Memeriksa string untuk data sensitif menggunakan beberapa aturan

Menggambarkan penerapan aturan pengecualian dan kata cepat. Kumpulan aturan cuplikan ini mencakup aturan kata cepat serta aturan pengecualian kamus dan ekspresi reguler. Perhatikan bahwa keempat aturan ditentukan dalam array dalam elemen aturan.

Mempelajari lebih lanjut

Untuk dokumentasi mendetail yang menyertakan contoh kode ini, lihat artikel berikut:

• Mengubah detektor infoType untuk meningkatkan kualitas hasil pemindaian

Contoh kode

C#GoJavaNode.jsPHPPython

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

using System;
using System.Text.RegularExpressions;
using Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
using static Google.Cloud.Dlp.V2.CustomInfoType.Types;

public class InspectStringMultipleRules
{
    public static InspectContentResponse Inspect(string projectId, string textToInspect)
    {
        var dlp = DlpServiceClient.Create();

        var byteContentItem = new ByteContentItem
        {
            Type = ByteContentItem.Types.BytesType.TextUtf8,
            Data = Google.Protobuf.ByteString.CopyFromUtf8(textToInspect)
        };

        var contentItem = new ContentItem
        {
            ByteItem = byteContentItem
        };

        var patientRule = new DetectionRule.Types.HotwordRule
        {
            HotwordRegex = new CustomInfoType.Types.Regex { Pattern = "patient" },
            Proximity = new DetectionRule.Types.Proximity { WindowBefore = 10 },
            LikelihoodAdjustment = new DetectionRule.Types.LikelihoodAdjustment { FixedLikelihood = Likelihood.VeryLikely }
        };

        var doctorRule = new DetectionRule.Types.HotwordRule
        {
            HotwordRegex = new CustomInfoType.Types.Regex { Pattern = "doctor" },
            Proximity = new DetectionRule.Types.Proximity { WindowBefore = 10 },
            LikelihoodAdjustment = new DetectionRule.Types.LikelihoodAdjustment { FixedLikelihood = Likelihood.Unlikely }
        };

        // Construct exclusion rules
        var quasimodoRule = new ExclusionRule
        {
            Dictionary = new Dictionary { WordList = new Dictionary.Types.WordList { Words = { "Quasimodo" } } },
            MatchingType = MatchingType.PartialMatch
        };

        var redactedRule = new ExclusionRule
        {
            Regex = new CustomInfoType.Types.Regex { Pattern = "REDACTED" },
            MatchingType = MatchingType.PartialMatch
        };

        var infoType = new InfoType { Name = "PERSON_NAME" };

        var inspectionRuleSet = new InspectionRuleSet
        {
            InfoTypes = { infoType },
            Rules =
            {
                new InspectionRule { HotwordRule = patientRule },
                new InspectionRule { HotwordRule = doctorRule},
                new InspectionRule { ExclusionRule = quasimodoRule },
                new InspectionRule { ExclusionRule = redactedRule }
            }
        };

        var inspectConfig = new InspectConfig
        {
            InfoTypes = { infoType },
            IncludeQuote = true,
            RuleSet = { inspectionRuleSet }
        };

        var request = new InspectContentRequest
        {
            Parent = new LocationName(projectId, "global").ToString(),
            Item = contentItem,
            InspectConfig = inspectConfig
        };

        var response = dlp.InspectContent(request);

        Console.WriteLine($"Findings: {response.Result.Findings.Count}");
        foreach (var f in response.Result.Findings)
        {
            Console.WriteLine("\tQuote: " + f.Quote);
            Console.WriteLine("\tInfo type: " + f.InfoType.Name);
            Console.WriteLine("\tLikelihood: " + f.Likelihood);
        }

        return response;
    }
}

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

import (
	"context"
	"fmt"
	"io"

