使用条件逻辑对表数据进行去标识化，然后替换为 infoType

仅在满足其他字段的特定条件时才转换结果。

深入探索

如需查看包含此代码示例的详细文档，请参阅以下内容：

• 对表格数据进行去标识化的示例

代码示例

C#

如需了解如何安装和使用敏感数据保护客户端库，请参阅 敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。 如需了解详情，请参阅为本地开发环境设置身份验证。

using System;
using System.Collections.Generic;
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;

public class DeidentifyTableUsingLogicInfoTypes
{
    public static Table Deidentify(
        string projectId,
        Table tableToInspect = null,
        IEnumerable<InfoType> infoTypes = null)
    {
        // Instantiate the dlp client.
        var dlp = DlpServiceClient.Create();

        // Construct the table if null.
        if (tableToInspect == null)
        {
            var row1 = new Value[]
            {
                new Value { StringValue = "101" },
                new Value { StringValue = "Charles Dickens" },
                new Value { StringValue = "95" },
                new Value { StringValue = "Charles Dickens name was a curse invented by Shakespeare." }
            };
            var row2 = new Value[]
            {
                new Value { StringValue = "22" },
                new Value { StringValue = "Jane Austin" },
                new Value { StringValue = "21" },
                new Value { StringValue = "There are 14 kisses in Jane Austen's novels." }
            };
            var row3 = new Value[]
            {
                new Value { StringValue = "55" },
                new Value { StringValue = "Mark Twain" },
                new Value { StringValue = "75" },
                new Value { StringValue = "Mark Twain loved cats." }
            };

            tableToInspect = new Table
            {
                Headers =
                {
                    new FieldId { Name = "AGE" },
                    new FieldId { Name = "PATIENT" },
                    new FieldId { Name = "HAPPINESS SCORE" },
                    new FieldId { Name = "FACTOID" }
                },
                Rows =
                {
                    new Table.Types.Row { Values = { row1 } },
                    new Table.Types.Row { Values = { row2 } },
                    new Table.Types.Row { Values = { row3 } }
                }
            };
        }

        // Construct the table content item.
        var contentItem = new ContentItem { Table = tableToInspect };

        // Specify that findings should be replaced with corresponding info type name.
        var infoTypeTransformation = new InfoTypeTransformations
        {
            Transformations =
            {
                new InfoTypeTransformations.Types.InfoTypeTransformation
                {
                    InfoTypes = { infoTypes ?? new InfoType[] { new InfoType { Name = "PERSON_NAME" } } },
                    PrimitiveTransformation = new PrimitiveTransformation
                    {
                        ReplaceWithInfoTypeConfig = new ReplaceWithInfoTypeConfig()
                    }
                }
            }
        };

        // Specify the fields to be de-identified.
        var fields = new FieldId[] { new FieldId { Name = "PATIENT" }, new FieldId { Name = "FACTOID" } };

        // Specify when the above fields should be de-identified using condition.
        var condition = new RecordCondition.Types.Conditions
        {
            Conditions_ =
            {
                new RecordCondition.Types.Condition
                {
                    Field = new FieldId { Name = "AGE" },
                    Operator = RelationalOperator.GreaterThan,
                    Value = new Value { IntegerValue = 89 }
                }
            }
        };

        // Apply the condition to records.
        var recordCondition = new RecordCondition
        {
            Expressions = new RecordCondition.Types.Expressions
            {
                Conditions = condition
            }
        };

        // Associate the de-identification and conditions with the specified fields.
        var deidentifiedConfig = new DeidentifyConfig
        {
            RecordTransformations = new RecordTransformations
            {
                FieldTransformations =
                {
                    new FieldTransformation
                    {
                        InfoTypeTransformations = infoTypeTransformation,
                        Fields = { fields },
                        Condition = recordCondition
                    }
                }
            }
        };

