pandera

Production-shaped MLOps Python package and reference implementation of the MLOps Coding Course: MLflow, scikit-learn, Pydantic, Pandera, uv, and mise.

A kedro plugin to use pandera in your kedro projects

Tutorial for implementing data validation in data science pipelines

An ETL Orchestration using Apache Airflow to extract CSV files from a Google Drive, validate, transform, and load into a PostgreSQL database.

Lightweight, open source, locally-hosted Modern Data Stack

Um scraper e processador de dados automatizado para extrair, limpar e organizar relatórios financeiros do portal IF.data do Banco Central do Brasil.

ETL pipeline that collects, validates and tracks UK video game prices across Nintendo eShop, PlayStation, Steam and Xbox, with price history, alerts, an API and a dashboard.

Pipeline ETL utilizando Pandera, pytest e CI

HDRUK Data Science Collaboration on Avoidable Admissions in the NHS.

Python SDK for Polymarket — every endpoint returns a pandas DataFrame. Sync + async HTTP, WebSockets, pandera schemas, order building & signing, on-chain CTF operations.

Pandera Report for row-based reporting by using the power of pandera.

📊 Swagger-like UI for Pandera schemas: browse columns, checks, and metadata in one place.

Privacy-preserving, local-first pipeline for multimodal clinical interview data. The gold aggregation is implemented twice, independently, in Python and SQL, then reconciled across all 981 columns of the real 141-session dataset. Synthetic-by-default, with deliberate fault injection to prove validation and quarantine actually work.

AetherFlow is a Python library that uses autonomous agent to automatically transform Pandas DataFrames to conform with a Pandera schema. It analyzes validation errors and applies the necessary tools to fix issues, iterating until the DataFrame adheres to the schema's rules.

End-to-end MLOps pipeline predicting Polish apartment prices - DVC + MLflow registry + FastAPI + Streamlit demo, with conformal prediction intervals and drift monitoring.

Production-grade Data Engineering Lakehouse using PySpark, Apache Airflow, Docker, PostgreSQL, Power BI and Medallion Architecture.

A problem-driven, 7-phase learning lab and pipeline for data contracts and quality engineering using Pandera and pandas.

Testing Pydantic, FastAPI, polyfactory, pandera and GraphQL with SQLModel and pydantic-mongo

Project that utilises Pandera to explore schema type check on pandas dataframe insertion, utilises Pipenv, .pre-commit-config.yaml and pytest coverage.

Demo for the talk "make model validation sexy again"