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: