mbeckerle commented on a change in pull request #651:
URL: https://github.com/apache/daffodil/pull/651#discussion_r725361996
##########
File path:
daffodil-runtime1/src/main/scala/org/apache/daffodil/layers/LayerTransformer.scala
##########
@@ -40,102 +42,41 @@ import
org.apache.daffodil.schema.annotation.props.gen.BitOrder
import org.apache.daffodil.processors.parsers.PState
import org.apache.daffodil.processors.unparsers.UState
import org.apache.daffodil.io.DirectOrBufferedDataOutputStream
+import org.apache.daffodil.processors.Evaluatable
+import org.apache.daffodil.processors.RuntimeData
import passera.unsigned.ULong
import org.apache.daffodil.processors.SequenceRuntimeData
+import org.apache.daffodil.processors.SuspendableOperation
+import org.apache.daffodil.processors.VariableRuntimeData
+import org.apache.daffodil.processors.charset.BitsCharsetJava
+import org.apache.daffodil.util.ByteBufferOutputStream
+import java.io.ByteArrayInputStream
+import java.io.EOFException
import java.io.InputStream
import java.io.OutputStream
-
-/**
- * Factory for a layer transformer.
- *
- * Responsible for digesting the various args, erroring if the wrong ones
- * are specified, and ultimately constructing the LayerTransformer
- * of the correct type with the parameters it needs.
- */
-abstract class LayerTransformerFactory(nom: String)
- extends Serializable {
-
- val name = nom.toUpperCase()
-
- def newInstance(
- maybeLayerCharsetEv: Maybe[LayerCharsetEv],
- maybeLayerLengthKind: Maybe[LayerLengthKind],
- maybeLayerLengthEv: Maybe[LayerLengthEv],
- maybeLayerLengthUnits: Maybe[LayerLengthUnits],
- maybeLayerBoundaryMarkEv: Maybe[LayerBoundaryMarkEv],
- srd: SequenceRuntimeData): LayerTransformer
-}
-
-/**
- * Transformers have factories. This lets you find the transformer factory
- * by the name obtained from dfdlx:layerTransform.
- */
-object LayerTransformerFactory {
-
- private lazy val transformerMap = new NonAllocatingMap(new HashMap[String,
LayerTransformerFactory])
-
- def register(factory: LayerTransformerFactory): Unit = {
- transformerMap.put(factory.name, factory)
- }
- /**
- * Given name, finds the factory for the transformer. SDE otherwise.
- *
- * The state is passed in order to provide diagnostic context if not found.
- */
- def find(name: String, state: ParseOrUnparseState): LayerTransformerFactory
= {
- val maybeFactory = transformerMap.get(name)
- if (maybeFactory.isEmpty) {
- val choices = transformerMap.keySet.mkString(", ")
- state.SDE("The dfdlx:layerTransform '%s' was not found. Available
choices are: %s", name, choices)
- } else {
- maybeFactory.get
- }
- }
-
- /**
- * All transformers must be registered so they are available by name.
- *
- * It is possible to package a transformer in a separate jar also, but then
- * someone has to register it by calling the register method.
- *
- * Transformers built into the primary Daffodil jars/packages should be
- * registered here.
- */
- register(Base64MIMETransformerFactory)
- register(GZIPTransformerFactory)
- register(IMFLineFoldedTransformerFactory)
- register(ICalendarLineFoldedTransformerFactory)
-
- /**
- * Arguably the above could be bundled with Daffodil.
- *
- * The transformers below really should be plugins defined
- * outside Daffodil, per DAFFODIL-1927.
- */
- register(AISPayloadArmoringTransformerFactory)
- register(FourByteSwapTransformerFactory)
-}
+import java.nio.ByteBuffer
+import java.nio.charset.Charset
/**
* Shared functionality of all LayerTransformers.
*
* A layer transformer is created at runtime as part of a single parse/unparse
call.
* Hence, they can be stateful without causing thread-safety issues.