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

// inspectStringMultipleRules inspects the provided text,
// avoiding matches specified in the exclusion list.
// this function implements the both exclusion and hot word rules.
func inspectStringMultipleRules(w io.Writer, projectID, textToInspect string) error {
	// projectID := "my-project-id"
	// textToInspect := "patient: Jane Doe"

	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 the type and content to be inspected.
	ContentItem := &dlppb.ContentItem{
		DataItem: &dlppb.ContentItem_ByteItem{
			ByteItem: &dlppb.ByteContentItem{
				Type: dlppb.ByteContentItem_TEXT_UTF8,
				Data: []byte(textToInspect),
			},
		},
	}

	// Construct the rule that adjust the likelihood of findings
	// within a certain proximity of hot-word("patient").
	patientRule := &dlppb.InspectionRule_HotwordRule{
		HotwordRule: &dlppb.CustomInfoType_DetectionRule_HotwordRule{
			HotwordRegex: &dlppb.CustomInfoType_Regex{
				Pattern: "patient",
			},
			Proximity: &dlppb.CustomInfoType_DetectionRule_Proximity{
				WindowBefore: 10,
			},
			LikelihoodAdjustment: &dlppb.CustomInfoType_DetectionRule_LikelihoodAdjustment{
				Adjustment: &dlppb.CustomInfoType_DetectionRule_LikelihoodAdjustment_FixedLikelihood{
					FixedLikelihood: dlppb.Likelihood_VERY_LIKELY,
				},
			},
		},
	}

	// Construct the rule that adjust the likelihood of findings
	// within a certain proximity of hot-word("doctor").
	doctorRule := &dlppb.InspectionRule_HotwordRule{
		HotwordRule: &dlppb.CustomInfoType_DetectionRule_HotwordRule{
			HotwordRegex: &dlppb.CustomInfoType_Regex{
				Pattern: "doctor",
			},
			Proximity: &dlppb.CustomInfoType_DetectionRule_Proximity{
				WindowBefore: 10,
			},
			LikelihoodAdjustment: &dlppb.CustomInfoType_DetectionRule_LikelihoodAdjustment{
				Adjustment: &dlppb.CustomInfoType_DetectionRule_LikelihoodAdjustment_FixedLikelihood{
					FixedLikelihood: dlppb.Likelihood_UNLIKELY,
				},
			},
		},
	}

	// Construct the exclusion rule that avoids the matches for the specified word list.
	quasimodoRule := &dlppb.ExclusionRule{
		Type: &dlppb.ExclusionRule_Dictionary{
			Dictionary: &dlppb.CustomInfoType_Dictionary{
				Source: &dlppb.CustomInfoType_Dictionary_WordList_{
					WordList: &dlppb.CustomInfoType_Dictionary_WordList{
						Words: []string{"Quasimodo"},
					},
				},
			},
		},
		MatchingType: dlppb.MatchingType_MATCHING_TYPE_PARTIAL_MATCH,
	}

	// Construct the exclusion rule that avoids the matches for the specified regex pattern.
	redactedRule := &dlppb.ExclusionRule{
		Type: &dlppb.ExclusionRule_Regex{
			Regex: &dlppb.CustomInfoType_Regex{
				Pattern: "REDACTED",
			},
		},
		MatchingType: dlppb.MatchingType_MATCHING_TYPE_PARTIAL_MATCH,
	}

	// Construct a ruleSet that applies the rules to the PERSON_NAME infoType.
	ruleSet := &dlppb.InspectionRuleSet{
		InfoTypes: []*dlppb.InfoType{
			{Name: "PERSON_NAME"},
		},
		Rules: []*dlppb.InspectionRule{
			{Type: &dlppb.InspectionRule_HotwordRule{HotwordRule: doctorRule.HotwordRule}},
			{Type: &dlppb.InspectionRule_HotwordRule{HotwordRule: patientRule.HotwordRule}},
			{Type: &dlppb.InspectionRule_ExclusionRule{ExclusionRule: quasimodoRule}},
			{Type: &dlppb.InspectionRule_ExclusionRule{ExclusionRule: redactedRule}},
		},
	}

