async def anonymize(piis: List[Pii], config: AnonymizerConfig):
anonymizer = Anonymizer(config)
try:
anonymized_piis = [
AnonymizedPii(text=pii.text, id=pii.id)
for pii in anonymizer.anonymize(piis) if pii.modified
]
except ParserError:
raise HTTPException(status_code=400, detail="Error parsing a pii")
if len(anonymized_piis) != len(piis):
# one or more piis were not flagged as `modified`
logger.error(
f"Invalid config (anonymized_piis={anonymized_piis}; piis={piis}")
raise HTTPException(status_code=400, detail="Invalid Config")
return AnonymizedPiisResponse(anonymized_piis=anonymized_piis)
def generate_data():
try:
generate_data = pd.DataFrame()
rows = int(request.form.get('num_rows'))
anonymize_data = Anonymizer()
fake_names, fake_first_names, fake_second_names = anonymize_data.fake_name_generator(
rows)
generate_data['name'] = fake_names
generate_data['first_name'] = fake_first_names
generate_data['last_name'] = fake_second_names
generate_data['city'] = anonymize_data.get_fake_cities(rows)
generate_data['country'] = anonymize_data.get_fake_countries(rows)
generate_data['street_address'] = anonymize_data.get_fake_addresses(
rows)
generate_data['url'] = anonymize_data.get_fake_uris(rows)
generate_data.to_csv('static/generated_data.csv',
sep='|',
index=None,
header=True)
flash('File successfully generated')
return render_template('index.html',
path_generated_data='static/generated_data.csv')
except:
return render_template('index.html')
def anonymize():
try:
global filepath
data = pd.read_csv(filepath, sep='|')
rows, c = data.shape
selected_name = request.form.get('options_name')
selected_city = request.form.get('options_city')
selected_country = request.form.get('options_country')
selected_address = request.form.get('options_address')
selected_url = request.form.get('options_uri')
anonymize_data = Anonymizer()
if selected_name != 'None':
fake_names, fake_first_names, fake_second_names = anonymize_data.fake_name_generator(
rows)
data[str(selected_name)] = fake_names
if selected_city != 'None':
data[str(selected_city)] = anonymize_data.get_fake_cities(rows)
if selected_country != 'None':
data[str(selected_country)] = anonymize_data.get_fake_countries(
rows)
if selected_address != 'None':
data[str(selected_address)] = anonymize_data.get_fake_addresses(
rows)
if selected_url != 'None':
data[str(selected_url)] = anonymize_data.get_fake_uris(rows)
data.to_csv('static/export_data.csv', sep='|', index=None, header=True)
flash('File successfully anonymized')
return render_template('index.html',
path_anonymize='static/export_data.csv')
except:
return render_template('index.html')
def main(input_path, image_output_path, weights_path, image_extensions,
face_threshold, plate_threshold, write_json, obfuscation_parameters):
download_weights(download_directory=weights_path)
kernel_size, sigma, box_kernel_size = obfuscation_parameters.split(',')
obfuscator = Obfuscator(kernel_size=int(kernel_size),
sigma=float(sigma),
box_kernel_size=int(box_kernel_size))
detectors = {
'face':
Detector(kind='face',
weights_path=get_weights_path(weights_path, kind='face')),
'plate':
Detector(kind='plate',
weights_path=get_weights_path(weights_path, kind='plate'))
}
detection_thresholds = {'face': face_threshold, 'plate': plate_threshold}
anonymizer = Anonymizer(obfuscator=obfuscator, detectors=detectors)
anonymizer.anonymize_images(input_path=input_path,
output_path=image_output_path,
detection_thresholds=detection_thresholds,
file_types=image_extensions.split(','),
write_json=write_json)
def get_structured_data():
inputText = request.form['inputText']
print(inputText)
anonymize_data = Anonymizer()
anonymizedText = anonymize_data.get_anonymize_text(inputText)
return jsonify({"status": "success", "response": anonymizedText})
def anonymize(consumer):
cache = deque()
for msg in consumer:
print(msg)
cache.append(msg)
if len(cache) > CACHE_SIZE:
output = anonymizer.process([{**msg.value} for msg in cache])
if isinstance(output, list):
for _ in output:
yield _
else:
yield output
CACHE_SIZE = 5
anonymizer = Anonymizer({
"drop": {
"keys": ["something-unimportant"]
},
"mean": {
"keys": ["some-number"]
}
})
for anon_msg in anonymize(consumer):
producer.send(
"anon", anon_msg.value
if hasattr(anon_msg, "value") else str(anon_msg).encode())
for line in file.readlines():
#print(line)
line = line.strip() # Guarding against erroneous leading and trailing whitespaces
