
The two methods copy()
and asImmutable()
are not much work to implement. For both you just need to return
a mutable or an immutable data manipulator respectively, containing the same data as the current instance.
The method toContainer()
is used for serialization purposes. Use a MemoryDataContainer
as the result
and apply to it the values stored within this instance. A DataContainer
is basically a map mapping DataQuery
s
to values. Since a Key
always contains a corresponding DataQuery
, just use those by passing the Key
directly.
public DataContainer toContainer() {
return new MemoryDataContainer()
.set(Keys.HEALTH, this.currentHealth)
.set(Keys.MAX_HEALTH, this.maximumHealth);
}
registerGettersAndSetters()
A DataManipulator
also provides methods to get and set data using keys. The implementation for this is handled
by AbstractData
, but we must tell it which data it can access and how. Therefore, in the
registerGettersAndSetters()
method we need to do the following for each value:
register a
Supplier
to directly get the valueregister a
Consumer
to directly set the valueregister a
Supplier<Value>
to get the mutableValue
Supplier
and Consumer
are functional interfaces, so Java 8 Lambdas can be used.
private void setCurrentHealthIfValid(double value) {
if (value >= DataConstants.MINIMUM_HEALTH && value <= (double) Float.MAX_VALUE) {
this.currentHealth = value;
} else {
throw new IllegalArgumentException("Invalid value for current health");
}
}
private void setMaximumHealthIfValid(double value) {
if (value >= DataConstants.MINIMUM_HEALTH && value <= (double) Float.MAX_VALUE) {
this.maximumHealth = value;
} else {
throw new IllegalArgumentException("Invalid value for maximum health");
}
}
private void registerGettersAndSetters() {
registerFieldGetter(Keys.HEALTH, () -> SpongeHealthData.this.currentHealth);
registerFieldSetter(Keys.HEALTH, SpongeHealthData.this::setCurrentHealthIfValid);
registerKeyValue(Keys.HEALTH, SpongeHealthData.this::health);
registerFieldGetter(Keys.MAX_HEALTH, () -> SpongeHealthData.this.maximumHealth);
registerFieldSetter(Keys.MAX_HEALTH, SpongeHealthData.this::setMaximumHealthIfValid);
registerKeyValue(Keys.MAX_HEALTH, SpongeHealthData.this::maxHealth);
}
The Consumer
registered as field setter must perform the adequate checks to make sure the supplied value is valid.
This applies especially for DataHolder``s which won't accept negative values. If a value is invalid, an
``IllegalArgumentException
should be thrown.
ちなみに
The validity criteria for those setters are the same as for the respective Value
object, so you might delegate
the validity check to a call of this.health().set()
and just set this.currentHealth = value
if the first
line has no thrown an exception yet.
That’s it. The DataManipulator
should be done now.
2. Implement the ImmutableDataManipulator
Implementing the ImmutableDataManipulator
is similar to implementing the mutable one.
The only differences are:
The class name is formed by prefixing the mutable
DataManipulator
s name withImmutableSponge
Inherit from
ImmutableAbstractData
insteadInstead of
registerGettersAndSetters()
, the method is calledregisterGetters()
When creating ImmutableDataHolder
s or ImmutableValue
s, check if it makes sense to use the
ImmutableDataCachingUtil
. For example if you have WetData
which contains nothing more than a boolean, it
is more feasible to retain only two cached instances of ImmutableWetData
- one for each possible value. For
manipulators and values with many possible values (like SignData
) however, caching is proven to be too expensive.
ちなみに
You should declare the fields of an ImmutableDataManipulator
as final
in order to
prevent accidental changes.
3. Register the Key in the KeyRegistry
The next step is to register your Key
s to the KeyRegistry
. To do so, locate the
org.spongepowered.common.data.key.KeyRegistry
class and find the static generateKeyMap()
function.
There add a line to register (and create) your used keys.
keyMap.put("health"), makeSingleKey(Double.class, MutableBoundedValue.class, of("Health")));
keyMap.put("max_health", makeSingleKey(Double.class, MutableBoundedValue.class, of("MaxHealth")));
The keyMap
maps strings to Key
s. The string used should be the corresponding constant name from
the Keys
utility class in lowercase. The Key
itself is created by one of the static methods
provided by KeyFactory
, in most cases makeSingleKey
. makeSingleKey
requires first a class reference
for the underlying data, which in our case is a 「Double」, then a class reference for the Value
type used.
The third argument is the DataQuery
used for serialization. It is created from the statically imported
DataQuery.of()
method accepting a string. This string should also be the constant name, stripped of
underscores and capitalization changed to upper camel case.
