O Cloud Data Loss Prevention (Cloud DLP) agora faz parte da Proteção de dados confidenciais. O nome da API continua o mesmo: API Cloud Data Loss Prevention (API DLP). Saiba mais sobre os serviços que fazem parte da
Proteção de dados confidenciais.
Inspecionar um arquivo local
Mantenha tudo organizado com as coleções
Salve e categorize o conteúdo com base nas suas preferências.
Demonstra como localizar dados confidenciais em um arquivo de texto ou imagem local.
Mais informações
Para ver a documentação detalhada que inclui este exemplo de código, consulte:
Exemplo de código
Python
Para saber como instalar e usar a biblioteca de cliente para proteção de dados sensíveis, consulte
Bibliotecas de cliente de proteção de dados sensíveis.
Para usar a proteção de dados sensíveis, configure o Application Default Credentials.
Para mais informações, consulte
Configurar a autenticação para um ambiente de desenvolvimento local.
import mimetypes
from typing import List
from typing import Optional
import google.cloud.dlp
def inspect_file(
project: str,
filename: str,
info_types: List[str],
min_likelihood: str = None,
custom_dictionaries: List[str] = None,
custom_regexes: List[str] = None,
max_findings: Optional[int] = None,
include_quote: bool = True,
mime_type: str = None,
) -> None:
"""Uses the Data Loss Prevention API to analyze a file for protected data.
Args:
project: The Google Cloud project id to use as a parent resource.
filename: The path to the file to inspect.
info_types: A list of strings representing info types to look for.
A full list of info type categories can be fetched from the API.
min_likelihood: A string representing the minimum likelihood threshold
that constitutes a match. One of: 'LIKELIHOOD_UNSPECIFIED',
'VERY_UNLIKELY', 'UNLIKELY', 'POSSIBLE', 'LIKELY', 'VERY_LIKELY'.
max_findings: The maximum number of findings to report; 0 = no maximum.
include_quote: Boolean for whether to display a quote of the detected
information in the results.
mime_type: The MIME type of the file. If not specified, the type is
inferred via the Python standard library's mimetypes module.
Returns:
None; the response from the API is printed to the terminal.
"""
# Instantiate a client.
dlp = google.cloud.dlp_v2.DlpServiceClient()
# Prepare info_types by converting the list of strings into a list of
# dictionaries (protos are also accepted).
if not info_types:
info_types = ["FIRST_NAME", "LAST_NAME", "EMAIL_ADDRESS"]
info_types = [{"name": info_type} for info_type in info_types]
# Prepare custom_info_types by parsing the dictionary word lists and
# regex patterns.
if custom_dictionaries is None:
custom_dictionaries = []
dictionaries = [
{
"info_type": {"name": f"CUSTOM_DICTIONARY_{i}"},
"dictionary": {"word_list": {"words": custom_dict.split(",")}},
}
for i, custom_dict in enumerate(custom_dictionaries)
]
if custom_regexes is None:
custom_regexes = []
regexes = [
{
"info_type": {"name": f"CUSTOM_REGEX_{i}"},
"regex": {"pattern": custom_regex},
}
for i, custom_regex in enumerate(custom_regexes)
]
custom_info_types = dictionaries + regexes
# Construct the configuration dictionary. Keys which are None may
# optionally be omitted entirely.
inspect_config = {
"info_types": info_types,
"custom_info_types": custom_info_types,
"min_likelihood": min_likelihood,
"include_quote": include_quote,
"limits": {"max_findings_per_request": max_findings},
}
# If mime_type is not specified, guess it from the filename.
if mime_type is None:
mime_guess = mimetypes.MimeTypes().guess_type(filename)
mime_type = mime_guess[0]
# Select the content type index from the list of supported types.
supported_content_types = {
None: 0, # "Unspecified"
"image/jpeg": 1,
"image/bmp": 2,
"image/png": 3,
"image/svg": 4,
"text/plain": 5,
}
content_type_index = supported_content_types.get(mime_type, 0)
# Construct the item, containing the file's byte data.
with open(filename, mode="rb") as f:
item = {"byte_item": {"type_": content_type_index, "data": f.read()}}
# 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:
try:
print(f"Quote: {finding.quote}")
except AttributeError:
pass
print(f"Info type: {finding.info_type.name}")
print(f"Likelihood: {finding.likelihood}")
else:
print("No findings.")
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