	// Construct the configuration for the Inspect request, including the ruleSet.
	inspectConfig := &dlppb.InspectConfig{
		InfoTypes: []*dlppb.InfoType{
			{Name: "PERSON_NAME"},
		},
		IncludeQuote: true,
		RuleSet: []*dlppb.InspectionRuleSet{
			ruleSet,
		},
	}

	// Create and send the request.
	req := &dlppb.InspectContentRequest{
		Parent:        fmt.Sprintf("projects/%s/locations/global", projectID),
		Item:          ContentItem,
		InspectConfig: inspectConfig,
	}

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

	// Process the results.
	fmt.Fprintf(w, "Findings: %v\n", len(resp.Result.Findings))
	for _, v := range resp.GetResult().Findings {
		fmt.Fprintf(w, "Quote: %v\n", v.GetQuote())
		fmt.Fprintf(w, "Infotype Name: %v\n", v.GetInfoType().GetName())
		fmt.Fprintf(w, "Likelihood: %v\n", v.GetLikelihood())
	}
	return nil

}

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.ByteContentItem;
import com.google.privacy.dlp.v2.ByteContentItem.BytesType;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.CustomInfoType.DetectionRule.HotwordRule;
import com.google.privacy.dlp.v2.CustomInfoType.DetectionRule.LikelihoodAdjustment;
import com.google.privacy.dlp.v2.CustomInfoType.DetectionRule.Proximity;
import com.google.privacy.dlp.v2.CustomInfoType.Dictionary;
import com.google.privacy.dlp.v2.CustomInfoType.Dictionary.WordList;
import com.google.privacy.dlp.v2.CustomInfoType.Regex;
import com.google.privacy.dlp.v2.ExclusionRule;
import com.google.privacy.dlp.v2.Finding;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.InspectContentRequest;
import com.google.privacy.dlp.v2.InspectContentResponse;
import com.google.privacy.dlp.v2.InspectionRule;
import com.google.privacy.dlp.v2.InspectionRuleSet;
import com.google.privacy.dlp.v2.Likelihood;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.MatchingType;
import com.google.protobuf.ByteString;
import java.io.IOException;

public class InspectStringMultipleRules {

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    String textToInspect = "patient: Jane Doe";
    inspectStringMultipleRules(projectId, textToInspect);
  }

  // Inspects the provided text, avoiding matches specified in the exclusion list.
  public static void inspectStringMultipleRules(String projectId, String textToInspect)
      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 the type and content to be inspected.
      ByteContentItem byteItem =
          ByteContentItem.newBuilder()
              .setType(BytesType.TEXT_UTF8)
              .setData(ByteString.copyFromUtf8(textToInspect))
              .build();
      ContentItem item = ContentItem.newBuilder().setByteItem(byteItem).build();

      // Construct hotword rules
      HotwordRule patientRule =
          HotwordRule.newBuilder()
              .setHotwordRegex(Regex.newBuilder().setPattern("patient"))
              .setProximity(Proximity.newBuilder().setWindowBefore(10))
              .setLikelihoodAdjustment(
                  LikelihoodAdjustment.newBuilder().setFixedLikelihood(Likelihood.VERY_LIKELY))
              .build();

      HotwordRule doctorRule =
          HotwordRule.newBuilder()
              .setHotwordRegex(Regex.newBuilder().setPattern("doctor"))
              .setProximity(Proximity.newBuilder().setWindowBefore(10))
              .setLikelihoodAdjustment(
                  LikelihoodAdjustment.newBuilder().setFixedLikelihood(Likelihood.UNLIKELY))
              .build();

      // Construct exclusion rules
      ExclusionRule quasimodoRule =
          ExclusionRule.newBuilder()
              .setDictionary(
                  Dictionary.newBuilder().setWordList(WordList.newBuilder().addWords("Quasimodo")))
              .setMatchingType(MatchingType.MATCHING_TYPE_PARTIAL_MATCH)
              .build();