4. DataProcessor の実装
Next up is the DataProcessor
. A DataProcessor
serves as a bridge between our DataManipulator
and
Minecraft’s objects. Whenever any data is requested from or offered to DataHolders
that exist in Vanilla
Minecraft, those calls end up being delegated to a DataProcessor
or a ValueProcessor
.
For your name, you should use the name of the DataManipulator
interface and append Processor
. Thus for HealthData
we create a HealthDataProcessor
.
In order to reduce boilerplate code, the DataProcessor
should inherit from the appropriate abstract class in
the org.spongepowered.common.data.processor.common
package. Since health can only be present on certain
entities, we can make use of the AbstractEntityDataProcessor
which is specifically targeted at Entities
based on net.minecraft.entity.Entity
. AbstractEntitySingleDataProcessor
would require less
implementation work, but cannot be used as HealthData
contains more than just one value.
public class HealthDataProcessor extends AbstractEntityDataProcessor<EntityLivingBase, HealthData, ImmutableHealthData> {
public HealthDataProcessor() {
super(EntityLivingBase.class);
}
[...]
}
Depending on which abstraction you use, the methods you have to implement may differ greatly, depending on how much implementation work already could be done in the abstract class. Generally, the methods can be categorized.
ちなみに
It is possible to create multiple DataProcessor
s for the same data. If vastly different DataHolder
s
should be supported (for example both a TileEntity
and a matching ItemStack
), it may be beneficial to
create one processor for each type of DataHolder
in order to make full use of the provided abstractions.
Make sure you follow the package structure for items, tileentities and entities.
Validation Methods
Always return a boolean value. If the method is called supports()
it should perform a general check if the supplied target generally supports the kind of data handled by our DataProcessor
.
For our HealthDataProcessor
supports()
is implemented by the AbstractEntityDataProcessor
. Per
default, it will return true if the supplied argument is an instance of the class specified when calling the
super()
constructor.
Instead, we are required to provide a doesDataExist()
method. Since the abstraction does not know how to
obtain the data, it leaves this function to be implemented. As the name says, the method should check if the data
already exists on the supported target. For the HealthDataProcessor
, this always returns true, since every
living entity always has health.
protected boolean doesDataExist(EntityLivingBase entity) {
return true;
}
Setter Methods
A setter method receives a DataHolder
of some sort and some data that should be applied to it, if possible.
The DataProcessor
interface defines a set()
method accepting a DataHolder
and a DataManipulator
which returns a DataTransactionResult
. Depending on the abstraction class used, some of the necessary
functionality might already be implemented.
In this case, the AbstractEntityDataProcessor
takes care of most of it and just requires a method to set
some values to return true
if it was successful and false
if it was not. All checks if the
DataHolder
supports the Data
is taken care of, the abstract class will just pass a Map mapping each
Key
from the DataManipulator
to its value and then construct a DataTransactionResult
depending on
whether the operation was successful or not.
protected boolean set(EntityLivingBase entity, Map<Key<?>, Object> keyValues) {
entity.getEntityAttribute(SharedMonsterAttributes.maxHealth)
.setBaseValue(((Double) keyValues.get(Keys.MAX_HEALTH)).floatValue());
entity.setHealth(((Double) keyValues.get(Keys.HEALTH)).floatValue());
return true;
}
ちなみに
To understand DataTransactionResult
s, check the corresponding docs page and refer to the
DataTransactionResult.Builder docs to create one.
警告
Especially when working with ItemStack
s it is likely that you will need to deal with NBTTagCompound
s
directly. Many NBT keys are already defined as constants in the org.spongepowered.common.data.util.NbtDataUtil
class. If your required key is not there, you need to add it in order to avoid 『magic values』 in the code.
Removal Method
The remove()
method attempts to remove data from the DataHolder
and returns a DataTransactionResult
.
Removal is not abstracted in any abstract DataProcessor
as the abstractions have no way of knowing if the data
is always present on a compatible DataHolder
(like WetData
or HealthData
) or if it may or may not be present
(like LoreData
). If the data is always present, remove()
must always fail. If it may or may not be present,
remove()
should remove it. In such cases the doesDataExist()
method should be overridden.
Since a living entity always has health, HealthData
is always present and removal therefore not supported.
Therefore we just return failNoData()
and do not override the doesDataExist()
method.
public DataTransactionResult remove(DataHolder dataHolder) {
return DataTransactionBuilder.failNoData();
}
Getter Methods
Getter methods obtain data from a DataHolder
and return an optional DataManipulator
. The
DataProcessor
interface specifies the methods from()
and createFrom()
, the difference being that
from()
will return Optional.empty()
if the data holder is compatible, but currently does not contain the
data, while createFrom()
will provide a DataManipulator
holding default values in that case.
