hydra-submitit-launcher
Submitit Launcher for Hydra apps
Decision gist · record as of 2026-08-14
Yes, if you are already using Hydra for configuration management and have access to a Slurm cluster. The integration is straightforward and the permissive license carries no restrictions. However, note that the package has not been updated since May 2022; verify compatibility with your versions of hydra-core and submitit before committing to production use, and monitor the repository for security or compatibility issues.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a Slurm cluster environment; local execution without Slurm will not work as intended.
- Low friction install with only two runtime dependencies (hydra-core and submitit).
- Package is aging—last release was 2022-05-17 with no updates in over 1550 days—but the repository remains active and unarchived.
License · maintenance · safety
permissive license (permissive) — Released under MIT License (permissive), allowing commercial and private use with minimal restrictions.
last release 2022-05-17 (1550 days) · last repo commit 2026-01-14 · 1,632 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 93,072 downloads/mo, #13,402 on PyPI
Alternatives
Verify before relying
pip install hydra-submitit-launcher
from hydra import compose, initialize
from hydra.core.config_store import ConfigStore
# Configure Hydra to use submitit launcher
cs = ConfigStore.instance()
cs.store(name="config", node={"hydra": {"launcher": {"_target_": "hydra_submitit_launcher.submitit_launcher.SlurmLauncher"}}})- Whether the package works with Python versions beyond 3.10 (classifiers list 3.7–3.10 but no explicit upper bound stated)
- Current compatibility with recent versions of hydra-core and submitit given the aging maintenance status
What it is and what it does
Hydra-submitit-launcher is a plugin that bridges Hydra (a configuration management framework) with Submitit (a Slurm job submission tool). It allows you to define your application configuration in Hydra and then submit jobs to a Slurm cluster without writing cluster-specific code directly in your Python functions. The launcher handles job submission, monitoring, and result retrieval through Hydra's standard launcher interface.
The package is designed for researchers and engineers running parameter sweeps, hyperparameter searches, or batch computations on shared clusters. Instead of manually crafting Slurm submission scripts or calling Submitit directly, you configure your job parameters in Hydra's YAML files and let the launcher handle cluster interaction. It abstracts away Slurm details while preserving direct control over individual job logs and preemption handling.
Use it for
- Run Hydra-configured machine learning experiments across multiple Slurm jobs with different hyperparameters.
- Submit batch data processing tasks from a Hydra application to a cluster without modifying core application code.
- Integrate parameter sweeps defined in Hydra config files directly to Slurm for large-scale research workflows.
- Switch between local testing and cluster execution by changing Hydra launcher configuration without code changes.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are already using Hydra for configuration management and have access to a Slurm cluster.
The integration is straightforward and the permissive license carries no restrictions. However, note that the package has not been updated since May 2022; verify compatibility with your versions of hydra-core and submitit before committing to production use, and monitor the repository for security or compatibility issues.
Install
hydra-submitit-launcher on PyPI
Before you install
Low friction install with only two runtime dependencies (hydra-core and submitit). Package is aging—last release was 2022-05-17 with no updates in over 1550 days—but the repository remains active and unarchived.
Requires a Slurm cluster environment; local execution without Slurm will not work as intended.
License in practice
Released under MIT License (permissive), allowing commercial and private use with minimal restrictions.
Quickstart
pip install hydra-submitit-launcher
from hydra import compose, initialize
from hydra.core.config_store import ConfigStore
# Configure Hydra to use submitit launcher
cs = ConfigStore.instance()
cs.store(name="config", node={"hydra": {"launcher": {"_target_": "hydra_submitit_launcher.submitit_launcher.SlurmLauncher"}}})Verify before relying
- Whether the package works with Python versions beyond 3.10 (classifiers list 3.7–3.10 but no explicit upper bound stated)
- Current compatibility with recent versions of hydra-core and submitit given the aging maintenance status
Package facts
| License | permissive license permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packageshydra-coresubmitit |
| Maintenance | Aging 1,550 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 93,072 / month, #13,402 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaLicense :: OSI Approved :: MIT LicenseOperating System :: MacOSOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9 |
Evidence: hydra_submitit_launcher-1.2.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “hydra slurm job submission”
- hydra-submitit-launcherIntegrates Hydra configuration framework with Submitit to submit…
- submititSubmitit wraps Slurm job submission and monitoring, letting you…
- dask-jobqueueDeploys Dask distributed computing clusters on job queuing systems…
Give your agent the search over MCP, or paste the wish link into any chat.
More Distributed Computing packages
gRPC Python is an HTTP/2-based RPC framework that enables you to define and call remote procedures across network boundaries using protocol buffers for serialization.
Install it if you need RPC communication in a distributed system or are integrating with existing gRPC services.
execnet lets you spawn and communicate with Python interpreters across local processes, remote hosts, and different platforms, using a simple API for task distribution and inter-process messaging.
However, the aging maintenance status (275 days since last release) means you should verify it meets your concurrency and performance needs before committing to a…
Cloudpickle extends Python's standard pickle module to serialize lambda functions, interactively-defined functions and classes, and other constructs that the default pickle cannot handle, making it suitable for cluster computing and remote code execution.
Install it if you need to serialize lambda functions, interactively-defined code, or non-standard Python constructs for cluster computing or distributed execution.
Provides a unified, open()-compatible Python API for streaming large files from remote storage (S3, GCS, Azure, HDFS, SFTP, HTTP) and local filesystems, with transparent compression support.
Install it if you work with large files on cloud storage or remote systems and want to avoid writing boilerplate around multiple SDKs.
Portalocker provides cross-platform file locking with support for exclusive and shared locks, plus Redis-based distributed locks and process-aware PID file locking.
Install it if you need file or process coordination; the optional extras (pywin32, redis) are only required for specific lock types.
Ray is a distributed computing framework that scales Python applications from a single machine to multi-node clusters, providing abstractions for parallel tasks, stateful actors, and shared objects.
See also submitit · dask-jobqueue · torchx · Flask-Executor · hydra-core · hydra-optuna-sweeper · aws-parallelcluster · slurm-usage · git-review · dora-search