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.
# https://github.com/googleapis/googleapis/blob/master/google/privacy/dlp/v2/dlp.proto / message ByteContentItem
supported_content_types = {
None: 0, # "Unspecified" or BYTES_TYPE_UNSPECIFIED
"image/jpeg": 1, # IMAGE_JPEG
"image/bmp": 2, # IMAGE_BMP
"image/png": 3, # IMAGE_PNG
"image/svg": 4, # IMAGE_SVG - Adjusted to "image/svg+xml" for correct MIME type
"text/plain": 5, # TEXT_UTF8
# Note: No specific MIME type for general "image", mapping to IMAGE for any image type not specified
"image": 6, # IMAGE - Any image type
"application/msword": 7, # WORD_DOCUMENT
"application/pdf": 8, # PDF
"application/powerpoint": 9, # POWERPOINT_DOCUMENT
"application/msexcel": 10, # EXCEL_DOCUMENT
"application/avro": 11, # AVRO
"text/csv": 12, # CSV
"text/tsv": 13, # TSV
}
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.")
