{"author":"Arturo Mendoza","author_email":null,"bugtrack_url":null,"classifiers":["Development Status :: 5 - Production/Stable","License :: OSI Approved :: GNU Affero General Public License v3","Operating System :: OS Independent","Programming Language :: Python :: 3"],"description":"

Simple Slurm

A simple Python wrapper for Slurm with flexibility in mind

\n $\"Run$ \n $\"PyPI$ \n $\"PyPI$ \n $\"Conda$ \n

\n\n\n```python\nimport datetime\n\nfrom simple_slurm import Slurm\n\nslurm = Slurm(\n array=range(3, 12),\n cpus_per_task=15,\n dependency=dict(after=65541, afterok=34987),\n gres=[\"gpu:kepler:2\", \"gpu:tesla:2\", \"mps:400\"],\n ignore_pbs=True,\n job_name=\"name\",\n output=f\"{Slurm.JOB_ARRAY_MASTER_ID}_{Slurm.JOB_ARRAY_ID}.out\",\n time=datetime.timedelta(days=1, hours=2, minutes=3, seconds=4),\n)\nslurm.add_cmd(\"module load python\")\nslurm.sbatch(\"python demo.py\", Slurm.SLURM_ARRAY_TASK_ID)\n```\nThe above snippet is equivalent to running the following command:\n\n```bash\nsbatch << EOF\n#!/bin/sh\n\n#SBATCH --array 3-11\n#SBATCH --cpus-per-task 15\n#SBATCH --dependency after:65541,afterok:34987\n#SBATCH --gres gpu:kepler:2,gpu:tesla:2,mps:400\n#SBATCH --ignore-pbs\n#SBATCH --job-name name\n#SBATCH --output %A_%a.out\n#SBATCH --time 1-02:03:04\n\nmodule load python\npython demo.py \\$SLURM_ARRAY_TASK_ID\n\nEOF\n```\n\n## Contents\n\n+ [Installation](#installation)\n+ [Introduction](#introduction)\n+ [Core Features](#core-features)\n - [Pythonic Slurm Syntax](#pythonic-slurm-syntax) *(was \"Many syntaxes available\")*\n - [Adding Commands with `add_cmd`](#adding-commands-with-add_cmd)\n - [Job Dependencies](#job-dependencies)\n+ [Advanced Features](#advanced-features)\n - [Command-Line Interface (CLI)](#command-line-interface-cli)\n - [Using Configuration Files](#using-configuration-files)\n - [Filename Patterns and Environment Variables](#filename-patterns-and-environment-variables)\n - [Change execution shell](#change-execution-shell)\n+ [Job Management](#job-management)\n - [Monitoring Jobs with `squeue`](#monitoring-jobs-with-squeue)\n - [Canceling Jobs with `scancel`](#canceling-jobs-with-scancel)\n+ [Error Handling](#error-handling)\n+ [Project Growth](#project-growth)\n\n\n## Installation\n\nThe source code is currently hosted : [https://github.com/amq92/simple_slurm](https://github.com/amq92/simple_slurm)\n\nInstall the latest `simple_slurm` version with:\n\n```bash\npip install simple_slurm\n```\nor using `conda`\n```bash\nconda install -c conda-forge simple_slurm\n```\n\n## Introduction\n\nThe [`sbatch`](https://slurm.schedmd.com/sbatch.html) and [`srun`](https://slurm.schedmd.com/srun.html) commands in [Slurm](https://slurm.schedmd.com/overview.html) allow submitting parallel jobs into a Linux cluster in the form of batch scripts that follow a certain structure.\n\nThe goal of this library is to provide a simple wrapper for these core functions so that Python code can be used for constructing and launching the aforementioned batch script.\n\nIndeed, the generated batch script can be shown by printing the `Slurm` object:\n\n```python\nfrom simple_slurm import Slurm\n\nslurm = Slurm(array=range(3, 12), job_name=\"name\")\nprint(slurm)\n```\n```bash\n>> #!/bin/sh\n>> \n>> #SBATCH --array 3-11\n>> #SBATCH --job-name name\n```\n\nThen, the job can be launched with either command:\n```python\nslurm.srun(\"echo hello!\")\nslurm.sbatch(\"echo hello!