pyper-dev/pyper

Health v2 · maintenance only

Adoption not part of the score

1518 stars · 32 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Pyper is a pure-Python library for building concurrent and parallel data pipelines using functional programming patterns. It unifies threading, multiprocessing, and asyncio behind a simple task decorator and pipe-based composition with zero dependencies.

Use cases

• build concurrent data pipelines in python
• combine asyncio and threading in one pipeline
• parallelize cpu-bound and io-bound steps
• process streaming data with worker pools
• write etl pipelines without race conditions
• compose functions into lazy data-processing pipelines

When to choose

• you want a lightweight, zero-dependency way to mix threads, processes, and async in one pipeline
• you prefer functional, composable pipeline definitions over framework boilerplate
• you need lazy streaming execution with configurable worker counts

When to avoid

• you need a full-featured distributed pipeline orchestrator like Airflow or Dagster
• your workload is trivially sequential and gains nothing from concurrency
• you need strict typing or validation of pipeline data schemas

Facets

library · maturity active

concurrency etl streaming workflow-automation developer-tools python cross-platform asyncio threading multiprocessing data-pipelines functional-programming parallel-computing data-engineering automation

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