{"library":"dask-jobqueue","type":"library","category":null,"description":"Dask-Jobqueue simplifies the deployment of Dask distributed clusters on traditional high-performance computing (HPC) job queuing systems such as PBS, Slurm, LSF, SGE, MOAB, OAR, and HTCondor. It allows users to dynamically launch Dask workers as jobs on a cluster, integrating Dask's parallel computing capabilities with existing HPC infrastructure. The library is actively maintained, with the current version being 0.9.0, and typically follows a regular release cadence aligned with Dask's ecosystem updates. [1, 5, 15, 16]","language":"python","status":"active","version":"0.9.0","tags":["dask","hpc","cluster","job queue","slurm","pbs","lsf","sge","moab","oar","htcondor","distributed computing"],"last_verified":"Tue May 26","install":[{"cmd":"pip install dask-jobqueue","imports":["from dask_jobqueue import PBSCluster","from dask_jobqueue import SLURMCluster","from dask_jobqueue import SGECluster","from dask_jobqueue import LSFCluster","from dask_jobqueue import HTCondorCluster","from dask_jobqueue import OARCluster","from dask_jobqueue import MoabCluster","from distributed import Client"]},{"cmd":"conda install conda-forge::dask-jobqueue","imports":[]}],"homepage":"https://jobqueue.dask.org","github":null,"docs":null,"changelog":null,"pypi":"https://pypi.org/project/dask-jobqueue/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":100,"avg_install_s":5.1,"avg_import_s":1.68,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/dask-jobqueue/compatibility"}}