if startsWithDateTime(line): # If a line starts with a Date Time pattern, then this indicates the beginning of a new message
if len(messageBuffer) > 0: # Check if the message buffer contains characters from previous iterations
parsedData.append([date, time, author, ' '.join(messageBuffer)]) # Save the tokens from the previous message in parsedData
messageBuffer.clear() # Clear the message buffer so that it can be used for the next message
date, time, author, message = getDataPoint(line) # Identify and extract tokens from the line
messageBuffer.append(message) # Append message to buffer
else:
messageBuffer.append(line) # If a line doesn't start with a Date Time pattern, then it is part of a multi-line message. So, just append to buffer
!pip install data-anonymizer-mapper
from anonymizer import Anonymizer
anonymizer = Anonymizer()
print(parsedData)
df = pd.DataFrame(parsedData, columns=['Date', 'Time', 'Author', 'Message'])
df['Author'] = df['Author'].apply(lambda s : anonymizer.get_anonymized_name(s) if s is not None else s)
df.head()
df.describe()
#Number of messages per author
author_messages=df['Author'].value_counts()
#print(author_messages)
author_messages.plot.barh()
messages_Scrum= df.loc[df['Message'].str.contains(pat='scrum')== True]
print(messages_Scrum)
def redact(input_dir, output_dir, anonymizer_config, recognizer_config):
"""Redact the documents in a directory.
This script tries to redact all documents in the given directory and its subdirectories.
Note: The redaction is done in an unsupervised manor. You have to ensure, that the chosen recognizers and
configuration provide results of a sufficient quality on the given data. Do not use for anything critical."""
if input_dir is None or output_dir is None:
raise UsageError("Please provide an input_dir and output_dir.")
input_dir = Path(input_dir)
output_dir = Path(output_dir)
anonymizer_config = Path(anonymizer_config)
recognizer_config = Path(recognizer_config)
with open(anonymizer_config, "r") as f:
config = AnonymizerConfig(**json.load(f))
anonymizer = Anonymizer(config)
with open(recognizer_config, "r") as f:
recognizer_config = nerwhal.Config(**json.load(f))
click.echo(f'Start redacting files in "{input_dir}" ...')
items_to_redact = []
for root, dirs, files in os.walk(input_dir):
for file in files:
items_to_redact += [(root, file)]
with progressbar(items_to_redact) as items:
for root, file in items:
relative_path = Path(os.path.relpath(root,
start=input_dir)) / Path(file)
in_path = input_dir / relative_path
try:
wrapper = FileWrapper(in_path)
except UnsupportedFormat:
click.echo(
f"Warning: Unsupported format for file {relative_path}! This file was skipped!"
)
continue
except Exception:
click.echo(
f"Error while processing file {relative_path}! This file was skipped!",
err=True)
continue
result = nerwhal.recognize(
wrapper.text,
config=recognizer_config,
combination_strategy="smart-fusion",
context_words=True,
return_tokens=False,
)
id_to_piis = {
str(idx): pii
for idx, pii in enumerate(result["ents"])
}
piis_for_anonymizer = [
Pii(tag=pii.tag, text=pii.text, id=idx)
for idx, pii in id_to_piis.items()
]
anonymized_piis = [
anonymized_pii
for anonymized_pii in anonymizer.anonymize(piis_for_anonymizer)
if anonymized_pii.modified
]
for anonymized_pii in anonymized_piis:
unanonymized_pii = id_to_piis[anonymized_pii.id]
wrapper.add_alter(unanonymized_pii.start_char,
unanonymized_pii.end_char,
anonymized_pii.text)
wrapper.apply_alters()
out_path = output_dir / relative_path
out_path.parent.mkdir(parents=True, exist_ok=True)
wrapper.save(out_path)
click.echo(f'The redacted files have been written to "{output_dir}".')
import json
from anonymizer import Anonymizer
from faker import Faker
from faker.providers import internet
import re
anonymizer = Anonymizer()
def anonymize_url(url):
identity = ('username', 'users', 'FirstName', 'lastName', 'LastName',
'FirstName', 'password', 'Password')
for value in identity:
if url.rfind(value) != -1:
return replace(url, value)
return url
def anonymize_ip():
fake = Faker()
fake.add_provider(internet)
ip = fake.ipv4_private()
return ip
def replace(url, string):
position = url.rfind(string) + len(string) + 1
substring = url[position:]
anonymized_string = anonymizer.get_anonymized_name(substring)
an_url = url.replace(substring, anonymized_string)
#print(anonymizer.get_original_name(anonymized_string))