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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:
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 Google.Api.Gax.ResourceNames;
using Google.Cloud.Dlp.V2;
public class DeidentifyUsingTableBucketing
{
public static Table DeidentifyData(
string projectId,
Table tableToInspect = null)
{
// Instantiate 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" }
};
var row2 = new Value[]
{
new Value { StringValue = "22" },
new Value { StringValue = "Jane Austin" },
new Value { StringValue = "21" }
};
var row3 = new Value[]
{
new Value { StringValue = "55" },
new Value { StringValue = "Mark Twain" },
new Value { StringValue = "75" }
};
tableToInspect = new Table
{
Headers =
{
new FieldId { Name = "AGE" },
new FieldId { Name = "PATIENT" },
new FieldId { Name = "HAPPINESS SCORE" }
},
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 how the content should be de-identified.
var fixedSizeBucketingConfig = new FixedSizeBucketingConfig
{
BucketSize = 10,
LowerBound = new Value { IntegerValue = 0 },
UpperBound = new Value { IntegerValue = 100 },
};
// Specify the fields to be encrypted.
var fields = new FieldId[] { new FieldId { Name = "HAPPINESS SCORE" } };
// Associate the encryption with the specified field.
var fieldTransformation = new FieldTransformation
{
PrimitiveTransformation = new PrimitiveTransformation
{
FixedSizeBucketingConfig = fixedSizeBucketingConfig
},
Fields = { fields }
};
// Construct the deidentify config.
var deidentifyConfig = new DeidentifyConfig
{
RecordTransformations = new RecordTransformations
{
FieldTransformations = { fieldTransformation }
}
};
// Construct the request.
var request = new DeidentifyContentRequest
{
ParentAsLocationName = new LocationName(projectId, "global"),
DeidentifyConfig = deidentifyConfig,
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"
)
// deIdentifyTableBucketing de-identifies data using table bucketing
func deIdentifyTableBucketing(w io.Writer, projectID string) error {
// projectId := "your-project-id"
// table := "your-table-value"
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"}},
},
}
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"}},
},
}
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"}},
},
}
table := &dlppb.Table{
Headers: []*dlppb.FieldId{
{Name: "AGE"},
{Name: "PATIENT"},
{Name: "HAPPINESS SCORE"},
},
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.
fixedSizeBucketingConfig := &dlppb.FixedSizeBucketingConfig{
BucketSize: 10,
LowerBound: &dlppb.Value{
Type: &dlppb.Value_IntegerValue{
IntegerValue: 0,
},
},
UpperBound: &dlppb.Value{
Type: &dlppb.Value_IntegerValue{
IntegerValue: 100,
},
},
}
primitiveTransformation := &dlppb.PrimitiveTransformation_FixedSizeBucketingConfig{
FixedSizeBucketingConfig: fixedSizeBucketingConfig,
}
// Specify field to be encrypted.
fieldId := &dlppb.FieldId{
Name: "HAPPINESS SCORE",
}
// Associate the encryption with the specified field.
fieldTransformation := &dlppb.FieldTransformation{
Transformation: &dlppb.FieldTransformation_PrimitiveTransformation{
PrimitiveTransformation: &dlppb.PrimitiveTransformation{
Transformation: primitiveTransformation,
},
},
Fields: []*dlppb.FieldId{
fieldId,
},
}
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.FixedSizeBucketingConfig;
import com.google.privacy.dlp.v2.LocationName;
import com.google.privacy.dlp.v2.PrimitiveTransformation;
import com.google.privacy.dlp.v2.RecordTransformations;
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;
public class DeIdentifyTableBucketing {
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())
.addRows(
Row.newBuilder()
.addValues(Value.newBuilder().setStringValue("101").build())
.addValues(Value.newBuilder().setStringValue("Charles Dickens").build())
.addValues(Value.newBuilder().setStringValue("95").build())
.build())
.addRows(
Row.newBuilder()
.addValues(Value.newBuilder().setStringValue("22").build())
.addValues(Value.newBuilder().setStringValue("Jane Austen").build())
.addValues(Value.newBuilder().setStringValue("21").build())
.build())
.addRows(
Row.newBuilder()
.addValues(Value.newBuilder().setStringValue("55").build())
.addValues(Value.newBuilder().setStringValue("Mark Twain").build())
.addValues(Value.newBuilder().setStringValue("75").build())
.build())
.build();
deIdentifyTableBucketing(projectId, tableToDeIdentify);
}
public static Table deIdentifyTableBucketing(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.
FixedSizeBucketingConfig fixedSizeBucketingConfig =
FixedSizeBucketingConfig.newBuilder()
.setBucketSize(10)
.setLowerBound(Value.newBuilder().setIntegerValue(0).build())
.setUpperBound(Value.newBuilder().setIntegerValue(100).build())
.build();
PrimitiveTransformation primitiveTransformation =
PrimitiveTransformation.newBuilder()
.setFixedSizeBucketingConfig(fixedSizeBucketingConfig)
.build();
// Specify field to be encrypted.
FieldId fieldId = FieldId.newBuilder().setName("HAPPINESS SCORE").build();
// Associate the encryption with the specified field.
