does anyone have an idea how to solve the issue with the invalidtoken?
The key(s) should be the same, but still I am getting this invalid token error.
I attached my code and an image of the fake table.
Cheers!
import pandas as pd
from cryptography.fernet import Fernet, InvalidToken
# Create an example dataframe
data = {'Name': ['Alice', 'Bob', 'Charlie'],
'Salary': [50000, 70000, 90000]}
df = pd.DataFrame(data)
# Generate a key for encryption
key = Fernet.generate_key()
# Create a Fernet object using the key
f = Fernet(key)
# Encrypt the 'Salary' column
df['Salary'] = df['Salary'].apply(lambda x: f.encrypt(str(x).encode()))
# Save the encrypted data to a CSV file
df.to_csv('encrypted_data.csv', index=False)
# Load the encrypted data from the CSV file
df = pd.read_csv('encrypted_data.csv')
# Decrypt the 'Salary' column
try:
df['Salary'] = df['Salary'].apply(lambda x: int(f.decrypt(x.encode()).decode()))
except InvalidToken as e:
print(f"Error: {e}")
print(f"Key: {key}")
raise
# Print the decrypted data
print(df)
I tried the code above and was expecting to decrypt the column salary. However, I got an invalidtoken error.
f.encrypt(...)
returns a bytes-like object. When storing with to_csv()
the string represenation is stored b'...'
, which can be seen in your screenshot.
When loading with read_csv()
this string is loaded and x.encode()
results in a b"b'...'"
which causes the decryption to fail.
To avoid this the ciphertext has to be UTF-8 decoded when encrypting:
df['Salary'] = df['Salary'].apply(lambda x: f.encrypt(str(x).encode()).decode())
Then decryption works and print(df)
returns for the encrypted and decrypted data: