Dev tools · alternatives · 2026
24 alternatives to PyExPool – Tiny Multi-Process Execution Pool for Python
Python Multi-Process Execution Pool: concurrent asynchronous execution pool with custom resource constraints (memory, timeouts, affinity, CPU cores and caching), load balancing and profiling capabilities of the external apps on NUMA architecture - eXascaleInfolab/PyExPool
PyExPool is a Python library that manages concurrent execution of tasks across multiple processes with customizable resource constraints including memory limits, timeouts, CPU core allocation, and processor affinity.… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. PyExPool – Tiny Multi-Process Execution Pool for Python launched in 2016; newer entries below may have overtaken it.
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shpool is a terminal session persistence tool developed internally at google to support remote workflows, which we have open sourced.
2024 · github.com · its alternatives →
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Hi everyone, I built PyXL — a hardware processor that executes a custom assembly generated from Python programs, without using a traditional interpreter or virtual machine. It compiles Python -> CPython Bytecode -> Instruction set designed for direct hardware execution. I’m sharing an early benchmark: a GPIO test where PyXL achieves a 480ns round-trip toggle — compared to 14-25 micro seconds on a MicroPython Pyboard - even though PyXL runs at a lower clock (100MHz vs. 168MHz). The design is stack-based, fully pipelined, and preserves Python's dynamic typing without static type restrictions.…
2025 · runpyxl.com · its alternatives →
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forkrun is the culmination of a 10-year-long journey focused on "how to make shell parallelization fast". What started as a standard "fork jobs in a loop" has turned into a lock-free, CAS-retry-loop-free, SIMD-accelerated, self-tuning, NUMA aware shell-based stream parallelization engine that is (mostly) a drop-in replacement for xargs -P and GNU parallel. On my 14-core/28-thread i9-7940x, forkrun achieves: * 200,000+ batch dispatches/sec (vs ~500 for GNU Parallel) * ~95–99% CPU utilization across all 28 logical cores, even when the workload is non-existant (bash no-ops / `:`)…
Mar 2026 · github.com · its alternatives →
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Utility function to parallelise pipelines of Python asyncio iterators/generators - michalc/asyncio-buffered-pipeline
2020 · github.com · its alternatives →
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2011 · adeel.github.com · its alternatives →
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Hello and happy new year! We're excited to introduce the Pyper package for concurrency & parallelism in Python. Pyper is a flexible framework for concurrent / parallel data processing, following the functional paradigm. Source code can be found on [github](https://github.com/pyper-dev/pyper) Key features: Intuitive API: Easy to learn, easy to think about. Implements clean abstractions to seamlessly unify threaded, multiprocessed, and asynchronous work. Functional Paradigm: Python functions are the building blocks of data pipelines. Let's you write clean, reusable…
2025 · github.com · its alternatives →
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This project explores the integration of multithreading into the asyncio event loop in Python. While this was initially built with enhancing CPU utilization for FastAPI servers in mind, the approach can be used with more general async programs too. If you’re interested in diving deeper into the details, I’ve written a blog post about it here: https://www.neilbotelho.com/blog/multithreaded-async.html
2024 · github.com · its alternatives →
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Hi HN ! Alex here. I'm excited to show you Asyncpal (https://github.com/pyrustic/asyncpal), a Python library for parallelism [1] and preemptive concurrency [2] tailored for sporadic workloads [3]. I've been working on a private project where it would be convenient to have asynchronous versions of some operations without using `async/await` [4]. Besides `async/await`, which represents cooperative concurrency via the `asyncio` package, Python also provides preemptive concurrency through its `threading` package. Additionally, the `concurrent.futures` package builds…
2024 · github.com · its alternatives →
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Python stream processing for humans. Contribute to omegaml/minibatch development by creating an account on GitHub.
2020 · github.com · its alternatives →
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DEPRECATED StackImpact Python Profiler - Production-Grade Performance Profiler: CPU, memory allocations, blocking calls, exceptions, metrics, and more - stackimpact/stackimpact-python
2017 · github.com · its alternatives →
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A lightweight database with Python syntax queries, using ZeroMQ - asrp/pyzdb
2017 · github.com · its alternatives →
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Hey HN, this is Will and David from Fortress (https://news.ycombinator.com/item?id=41426998). We use a lot of async Rust internally, and created this library out of a need for an async-aware concurrent hashmap since there weren’t many available in the Rust ecosystem. Whirlwind is a sharded HashMap with a fully asynchronous API. Just as dashmap is a replacement for std::sync::RwLock, whirlwind aims to be a replacement for tokio::sync::RwLock. It has a similar design and performance characteristics to dashmap, but seems to perform better in read-heavy workloads with tokio's…
2024 · github.com · its alternatives →
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Dead easy interface for executing many HTTP requests asynchronously. Also provides helper functions for executing embarrassingly parallel async coroutines. - joshlk/many_requests
2020 · github.com · its alternatives →
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2018 · gitlab.com · its alternatives →
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This project launches multiple independent programs into a single shared virtual address space, while still behaving like separate processes (independent binaries, globals, and lifetimes). When threadprocs share their address space, pointers are valid across them with no code changes for well-behaved Linux binaries. Unlike threads, each threadproc is a standalone and semi-isolated process. Unlike dlopen-based plugin systems, threadprocs run traditional executables with a `main()` function. Unlike POSIX processes, pointers remain valid across threadprocs because they share the same address…
Mar 2026 · github.com · its alternatives →
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Pydoll is a library for automating chromium-based browsers without a WebDriver, offering realistic interactions. - GitHub - autoscrape-labs/pydoll: Pydoll is a library for automating chromium-based browsers without a WebDriver, offering realistic interactions.
2025 · github.com · its alternatives →
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Simple Python Calculation Engine. Contribute to bsdz/calcengine development by creating an account on GitHub.
2021 · github.com · its alternatives →
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Pyexperiment▲49Run experiments with Python - quick and clean. Contribute to duerrp/pyexperiment development by creating an account on GitHub.
2015 · github.com · its alternatives →
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2016 · samanbarghi.com · its alternatives →
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Python ports of useful syscalls, using asynchronous I/O. - zacharyvoase/teena
2012 · github.com · its alternatives →
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Real Goroutines for Python 3.13t+ free-threaded. Contribute to robertsdotpm/runloom development by creating an account on GitHub.
Jul 2026 · github.com · its alternatives →
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Python Stream Processing. Contribute to bytewax/bytewax development by creating an account on GitHub.
2022 · github.com · its alternatives →
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Typed Python API for tmux. Control servers, sessions, windows, and panes as Python objects. Quickstart Install and make your first API call in 5 minutes. Quickstart Topics Architecture, traversal, ...
2016 · libtmux.git-pull.com · its alternatives →
Also compare
- Shpool, a Lightweight Tmux Alternative alternatives
- I built a hardware processor that runs Python alternatives
- Forkrun – NUMA-aware shell parallelizer (50×–400× faster than parallel) alternatives
- Parallelise pipelines of Python async iterables alternatives
- Pump, a dead simple Pythonic abstraction of HTTP. alternatives
- Pyper – Concurrent Python Made Simple alternatives
Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →