htmlparser.py

import os
from bs4 import BeautifulSoup


# Splitting the list as usually the servers have only 5 columns with data in them
def split(list_a, chunk):
    # Some lists contain over 20 items, and we only need 5 of those for each mountpoint
    # In our case chunk is the actual number of columns that we see in the report and want to set in our list.
    for i in range(0, len(list_a), chunk):
        # yield is used here because we are generating another list
        yield list_a[i:i + chunk]


# Opening all the reports from a directory
for report in os.listdir("reports"):
    with open(os.path.join("reports", report)) as fp:
        soup = BeautifulSoup(fp, 'lxml')
    # Finding all tr that contain the required data in our report
    tableuptime = soup.find('table', id="tableUptime").find("tbody").find_all("tr")
    for row in tableuptime:
        cells = row.find_all('td')
        # Because the output looks like this ['11:12,', 'Days']
        uptime = cells[1].text.split()
        # A simple check to see if the list that we create using the table data has at least 2 items in it.
        if len(uptime) == 2:
            # If the uptime is in 24hours format it's not going to be considered a digit.
            if uptime[0].isdigit() and int(uptime[0]) >= 4:
                pass
            else:
                print(f"In report {report} Server: {cells[0].text} has the following uptime: {cells[1].text}")
        else:
            print(f"In report {report} Server: {cells[0].text} has the following uptime: {cells[1].text}")

    tableping = soup.find('table', id="tableMonitoredHosts").find("tbody").find_all("tr")
    for row in tableping:
        cells = row.find_all("td")
        pingable = cells[2].text
        # Output looking like <td>True</td> that's why we check it like this.
        if pingable != 'True':
            print(f"In report {report} Server: {cells[0].text} has pingable status of: {cells[2].text}")

    # In the report provided all the tables have different id's but the same class name, so we find them.
    tableusage = soup.find_all("table", class_="DiskUsage")
    for row in tableusage:
        cells = row.find_all("td")

        # The split used here is the actual function created at the top of this script.
        # This for is only used to iterate over every list as this has created a list in list.
        for data in list(split(cells, 5)):
            # print(data[4].text)
            if data[4].text.strip('%').isdigit() and float(data[4].text.strip('%')) >= 85:
                print(f"In report {report} Mountpoint: {data[0].text} is at: {data[4].text}")