Again, AbstractEntityDataProcessor
will provide most of the implementation for this and only requires a
method to get the actual values present on the DataHolder
. This method is only called after supports()
and doesDataExist()
both returned true, which means it is run under the assumption that the data is present.
警告
If the data may not always exist on the target DataHolder
, e.g. if the remove()
function may be successful
(see above), it is imperative that you override the doesDataExist()
method so that it returns true
if the data is present and false
if it is not.
protected Map<Key<?>, ?> getValues(EntityLivingBase entity) {
final double health = entity.getHealth();
final double maxHealth = entity.getMaxHealth();
return ImmutableMap.<Key<?>, Object>of(Keys.HEALTH, health, Keys.MAX_HEALTH, maxHealth);
}
Filler Methods
A filler method is different from a getter method in that it receives a DataManipulator
to fill with values.
These values either come from a DataHolder
or have to be deserialized from a DataContainer
. The method
returns Optional.empty()
if the DataHolder
is incompatible.
AbstractEntityDataProcessor
already handles filling from DataHolders
by creating a DataManipulator
from the holder and then merging it with the supplied manipulator, but the DataContainer
deserialization it
can not provide.
public Optional<HealthData> fill(DataContainer container, HealthData healthData) {
final Optional<Double> health = container.getDouble(Keys.HEALTH.getQuery());
final Optional<Double> maxHealth = container.getDouble(Keys.MAX_HEALTH.getQuery());
if (health.isPresent() && maxHealth.isPresent()) {
healthData.set(Keys.HEALTH, health.get());
healthData.set(Keys.MAX_HEALTH, maxHealth.get());
return Optional.of(healthData);
}
return Optional.empty();
}
The fill()
method is to return an Optional
of the altered healthData, if and only if all required data could
be obtained from the DataContainer
.
Other Methods
Depending on the abstract superclass used, some other methods may be required. For instance,
AbstractEntityDataProcessor
needs to create DataManipulator
instances in various points. It can’t do this
since it knows neither the implementation class nor the constructor to use. Therefore it utilizes an abstract
function that has to be provided by the final implementation. This does nothing more than create a
DataManipulator
with default data.
If you implemented your DataManipulator
as recommended, you can just use the no-args constructor.
protected HealthData createManipulator() {
return new SpongeHealthData();
}
5. ValueProcessor の実装
Not only a DataManipulator
may be offered to a DataHolder
, but also a keyed Value
on its own.
Therefore, you need to provide at least one ValueProcessor
for every Key
present in your
DataManipulator
. A ValueProcessor
is named after the constant name of its Key
in the Keys
class
in a fashion similar to its DataQuery
. The constant name is stripped of underscores, used in upper camel case
and then suffixed with ValueProcessor
.
A ValueProcessor
should always inherit from AbstractSpongeValueProcessor
, which already will handle a
portion of the supports()
checks based on the type of the DataHolder
. For Keys.HEALTH
, we’ll create
and construct HealthValueProcessor
as follows.
public class HealthValueProcessor extends AbstractSpongeValueProcessor<EntityLivingBase, Double,
MutableBoundedValue<Double> {
public HealthValueProcessor() {
super(EntityLivingBase.class, Keys.HEALTH);
}
[...]
}
Now the AbstractSpongeValueProcessor
will relieve us of the necessity to check if the value is supported.
It is assumed to be supported if the target ValueContainer
is of the type EntityLivingBase
.
ちなみに
For a more fine-grained control over what EntityLivingBase
objects are supported, the
supports(EntityLivingBase)
method can be overridden.
Again, most work is done by the abstraction class. We just need to implement two helper methods for creating
a Value
and its immutable counterpart and three methods to get, set and remove data.
protected MutableBoundedValue<Double> constructValue(Double value) {
return SpongeValueFactory.boundedBuilder(Keys.HEALTH)
.minimum(DataConstants.MINIMUM_HEALTH)
.maximum((double) Float.MAX_VALUE)
.defaultValue(DataConstants.DEFAULT_HEALTH)
.actualValue(value)
.build();
}
protected ImmutableValue<Double> constructImmutableValue(Double value) {
return constructValue(value).asImmutable();
}
protected Optional<Double> getVal(EntityLivingBase container) {
return Optional.of((double) container.getHealth());
}
Since it is impossible for an EntityLivingBase
to not have health, this method will never return
Optional.empty()
.
protected boolean set(EntityLivingBase container, Double value) {
if (value >= DataConstants.MINIMUM_HEALTH && value <= (double) Float.MAX_VALUE) {
container.setHealth(value.floatValue());
return true;
}
return false;
}
The set()
method will return a boolean value indicating whether the value could successfully be set.