\")\n```\n```bash\n>> Submitted batch job 34987\n```\n\nWhile both commands are quite similar, [`srun`](https://slurm.schedmd.com/srun.html) will wait for the job completion, while [`sbatch`](https://slurm.schedmd.com/sbatch.html) will launch and disconnect from the jobs.\n> More information can be found in [Slurm's Quick Start Guide](https://slurm.schedmd.com/quickstart.html) and in [here](https://stackoverflow.com/questions/43767866/slurm-srun-vs-sbatch-and-their-parameters).\n\n\n\n## Core Features\n\n### Pythonic Slurm Syntax\n\n```python\nslurm = Slurm(\"-a\", \"3-11\")\nslurm = Slurm(\"--array\", \"3-11\")\nslurm = Slurm(\"array\", \"3-11\")\nslurm = Slurm(array=\"3-11\")\nslurm = Slurm(array=range(3, 12))\nslurm.add_arguments(array=range(3, 12))\nslurm.set_array(range(3, 12))\n```\n\nAll these arguments are equivalent!\nIt's up to you to choose the one(s) that best suits you needs.\n\n> *\"With great flexibility comes great responsability\"*\n\nYou can either keep a command-line-like syntax or a more Python-like one.\n\n```python\nslurm = Slurm()\nslurm.set_dependency(\"after:65541,afterok:34987\")\nslurm.set_dependency([\"after:65541\", \"afterok:34987\"])\nslurm.set_dependency(dict(after=65541, afterok=34987))\n```\n\nAll the possible arguments have their own setter methods\n(ex. `set_array`, `set_dependency`, `set_job_name`).\n\nPlease note that hyphenated arguments, such as `--job-name`, need to be underscored\n(so to comply with Python syntax and be coherent).\n\n```python\nslurm = Slurm(\"--job_name\", \"name\")\nslurm = Slurm(job_name=\"name\")\n\n# slurm = Slurm(\"--job-name\", \"name\") # NOT VALID\n# slurm = Slurm(job-name=\"name\") # NOT VALID\n```\n\nMoreover, boolean arguments such as `--contiguous`, `--ignore_pbs` or `--overcommit` \ncan be activated with `True` or an empty string.\n\n```python\nslurm = Slurm(\"--contiguous\", True)\nslurm.add_arguments(ignore_pbs=\"\")\nslurm.set_wait(False)\nprint(slurm)\n```\n```bash\n#!/bin/sh\n\n#SBATCH --contiguous\n#SBATCH --ignore-pbs\n```\n\n\n### Adding Commands with `add_cmd`\n\nThe `add_cmd` method allows you to add multiple commands to the Slurm job script. These commands will be executed in the order they are added before the main command specified in `sbatch` or `srun` directive.\n\n```python\nfrom simple_slurm import Slurm\n\nslurm = Slurm(job_name=\"my_job\", output=\"output.log\")\n\n# Add multiple commands\nslurm.add_cmd(\"module load python\")\nslurm.add_cmd(\"export PYTHONPATH=/path/to/my/module\")\nslurm.add_cmd('echo \"Environment setup complete\"')\n\n# Submit the job with the main command\nslurm.sbatch(\"python my_script.py\")\n```\n\nThis will generate a Slurm job script like:\n\n```bash\n#!/bin/sh\n\n#SBATCH --job-name my_job\n#SBATCH --output output.log\n\nmodule load python\nexport PYTHONPATH=/path/to/my/module\necho \"Environment setup complete\"\npython my_script.py\n```\n\nYou can reset the list of commands using the `reset_cmd` method:\n\n```python\nslurm.reset_cmd() # Clears all previously added commands\n```\n\n\n### Job dependencies\n\nThe `sbatch` call prints a message if successful and returns the corresponding `job_id` \n\n```python\njob_id = slurm.sbatch(\"python demo.py \" + Slurm.SLURM_ARRAY_TAKSK_ID)\n```\n\nIf the job submission was successful, it prints:\n\n```\nSubmitted batch job 34987\n```\n\nAnd returns the variable `job_id = 34987`, which can be used for setting dependencies on subsequent jobs\n\n```python\nslurm_after = Slurm(dependency=dict(afterok=job_id)))\n```\n\n\n## Advanced Features\n\n### Command-Line Interface (CLI)\n\nFor simpler dispatch jobs, a command line entry point is also made available.