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    "info": {
        "author": "Abdulelah Bin Mahfoodh",
        "author_email": "",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.7",
            "Programming Language :: Python :: 3.8",
            "Topic :: Software Development :: Libraries",
            "Topic :: Software Development :: Libraries :: Python Modules",
            "Topic :: System :: Monitoring",
            "Topic :: System :: Systems Administration",
            "Topic :: Utilities"
        ],
        "description": "\n# pdsys\n\nPandas-like Python package for systems monitoring\n\n### Basic usage\n\n```python\nimport pdsys\n```\n\nTo get a system utilization report (as dataframe) on local:\n\n```python\ndf = pdsys.report()\n```\n\npdsys returns by default all process attributes information from ***psutil*** process iterator:\n\n```python\ndf.columns.tolist()\n>>> ['cmdline',\n 'connections',\n 'cpu_affinity',\n 'cpu_num',\n 'cpu_percent',\n 'cpu_times.children_system',\n 'cpu_times.children_user',\n 'cpu_times.system',\n 'cpu_times.user',\n 'create_time',\n 'cwd',\n 'environ',\n 'exe',\n 'gids.effective',\n 'gids.real',\n 'gids.saved',\n 'hostname',\n 'io_counters',\n 'io_counters.read_bytes',\n 'io_counters.read_chars',\n 'io_counters.read_count',\n 'io_counters.write_bytes',\n 'io_counters.write_chars',\n 'io_counters.write_count',\n 'ionice.value',\n 'memory_full_info',\n 'memory_full_info.data',\n 'memory_full_info.dirty',\n 'memory_full_info.lib',\n 'memory_full_info.pss',\n 'memory_full_info.rss',\n 'memory_full_info.shared',\n 'memory_full_info.swap',\n 'memory_full_info.text',\n 'memory_full_info.uss',\n 'memory_full_info.vms',\n 'memory_info.data',\n 'memory_info.dirty',\n 'memory_info.lib',\n 'memory_info.rss',\n 'memory_info.shared',\n 'memory_info.text',\n 'memory_info.vms',\n 'memory_maps',\n 'memory_percent',\n 'name',\n 'nice',\n 'num_ctx_switches.involuntary',\n 'num_ctx_switches.voluntary',\n 'num_fds',\n 'num_threads',\n 'open_files',\n 'pid',\n 'ppid',\n 'status',\n 'terminal',\n 'threads',\n 'uids.effective',\n 'uids.real',\n 'uids.saved',\n 'username']\n```\n\nYou can query the output dataframe to get more insights about the system:\n```python\n# getting top 5 processes sorted by memory utilization \ndf.sort_values(by='memory_percent', \n               ascending=False)[['name', 'memory_percent']].head(5)\n```\n\n|     | name             |   memory_percent |\n|----:|:-----------------|-----------------:|\n| 104 | systemd-journald |         20.865   |\n|  76 | gunicorn         |          4.06886 |\n|  75 | gunicorn         |          4.05697 |\n|  77 | gunicorn         |          4.01536 |\n|  74 | gunicorn         |          1.92189 |\n\n\nAlso, pdsys can run reports from remote systems by providing list of hosts:\n```python\ndf = pdsys.report(hosts=['user@host1', 'user@host2'])\ndf[df.memory_percent > 0.9].groupby(['hostname',\n                                     'name']).agg({'memory_percent': 'sum',\n                                                   'pid': 'count',\n                                                   'num_threads': 'sum',\n                                                   'memory_info.rss': lambda x: sum(x) / 1e6})\n```\n|    | hostname   | name                            |   memory_percent |   pid |   num_threads |   memory_info.rss |\n|---:|:-----------|:--------------------------------|-----------------:|------:|--------------:|------------------:|\n|  0 | host1      | Google Chrome                   |          2.13456 |     1 |            31 |          183.357  |\n|  1 | host1      | Google Chrome Helper (GPU)      |          1.31197 |     1 |             9 |          112.697  |\n|  2 | host1      | Google Chrome Helper (Renderer) |          9.3699  |     8 |           107 |          804.868  |\n|  3 | host1      | Python                          |          1.0848  |     1 |            12 |           93.184  |\n|  4 | host1      | Terminal                        |          1.7745  |     1 |             6 |          152.429  |\n|  5 | host1      | pycharm                         |          9.88402 |     1 |            66 |          849.031  |\n|  6 | host2      | do-agent                        |          1.19791 |     1 |             6 |           12.3822 |\n|  7 | host2      | gunicorn                        |         14.0631  |     4 |             4 |          145.363  |\n|  8 | host2      | postgres                        |          1.54504 |     1 |             1 |           15.9703 |\n|  9 | host2      | python3                         |          3.47208 |     3 |             4 |           35.8892 |\n| 10 | host2      | systemd-journald                |         21.0484  |     1 |             1 |          217.567  |\n\n",
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        "home_page": "https://github.com/abduhbm/pdsys",
        "keywords": "system monitoring pandas metrics performance",
        "license": "MIT",
        "maintainer": "",
        "maintainer_email": "",
        "name": "pdsys",
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