        // Construct the request.
        var request = new DeidentifyContentRequest
        {
            ParentAsLocationName = new LocationName(projectId, "global"),
            DeidentifyConfig = deidentifiedConfig,
            Item = contentItem
        };

        // Call the API.
        var response = dlp.DeidentifyContent(request);

        // Inspect the response.
        Console.WriteLine(response.Item.Table);
        return response.Item.Table;
    }
}

Go

如需了解如何安装和使用敏感数据保护客户端库，请参阅 敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。 如需了解详情，请参阅为本地开发环境设置身份验证。

import (
	"context"
	"fmt"
	"io"

	dlp "cloud.google.com/go/dlp/apiv2"
	"cloud.google.com/go/dlp/apiv2/dlppb"
)

// deidentifyTableConditionInfoTypes de-identifies table data
// using conditional logic and replace with infoTypes
func deidentifyTableConditionInfoTypes(w io.Writer, projectID string, columnNames []string) error {
	// projectId := "your-project-id"
	// columnNames := []string{"PATIENT", "FACTOID"}

	row1 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "22"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Jane Austen"}},
			{Type: &dlppb.Value_StringValue{StringValue: "21"}},
			{Type: &dlppb.Value_StringValue{StringValue: "There are 14 kisses in Jane Austen's novels."}},
		},
	}

	row2 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "55"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Mark Twain"}},
			{Type: &dlppb.Value_StringValue{StringValue: "75"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Mark Twain loved cats."}},
		},
	}

	row3 := &dlppb.Table_Row{
		Values: []*dlppb.Value{
			{Type: &dlppb.Value_StringValue{StringValue: "101"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Charles Dickens"}},
			{Type: &dlppb.Value_StringValue{StringValue: "95"}},
			{Type: &dlppb.Value_StringValue{StringValue: "Charles Dickens name was a curse invented by Shakespeare."}},
		},
	}

	table := &dlppb.Table{
		Headers: []*dlppb.FieldId{
			{Name: "AGE"},
			{Name: "PATIENT"},
			{Name: "HAPPINESS SCORE"},
			{Name: "FACTOID"},
		},
		Rows: []*dlppb.Table_Row{
			{Values: row1.Values},
			{Values: row2.Values},
			{Values: row3.Values},
		},
	}

	ctx := context.Background()

	// Initialize a client once and reuse it to send multiple requests. Clients
	// are safe to use across goroutines. When the client is no longer needed,
	// call the Close method to cleanup its resources.
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return err
	}

	// Closing the client safely cleans up background resources.
	defer client.Close()

	// Specify what content you want the service to de-identify.
	contentItem := &dlppb.ContentItem{
		DataItem: &dlppb.ContentItem_Table{
			Table: table,
		},
	}

	// Specify how the content should be de-identified.
	// Select type of info to be replaced.
	infoTypes := []*dlppb.InfoType{
		{Name: "PERSON_NAME"},
	}

	// Specify that findings should be replaced with corresponding info type name.
	primitiveTransformation := &dlppb.PrimitiveTransformation{
		Transformation: &dlppb.PrimitiveTransformation_ReplaceWithInfoTypeConfig{},
	}

	// Associate info type with the replacement strategy
	infoTypeTransformation := &dlppb.InfoTypeTransformations_InfoTypeTransformation{
		InfoTypes:               infoTypes,
		PrimitiveTransformation: primitiveTransformation,
	}

	infoTypeTransformations := &dlppb.InfoTypeTransformations{
		Transformations: []*dlppb.InfoTypeTransformations_InfoTypeTransformation{
			infoTypeTransformation,
		},
	}

	// Specify fields to be de-identified.
	var f []*dlppb.FieldId
	for _, c := range columnNames {
		f = append(f, &dlppb.FieldId{Name: c})
	}

