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A database migrations tool for SQLAlchemy.
DuckDB-powered Postgres for high performance apps & analytics.
Lightweight and extensible compatibility layer between dataframe libraries!
A DuckDB-powered command line interface for Snowflake security, governance, operations, and cost optimization.
A flexible, intuitive and fast forecasting library
A self-hostable CDN for databases. Spice provides a unified SQL query interface and portable runtime to locally materialize, accelerate, and query datasets across databases, data warehouses, and daβ¦
Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data.
Turning PySpark Into a Universal DataFrame API
This is a repo with links to everything you'd ever want to learn about data engineering
Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.
Custom component with dynamic multiselect filters for Streamlit
π² Git scraping for bike sharing APIs
Configs and boilerplates for Label Studio's Machine Learning backend
Kickstart your MLOps initiative with a flexible, robust, and productive Python package.
Distributed DataFrame for Python designed for the cloud, powered by Rust
β¨ The Next Gen Airtable Alternative: No-Code Postgres
Sling is a CLI tool that extracts data from a source storage/database and loads it in a target storage/database.
The Lakehouse Engine is a configuration driven Spark framework, written in Python, serving as a scalable and distributed engine for several lakehouse algorithms, data flows and utilities for Data Pβ¦
Temporian is an open-source Python library for preprocessing β‘ and feature engineering π temporal data π for machine learning applications π€
Make awesome display tables using Python.
A modern Python package and dependency manager supporting the latest PEP standards
Turns Data and AI algorithms into production-ready web applications in no time.
Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
π Build and manage real-life ML, AI, and data science projects with ease!