Merge branch 'main' into python-bigquery-migration-migration

dlp/snippets/deid.py

@@ -914,6 +914,137 @@ def write_data(data: types.storage.Value) -> str:
 # [END dlp_deidentify_date_shift]
 
 
+# [START dlp_deidentify_time_extract]
+import csv  # noqa: F811, E402, I100
+from datetime import datetime  # noqa: F811, E402, I100
+from typing import List  # noqa: F811, E402
+
+import google.cloud.dlp  # noqa: F811, E402
+
+
+def deidentify_with_time_extract(
+    project: str,
+    date_fields: List[str],
+    input_csv_file: str,
+    output_csv_file: str,
+) -> None:
+    """ Uses the Data Loss Prevention API to deidentify dates in a CSV file through
+     time part extraction.
+    Args:
+        project: The Google Cloud project id to use as a parent resource.
+        date_fields: A list of (date) fields in CSV file to de-identify
+            through time extraction. Example: ['birth_date', 'register_date'].
+            Date values in format: mm/DD/YYYY are considered as part of this
+            sample.
+        input_csv_file: The path to the CSV file to deidentify. The first row
+            of the file must specify column names, and all other rows must
+            contain valid values.
+        output_csv_file: The output file path to save the time extracted data.
+    """
+
+    # Instantiate a client.
+    dlp = google.cloud.dlp_v2.DlpServiceClient()
+
+    # Convert date field list to Protobuf type.
+    def map_fields(field):
+        return {"name": field}
+
+    if date_fields:
+        date_fields = map(map_fields, date_fields)
+    else:
+        date_fields = []
+
+    csv_lines = []
+    with open(input_csv_file) as csvfile:
+        reader = csv.reader(csvfile)
+        for row in reader:
+            csv_lines.append(row)
+
+    #  Helper function for converting CSV rows to Protobuf types
+    def map_headers(header):
+        return {"name": header}
+
+    def map_data(value):
+        try:
+            date = datetime.strptime(value, "%m/%d/%Y")
+            return {
+                "date_value": {
+                    "year": date.year, "month": date.month, "day": date.day
+                }
+            }
+        except ValueError:
+            return {"string_value": value}
+
+    def map_rows(row):
+        return {"values": map(map_data, row)}
+
+    # Using the helper functions, convert CSV rows to protobuf-compatible
+    # dictionaries.
+    csv_headers = map(map_headers, csv_lines[0])
+    csv_rows = map(map_rows, csv_lines[1:])
+
+    # Construct the table dictionary.
+    table = {"headers": csv_headers, "rows": csv_rows}
+
+    # Construct the `item` for table to de-identify.
+    item = {"table": table}
+
+    # Construct deidentify configuration dictionary.
+    deidentify_config = {
+        "record_transformations": {
+            "field_transformations": [
+                {
+                    "primitive_transformation": {
+                        "time_part_config": {
+                            "part_to_extract": "YEAR"
+                        }
+                    },
+                    "fields": date_fields,
+                }
+            ]
+        }
+    }
+
+    # Write to CSV helper methods.
+    def write_header(header):
+        return header.name
+
+    def write_data(data):
+        return data.string_value or "{}/{}/{}".format(
+            data.date_value.month,
+            data.date_value.day,
+            data.date_value.year,
+        )
+
+    # Convert the project id into a full resource id.
+    parent = f"projects/{project}"
+
+    # Call the API
+    response = dlp.deidentify_content(
+        request={
+            "parent": parent,
+            "deidentify_config": deidentify_config,
+            "item": item,
+        }
+    )
+
+    # Print the result.
+    print("Table after de-identification: {}".format(response.item.table))
+
+    # Write results to CSV file.
+    with open(output_csv_file, "w") as csvfile:
+        write_file = csv.writer(csvfile, delimiter=",")
+        write_file.writerow(map(write_header, response.item.table.headers))
+        for row in response.item.table.rows:
+            write_file.writerow(map(write_data, row.values))
+
+    # Print status.
+    print(f"Successfully saved date-extracted output to {output_csv_file}")
+
+
+# [END dlp_deidentify_time_extract]
+
+
 # [START dlp_deidentify_replace_infotype]
 from typing import List  # noqa: F811, E402, I100
 
@@ -2124,6 +2255,30 @@ def deidentify_table_with_multiple_crypto_hash(
         "key_name.",
     )
 
+    time_extract_parser = subparsers.add_parser(
+        "deid_time_extract",
+        help="Deidentify dates in a CSV file by extracting a date part.",
+    )
+    time_extract_parser.add_argument(
+        "project",
+        help="The Google Cloud project id to use as a parent resource.",
+    )
+    time_extract_parser.add_argument(
+        "input_csv_file",
+        help="The path to the CSV file to deidentify. The first row of the "
+             "file must specify column names, and all other rows must contain "
+             "valid values.",
+    )
+    time_extract_parser.add_argument(
+        "date_fields",
+        nargs="+",
+        help="The list of date fields in the CSV file to de-identify. Example: "
+             "['birth_date', 'register_date']",
+    )
+    time_extract_parser.add_argument(
+        "output_csv_file", help="The path to save the time-extracted data."
+    )
+
     replace_with_infotype_parser = subparsers.add_parser(
         "replace_with_infotype",
         help="Deidentify sensitive data in a string by replacing it with the "
@@ -2485,6 +2640,13 @@ def deidentify_table_with_multiple_crypto_hash(
             wrapped_key=args.wrapped_key,
             key_name=args.key_name,
         )
+    elif args.content == "deid_time_extract":
+        deidentify_with_time_extract(
+            args.project,
+            date_fields=args.date_fields,
+            input_csv_file=args.input_csv_file,
+            output_csv_file=args.output_csv_file,
+        )
     elif args.content == "replace_with_infotype":
         deidentify_with_replace_infotype(
             args.project,

dlp/snippets/deid_test.py

@@ -230,6 +230,21 @@ def test_deidentify_with_date_shift_using_context_field(
     assert "Successful" in out
 
 
+def test_deidentify_with_time_extract(tempdir: TextIO, capsys: pytest.CaptureFixture) -> None:
+    output_filepath = os.path.join(str(tempdir), "year-extracted.csv")
+
+    deid.deidentify_with_time_extract(
+        GCLOUD_PROJECT,
+        input_csv_file=CSV_FILE,
+        output_csv_file=output_filepath,
+        date_fields=DATE_FIELDS,
+    )
+
+    out, _ = capsys.readouterr()
+
+    assert "Successful" in out
+
+
 def test_reidentify_with_fpe(capsys: pytest.CaptureFixture) -> None:
     labeled_fpe_string = "My SSN is SSN_TOKEN(9):731997681"