	// Specify when the above fields should be de-identified.
	condition := &dlppb.RecordCondition{
		Expressions: &dlppb.RecordCondition_Expressions{
			Type: &dlppb.RecordCondition_Expressions_Conditions{
				Conditions: &dlppb.RecordCondition_Conditions{
					Conditions: []*dlppb.RecordCondition_Condition{
						{
							Field: &dlppb.FieldId{
								Name: "AGE",
							},
							Operator: dlppb.RelationalOperator_GREATER_THAN,
							Value: &dlppb.Value{
								Type: &dlppb.Value_IntegerValue{
									IntegerValue: 89,
								},
							},
						},
					},
				},
			},
		},
	}

	// Associate the de-identification and conditions with the specified fields.
	fieldTransformation := &dlppb.FieldTransformation{
		Fields:    f,
		Condition: condition,
		Transformation: &dlppb.FieldTransformation_InfoTypeTransformations{
			InfoTypeTransformations: infoTypeTransformations,
		},
	}

	recordTransformations := &dlppb.RecordTransformations{
		FieldTransformations: []*dlppb.FieldTransformation{
			fieldTransformation,
		},
	}

	// Construct the de-identification request to be sent by the client.
	req := &dlppb.DeidentifyContentRequest{
		Parent: fmt.Sprintf("projects/%s/locations/global", projectID),
		DeidentifyConfig: &dlppb.DeidentifyConfig{
			Transformation: &dlppb.DeidentifyConfig_RecordTransformations{
				RecordTransformations: recordTransformations,
			},
		},
		Item: contentItem,
	}

	// Send the request.
	resp, err := client.DeidentifyContent(ctx, req)
	if err != nil {
		return err
	}

	// Print the results.
	fmt.Fprintf(w, "Table after de-identification : %v", resp.GetItem().GetTable())
	return nil

}

Java

如需了解如何安装和使用敏感数据保护客户端库，请参阅 敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。 如需了解详情，请参阅为本地开发环境设置身份验证。

import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.DeidentifyConfig;
import com.google.privacy.dlp.v2.DeidentifyContentRequest;
import com.google.privacy.dlp.v2.DeidentifyContentResponse;
import com.google.privacy.dlp.v2.FieldId;
import com.google.privacy.dlp.v2.FieldTransformation;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InfoTypeTransformations;
import com.google.privacy.dlp.v2.InfoTypeTransformations.InfoTypeTransformation;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.PrimitiveTransformation;
import com.google.privacy.dlp.v2.RecordCondition;
import com.google.privacy.dlp.v2.RecordCondition.Condition;
import com.google.privacy.dlp.v2.RecordCondition.Conditions;
import com.google.privacy.dlp.v2.RecordCondition.Expressions;
import com.google.privacy.dlp.v2.RecordTransformations;
import com.google.privacy.dlp.v2.RelationalOperator;
import com.google.privacy.dlp.v2.ReplaceWithInfoTypeConfig;
import com.google.privacy.dlp.v2.Table;
import com.google.privacy.dlp.v2.Table.Row;
import com.google.privacy.dlp.v2.Value;
import java.io.IOException;
import java.util.List;
import java.util.stream.Collectors;
import java.util.stream.Stream;

public class DeIdentifyTableConditionInfoTypes {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    Table tableToDeIdentify =
        Table.newBuilder()
            .addHeaders(FieldId.newBuilder().setName("AGE").build())
            .addHeaders(FieldId.newBuilder().setName("PATIENT").build())
            .addHeaders(FieldId.newBuilder().setName("HAPPINESS SCORE").build())
            .addHeaders(FieldId.newBuilder().setName("FACTOID").build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("101").build())
                    .addValues(Value.newBuilder().setStringValue("Charles Dickens").build())
                    .addValues(Value.newBuilder().setStringValue("95").build())
                    .addValues(
                        Value.newBuilder()
                            .setStringValue(
                                "Charles Dickens name was a curse invented by Shakespeare.")
                            .build())
                    .build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("22").build())
                    .addValues(Value.newBuilder().setStringValue("Jane Austen").build())
                    .addValues(Value.newBuilder().setStringValue("21").build())
                    .addValues(
                        Value.newBuilder()
                            .setStringValue("There are 14 kisses in Jane Austen's novels.")
                            .build())
                    .build())
            .addRows(
                Row.newBuilder()
                    .addValues(Value.newBuilder().setStringValue("55").build())
                    .addValues(Value.newBuilder().setStringValue("Mark Twain").build())
                    .addValues(Value.newBuilder().setStringValue("75").build())
                    .addValues(Value.newBuilder().setStringValue("Mark Twain loved cats.").build())
                    .build())
            .build();

