Jws To Csv Converter Link

"user": "id": 123, "name": "Alice", "permissions": ["read", "write"]

def jws_to_csv(input_file, output_file, fields_of_interest=None): """ Convert a file of JWS tokens (one per line) to CSV. fields_of_interest: list of claim names to extract (e.g., ['sub', 'exp', 'role']) """ tokens = Path(input_file).read_text().splitlines() rows = [] jws to csv converter

Opening a raw .log file full of base64url-encoded strings isn’t practical. But dropping that data into a CSV? Now you can sort, filter, and pivot. "user": "id": 123

To flatten these into CSV columns (e.g., user.id , permissions.0 ), you can use pandas.json_normalize() instead of the direct DataFrame constructor. "write"] def jws_to_csv(input_file

Replace the row-building section with:

eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiIxMjMiLCJyb2xlIjoidXNlciIsImV4cCI6MTczNTY4OTAwMH0.signature1 eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiI0NTYiLCJyb2xlIjoiYWRtaW4iLCJleHAiOjE3MzU2ODkwMDB9.signature2 python jws_to_csv.py tokens.txt output.csv --fields sub,role