\n\n```bash\nsimple_slurm [OPTIONS] \"COMMAND_TO_RUN_WITH_SBATCH\"\n```\n\nAs such, both of these `python` and `bash` calls are equivalent.\n\n```python\nslurm = Slurm(partition=\"compute.p\", output=\"slurm.log\", ignore_pbs=True)\nslurm.sbatch(\"echo \\$HOSTNAME\")\n```\n```bash\nsimple_slurm --partition=compute.p --output slurm.log --ignore_pbs \"echo \\$HOSTNAME\"\n```\n\n\n### Using Configuration Files\n\nLet's define the *static* components of a job definition in a YAML file `slurm_default.yml`\n\n```yaml\ncpus_per_task: 15\njob_name: \"name\"\noutput: \"%A_%a.out\"\n```\n\nIncluding these options with the using the `yaml` package is very *simple*\n\n```python\nimport yaml\n\nfrom simple_slurm import Slurm\n\nslurm = Slurm(**yaml.load(open(\"slurm_default.yml\", \"r\")))\n\n...\n\nslurm.set_array(range(NUMBER_OF_SIMULATIONS))\n```\n\nThe job can be updated according to the *dynamic* project needs (ex. `NUMBER_OF_SIMULATIONS`).\n\n\n\n\n### Filename Patterns and Environment Variables\n\nFor convenience, Filename Patterns and Output Environment Variables are available as attributes of the Simple Slurm object.\n\nSee [https://slurm.schedmd.com/sbatch.html](https://slurm.schedmd.com/sbatch.html#lbAH) for details on the commands.\n\n```python\nfrom slurm import Slurm\n\nslurm = Slurm(output=('{}_{}.out'.format(\n Slurm.JOB_ARRAY_MASTER_ID,\n Slurm.JOB_ARRAY_ID))\nslurm.sbatch('python demo.py ' + slurm.SLURM_ARRAY_JOB_ID)\n```\n\nThis example would result in output files of the form `65541_15.out`.\nHere the job submission ID is `65541`, and this output file corresponds to the submission number `15` in the job array. Moreover, this index is passed to the Python code `demo.py` as an argument.\n\n\n`sbatch` allows for a filename pattern to contain one or more replacement symbols. They can be accessed with `Slurm.`\n\nname | value | description\n:-------------------|------:|:-----------\nJOB_ARRAY_MASTER_ID | %A | job array's master job allocation number\nJOB_ARRAY_ID | %a | job array id (index) number\nJOB_ID_STEP_ID | %J | jobid.stepid of the running job. (e.g. \"128.0\")\nJOB_ID | %j | jobid of the running job\nHOSTNAME | %N | short hostname. this will create a separate io file per node\nNODE_IDENTIFIER | %n | node identifier relative to current job (e.g. \"0\" is the first node of the running job) this will create a separate io file per node\nSTEP_ID | %s | stepid of the running job\nTASK_IDENTIFIER | %t | task identifier (rank) relative to current job. this will create a separate io file per task\nUSER_NAME | %u | user name\nJOB_NAME | %x | job name\nPERCENTAGE | %% | the character \"%\"\nDO_NOT_PROCESS | \\\\\\\\ | do not process any of the replacement symbols\n\n\n\nThe Slurm controller will set the following variables in the environment of the batch script. They can be accessed with `Slurm.`.\n\nname | description\n:----------------------|:-----------\nSLURM_ARRAY_TASK_COUNT | total number of tasks in a job array\nSLURM_ARRAY_TASK_ID | job array id (index) number\nSLURM_ARRAY_TASK_MAX | job array's maximum id (index) number\nSLURM_ARRAY_TASK_MIN | job array's minimum id (index) number\nSLURM_ARRAY_TASK_STEP | job array's index step size\nSLURM_ARRAY_JOB_ID | job array's master job id number\n... | ...