    deIdentifyTableConditionInfoTypes(projectId, tableToDeIdentify);
  }

  public static Table deIdentifyTableConditionInfoTypes(String projectId, Table tableToDeIdentify)
      throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify what content you want the service to de-identify.
      ContentItem contentItem = ContentItem.newBuilder().setTable(tableToDeIdentify).build();

      // Specify how the content should be de-identified.
      // Select type of info to be replaced.
      InfoType infoType = InfoType.newBuilder().setName("PERSON_NAME").build();
      // Specify that findings should be replaced with corresponding info type name.
      ReplaceWithInfoTypeConfig replaceWithInfoTypeConfig =
          ReplaceWithInfoTypeConfig.getDefaultInstance();
      PrimitiveTransformation primitiveTransformation =
          PrimitiveTransformation.newBuilder()
              .setReplaceWithInfoTypeConfig(replaceWithInfoTypeConfig)
              .build();
      // Associate info type with the replacement strategy
      InfoTypeTransformation infoTypeTransformation =
          InfoTypeTransformation.newBuilder()
              .addInfoTypes(infoType)
              .setPrimitiveTransformation(primitiveTransformation)
              .build();
      InfoTypeTransformations infoTypeTransformations =
          InfoTypeTransformations.newBuilder().addTransformations(infoTypeTransformation).build();

      // Specify fields to be de-identified.
      List<FieldId> fieldIds =
          Stream.of("PATIENT", "FACTOID")
              .map(id -> FieldId.newBuilder().setName(id).build())
              .collect(Collectors.toList());

      // Specify when the above fields should be de-identified.
      Condition condition =
          Condition.newBuilder()
              .setField(FieldId.newBuilder().setName("AGE").build())
              .setOperator(RelationalOperator.GREATER_THAN)
              .setValue(Value.newBuilder().setIntegerValue(89).build())
              .build();
      // Apply the condition to records
      RecordCondition recordCondition =
          RecordCondition.newBuilder()
              .setExpressions(
                  Expressions.newBuilder()
                      .setConditions(Conditions.newBuilder().addConditions(condition).build())
                      .build())
              .build();

      // Associate the de-identification and conditions with the specified fields.
      FieldTransformation fieldTransformation =
          FieldTransformation.newBuilder()
              .setInfoTypeTransformations(infoTypeTransformations)
              .addAllFields(fieldIds)
              .setCondition(recordCondition)
              .build();
      RecordTransformations transformations =
          RecordTransformations.newBuilder().addFieldTransformations(fieldTransformation).build();

      DeidentifyConfig deidentifyConfig =
          DeidentifyConfig.newBuilder().setRecordTransformations(transformations).build();

      // Combine configurations into a request for the service.
      DeidentifyContentRequest request =
          DeidentifyContentRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setItem(contentItem)
              .setDeidentifyConfig(deidentifyConfig)
              .build();

      // Send the request and receive response from the service.
      DeidentifyContentResponse response = dlp.deidentifyContent(request);

      // Print the results.
      System.out.println("Table after de-identification: " + response.getItem().getTable());

      return response.getItem().getTable();
    }
  }
}

Node.js

如需了解如何安装和使用敏感数据保护客户端库，请参阅 敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。 如需了解详情，请参阅为本地开发环境设置身份验证。

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Initialize google DLP Client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under
// const projectId = 'my-project';

