At PyRun, we believe in the power of open source. Our platform is built on top of battle-tested open source technologies, and we actively contribute back to the community.
All the tools we use at PyRun are open source. We're committed to transparency and collaboration with the developer community. Below you'll find the key repositories that power our platform.
Lithops is a Python multi-cloud distributed computing framework. It allows you to run unmodified local python code at massive scale in the cloud. It's the core execution engine that powers PyRun's serverless computing capabilities.
An extension of Lithops specifically designed for High-Performance Computing (HPC) environments. This integration enables PyRun users to leverage HPC clusters for computationally intensive workloads, combining the simplicity of serverless with the power of traditional HPC.
Dataplug is an intelligent data partitioning library developed by CloudLab URV. It enables efficient data splitting and distribution for parallel processing, making it essential for handling large datasets in distributed computing scenarios within PyRun.
Our GitHub organization hosts all our ready-to-use pipelines with real-world examples covering various domains. Whether you're working on AI/ML projects, data processing workflows, or cloud computing tasks, you'll find templates and examples to get started quickly.
Pre-built pipelines for training models, batch inference, and distributed ML workflows.
ETL pipelines, data transformation, and large-scale data analysis examples.
Multi-cloud deployment patterns and serverless architecture examples.
Geospatial analysis, genomics, metabolomics, and research-oriented workflows.
PyRun integrates seamlessly with OpenNebula, the open source cloud & edge computing platform. This repository contains the infrastructure code and marketplace appliances that allow you to deploy PyRun on your own OpenNebula infrastructure, giving you complete control over your cloud environment.
We also developed a new backend for Dask Cloudprovider that integrates IBM Code Engine, extending Dask's cloud deployment options with a serverless execution path for distributed workloads.
We welcome contributions from the community! Whether it's bug fixes, new features, documentation improvements, or new pipeline examples, your contributions help make PyRun better for everyone.
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