\n\n\n### Change execution shell\n\n`/bin/sh` is the default shell path used in the script's first line.\nIt can be modified with :\n```python\nslurm.set_shell(\"/bin/sh\")\nslurm.sbatch(\"/bin/sh\")\n```\nIn both cases, the default shell is modified in the Slurm object (*i.e.* applicable to successive `sbatch` calls).\n\n## Job Management\n\nSimple Slurm provides a simple interface to Slurm's job management tools (`squeue` and `scance`l) to let you monitor and control running jobs.\n\n### Monitoring Jobs with `squeue`\n\nRetrieve and display job information for the current user:\n\n```python\nfrom simple_slurm import Slurm\n\nslurm = Slurm()\nslurm.squeue.update_squeue() # Fetch latest job data\nslurm.squeue.display_jobs()\n\n# Get the jobs as a dictionary\njobs = slurm.squeue.jobs\n\nfor job_id, job in jobs.items():\n print(job)\n```\n\n\n### Canceling Jobs with `scancel`\n\nCancel single jobs or entire job arrays:\n\n```python\nfrom simple_slurm import Slurm\n\nslurm = Slurm()\n\n# Cancel a specific job\nslurm.scancel.cancel_job(34987)\n\n# Cancel multiple jobs\nfor job_id in [34987, 34988, 34989]:\n slurm.scancel.cancel_job(job_id)\n\n# Send SIGTERM before canceling (graceful termination)\nslurm.scancel.signal_job(34987)\nslurm.scancel.cancel_job(34987)\n```\n\n\n## Error Handling\nThe library does not raise specific exceptions for invalid Slurm arguments or job submission failures. Instead, it relies on the underlying Slurm commands (`sbatch`, `srun`, etc.) to handle errors. If a job submission fails, the error message from Slurm will be printed to the console.\n\nAdditionally, if invalid arguments are passed to the Slurm object, the library uses `argparse` to validate them. If an argument is invalid, `argparse` will raise an error and print a helpful message.\n\nFor example:\n\n```bash\nsimple_slurm --invalid_argument=value \"echo \\$HOSTNAME\"\n```\n\nThis will result in an error like:\n\n```bash\nusage: simple_slurm [OPTIONS] \"COMMAND_TO_RUN_WITH_SBATCH\"\nsimple_slurm: error: unrecognized arguments: --invalid_argument=value\n```\n\n\n## Project growth\n[![Star History Chart](https://api.star-history.com/svg?repos=amq92/simple_slurm&type=Date)](https://star-history.com/#amq92/simple_slurm&Date)\n","description_content_type":"text/markdown","docs_url":null,"download_url":null,"downloads":{"last_day":-1,"last_month":-1,"last_week":-1},"dynamic":["Author","Classifier","Description","Description-Content-Type","Home-Page","License","License-File","Requires-Python","Summary"],"home_page":"https://github.com/amq92/simple_slurm","keywords":null,"license":"GNU Affero General Public License v3","license_expression":null,"license_files":["LICENSE"],"maintainer":null,"maintainer_email":null,"name":"simple-slurm","package_url":"https://pypi.org/project/simple-slurm/","platform":null,"project_url":"https://pypi.org/project/simple-slurm/","project_urls":{"Homepage":"https://github.com/amq92/simple_slurm"},"provides_extra":null,"release_url":"https://pypi.org/project/simple-slurm/0.3.6/","requires_dist":null,"requires_python":">=3.6","summary":"A simple Python wrapper for Slurm with flexibility in mind.","version":"0.3.6","yanked":false,"yanked_reason":null}

Package search

simple-slurm

project_urls

Dependencies

All package metadata

Releases