/*
 * 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.visualization.pieChart

import com.fasterxml.jackson.annotation.{JsonProperty, JsonPropertyDescription}
import com.kjetland.jackson.jsonSchema.annotations.{JsonSchemaInject, JsonSchemaTitle}
import org.apache.texera.amber.core.tuple.{AttributeType, Schema}
import org.apache.texera.amber.pybuilder.PythonTemplateBuilder.PythonTemplateBuilderStringContext
import org.apache.texera.amber.pybuilder.PyStringTypes.EncodableString
import org.apache.texera.amber.core.workflow.PortIdentity
import org.apache.texera.amber.operator.PythonOperatorDescriptor
import org.apache.texera.amber.operator.metadata.annotations.AutofillAttributeName
import org.apache.texera.amber.operator.metadata.{OperatorGroupConstants, OperatorInfo}
import org.apache.texera.amber.pybuilder.PythonTemplateBuilder

import javax.validation.constraints.NotNull

// type constraint: value can only be numeric
@JsonSchemaInject(json = """
{
  "attributeTypeRules": {
    "value": {
      "enum": ["integer", "long", "double"]
    }
  }
}
""")
class PieChartOpDesc extends PythonOperatorDescriptor {

  @JsonProperty(value = "value", required = true)
  @JsonSchemaTitle("Value Column")
  @JsonPropertyDescription("The value associated with slice of pie")
  @AutofillAttributeName
  @NotNull(message = "Value column cannot be empty")
  var value: EncodableString = ""

  @JsonProperty(value = "name", required = true)
  @JsonSchemaTitle("Name Column")
  @JsonPropertyDescription("The name of the slice of pie")
  @AutofillAttributeName
  @NotNull(message = "Name column cannot be empty")
  var name: EncodableString = ""

  override def getOutputSchemas(
      inputSchemas: Map[PortIdentity, Schema]
  ): Map[PortIdentity, Schema] = {
    val outputSchema = Schema()
      .add("html-content", AttributeType.STRING)
    Map(operatorInfo.outputPorts.head.id -> outputSchema)
    Map(operatorInfo.outputPorts.head.id -> outputSchema)
  }

  override def operatorInfo: OperatorInfo =
    OperatorInfo.forVisualization(
      "Pie Chart",
      "Visualize data in a Pie Chart",
      OperatorGroupConstants.VISUALIZATION_BASIC_GROUP
    )

  def manipulateTable(): PythonTemplateBuilder = {
    assert(value.nonEmpty)
    pyb"""
         |        table.dropna(subset = [$value, $name], inplace = True) #remove missing values
         |"""
  }

  def createPlotlyFigure(): PythonTemplateBuilder = {
    assert(value.nonEmpty)
    pyb"""
       |        fig = px.pie(table, names=$name, values=$value)
       |        fig.update_traces(textposition='inside', textinfo='percent+label')
       |        fig.update_layout(margin=dict(t=0, b=0, l=0, r=0))
       |"""
  }

  override def generatePythonCode(): String = {
    val finalcode =
      pyb"""
         |from pytexera import *
         |
         |import plotly.express as px
         |import plotly.graph_objects as go
         |import plotly.io
         |import numpy as np
         |
         |class ProcessTableOperator(UDFTableOperator):
         |    def render_error(self, error_msg):
         |        return '''<h1>PieChart is not available.</h1>
         |                  <p>Reason is: {} </p>
         |               '''.format(error_msg)
         |
         |    @overrides
         |    def process_table(self, table: Table, port: int) -> Iterator[Optional[TableLike]]:
         |        original_table = table
         |        if table.empty:
         |           yield {'html-content': self.render_error("input table is empty.")}
         |           return
         |        ${manipulateTable()}
         |        if table.empty:
         |           yield {'html-content': self.render_error("value column contains only non-positive numbers.")}
         |           return
         |        duplicates = table.duplicated(subset=[$name])
         |        if duplicates.any():
         |           yield {'html-content': self.render_error("duplicates in name column, need to aggregate")}
         |           return
         |        ${createPlotlyFigure()}
         |        # convert fig to html content
         |        html = plotly.io.to_html(fig, include_plotlyjs='cdn', auto_play=False)
         |        yield {'html-content': html}
         |
         |"""
    finalcode.encode
  }

}
