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  # to you under the Apache License, Version 2.0 (the
  # "License"); you may not use this file except in compliance
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  #
  #   http://www.apache.org/licenses/LICENSE-2.0
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  # "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.
  """
  This module contains operator for copying
  data from Cassandra to Google Cloud Storage in JSON format.
  """
  
  import json
  import warnings
  from base64 import b64encode
  from datetime import datetime
  from decimal import Decimal
  from tempfile import NamedTemporaryFile
  from typing import Any, Dict, Iterable, List, NewType, Optional, Sequence, Tuple, Union
  from uuid import UUID
  
  from cassandra.util import Date, OrderedMapSerializedKey, SortedSet, Time
  
  from airflow.exceptions import AirflowException
  from airflow.models import BaseOperator
  from airflow.providers.apache.cassandra.hooks.cassandra import CassandraHook
  from airflow.providers.google.cloud.hooks.gcs import GCSHook
  
  NotSetType = NewType('NotSetType', object)
  NOT_SET = NotSetType(object())
  
  
  class CassandraToGCSOperator(BaseOperator):
      """
      Copy data from Cassandra to Google Cloud Storage in JSON format
  
      Note: Arrays of arrays are not supported.
  
      :param cql: The CQL to execute on the Cassandra table.
      :type cql: str
      :param bucket: The bucket to upload to.
      :type bucket: str
      :param filename: The filename to use as the object name when uploading
          to Google Cloud Storage. A {} should be specified in the filename
          to allow the operator to inject file numbers in cases where the
          file is split due to size.
      :type filename: str
      :param schema_filename: If set, the filename to use as the object name
          when uploading a .json file containing the BigQuery schema fields
          for the table that was dumped from MySQL.
      :type schema_filename: str
      :param approx_max_file_size_bytes: This operator supports the ability
          to split large table dumps into multiple files (see notes in the
          filename param docs above). This param allows developers to specify the
          file size of the splits. Check https://cloud.google.com/storage/quotas
          to see the maximum allowed file size for a single object.
      :type approx_max_file_size_bytes: long
      :param cassandra_conn_id: Reference to a specific Cassandra hook.
      :type cassandra_conn_id: str
      :param gzip: Option to compress file for upload
      :type gzip: bool
      :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud.
      :type gcp_conn_id: str
      :param google_cloud_storage_conn_id: (Deprecated) The connection ID used to connect to Google Cloud.
          This parameter has been deprecated. You should pass the gcp_conn_id parameter instead.
      :type google_cloud_storage_conn_id: str
      :param delegate_to: The account to impersonate using domain-wide delegation of authority,
          if any. For this to work, the service account making the request must have
          domain-wide delegation enabled.
      :type delegate_to: str
      :param impersonation_chain: Optional service account to impersonate using short-term
          credentials, or chained list of accounts required to get the access_token
          of the last account in the list, which will be impersonated in the request.
          If set as a string, the account must grant the originating account
          the Service Account Token Creator IAM role.
          If set as a sequence, the identities from the list must grant
          Service Account Token Creator IAM role to the directly preceding identity, with first
          account from the list granting this role to the originating account (templated).
      :type impersonation_chain: Union[str, Sequence[str]]
      :param query_timeout: (Optional) The amount of time, in seconds, used to execute the Cassandra query.
          If not set, the timeout value will be set in Session.execute() by Cassandra driver.
          If set to None, there is no timeout.
      :type query_timeout: float | None
      """
  
      template_fields = (
          'cql',
          'bucket',
          'filename',
          'schema_filename',
          'impersonation_chain',
      )
      template_ext = ('.cql',)
      ui_color = '#a0e08c'
  
      def __init__(
          self,
          *,
          cql: str,
          bucket: str,
          filename: str,
          schema_filename: Optional[str] = None,
          approx_max_file_size_bytes: int = 1900000000,
          gzip: bool = False,
          cassandra_conn_id: str = 'cassandra_default',
          gcp_conn_id: str = 'google_cloud_default',
          google_cloud_storage_conn_id: Optional[str] = None,
          delegate_to: Optional[str] = None,
          impersonation_chain: Optional[Union[str, Sequence[str]]] = None,
          query_timeout: Union[float, None, NotSetType] = NOT_SET,
          **kwargs,
      ) -> None:
          super().__init__(**kwargs)
  
          if google_cloud_storage_conn_id:
              warnings.warn(
                  "The google_cloud_storage_conn_id parameter has been deprecated. You should pass "
                  "the gcp_conn_id parameter.",
                  DeprecationWarning,
                  stacklevel=3,
              )
              gcp_conn_id = google_cloud_storage_conn_id
  
          self.cql = cql
          self.bucket = bucket
          self.filename = filename
          self.schema_filename = schema_filename
          self.approx_max_file_size_bytes = approx_max_file_size_bytes
          self.cassandra_conn_id = cassandra_conn_id
          self.gcp_conn_id = gcp_conn_id
          self.delegate_to = delegate_to
          self.gzip = gzip
          self.impersonation_chain = impersonation_chain
          self.query_timeout = query_timeout
  