      ExclusionRule redactedRule =
          ExclusionRule.newBuilder()
              .setRegex(Regex.newBuilder().setPattern("REDACTED"))
              .setMatchingType(MatchingType.MATCHING_TYPE_PARTIAL_MATCH)
              .build();

      // Construct a ruleset that applies the rules to the PERSON_NAME infotype.
      InspectionRuleSet ruleSet =
          InspectionRuleSet.newBuilder()
              .addInfoTypes(InfoType.newBuilder().setName("PERSON_NAME"))
              .addRules(InspectionRule.newBuilder().setHotwordRule(patientRule))
              .addRules(InspectionRule.newBuilder().setHotwordRule(doctorRule))
              .addRules(InspectionRule.newBuilder().setExclusionRule(quasimodoRule))
              .addRules(InspectionRule.newBuilder().setExclusionRule(redactedRule))
              .build();

      // Construct the configuration for the Inspect request, including the ruleset.
      InspectConfig config =
          InspectConfig.newBuilder()
              .addInfoTypes(InfoType.newBuilder().setName("PERSON_NAME"))
              .setIncludeQuote(true)
              .addRuleSet(ruleSet)
              .build();

      // Construct the Inspect request to be sent by the client.
      InspectContentRequest request =
          InspectContentRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setItem(item)
              .setInspectConfig(config)
              .build();

      // Use the client to send the API request.
      InspectContentResponse response = dlp.inspectContent(request);

      // Parse the response and process results
      System.out.println("Findings: " + response.getResult().getFindingsCount());
      for (Finding f : response.getResult().getFindingsList()) {
        System.out.println("\tQuote: " + f.getQuote());
        System.out.println("\tInfo type: " + f.getInfoType().getName());
        System.out.println("\tLikelihood: " + f.getLikelihood());
      }
    }
  }
}

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

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

// Instantiates a client
const dlp = new DLP.DlpServiceClient();

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

// The string to inspect
// const string = 'patient: Jane Doe';

async function inspectStringMultipleRules() {
  // Construct item to inspect
  const item = {value: string};

  // Construct hotword rules
  const patientRule = {
    hotwordRegex: {pattern: 'patient'},
    proximity: {windowBefore: 10},
    likelihoodAdjustment: {
      fixedLikelihood:
        DLP.protos.google.privacy.dlp.v2.Likelihood.VERY_LIKELY,
    },
  };

  const doctorRule = {
    hotwordRegex: {pattern: 'doctor'},
    proximity: {windowBefore: 10},
    likelihoodAdjustment: {
      fixedLikelihood: DLP.protos.google.privacy.dlp.v2.Likelihood.UNLIKELY,
    },
  };

  // Construct exclusion rules
  const quasimodoRule = {
    dictionary: {wordList: {words: ['quasimodo']}},
    matchingType:
      DLP.protos.google.privacy.dlp.v2.MatchingType
        .MATCHING_TYPE_PARTIAL_MATCH,
  };

  const redactedRule = {
    regex: {pattern: 'REDACTED'},
    matchingType:
      DLP.protos.google.privacy.dlp.v2.MatchingType
        .MATCHING_TYPE_PARTIAL_MATCH,
  };

  // The infoTypes of information to match
  const infoTypes = [{name: 'PERSON_NAME'}];

  // Construct a ruleset that applies the rules to the PERSON_NAME infotype.
  const ruleSet = [
    {
      infoTypes: infoTypes,
      rules: [
        {hotwordRule: patientRule},
        {hotwordRule: doctorRule},
        {exclusionRule: quasimodoRule},
        {exclusionRule: redactedRule},
      ],
    },
  ];

  // Construct the configuration for the Inspect request, including the ruleset.
  const inspectConfig = {
    infoTypes: infoTypes,
    ruleSet: ruleSet,
    includeQuote: true,
  };