// Construct the tabular data
const tablularData = {
  headers: [
    {name: 'AGE'},
    {name: 'PATIENT'},
    {name: 'HAPPINESS SCORE'},
    {name: 'FACTOID'},
  ],
  rows: [
    {
      values: [
        {integerValue: 101},
        {stringValue: 'Charles Dickens'},
        {integerValue: 95},
        {
          stringValue:
            'Charles Dickens name was a curse invented by Shakespeare.',
        },
      ],
    },
    {
      values: [
        {integerValue: 22},
        {stringValue: 'Jane Austen'},
        {integerValue: 21},
        {stringValue: "There are 14 kisses in Jane Austen's novels."},
      ],
    },
    {
      values: [
        {integerValue: 55},
        {stringValue: 'Mark Twain'},
        {integerValue: 75},
        {stringValue: 'Mark Twain loved cats.'},
      ],
    },
  ],
};

async function deIdentifyTableConditionalInfoType() {
  // Specify fields to be de-identified.
  const fieldIds = [{name: 'PATIENT'}, {name: 'FACTOID'}];

  // Associate info type with the replacement strategy
  const infoTypeTransformations = {
    transformations: [
      {
        infoTypes: [{name: 'PERSON_NAME'}],
        primitiveTransformation: {
          replaceWithInfoTypeConfig: {},
        },
      },
    ],
  };

  // Specify when the above fields should be de-identified.
  const condition = {
    expressions: {
      conditions: {
        conditions: [
          {
            field: {name: 'AGE'},
            operator: 'GREATER_THAN',
            value: {integerValue: 89},
          },
        ],
      },
    },
  };

  // Apply the condition to records.
  const recordTransformations = {
    fieldTransformations: [
      {
        infoTypeTransformations,
        fields: fieldIds,
        condition: condition,
      },
    ],
  };

  // Combine configurations into a request for the service.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    item: {
      table: tablularData,
    },
    deidentifyConfig: {
      recordTransformations,
    },
  };
  // Send the request and receive response from the service.
  const [response] = await dlp.deidentifyContent(request);

  // Print the results.
  console.log(
    `Table after de-identification: ${JSON.stringify(response.item.table)}`
  );
}

deIdentifyTableConditionalInfoType();

PHP

如需了解如何安装和使用敏感数据保护客户端库，请参阅 敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。 如需了解详情，请参阅为本地开发环境设置身份验证。

use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\ContentItem;
use Google\Cloud\Dlp\V2\DeidentifyConfig;
use Google\Cloud\Dlp\V2\DeidentifyContentRequest;
use Google\Cloud\Dlp\V2\FieldId;
use Google\Cloud\Dlp\V2\FieldTransformation;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InfoTypeTransformations;
use Google\Cloud\Dlp\V2\InfoTypeTransformations\InfoTypeTransformation;
use Google\Cloud\Dlp\V2\PrimitiveTransformation;
use Google\Cloud\Dlp\V2\RecordCondition;
use Google\Cloud\Dlp\V2\RecordCondition\Condition;
use Google\Cloud\Dlp\V2\RecordCondition\Conditions;
use Google\Cloud\Dlp\V2\RecordCondition\Expressions;
use Google\Cloud\Dlp\V2\RecordTransformations;
use Google\Cloud\Dlp\V2\RelationalOperator;
use Google\Cloud\Dlp\V2\ReplaceWithInfoTypeConfig;
use Google\Cloud\Dlp\V2\Table;
use Google\Cloud\Dlp\V2\Table\Row;
use Google\Cloud\Dlp\V2\Value;

/**
 * De-identify table data using conditional logic and replace with infoTypes.
 * Transform findings only when specific conditions are met on another field.
 *
 * @param string $callingProjectId      The Google Cloud project id to use as a parent resource.
 * @param string $inputCsvFile          The input file(csv) path  to deidentify
 * @param string $outputCsvFile         The oupt file path to save deidentify content
 */

function deidentify_table_condition_infotypes(
    // TODO(developer): Replace sample parameters before running the code.
    string $callingProjectId,
    string $inputCsvFile = './test/data/table1.csv',
    string $outputCsvFile = './test/data/deidentify_table_condition_infotypes_output.csv'
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