      # Default Cassandra to BigQuery type mapping
      CQL_TYPE_MAP = {
          'BytesType': 'STRING',
          'DecimalType': 'FLOAT',
          'UUIDType': 'STRING',
          'BooleanType': 'BOOL',
          'ByteType': 'INTEGER',
          'AsciiType': 'STRING',
          'FloatType': 'FLOAT',
          'DoubleType': 'FLOAT',
          'LongType': 'INTEGER',
          'Int32Type': 'INTEGER',
          'IntegerType': 'INTEGER',
          'InetAddressType': 'STRING',
          'CounterColumnType': 'INTEGER',
          'DateType': 'TIMESTAMP',
          'SimpleDateType': 'DATE',
          'TimestampType': 'TIMESTAMP',
          'TimeUUIDType': 'STRING',
          'ShortType': 'INTEGER',
          'TimeType': 'TIME',
          'DurationType': 'INTEGER',
          'UTF8Type': 'STRING',
          'VarcharType': 'STRING',
      }
  
      def execute(self, context: Dict[str, str]):
          hook = CassandraHook(cassandra_conn_id=self.cassandra_conn_id)
  
          query_extra = {}
          if self.query_timeout is not NOT_SET:
              query_extra['timeout'] = self.query_timeout
  
          cursor = hook.get_conn().execute(self.cql, **query_extra)
  
          files_to_upload = self._write_local_data_files(cursor)
  
          # If a schema is set, create a BQ schema JSON file.
          if self.schema_filename:
              files_to_upload.update(self._write_local_schema_file(cursor))
  
          # Flush all files before uploading
          for file_handle in files_to_upload.values():
              file_handle.flush()
  
          self._upload_to_gcs(files_to_upload)
  
          # Close all temp file handles.
          for file_handle in files_to_upload.values():
              file_handle.close()
  
          # Close all sessions and connection associated with this Cassandra cluster
          hook.shutdown_cluster()
  
      def _write_local_data_files(self, cursor):
          """
          Takes a cursor, and writes results to a local file.
  
          :return: A dictionary where keys are filenames to be used as object
              names in GCS, and values are file handles to local files that
              contain the data for the GCS objects.
          """
          file_no = 0
          tmp_file_handle = NamedTemporaryFile(delete=True)
          tmp_file_handles = {self.filename.format(file_no): tmp_file_handle}
          for row in cursor:
              row_dict = self.generate_data_dict(row._fields, row)
              content = json.dumps(row_dict).encode('utf-8')
              tmp_file_handle.write(content)
  
              # Append newline to make dumps BigQuery compatible.
              tmp_file_handle.write(b'\n')
  
              if tmp_file_handle.tell() >= self.approx_max_file_size_bytes:
                  file_no += 1
                  tmp_file_handle = NamedTemporaryFile(delete=True)
                  tmp_file_handles[self.filename.format(file_no)] = tmp_file_handle
  
          return tmp_file_handles
  
      def _write_local_schema_file(self, cursor):
          """
          Takes a cursor, and writes the BigQuery schema for the results to a
          local file system.
  
          :return: A dictionary where key is a filename to be used as an object
              name in GCS, and values are file handles to local files that
              contains the BigQuery schema fields in .json format.
          """
          schema = []
          tmp_schema_file_handle = NamedTemporaryFile(delete=True)
  
          for name, type_ in zip(cursor.column_names, cursor.column_types):
              schema.append(self.generate_schema_dict(name, type_))
          json_serialized_schema = json.dumps(schema).encode('utf-8')
  
          tmp_schema_file_handle.write(json_serialized_schema)
          return {self.schema_filename: tmp_schema_file_handle}
  
      def _upload_to_gcs(self, files_to_upload: Dict[str, Any]):
          hook = GCSHook(
              gcp_conn_id=self.gcp_conn_id,
              delegate_to=self.delegate_to,
              impersonation_chain=self.impersonation_chain,
          )
          for obj, tmp_file_handle in files_to_upload.items():
              hook.upload(
                  bucket_name=self.bucket,
                  object_name=obj,
                  filename=tmp_file_handle.name,
                  mime_type='application/json',
                  gzip=self.gzip,
              )
  
      @classmethod
      def generate_data_dict(cls, names: Iterable[str], values: Any) -> Dict[str, Any]:
          """Generates data structure that will be stored as file in GCS."""
          return {n: cls.convert_value(v) for n, v in zip(names, values)}
  