  // Construct the Inspect request to be sent by the client.
  const request = {
    parent: `projects/${projectId}/locations/global`,
    inspectConfig: inspectConfig,
    item: item,
  };

  // Use the client to send the API request.
  const [response] = await dlp.inspectContent(request);

  // Print findings.
  const findings = response.result.findings;
  if (findings.length > 0) {
    console.log(`Findings: ${findings.length}\n`);
    findings.forEach(finding => {
      console.log(`InfoType: ${finding.infoType.name}`);
      console.log(`\tQuote: ${finding.quote}`);
      console.log(`\tLikelihood: ${finding.likelihood} \n`);
    });
  } else {
    console.log('No findings.');
  }
}
inspectStringMultipleRules();

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

use Google\Cloud\Dlp\V2\Client\DlpServiceClient;
use Google\Cloud\Dlp\V2\ContentItem;
use Google\Cloud\Dlp\V2\CustomInfoType\DetectionRule\HotwordRule;
use Google\Cloud\Dlp\V2\CustomInfoType\DetectionRule\LikelihoodAdjustment;
use Google\Cloud\Dlp\V2\CustomInfoType\DetectionRule\Proximity;
use Google\Cloud\Dlp\V2\CustomInfoType\Dictionary;
use Google\Cloud\Dlp\V2\CustomInfoType\Dictionary\WordList;
use Google\Cloud\Dlp\V2\CustomInfoType\Regex;
use Google\Cloud\Dlp\V2\ExclusionRule;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\InspectContentRequest;
use Google\Cloud\Dlp\V2\InspectionRule;
use Google\Cloud\Dlp\V2\InspectionRuleSet;
use Google\Cloud\Dlp\V2\Likelihood;
use Google\Cloud\Dlp\V2\MatchingType;

/**
 * Inspect a string for sensitive data by using multiple rules
 * Illustrates applying both exclusion and hotword rules. This snippet's rule set includes both hotword rules and dictionary and regex exclusion rules. Notice that the four rules are specified in an array within the rules element.
 *
 * @param string $projectId         The Google Cloud project id to use as a parent resource.
 * @param string $textToInspect     The string to inspect.
 */
function inspect_string_multiple_rules(
    // TODO(developer): Replace sample parameters before running the code.
    string $projectId,
    string $textToInspect = 'patient: Jane Doe'
): void {
    // Instantiate a client.
    $dlp = new DlpServiceClient();

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

    // Specify what content you want the service to Inspect.
    $item = (new ContentItem())
        ->setValue($textToInspect);

    // Construct hotword rules
    $patientRule = (new HotwordRule())
        ->setHotwordRegex((new Regex())
            ->setPattern('patient'))
        ->setProximity((new Proximity())
            ->setWindowBefore(10))
        ->setLikelihoodAdjustment((new LikelihoodAdjustment())
            ->setFixedLikelihood(Likelihood::VERY_LIKELY));

    $doctorRule = (new HotwordRule())
        ->setHotwordRegex((new Regex())
            ->setPattern('doctor'))
        ->setProximity((new Proximity())
            ->setWindowBefore(10))
        ->setLikelihoodAdjustment((new LikelihoodAdjustment())
            ->setFixedLikelihood(Likelihood::VERY_UNLIKELY));

    // Construct exclusion rules
    $wordList = (new Dictionary())
        ->setWordList((new WordList())
            ->setWords(['Quasimodo']));

    $quasimodoRule = (new ExclusionRule())
        ->setMatchingType(MatchingType::MATCHING_TYPE_PARTIAL_MATCH)
        ->setDictionary($wordList);

    $redactedRule = (new ExclusionRule())
        ->setMatchingType(MatchingType::MATCHING_TYPE_PARTIAL_MATCH)
        ->setRegex((new Regex())
            ->setPattern('REDACTED'));

