TokenLib: Versatile Token Generation and Formatting

TokenLib is a powerful and flexible Python library designed for generating, formatting, and managing various types of tokens. It supports custom schema definitions, advanced security features like multiple security versions, and includes utilities for hashing sensitive IDs (e.g., Telegram/Discord) and exporting token data to common formats like SQLite and JSON.

Whether you need to create secure access tokens, unique identifiers, or session keys, TokenLib provides the tools to define your token structure, embed dynamic data, and manage your generated tokens efficiently.

Features

• Custom Token Schemas: Define the exact structure and fields of your tokens.
• Dynamic Data Embedding: Easily embed user IDs, timestamps, event types, and any other relevant data.
• ID Hashing Utilities: Securely hash Telegram, Discord, or other sensitive IDs within your tokens.
• Multiple Security Versions: Implement different token security algorithms or formats for backward compatibility or progressive updates.
• Data Export: Conveniently export generated token data to SQLite databases or JSON files.
• Extensible Design: Designed to be easily extendable for custom encoding, encryption, or formatting needs.

Installation

You can install TokenLib using pip:

bash pip install tokenlib

Basic Usage

Generating Tokens with Custom Schemas

Define your token structure and generate tokens based on your specified data.

python from tokenlib import TokenGenerator

Initialize a token generator with a custom schema and security version

The schema defines the fields that will be included in the token's payload.

generator_v1 = TokenGenerator( schema=["user_id", "session_id", "timestamp"], security_version=1, secret_key="your_super_secret_key_v1" # A real secret key is crucial for security )

Generate a token by providing data matching the schema

token_str_v1 = generator_v1.generate( user_id="alice", session_id="abc-123", timestamp=1678886400 # Example Unix timestamp ) print(f"Generated Token (v1): {token_str_v1}")

You can define a different schema and security version for other token types

generator_v2 = TokenGenerator( schema=["event_type", "entity_id", "initiator_ip"], security_version=2, secret_key="another_secret_key_for_v2" # Different secret key for different version )

token_str_v2 = generator_v2.generate( event_type="login_success", entity_id="product_456", initiator_ip="192.168.1.1" ) print(f"Generated Token (v2): {token_str_v2}")

Hashing Telegram/Discord IDs

TokenLib provides utility functions to hash sensitive IDs before embedding them into tokens, enhancing privacy and security.

python from tokenlib import hash_id

Example Telegram ID hashing

telegram_id = 123456789 hashed_telegram_id = hash_id(telegram_id, service="telegram", salt="your_unique_salt") print(f"Original Telegram ID: {telegram_id}") print(f"Hashed Telegram ID: {hashed_telegram_id}")

Example Discord ID hashing

discord_id = 987654321012345678 hashed_discord_id = hash_id(discord_id, service="discord", salt="another_unique_salt") print(f"Original Discord ID: {discord_id}") print(f"Hashed Discord ID: {hashed_discord_id}")

You can integrate these hashed IDs into your token generation:

generator_secure = TokenGenerator( schema=["user_hash", "action"], security_version=1, secret_key="my_secure_secret" ) token_with_hashed_id = generator_secure.generate( user_hash=hashed_telegram_id, action="view_profile" ) print(f"Token with Hashed ID: {token_with_hashed_id}")

Exporting Token Data

Generated token data can be easily exported to JSON files or SQLite databases for storage, analysis, or integration with other systems.

python from tokenlib import TokenGenerator, export_to_json, export_to_sqlite import os

generator = TokenGenerator( schema=["token_id", "item_name", "price", "generated_at"], security_version=1, secret_key="export_key" )

To export, it's often useful to store the data that generated the token

along with the token string itself.

generated_tokens_data = []

Generate several tokens and store their data

for i in range(3): data = { "token_id": f"TXN-{i+1:03d}", "item_name": f"Product-X{i}", "price": 10.99 + i, "generated_at": 1678886400 + i * 3600 # Increment timestamp } token_string = generator.generate(**data) generated_tokens_data.append({"token_string": token_string, **data})

Export to JSON

json_filename = "tokens_export.json" export_to_json(generated_tokens_data, json_filename) print(f"Tokens exported to {json_filename}")

Clean up for demonstration

os.remove(json_filename)

Export to SQLite

sqlite_filename = "tokens_export.db" export_to_sqlite(generated_tokens_data, sqlite_filename, table_name="transaction_tokens") print(f"Tokens exported to {sqlite_filename} in table 'transaction_tokens'")

Clean up for demonstration

os.remove(sqlite_filename)