Totbatch

Totbatch is a batch processing framework designed to organize and execute large numbers of computational tasks across distributed computing resources. It provides a task queue, a scheduling component, and executors that can run tasks locally, in containers, or on remote clusters. The project is typically described as a lightweight alternative to heavier workflow managers, focusing on simplicity, determinism, and extensibility.

Origins and development: Totbatch emerged in open-source communities in the 2010s as developers sought a pragmatic tool for batch-oriented workloads in scientific computing and data processing.

Architecture and features: Key components include a pluggable backend, a dependency-aware scheduler, retry policies, and a persistent job store. It supports priorities, resource constraints, and failure handling. Interfaces include a Python API and a command-line interface; workers can run tasks on CPUs, GPUs, or in containers.

Usage and integrations: Common use cases: data pipelines, simulations, and ETL tasks. It can integrate with cloud storage, message queues, and container orchestration systems; backends may be local, Docker, or Kubernetes. It aims to be complementary to existing tools and can be combined with other schedulers.

Limitations: As a relatively new or niche project, totbatch may have smaller community support and less mature documentation than established frameworks; performance and stability are workload-dependent.