    // Specify the exclusion rule and build-in info type the inspection will look for.
    $personName = (new InfoType())
        ->setName('PERSON_NAME');
    $inspectionRuleSet = (new InspectionRuleSet())
        ->setInfoTypes([$personName])
        ->setRules([
            (new InspectionRule())
                ->setHotwordRule($patientRule),
            (new InspectionRule())
                ->setHotwordRule($doctorRule),
            (new InspectionRule())
                ->setExclusionRule($quasimodoRule),
            (new InspectionRule())
                ->setExclusionRule($redactedRule),
        ]);

    // Construct the configuration for the Inspect request, including the ruleset.
    $inspectConfig = (new InspectConfig())
        ->setInfoTypes([$personName])
        ->setIncludeQuote(true)
        ->setRuleSet([$inspectionRuleSet]);

    // Run request
    $inspectContentRequest = (new InspectContentRequest())
        ->setParent($parent)
        ->setInspectConfig($inspectConfig)
        ->setItem($item);
    $response = $dlp->inspectContent($inspectContentRequest);

    // Print the results
    $findings = $response->getResult()->getFindings();
    if (count($findings) == 0) {
        printf('No findings.' . PHP_EOL);
    } else {
        printf('Findings:' . PHP_EOL);
        foreach ($findings as $finding) {
            printf('  Quote: %s' . PHP_EOL, $finding->getQuote());
            printf('  Info type: %s' . PHP_EOL, $finding->getInfoType()->getName());
            printf('  Likelihood: %s' . PHP_EOL, Likelihood::name($finding->getLikelihood()));
        }
    }
}

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Perlindungan Data Sensitif, lihat library klien Perlindungan Data Sensitif.

Untuk melakukan autentikasi ke Perlindungan Data Sensitif, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

import google.cloud.dlp


def inspect_string_multiple_rules(project: str, content_string: str) -> None:
    """Uses the Data Loss Prevention API to modify likelihood for matches on
       PERSON_NAME combining multiple hotword and exclusion rules.

    Args:
        project: The Google Cloud project id to use as a parent resource.
        content_string: The string to inspect.

    Returns:
        None; the response from the API is printed to the terminal.
    """

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

    # Construct hotword rules
    patient_rule = {
        "hotword_regex": {"pattern": "patient"},
        "proximity": {"window_before": 10},
        "likelihood_adjustment": {
            "fixed_likelihood": google.cloud.dlp_v2.Likelihood.VERY_LIKELY
        },
    }
    doctor_rule = {
        "hotword_regex": {"pattern": "doctor"},
        "proximity": {"window_before": 10},
        "likelihood_adjustment": {
            "fixed_likelihood": google.cloud.dlp_v2.Likelihood.UNLIKELY
        },
    }

    # Construct exclusion rules
    quasimodo_rule = {
        "dictionary": {"word_list": {"words": ["quasimodo"]}},
        "matching_type": google.cloud.dlp_v2.MatchingType.MATCHING_TYPE_PARTIAL_MATCH,
    }
    redacted_rule = {
        "regex": {"pattern": "REDACTED"},
        "matching_type": google.cloud.dlp_v2.MatchingType.MATCHING_TYPE_PARTIAL_MATCH,
    }

    # Construct the rule set, combining the above rules
    rule_set = [
        {
            "info_types": [{"name": "PERSON_NAME"}],
            "rules": [
                {"hotword_rule": patient_rule},
                {"hotword_rule": doctor_rule},
                {"exclusion_rule": quasimodo_rule},
                {"exclusion_rule": redacted_rule},
            ],
        }
    ]

    # Construct the configuration dictionary
    inspect_config = {
        "info_types": [{"name": "PERSON_NAME"}],
        "rule_set": rule_set,
        "include_quote": True,
    }

    # Construct the `item`.
    item = {"value": content_string}

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

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

    # Print out the results.
    if response.result.findings:
        for finding in response.result.findings:
            print(f"Quote: {finding.quote}")
            print(f"Info type: {finding.info_type.name}")
            print(f"Likelihood: {finding.likelihood}")
    else:
        print("No findings.")

Langkah berikutnya

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