Guardrail capabilities for Pydantic AI — cost tracking, prompt injection detection, PII filtering, secret redaction, tool permissions, and async guardrails. Built on pydantic-ai's native capabilities API.

A production-grade control layer that sits between your application logic and any LLM — input validation, schema enforcement, circuit breaking, targeted retry, and audit logging in one composable pipeline.

Cooked Input library for getting and validating input from the command line.

SecureBankingSystem - is a desktop bankAccount manager built with Python and Tkinter, using SQLite for persistence and Argon2id for secure password/PIN hashing. It supports admin/customer workflows, account creation, deposits/withdrawals, PIN changes, and transaction history—designed for learning secure app patterns and prototyping fintech features

CTkEntry widget with provision to add short information, warning, and error messages below the widget.

Advanced Command Line Arguments Parser for Python 3

A python module to validate input.

A python package designed to certify that variables are formatted as intended, and have the right contents

Opinionated schema validation for Python - chain type-safe filters with | like UNIX pipes

ai-workflow-automator turns plain text into validated AI pipeline configs for seamless serverless data workflows.

Validate data in one line. 51+ built-in rules, zero dependencies, clean pipe syntax.

This program is a text-based version of Wordle, the popular word guessing game. The computer randomly selects a hidden five-letter word, and the player has a limited number of attempts to guess it correctly.

A Python package to check input for validity and plausibility. Convert input into standardized formats.

This python script checks a password by hashing it + salt with sha256

Self-improving security filter for AI applications. Learns from missed attacks, auto-deploys validated rules, and self-prunes false positives.

Python bootcamp exercises and assignments focused on exception handling, input validation, and writing robust error-resistant programs.

User input validation with defaults for the Google App Engine datastore.

I love schemas

Python bootcamp exercises and assignments focusing on flow control using loops, conditionals, and structured program logic.