    $parent = "projects/$callingProjectId/locations/global";

    // Read a CSV file
    $csvLines = file($inputCsvFile, FILE_IGNORE_NEW_LINES);
    $csvHeaders = explode(',', $csvLines[0]);
    $csvRows = array_slice($csvLines, 1);

    // Convert CSV file into protobuf objects
    $tableHeaders = array_map(function ($csvHeader) {
        return (new FieldId)
            ->setName($csvHeader);
    }, $csvHeaders);

    $tableRows = array_map(function ($csvRow) {
        $rowValues = array_map(function ($csvValue) {
            return (new Value())
                ->setStringValue($csvValue);
        }, explode(',', $csvRow));
        return (new Row())
            ->setValues($rowValues);
    }, $csvRows);

    // Construct the table object
    $tableToDeIdentify = (new Table())
        ->setHeaders($tableHeaders)
        ->setRows($tableRows);

    // Specify what content you want the service to de-identify.
    $content = (new ContentItem())
        ->setTable($tableToDeIdentify);

    // Specify the type of info the inspection will look for.
    $personNameInfoType = (new InfoType())
        ->setName('PERSON_NAME');

    // Specify that findings should be replaced with corresponding info type name.
    $primitiveTransformation = (new PrimitiveTransformation())
        ->setReplaceWithInfoTypeConfig(new ReplaceWithInfoTypeConfig());

    // Associate info type with the replacement strategy
    $infoTypeTransformation = (new InfoTypeTransformation())
        ->setPrimitiveTransformation($primitiveTransformation)
        ->setInfoTypes([$personNameInfoType]);

    $infoTypeTransformations = (new InfoTypeTransformations())
        ->setTransformations([$infoTypeTransformation]);

    // Specify fields to be de-identified.
    $fieldIds = [
        (new FieldId())->setName('PATIENT'),
        (new FieldId())->setName('FACTOID'),
    ];

    // Specify when the above fields should be de-identified.
    $condition = (new Condition())
        ->setField((new FieldId())
            ->setName('AGE'))
        ->setOperator(RelationalOperator::GREATER_THAN)
        ->setValue((new Value())
            ->setIntegerValue(89));

    // Apply the condition to records
    $recordCondition = (new RecordCondition())
        ->setExpressions((new Expressions())
                ->setConditions((new Conditions())
                        ->setConditions([$condition])
                )
        );

    // Associate the de-identification and conditions with the specified fields.
    $fieldTransformation = (new FieldTransformation())
        ->setInfoTypeTransformations($infoTypeTransformations)
        ->setFields($fieldIds)
        ->setCondition($recordCondition);

    $recordtransformations = (new RecordTransformations())
        ->setFieldTransformations([$fieldTransformation]);

    $deidentifyConfig = (new DeidentifyConfig())
        ->setRecordTransformations($recordtransformations);

    // Run request
    $deidentifyContentRequest = (new DeidentifyContentRequest())
        ->setParent($parent)
        ->setDeidentifyConfig($deidentifyConfig)
        ->setItem($content);
    $response = $dlp->deidentifyContent($deidentifyContentRequest);

    // Print results
    $csvRef = fopen($outputCsvFile, 'w');
    fputcsv($csvRef, $csvHeaders);
    foreach ($response->getItem()->getTable()->getRows() as $tableRow) {
        $values = array_map(function ($tableValue) {
            return $tableValue->getStringValue();
        }, iterator_to_array($tableRow->getValues()));
        fputcsv($csvRef, $values);
    };
    printf($outputCsvFile);
}

