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    "info": {
        "author": "Bas Nijholt",
        "author_email": "basnijholt@gmail.com",
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        "description": "# hpc05\n[![PyPI](https://img.shields.io/pypi/v/hpc05.svg)](https://pypi.python.org/pypi/hpc05)\n[![Conda](https://anaconda.org/conda-forge/hpc05/badges/installer/conda.svg)](https://anaconda.org/conda-forge/hpc05)\n[![Downloads](https://anaconda.org/conda-forge/hpc05/badges/downloads.svg)](https://anaconda.org/conda-forge/hpc05)\n\n\ud83d\udda5 `ipyparallel.Client` package for a PBS or SLURM cluster with a headnode.\n\nScript that connects to PBS or SLURM cluster with headnode over ssh. Since `ipyparallel` doesn't cull enginges when inactive and people are lazy (because they forget to `qdel` their jobs), it automatically kills the `ipengines` after the set timeout (default=15 min). Note that this package doesn't only work for the `hpc05` cluster on the TU Delft but also other clusters.\n\n# Installation\nFirst install this package on **both** your machine and the cluster.\n\n```bash\nconda config --add channels conda-forge\nconda install hpc05\n```\nor using `pip`\n```\npip install hpc05\n```\n\nMake sure you can connect over `ssh` passwordless by copying your ssh key:\n\n```bash\nssh-copy-id hpc05\n```\n\n# Setup profile\nYou need a parallel profile on your cluster, which can be created by the following command on your local machine:\n```python\nimport hpc05\n# for PBS use\nhpc05.create_remote_pbs_profile(profile='pbs', hostname='hpc05')  # on the remote machine\n# or\nhpc05.create_local_pbs_profile(profile='pbs')  # on the cluster\n\n# for SLURM use\nhpc05.create_remote_slurm_profile(profile='slurm', hostname='hpc05')  # on the remote machine\n# or\nhpc05.create_local_slurm_profile(profile='slurm')  # on the cluster\n```\n\n# Start `ipcluster` and connect (via `ssh`)\nTo start **and** connect to an `ipcluster` just do (and read the error messages if any, for instructions):\n```python\nclient, dview, lview = hpc05.start_remote_and_connect(\n\tn=100, profile='pbs', hostname='hpc05', folder='~/your_folder_on_the_cluster/')\n```\n\nThis is equivent to the following three commmands:\n```python\n# 0. Killing and removing files of an old ipcluster (this is optional with\n#    the `start_remote_and_connect` function, use the `kill_old_ipcluster` argument)\nhpc05.kill_remote_ipcluster(hostname='hpc05')\n\n# 1. starting an `ipcluster`, similar to running\n#    `ipcluster start --n=100 --profile=pbs` on the cluster headnode.\nhpc05.start_remote_ipcluster(n=100, profile='pbs', hostname='hpc05')\n\n# 2. Connecting to the started ipcluster and adding a folder to the cluster's `PATH`\nclient, dview, lview = hpc05.connect_ipcluster(\n\tn=200, profile='pbs', hostname='hpc05', folder='~/your_folder_on_the_cluster/')\n\n```\n\n\n# Start `ipcluster` and connect (on cluster headnode)\nTo start **and** connect to an `ipcluster` just do (and read the error messages if any, for instructions):\n```python\nclient, dview, lview = hpc05.start_and_connect(\n\tn=100, profile='pbs',  folder='~/your_folder_on_the_cluster/')\n```\n\nThis is equivent to the following three commmands:\n```python\n# 0. Killing and removing files of an old ipcluster (this is optional with\n#    the `start_remote_and_connect` function, use the `kill_old_ipcluster` argument)\nhpc05.kill_ipcluster()\n\n# 1. starting an `ipcluster`, similar to `ipcluster start --n=200 --profile=pbs`\nhpc05.start_ipcluster(n=200, profile='pbs')\n\n# 2. Connecting to the started ipcluster and adding a folder to the cluster's `PATH`\nclient, dview, lview = hpc05.connect_ipcluster(\n\tn=200, profile='pbs', folder='~/your_folder_on_the_cluster/')\n\n```\n\n# Monitor resources\nThis package will monitor your resources if you start it with `hpc05_monitor.start(client)`, see the following example use:\n```python\nimport time\nimport hpc05_monitor\nhpc05_monitor.start(client, interval=5)  # update hpc05_monitor.MAX_USAGE every 'interval' seconds.\n\nwhile not hpc05_monitor.LATEST_DATA:\n    time.sleep(1)\n\nhpc05_monitor.print_usage()  # uses hpc05_monitor.LATEST_DATA by default\n\nhpc05_monitor.print_max_usage()  # uses hpc05_monitor.MAX_USAGE\n```\n\nWith output:\n```\n id hostname             date                             CPU% MEM%\n 15 node29.q1cluster     2018-09-10T14:25:05.350499       190%   3%\n 19 node29.q1cluster     2018-09-10T14:25:04.860693       200%   3%\n 26 node29.q1cluster     2018-09-10T14:25:05.324466       200%   3%\n 28 node29.q1cluster     2018-09-10T14:25:05.148623       190%   2%\n 29 node29.q1cluster     2018-09-10T14:25:04.737664       190%   3%\n ...\n```\n\n\n## Development\n\nWe use [pre-commit](https://pre-commit.com) for linting of the code, so `pip install pre_commit` and run\n```\npre-commit install\n```\nin the repository.\n\n\n",
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