This implementation will reject values outside of the bounds used in our value construction methods above.
public DataTransactionResult removeFrom(ValueContainer<?> container) {
return DataTransactionBuilder.failNoData();
}
Since the data is guaranteed to be always present, attempts to remove it will just fail.
6. Register Processors
In order for Sponge to be able to use our manipulators and processors, we need to register them. This is done
in the org.spongepowered.common.data.SpongeSerializationRegistry
class. In the setupSerialization
method
there are two large blocks of registrations to which we add our processors.
DataProcessors
A DataProcessor
is registered alongside the interface and implementation classes of the DataManipulator
it
handles. For every pair of mutable / immutable DataManipulator
s at least one DataProcessor
must be registered.
dataRegistry.registerDataProcessorAndImpl(HealthData.class, SpongeHealthData.class,
ImmutableHealthData.class, ImmutableSpongeHealthData.class,
new HealthDataProcessor());
ValueProcessors
Value processors are registered at the bottom of the very same function. For each Key
multiple processors
can be registered by subsequent calls of the registerValueProcessor()
method.
dataRegistry.registerValueProcessor(Keys.HEALTH, new HealthValueProcessor());
dataRegistry.registerValueProcessor(Keys.MAX_HEALTH, new MaxHealthValueProcessor());
Implementing Block Data
Block data is somewhat different from other types of data in that it is implemented by mixing in to the block itself.
There are several methods in org.spongepowered.mixin.core.block.MixinBlock
that must be overridden to implement
data for blocks.
@Mixin(BlockHorizontal.class)
public abstract class MixinBlockHorizontal extends MixinBlock {
[...]
}
supports()
should return true
if either the ImmutableDataManipulator
interface is assignable from the
Class
passed in as the argument, or the superclass supports it.
@Override
public boolean supports(Class<? extends ImmutableDataManipulator<?, ?>> immutable) {
return super.supports(immutable) || ImmutableDirectionalData.class.isAssignableFrom(immutable);
}
getStateWithData()
should return a new BlockState
with the data from the ImmutableDataManipulator
applied
to it. If the manipulator is not directly supported, the method should delegate to the superclass.
@Override
public Optional<BlockState> getStateWithData(IBlockState blockState, ImmutableDataManipulator<?, ?> manipulator) {
if (manipulator instanceof ImmutableDirectionalData) {
final Direction direction = ((ImmutableDirectionalData) manipulator).direction().get();
final EnumFacing facing = DirectionResolver.getFor(direction);
return Optional.of((BlockState) blockState.withProperty(BlockHorizontal.FACING, facing));
}
return super.getStateWithData(blockState, manipulator);
}
getStateWithValue()
is the equivalent of getStateWithData()
, but works with single Key
s.
@Override
public <E> Optional<BlockState> getStateWithValue(IBlockState blockState, Key<? extends BaseValue<E>> key, E value) {
if (key.equals(Keys.DIRECTION)) {
final Direction direction = (Direction) value;
final EnumFacing facing = DirectionResolver.getFor(direction);
return Optional.of((BlockState) blockState.withProperty(BlockHorizontal.FACING, facing));
}
return super.getStateWithValue(blockState, key, value);
}
Finally, getManipulators()
should return a list of all ImmutableDataManipulator
s the block supports, along with
the current values for the provided IBlockState
. It should include all ImmutableDataManipulator
s from the
superclass.
@Override
public List<ImmutableDataManipulator<?, ?>> getManipulators(IBlockState blockState) {
return ImmutableList.<ImmutableDataManipulator<?, ?>>builder()
.addAll(super.getManipulators(blockState))
.add(new ImmutableSpongeDirectionalData(DirectionResolver.getFor(blockState.getValue(BlockHorizontal.FACING))))
.build();
}
Further Information
With Data
being a rather abstract concept in Sponge, it is hard to give general directions on how to
acquire the needed data from the Minecraft classes itself. It may be helpful to take a look at already
implemented processors similar to the one you are working on to get a better understanding of how it should work.
If you are stuck or are unsure about certain aspects, go visit the #spongedev
IRC channel, the forums, or
open up an Issue on GitHub. Be sure to check the Data Processor Implementation Checklist for general
contribution requirements.