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# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
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"""``PTransforms`` that implement Google Cloud Data Loss Prevention
functionality.
"""

from __future__ import absolute_import

import logging

from google.cloud import dlp_v2

from apache_beam.options.pipeline_options import GoogleCloudOptions
from apache_beam.transforms import DoFn
from apache_beam.transforms import ParDo
from apache_beam.transforms import PTransform
from apache_beam.utils.annotations import experimental

__all__ = ['MaskDetectedDetails', 'InspectForDetails']

_LOGGER = logging.getLogger(__name__)


@experimental()
class MaskDetectedDetails(PTransform):
  """Scrubs sensitive information detected in text.
  The ``PTransform`` returns a ``PCollection`` of ``str``
  Example usage::

    pipeline | MaskDetectedDetails(project='example-gcp-project',
      deidentification_config={
          'info_type_transformations: {
              'transformations': [{
                  'primitive_transformation': {
                      'character_mask_config': {
                          'masking_character': '#'
                      }
                  }
              }]
          }
      }, inspection_config={'info_types': [{'name': 'EMAIL_ADDRESS'}]})

  """
  def __init__(
      self,
      project=None,
      deidentification_template_name=None,
      deidentification_config=None,
      inspection_template_name=None,
      inspection_config=None,
      timeout=None):
    """Initializes a :class:`MaskDetectedDetails` transform.

    Args:
      project: Optional. GCP project name in which inspection will be performed
      deidentification_template_name (str): Either this or
        `deidentification_config` required. Name of
        deidentification template to be used on detected sensitive information
        instances in text.
      deidentification_config
        (``Union[dict, google.cloud.dlp_v2.types.DeidentifyConfig]``):
        Configuration for the de-identification of the content item.
        If both template name and config are supplied,
        config is more important.
      inspection_template_name (str): This or `inspection_config` required.
        Name of inspection template to be used
        to detect sensitive data in text.
      inspection_config
        (``Union[dict, google.cloud.dlp_v2.types.InspectConfig]``):
        Configuration for the inspector used to detect sensitive data in text.
        If both template name and config are supplied,
        config takes precedence.
      timeout (float): Optional. The amount of time, in seconds, to wait for
        the request to complete.

    """
    self.config = {}
    self.project = project
    self.timeout = timeout
    if deidentification_template_name is not None \
        and deidentification_config is not None:
      raise ValueError(
          'Both deidentification_template_name and '
          'deidentification_config were specified.'
          ' Please specify only one of these.')
    elif deidentification_template_name is None \
        and deidentification_config is None:
      raise ValueError(
          'deidentification_template_name or '
          'deidentification_config must be specified.')
    elif deidentification_template_name is not None:
      self.config['deidentify_template_name'] = deidentification_template_name
    else:
      self.config['deidentify_config'] = deidentification_config

    if inspection_config is None and inspection_template_name is None:
      raise ValueError(
          'inspection_template_name or inspection_config must be specified')
    if inspection_template_name is not None:
      self.config['inspect_template_name'] = inspection_template_name
    if inspection_config is not None:
      self.config['inspect_config'] = inspection_config

  def expand(self, pcoll):
    if self.project is None:
      self.project = pcoll.pipeline.options.view_as(GoogleCloudOptions).project
    if self.project is None:
      raise ValueError(
          'GCP project name needs to be specified in "project" pipeline option')
    return (
        pcoll
        | ParDo(_DeidentifyFn(self.config, self.timeout, self.project)))


@experimental()
class InspectForDetails(PTransform):
  """Inspects input text for sensitive information.
  the ``PTransform`` returns a ``PCollection`` of
  ``List[google.cloud.dlp_v2.proto.dlp_pb2.Finding]``
  Example usage::

      pipeline | InspectForDetails(project='example-gcp-project',
                inspection_config={'info_types': [{'name': 'EMAIL_ADDRESS'}]})
  """
  def __init__(
      self,
      project=None,
      inspection_template_name=None,
      inspection_config=None,
      timeout=None):
    """Initializes a :class:`InspectForDetails` transform.

    Args:
      project: Optional. GCP project name in which inspection will be performed
      inspection_template_name (str): This or `inspection_config` required.
        Name of inspection template to be used
        to detect sensitive data in text.
      inspection_config
        (``Union[dict, google.cloud.dlp_v2.types.InspectConfig]``):
        Configuration for the inspector used to detect sensitive data in text.
        If both template name and config are supplied,
        config takes precedence.
      timeout (float): Optional. The amount of time, in seconds, to wait for
        the request to complete.

    """
    self.timeout = timeout
    self.config = {}
    self.project = project
    if inspection_config is None and inspection_template_name is None:
      raise ValueError(
          'inspection_template_name or inspection_config must be specified')
    if inspection_template_name is not None:
      self.config['inspect_template_name'] = inspection_template_name
    if inspection_config is not None:
      self.config['inspect_config'] = inspection_config

  def expand(self, pcoll):
    if self.project is None:
      self.project = pcoll.pipeline.options.view_as(GoogleCloudOptions).project
    if self.project is None:
      raise ValueError(
          'GCP project name needs to be specified in "project" pipeline option')
    return pcoll | ParDo(_InspectFn(self.config, self.timeout, self.project))


class _DeidentifyFn(DoFn):
  def __init__(self, config=None, timeout=None, project=None, client=None):
    self.config = config
    self.timeout = timeout
    self.client = client
    self.project = project
    self.params = {}

  def setup(self):
    if self.client is None:
      self.client = dlp_v2.DlpServiceClient()
    self.params = {
        'timeout': self.timeout,
        'parent': self.client.project_path(self.project)
    }
    self.params.update(self.config)

  def process(self, element, **kwargs):
    operation = self.client.deidentify_content(
        item={"value": element}, **self.params)
    yield operation.item.value


class _InspectFn(DoFn):
  def __init__(self, config=None, timeout=None, project=None):
    self.config = config
    self.timeout = timeout
    self.client = None
    self.project = project
    self.params = {}

  def setup(self):
    if self.client is None:
      self.client = dlp_v2.DlpServiceClient()
    self.params = {
        'timeout': self.timeout,
        "parent": self.client.project_path(self.project)
    }
    self.params.update(self.config)

  def process(self, element, **kwargs):
    operation = self.client.inspect_content(
        item={"value": element}, **self.params)
    hits = [x for x in operation.result.findings]
    yield hits
