/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing,
 * software distributed under the License is distributed on an
 * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
 * KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
 * under the License.
 */

package org.apache.texera.amber.operator

import org.apache.texera.amber.core.executor.OpExecWithCode
import org.apache.texera.amber.core.tuple.Schema
import org.apache.texera.amber.core.virtualidentity.{ExecutionIdentity, WorkflowIdentity}
import org.apache.texera.amber.core.workflow.{PhysicalOp, PortIdentity, SchemaPropagationFunc}

trait PythonOperatorDescriptor extends LogicalOp {
  private def generatePythonCodeForRaisingException(ex: Throwable): String = {
    s"#EXCEPTION DURING CODE GENERATION: ${ex.getMessage}"
  }

  override def getPhysicalOp(
      workflowId: WorkflowIdentity,
      executionId: ExecutionIdentity
  ): PhysicalOp = {
    val pythonCode =
      try {
        generatePythonCode()
      } catch {
        case ex: Throwable =>
          // instead of throwing error directly, we embed the error in the code
          // this can let upper-level compiler catch the error without interrupting the schema propagation
          generatePythonCodeForRaisingException(ex)
      }
    val physicalOp = if (asSource()) {
      PhysicalOp.sourcePhysicalOp(
        workflowId,
        executionId,
        operatorIdentifier,
        OpExecWithCode(pythonCode, "python")
      )
    } else {
      PhysicalOp.oneToOnePhysicalOp(
        workflowId,
        executionId,
        operatorIdentifier,
        OpExecWithCode(pythonCode, "python")
      )
    }

    physicalOp
      .withInputPorts(operatorInfo.inputPorts)
      .withOutputPorts(operatorInfo.outputPorts)
      .withParallelizable(parallelizable())
      .withPropagateSchema(SchemaPropagationFunc(inputSchemas => getOutputSchemas(inputSchemas)))
  }

  def parallelizable(): Boolean = false

  def asSource(): Boolean = false

  /**
    * This method is to be implemented to generate the actual Python source code
    * based on operators predicates.
    *
    * @return a String representation of the executable Python source code.
    */
  def generatePythonCode(): String

  def getOutputSchemas(inputSchemas: Map[PortIdentity, Schema]): Map[PortIdentity, Schema]

}
