/*
 * 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.funnelPlot

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
@JsonSchemaInject(json = """
{
  "attributeTypeRules": {
    "title": "string"
  }
}
""")
class FunnelPlotOpDesc extends PythonOperatorDescriptor {

  @JsonProperty(required = true)
  @JsonSchemaTitle("X Column")
  @JsonPropertyDescription("Data column for the x-axis")
  @AutofillAttributeName
  var x: EncodableString = ""

  @JsonProperty(required = true)
  @JsonSchemaTitle("Y Column")
  @JsonPropertyDescription("Data column for the y-axis")
  @AutofillAttributeName
  var y: EncodableString = ""

  @JsonProperty(required = false)
  @JsonSchemaTitle("Color Column")
  @JsonPropertyDescription("Column to categorically colorize funnel sections")
  @AutofillAttributeName
  var color: 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(
      "Funnel Plot",
      "Visualize data in a Funnel Plot",
      OperatorGroupConstants.VISUALIZATION_FINANCIAL_GROUP
    )

  private def createPlotlyFigure(): PythonTemplateBuilder = {
    assert(x.nonEmpty)
    assert(y.nonEmpty)
    val colorArg = if (color.nonEmpty) pyb""", color=$color""" else ""
    pyb"""
         |        fig = go.Figure(px.funnel(table, x =$x, y = $y$colorArg))
         |        fig.update_layout(
         |            scene=dict(
         |                xaxis_title='X: ' + $x,
         |                yaxis_title='Y: ' + $y,
         |            ),
         |            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 pandas as pd
         |import numpy as np
         |
         |class ProcessTableOperator(UDFTableOperator):
         |    def render_error(self, error_msg):
         |        return '''<h1>Chart is not available.</h1>
         |                  <p>Reason is: {} </p>
         |               '''.format(error_msg)
         |
         |    @overrides
         |    def process_table(self, table: Table, port: int) -> Iterator[Optional[TableLike]]:
         |        if table.empty:
         |           yield {'html-content': self.render_error("input table is empty.")}
         |           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
  }
}