Python

如需了解如何安装和使用敏感数据保护客户端库，请参阅 敏感数据保护客户端库。

如需向 Sensitive Data Protection 进行身份验证，请设置应用默认凭据。 如需了解详情，请参阅为本地开发环境设置身份验证。

from typing import Dict, List, Union

import google.cloud.dlp
from google.cloud.dlp_v2 import types


def deidentify_table_condition_replace_with_info_types(
    project: str,
    table_data: Dict[str, Union[List[str], List[List[str]]]],
    deid_content_list: List[str],
    info_types: List[str],
    condition_field: str = None,
    condition_operator: str = None,
    condition_value: int = None,
) -> types.dlp.Table:
    """Uses the Data Loss Prevention API to de-identify sensitive data in a
    table by replacing them with info-types based on a condition.
    Args:
       project: The Google Cloud project id to use as a parent resource.
       table_data: Json string representing table data.
       deid_content_list: A list of fields in table to de-identify.
       info_types: A list of strings representing info types to look for.
           A full list of info categories and types is available from the API.
           Examples include "FIRST_NAME", "LAST_NAME", "EMAIL_ADDRESS". '
       condition_field: A table field within the record this condition is evaluated against.
       condition_operator: Operator used to compare the field or infoType to the value. One of:
           RELATIONAL_OPERATOR_UNSPECIFIED, EQUAL_TO, NOT_EQUAL_TO, GREATER_THAN, LESS_THAN, GREATER_THAN_OR_EQUALS,
           LESS_THAN_OR_EQUALS, EXISTS.
       condition_value: Value to compare against. [Mandatory, except for ``EXISTS`` tests.].

    Returns:
       De-identified table is returned;
       the response from the API is also printed to the terminal.

    Example:
    >> $ python deidentify_table_condition_infotypes.py \
    '{"header": ["email", "phone number", "age"],
    "rows": [["[e-mail]", "4232342345", "45"],
    ["[e-mail]", "4253458383", "63"]]}' ["email"] \
    ["EMAIL_ADDRESS"] "age" "GREATER_THAN" 50
    >> '{"header": ["email", "phone number", "age"],
        "rows": [["[e-mail]", "4232342345", "45"],
        ["[EMAIL_ADDRESS]", "4253458383", "63"]]}'
    """

    # Instantiate a client.
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Construct the `table`. For more details on the table schema, please see
    # https://cloud.google.com/dlp/docs/reference/rest/v2/ContentItem#Table
    headers = [{"name": val} for val in table_data["header"]]
    rows = []
    for row in table_data["rows"]:
        rows.append({"values": [{"string_value": cell_val} for cell_val in row]})

    table = {"headers": headers, "rows": rows}

    # Construct the item
    item = {"table": table}

    # Specify fields to be de-identified
    deid_field_list = [{"name": _i} for _i in deid_content_list]

    # Construct inspect configuration dictionary
    inspect_config = {"info_types": [{"name": info_type} for info_type in info_types]}

    # Construct condition list
    condition = [
        {
            "field": {"name": condition_field},
            "operator": condition_operator,
            "value": {"integer_value": condition_value},
        }
    ]

    # Construct deidentify configuration dictionary
    deidentify_config = {
        "record_transformations": {
            "field_transformations": [
                {
                    "info_type_transformations": {
                        "transformations": [
                            {
                                "primitive_transformation": {
                                    "replace_with_info_type_config": {}
                                }
                            }
                        ]
                    },
                    "fields": deid_field_list,
                    "condition": {
                        "expressions": {"conditions": {"conditions": condition}}
                    },
                }
            ]
        }
    }

    # Convert the project id into a full resource id.
    parent = f"projects/{project}/locations/global"

    # Call the API.
    response = dlp.deidentify_content(
        request={
            "parent": parent,
            "deidentify_config": deidentify_config,
            "item": item,
            "inspect_config": inspect_config,
        }
    )

    print(f"Table after de-identification: {response.item.table}")

    return response.item.table

后续步骤

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