*/
-abstract class LayerTransformer() {
+abstract class LayerTransformer(layerName: String, layerRuntimeInfo:
LayerRuntimeInfo) {
protected def wrapLayerDecoder(jis: InputStream): InputStream
- protected def wrapLimitingStream(jis: InputStream, state: PState):
InputStream
+ protected def wrapLimitingStream(jis: InputStream): InputStream
def wrapJavaInputStream(s: InputSourceDataInputStream, fInfo: FormatInfo):
InputStream = {
Review comment:
yes
##########
File path:
daffodil-runtime1/src/main/scala/org/apache/daffodil/layers/LayerTransformer.scala
##########
@@ -40,102 +42,41 @@ import
org.apache.daffodil.schema.annotation.props.gen.BitOrder
import org.apache.daffodil.processors.parsers.PState
import org.apache.daffodil.processors.unparsers.UState
import org.apache.daffodil.io.DirectOrBufferedDataOutputStream
+import org.apache.daffodil.processors.Evaluatable
+import org.apache.daffodil.processors.RuntimeData
import passera.unsigned.ULong
import org.apache.daffodil.processors.SequenceRuntimeData
+import org.apache.daffodil.processors.SuspendableOperation
+import org.apache.daffodil.processors.VariableRuntimeData
+import org.apache.daffodil.processors.charset.BitsCharsetJava
+import org.apache.daffodil.util.ByteBufferOutputStream
+import java.io.ByteArrayInputStream
+import java.io.EOFException
import java.io.InputStream
import java.io.OutputStream
-
-/**
- * Factory for a layer transformer.
- *
- * Responsible for digesting the various args, erroring if the wrong ones
- * are specified, and ultimately constructing the LayerTransformer
- * of the correct type with the parameters it needs.
- */
-abstract class LayerTransformerFactory(nom: String)
- extends Serializable {
-
- val name = nom.toUpperCase()
-
- def newInstance(
- maybeLayerCharsetEv: Maybe[LayerCharsetEv],
- maybeLayerLengthKind: Maybe[LayerLengthKind],
- maybeLayerLengthEv: Maybe[LayerLengthEv],
- maybeLayerLengthUnits: Maybe[LayerLengthUnits],
- maybeLayerBoundaryMarkEv: Maybe[LayerBoundaryMarkEv],
- srd: SequenceRuntimeData): LayerTransformer
-}
-
-/**
- * Transformers have factories. This lets you find the transformer factory
- * by the name obtained from dfdlx:layerTransform.
- */
-object LayerTransformerFactory {
-
- private lazy val transformerMap = new NonAllocatingMap(new HashMap[String,
LayerTransformerFactory])
-
- def register(factory: LayerTransformerFactory): Unit = {
- transformerMap.put(factory.name, factory)
- }
- /**
- * Given name, finds the factory for the transformer. SDE otherwise.
- *
- * The state is passed in order to provide diagnostic context if not found.
- */
- def find(name: String, state: ParseOrUnparseState): LayerTransformerFactory
= {
- val maybeFactory = transformerMap.get(name)
- if (maybeFactory.isEmpty) {
- val choices = transformerMap.keySet.mkString(", ")
- state.SDE("The dfdlx:layerTransform '%s' was not found. Available
choices are: %s", name, choices)
- } else {
- maybeFactory.get
- }
- }
-
- /**
- * All transformers must be registered so they are available by name.
- *
- * It is possible to package a transformer in a separate jar also, but then
- * someone has to register it by calling the register method.
- *
- * Transformers built into the primary Daffodil jars/packages should be
- * registered here.
- */
- register(Base64MIMETransformerFactory)
- register(GZIPTransformerFactory)
- register(IMFLineFoldedTransformerFactory)
- register(ICalendarLineFoldedTransformerFactory)
-
- /**
- * Arguably the above could be bundled with Daffodil.
- *
- * The transformers below really should be plugins defined
- * outside Daffodil, per DAFFODIL-1927.
- */
- register(AISPayloadArmoringTransformerFactory)
- register(FourByteSwapTransformerFactory)
-}
+import java.nio.ByteBuffer
+import java.nio.charset.Charset
/**
* Shared functionality of all LayerTransformers.
*
* A layer transformer is created at runtime as part of a single parse/unparse
call.
* Hence, they can be stateful without causing thread-safety issues.
*/
-abstract class LayerTransformer() {
+abstract class LayerTransformer(layerName: String, layerRuntimeInfo:
LayerRuntimeInfo) {
protected def wrapLayerDecoder(jis: InputStream): InputStream
- protected def wrapLimitingStream(jis: InputStream, state: PState):
InputStream
+ protected def wrapLimitingStream(jis: InputStream): InputStream
def wrapJavaInputStream(s: InputSourceDataInputStream, fInfo: FormatInfo):
InputStream = {
new JavaIOInputStream(s, fInfo)
}
protected def wrapLayerEncoder(jos: OutputStream): OutputStream
- protected def wrapLimitingStream(jis: OutputStream, state: UState):
OutputStream
+ protected def wrapLimitingStream(jis: OutputStream): OutputStream
def wrapJavaOutputStream(s: DataOutputStream, fInfo: FormatInfo):
OutputStream = {
Review comment:
yes
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