A command-line task management tool for sequential and parallel execution of long-running shell commands.
Pueue is a command-line task management tool that processes a queue of shell commands, enabling sequential and parallel execution of long-running tasks. It runs as a background daemon, allowing users to manage tasks from any terminal and ensuring continuous processing even without active sessions. It focuses on human-centric task management with features like task scheduling, groups, and persistence.
Developers and system administrators who need to manage long-running shell commands, such as data processing pipelines, build systems, or batch jobs, and want a persistent, background queue that survives terminal sessions. It's suited for single users on Linux, macOS, or Windows.
Developers choose Pueue for its simplicity, persistence, and background execution, which allows tasks to run independently of terminal sessions. Unlike heavy-duty schedulers, it prioritizes human interaction with features like easy output inspection, task groups, and cross-platform support without complex setup.
:stars: Manage your shell commands.
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Tasks run independently of terminal sessions, with environment variables and working directories preserved, ensuring continuous processing even after SSH disconnects or logouts.
Supports configurable task groups with parallel limits, allowing users to manage multiple queues and run tasks concurrently based on specific needs, such as concurrent downloads or builds.
Features like easy output inspection, pause/resume, and sending input to running processes make it convenient for interactive task management without heavy scripting.
Fully supported on Linux, macOS, and Windows, with queue and log persistence to disk, surviving crashes or reboots for reliable batch job management.
Designed for single-user interaction, it's not optimized for hundreds of tasks or complex, script-heavy workflows, as the README admits it's not built for heavy-duty work.
Lacks support for multi-user access controls and distributed task execution, focusing solely on local, single-machine use, which limits collaborative or scaled environments.
The scheduling is naive and not designed for advanced load balancing or priority-based execution, which might be insufficient for projects requiring sophisticated optimization.