FieldTransformation fieldTransformation =
FieldTransformation.newBuilder()
.setPrimitiveTransformation(primitiveTransformation)
.addFields(fieldId)
.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'}],
rows: [
{
values: [
{integerValue: 101},
{stringValue: 'Charles Dickens'},
{integerValue: 95},
],
},
{
values: [
{integerValue: 22},
{stringValue: 'Jane Austen'},
{integerValue: 21},
],
},
{
values: [
{integerValue: 55},
{stringValue: 'Mark Twain'},
{integerValue: 75},
],
},
],
};
async function deIdentifyTableBucketing() {
// Specify field to be de-identified.
const targetColumn = {name: 'HAPPINESS SCORE'};
// Specify how the content should be de-identified.
const bucketingConfig = {
bucketSize: 10,
lowerBound: {
integerValue: 0,
},
upperBound: {
integerValue: 100,
},
};
const primitiveTransformation = {
fixedSizeBucketingConfig: bucketingConfig,
};
// Combine configurations into a request for the service.
const request = {
parent: `projects/${projectId}/locations/global`,
item: {
table: tablularData,
},
deidentifyConfig: {
recordTransformations: {
fieldTransformations: [
{
fields: [targetColumn],
primitiveTransformation,
},
],
},
},
};
// 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)}`
);
}
deIdentifyTableBucketing();
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\FixedSizeBucketingConfig;
use Google\Cloud\Dlp\V2\PrimitiveTransformation;
use Google\Cloud\Dlp\V2\RecordTransformations;
use Google\Cloud\Dlp\V2\Table;
use Google\Cloud\Dlp\V2\Table\Row;
use Google\Cloud\Dlp\V2\Value;
/**
* De-identify data using table bucketing
* Transform a column without inspection. To transform a column in which the content is
* already known, you can skip inspection and specify a transformation directly.
*
* @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_bucketing(
// TODO(developer): Replace sample parameters before running the code.
string $callingProjectId,
string $inputCsvFile = './test/data/table2.csv',
string $outputCsvFile = './test/data/deidentify_table_bucketing_output.csv'
): void {
// Instantiate a client.
$dlp = new DlpServiceClient();
// 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.
$contentItem = (new ContentItem())
->setTable($tableToDeIdentify);
// Specify how the content should be de-identified.
$fixedSizeBucketingConfig = (new FixedSizeBucketingConfig())
->setBucketSize(10)
->setLowerBound((new Value())
->setIntegerValue(10))
->setUpperBound((new Value())
->setIntegerValue(100));
$primitiveTransformation = (new PrimitiveTransformation())
->setFixedSizeBucketingConfig($fixedSizeBucketingConfig);
// Specify the field to to apply bucketing transform on
$fieldId = (new FieldId())
->setName('HAPPINESS_SCORE');
// Associate the encryption with the specified field.
$fieldTransformation = (new FieldTransformation())
->setPrimitiveTransformation($primitiveTransformation)
->setFields([$fieldId]);
$recordTransformations = (new RecordTransformations())
->setFieldTransformations([$fieldTransformation]);
// Create the deidentification configuration object
$deidentifyConfig = (new DeidentifyConfig())
->setRecordTransformations($recordTransformations);
$parent = "projects/$callingProjectId/locations/global";
// Run request
$deidentifyContentRequest = (new DeidentifyContentRequest())
->setParent($parent)
->setDeidentifyConfig($deidentifyConfig)
->setItem($contentItem);
$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_bucketing(
project: str,
table_data: Dict[str, Union[List[str], List[List[str]]]],
deid_content_list: List[str],
bucket_size: int,
bucketing_lower_bound: int,
bucketing_upper_bound: int,
) -> types.dlp.Table:
"""Uses the Data Loss Prevention API to de-identify sensitive data in a
table by replacing them with fixed size bucket ranges.
Args:
project: The Google Cloud project id to use as a parent resource.
table_data: Dictionary representing table data.
deid_content_list: A list of fields in table to de-identify.
bucket_size: Size of each bucket for fixed sized bucketing
(except for minimum and maximum buckets). So if ``bucketing_lower_bound`` = 10,
``bucketing_upper_bound`` = 89, and ``bucket_size`` = 10, then the
following buckets would be used: -10, 10-20, 20-30, 30-40,
40-50, 50-60, 60-70, 70-80, 80-89, 89+.
bucketing_lower_bound: Lower bound value of buckets.
bucketing_upper_bound: Upper bound value of buckets.
Returns:
De-identified table is returned;
the response from the API is also printed to the terminal.
Example:
>> $ python deidentify_table_bucketing.py \
'{"header": ["email", "phone number", "age"],
"rows": [["robertfrost@example.com", "4232342345", "35"],
["johndoe@example.com", "4253458383", "68"]]}' \
["age"] 10 0 100
>> '{"header": ["email", "phone number", "age"],
"rows": [["robertfrost@example.com", "4232342345", "30:40"],
["johndoe@example.com", "4253458383", "60:70"]]}'
"""
# Instantiate a client.
dlp = google.cloud.dlp_v2.DlpServiceClient()
# Convert the project id into a full resource id.
parent = f"projects/{project}/locations/global"
# 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}
# Construct fixed sized bucketing configuration
fixed_size_bucketing_config = {
"bucket_size": bucket_size,
"lower_bound": {"integer_value": bucketing_lower_bound},
"upper_bound": {"integer_value": bucketing_upper_bound},
}
# Specify fields to be de-identified
deid_content_list = [{"name": _i} for _i in deid_content_list]
# Construct Deidentify Config
deidentify_config = {
"record_transformations": {
"field_transformations": [
{
"fields": deid_content_list,
"primitive_transformation": {
"fixed_size_bucketing_config": fixed_size_bucketing_config
},
}
]
}
}
# Call the API.
response = dlp.deidentify_content(
request={"parent": parent, "deidentify_config": deidentify_config, "item": item}
)
# Print the results.
print(f"Table after de-identification: {response.item.table}")
# Return the response.
return response.item.table
后续步骤
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