# submitit **Repository Path**: mirrors_facebookincubator/submitit ## Basic Information - **Project Name**: submitit - **Description**: Python 3.8+ toolbox for submitting jobs to Slurm - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2020-08-08 - **Last Updated**: 2026-03-28 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README [![CircleCI](https://circleci.com/gh/facebookincubator/submitit.svg?style=svg)](https://circleci.com/gh/facebookincubator/workflows/submitit) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![Pypi](https://img.shields.io/pypi/v/submitit)](https://pypi.org/project/submitit/) [![conda-forge](https://img.shields.io/conda/vn/conda-forge/submitit)](https://anaconda.org/conda-forge/submitit) # Submit it! ## What is submitit? Submitit is a lightweight tool for submitting Python functions for computation within a Slurm cluster. It basically wraps submission and provide access to results, logs and more. [Slurm](https://slurm.schedmd.com/quickstart.html) is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for large and small Linux clusters. Submitit allows to switch seamlessly between executing on Slurm or locally. ### An example is worth a thousand words: performing an addition From inside an environment with `submitit` installed: ```python import submitit def add(a, b): return a + b # executor is the submission interface (logs are dumped in the folder) executor = submitit.AutoExecutor(folder="log_test") # set timeout in min, and partition for running the job executor.update_parameters(timeout_min=1, slurm_partition="dev") job = executor.submit(add, 5, 7) # will compute add(5, 7) print(job.job_id) # ID of your job output = job.result() # waits for completion and returns output assert output == 12 # 5 + 7 = 12... your addition was computed in the cluster ``` The `Job` class also provides tools for reading the log files (`job.stdout()` and `job.stderr()`). If what you want to run is a command, turn it into a Python function using `submitit.helpers.CommandFunction`, then submit it. By default stdout is silenced in `CommandFunction`, but it can be unsilenced with `verbose=True`. **Find more examples [here](docs/examples.md)!!!** Submitit is a Python 3.8+ toolbox for submitting jobs to Slurm. It aims at running python function from python code. ## Install Quick install, in a virtualenv/conda environment where `pip` is installed (check `which pip`): - stable release: ``` pip install submitit ``` - stable release using __conda__: ``` conda install -c conda-forge submitit ``` - main branch: ``` pip install git+https://github.com/facebookincubator/submitit@main#egg=submitit ``` You can try running the [MNIST example](docs/mnist.py) to check that everything is working as expected (requires sklearn). ## Documentation See the following pages for more detailled information: - [Examples](docs/examples.md): for a bunch of examples dealing with errors, concurrency, multi-tasking etc... - [Structure and main objects](docs/structure.md): to get a better understanding of how `submitit` works, which files are created for each job, and the main objects you will interact with. - [Checkpointing](docs/checkpointing.md): to understand how you can configure your job to get checkpointed when preempted and/or timed-out. - [Tips and caveats](docs/tips.md): for a bunch of information that can be handy when working with `submitit`. - [Hyperparameter search with nevergrad](docs/nevergrad.md): basic example of `nevergrad` usage and how it interfaces with `submitit`. ### Goals The aim of this Python3 package is to be able to launch jobs on Slurm painlessly from *inside Python*, using the same submission and job patterns than the standard library package `concurrent.futures`: Here are a few benefits of using this lightweight package: - submit any function, even lambda and script-defined functions. - raises an error with stack trace if the job failed. - requeue preempted jobs (Slurm only) - swap between `submitit` executor and one of `concurrent.futures` executors in a line, so that it is easy to run your code either on slurm, or locally with multithreading for instance. - checkpoints stateful callables when preempted or timed-out and requeue from current state (advanced feature). - easy access to task local/global rank for multi-nodes/tasks jobs. - same code can work for different clusters thanks to a plugin system. Submitit is used by FAIR researchers on the FAIR cluster. The defaults are chosen to make their life easier, and might not be ideal for every cluster. ### Non-goals - a commandline tool for running slurm jobs. Here, everything happens inside Python. To this end, you can however use [Hydra](https://hydra.cc/)'s [submitit plugin](https://hydra.cc/docs/next/plugins/submitit_launcher) (version >= 1.0.0). - a task queue, this only implements the ability to launch tasks, but does not schedule them in any way. - being used in Python2! This is a Python3.8+ only package :) ### Comparison with dask.distributed [`dask`](https://distributed.dask.org/en/latest/) is a nice framework for distributed computing. `dask.distributed` provides the same `concurrent.futures` executor API as `submitit`: ```python from distributed import Client from dask_jobqueue import SLURMCluster cluster = SLURMCluster(processes=1, cores=2, memory="2GB") cluster.scale(2) # this may take a few seconds to launch executor = Client(cluster) executor.submit(...) ``` The key difference with `submitit` is that `dask.distributed` distributes the jobs to a pool of workers (see the `cluster` variable above) while `submitit` jobs are directly jobs on the cluster. In that sense `submitit` is a lower level interface than `dask.distributed` and you get more direct control over your jobs, including individual `stdout` and `stderr`, and possibly checkpointing in case of preemption and timeout. On the other hand, you should avoid submitting multiple small tasks with `submitit`, which would create many independent jobs and possibly overload the cluster, while you can do it without any problem through `dask.distributed`. ## Contributors By chronological order: Jérémy Rapin, Louis Martin, Lowik Chanussot, Lucas Hosseini, Fabio Petroni, Francisco Massa, Guillaume Wenzek, Thibaut Lavril, Vinayak Tantia, Andrea Vedaldi, Max Nickel, Quentin Duval, Rushil Patel (feel free to [contribute](.github/CONTRIBUTING.md) and add your name ;) ) ## License Submitit is released under the [MIT License](LICENSE).