      @classmethod
      def convert_value(cls, value: Optional[Any]) -> Optional[Any]:
          """Convert value to BQ type."""
          if not value:
              return value
          elif isinstance(value, (str, int, float, bool, dict)):
              return value
          elif isinstance(value, bytes):
              return b64encode(value).decode('ascii')
          elif isinstance(value, UUID):
              return b64encode(value.bytes).decode('ascii')
          elif isinstance(value, (datetime, Date)):
              return str(value)
          elif isinstance(value, Decimal):
              return float(value)
          elif isinstance(value, Time):
              return str(value).split('.')[0]
          elif isinstance(value, (list, SortedSet)):
              return cls.convert_array_types(value)
          elif hasattr(value, '_fields'):
              return cls.convert_user_type(value)
          elif isinstance(value, tuple):
              return cls.convert_tuple_type(value)
          elif isinstance(value, OrderedMapSerializedKey):
              return cls.convert_map_type(value)
          else:
              raise AirflowException('Unexpected value: ' + str(value))
  
      @classmethod
      def convert_array_types(cls, value: Union[List[Any], SortedSet]) -> List[Any]:
          """Maps convert_value over array."""
          return [cls.convert_value(nested_value) for nested_value in value]
  
      @classmethod
      def convert_user_type(cls, value: Any) -> Dict[str, Any]:
          """
          Converts a user type to RECORD that contains n fields, where n is the
          number of attributes. Each element in the user type class will be converted to its
          corresponding data type in BQ.
          """
          names = value._fields
          values = [cls.convert_value(getattr(value, name)) for name in names]
          return cls.generate_data_dict(names, values)
  
      @classmethod
      def convert_tuple_type(cls, values: Tuple[Any]) -> Dict[str, Any]:
          """
          Converts a tuple to RECORD that contains n fields, each will be converted
          to its corresponding data type in bq and will be named 'field_<index>', where
          index is determined by the order of the tuple elements defined in cassandra.
          """
          names = ['field_' + str(i) for i in range(len(values))]
          return cls.generate_data_dict(names, values)
  
      @classmethod
      def convert_map_type(cls, value: OrderedMapSerializedKey) -> List[Dict[str, Any]]:
          """
          Converts a map to a repeated RECORD that contains two fields: 'key' and 'value',
          each will be converted to its corresponding data type in BQ.
          """
          converted_map = []
          for k, v in zip(value.keys(), value.values()):
              converted_map.append({'key': cls.convert_value(k), 'value': cls.convert_value(v)})
          return converted_map
  
      @classmethod
      def generate_schema_dict(cls, name: str, type_: Any) -> Dict[str, Any]:
          """Generates BQ schema."""
          field_schema: Dict[str, Any] = {}
          field_schema.update({'name': name})
          field_schema.update({'type_': cls.get_bq_type(type_)})
          field_schema.update({'mode': cls.get_bq_mode(type_)})
          fields = cls.get_bq_fields(type_)
          if fields:
              field_schema.update({'fields': fields})
          return field_schema
  
      @classmethod
      def get_bq_fields(cls, type_: Any) -> List[Dict[str, Any]]:
          """Converts non simple type value to BQ representation."""
          if cls.is_simple_type(type_):
              return []
  
          # In case of not simple type
          names: List[str] = []
          types: List[Any] = []
          if cls.is_array_type(type_) and cls.is_record_type(type_.subtypes[0]):
              names = type_.subtypes[0].fieldnames
              types = type_.subtypes[0].subtypes
          elif cls.is_record_type(type_):
              names = type_.fieldnames
              types = type_.subtypes
  
          if types and not names and type_.cassname == 'TupleType':
              names = ['field_' + str(i) for i in range(len(types))]
          elif types and not names and type_.cassname == 'MapType':
              names = ['key', 'value']
  
          return [cls.generate_schema_dict(n, t) for n, t in zip(names, types)]
  
      @staticmethod
      def is_simple_type(type_: Any) -> bool:
          """Check if type is a simple type."""
          return type_.cassname in CassandraToGCSOperator.CQL_TYPE_MAP
  
      @staticmethod
      def is_array_type(type_: Any) -> bool:
          """Check if type is an array type."""
          return type_.cassname in ['ListType', 'SetType']
  
      @staticmethod
      def is_record_type(type_: Any) -> bool:
          """Checks the record type."""
          return type_.cassname in ['UserType', 'TupleType', 'MapType']
  
      @classmethod
      def get_bq_type(cls, type_: Any) -> str:
          """Converts type to equivalent BQ type."""
          if cls.is_simple_type(type_):
              return CassandraToGCSOperator.CQL_TYPE_MAP[type_.cassname]
          elif cls.is_record_type(type_):
              return 'RECORD'
          elif cls.is_array_type(type_):
              return cls.get_bq_type(type_.subtypes[0])
          else:
              raise AirflowException('Not a supported type_: ' + type_.cassname)
  
      @classmethod
      def get_bq_mode(cls, type_: Any) -> str:
          """Converts type to equivalent BQ mode."""
          if cls.is_array_type(type_) or type_.cassname == 'MapType':
              return 'REPEATED'
          elif cls.is_record_type(type_) or cls.is_simple_type(type_):
              return 'NULLABLE'
          else:
              raise AirflowException('Not a supported type_: ' + type_.cassname)
  