FM / clsummary

/opt/cloudlinux/venv/lib/python3.11/site-packages/clsummary/

/opt/cloudlinux/venv/lib/python3.11/site-packages/clsummary

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
arg_parse.py	2289	0644	edit dl rm
hardware_statistics.py	3910	0644	edit dl rm
net_acct.py	5337	0644	edit dl rm
rpm_packages_statistics.py	4200	0644	edit dl rm
storage.py	2532	0644	edit dl rm
summary.py	166563	0644	edit dl rm
utils.py	11701	0644	edit dl rm
__init__.py	271	0644	edit dl rm

Edit: /opt/cloudlinux/venv/lib/python3.11/site-packages/clsummary/hardware_statistics.py (3910B)

# coding=utf-8
#
# Copyright © Cloud Linux GmbH & Cloud Linux Software, Inc 2010-2019 All Rights Reserved
#
# Licensed under CLOUD LINUX LICENSE AGREEMENT
# http://cloudlinux.com/docs/LICENSE.TXT

import os
from typing import Optional, Dict, AnyStr, Union, List

class NotSupported(Exception):
    """
    Custom error to handle compatibility issues
    """
    pass

def get_proc_info_as_list_of_dicts(
        file_content: AnyStr
) -> List[Optional[Dict[AnyStr, AnyStr]]]:
    """
    Parses the response of /proc files
    Since this file has a possibility to include multiple
    objects info, we need to parse all of them in the separate dicts
    :file_content: /proc file content. Example:

processor       : 0
        vendor_id       : AuthenticAMD

processor       : 1
        vendor_id       : AuthenticAMD_1

return: list of dicts with each node

"""
    result = []
    for info_object in file_content.split("\n\n"):
        temp_dict = {}
        if not info_object:
            continue
        for info_attr in info_object.split("\n"):
            values = info_attr.split(":")
            if len(values) == 2:
                temp_dict[values[0].strip()] = values[1].strip()
        result.append(temp_dict)
    return result

def convert_string_kb_to_mb_value(value: str) -> float:
    """
    Helper to get numeric value of string record and convert it to mb

:value: metric value from /proc file. Example: '512 KB'
    return: converted value. Example: 0.5
    """
    return float(value.split()[0]) / 1024

def get_cpu_metrics() -> List[Optional[Dict[AnyStr,
                                            Union[AnyStr, float, int]]]]:
    """
    Prepare list of dicts with required cpu metrics
    The base of this method was taken from rhn_client_tools
    (src/up2date_client/hardware.py)

Each CPU will be represented with a dict
    {
        "model": "foo",
        "cache_mb": 100,
        "frequency_mhz": 100,
        "id": 0
    }

return: list of dicts with cpu metrics
    """
    result_list = []
    uname = os.uname().machine
    # We can't read the /proc/cpuinfo file or arch isn't compatible
    if not os.access("/proc/cpuinfo", os.R_OK):
        raise OSError("File for cpuinfo is restricted!")
    if uname not in ["x86_64", "i386"]:
        raise NotSupported(f"Machine arch {uname} isn't compatible!")

with open("/proc/cpuinfo", "r", encoding="utf-8") as f:
        proc_cpuinfo = f.read()
    cpu_list = get_proc_info_as_list_of_dicts(proc_cpuinfo)
    for cpu in cpu_list:
        cpu_dict = {
            "id": int(cpu.get('processor', "0")),
            # Idea of set a default value from machine arch
            # was taken from rhn-client-tools hw getter
            "model": cpu.get('model name', uname),
            "cache_mb": convert_string_kb_to_mb_value(cpu.get('cache size', "0 KB")),
            "frequency_mhz": float(cpu.get('cpu MHz', "0"))
        }
        result_list.append(cpu_dict)
    return result_list

def get_memory_metrics() -> Dict[AnyStr, float]:
    """
    Prepare dict of memory metrics

Dict will be represented as:
    {
        "ram_mb": 8.5
        "swap_mb": 2.04
    }
    """
    if not os.access("/proc/meminfo", os.R_OK):
        raise OSError("File for meminfo is restricted!")
    with open("/proc/meminfo", "r", encoding="utf-8") as f:
        proc_meminfo = f.read()
    # meminfo return only one info object
    mem_dict = get_proc_info_as_list_of_dicts(proc_meminfo)[0]
    # All mem_dict values are represented as string. Example:
    # 1000 KB
    # We need to split them, convert to int and divide on 1024
    # Thus, we will get MB representation of metric
    result = {
        "ram_mb": convert_string_kb_to_mb_value(mem_dict.get("MemTotal", "0 KB")),
        "swap_mb": convert_string_kb_to_mb_value(mem_dict.get("SwapTotal", "0 KB")),
    }
    return result

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