import os
import time
from datetime import datetime

now = datetime.now() # current date and time
date_time = now.strftime("%m/%d/%Y,%H:%M:%S")

start = time.time()

# DIRECTORY WHERE ALL IP LISTS RESIDE
directory = 'Lists'

# RETURN LIST OF ALL FILES IN THE "DIRECTORY" PROVIDED ABOVE.
for entry in os.scandir(directory):
    
    # THIS WILL LOOP THROUGH ALL TEXT FILES IN DIRECTORY
    if entry.is_file() and entry.name.endswith('.txt'):
        
        # THIS WILL ONLY LOOK FOR AND RETURN FILES WITH IP_LIST IN THE NAME SINCE THOSE ARE THE ONES WITH THE SPECIFIC IP'S
        if 'ip_list' in entry.name:
            
            # FILE PATH FOR EACH FILE TO PROCESS(EX. Lists/Register_ip_list.txt)
            pt = directory + '/' + entry.name
            
            # THIS WILL PARSE OUT THE VALUE BEFORE THE FIRST '_' TO SET THE VARIABLE AND USE LATER FOR SAVING THE RESULTS.
            parts = entry.name.split('_')
            
            # OPEN EACH TEXT FILE THAT CONTAINS IPS TO PROCESS
            with open(pt) as file:
                park = file.read()
                park = park.splitlines()
                #print(" {park}  \n")
                
                # THIS IS TO CLEAR THE FILE BEFORE WRITING TO IT(WONT NEED THIS ONCE WE START INSERTING THE DATE INTO A DATABASE)
                file_to_clear = open("Lists/" + parts[0] +"_ip_output.txt",'w')
                file_to_clear.close()
                
            # PING EACH IP IN FILE LIST
            for ip in park:
                response = os.popen(f"ping -c 1 {ip} ").read()
                
                # SAVE PING STATUS INTO FILE FOR DASHBOARD (IP,STATUS,DATETIME)
                if("Request timed out." or "unreachable") in response:
                        #print(response)
                        f = open("Lists/" + parts[0] +"_ip_output.txt","a")
                        f.write(str(ip) + ',down,'+ date_time +'\n')
                        f.close() 
                else:
                        #print(response)
                        f = open("Lists/" + parts[0] +"_ip_output.txt","a")  
                        f.write(str(ip) + ',up,'+ date_time +'\n')
                        f.close() 
            # PRINT COMPLETE RESULTS TO CONSOLE WINDOW (DEBUGGING PURPOSES)
            # with open("Lists/" + parts[0] +"_ip_output.txt") as file:
            #     output = file.read()
            #     f.close()
            #     print(output)
            # THIS CLEARS THE FILE AFTER ITS WRITTEN TO THE CONSOLE
            #with open("Lists/ip_output.txt","w") as file:    
            #                pass

# CALCULATED THE RUNTIME OF THE SCRIPT (FUTURE UPDATES TO INCLUDE CAPTURING RUNTIMES IN SEPARATE FILE FOR REVIEW, TO INCLUDE FILENAME, ROW COUNT AND DURATION)
end = time.time()
print(end - start)

import subprocess
from concurrent.futures import ThreadPoolExecutor


ips = ["10.0.0.5", "127.0.0.1", "::1"]


def ping(ip):
    return (
        ip,
        subprocess.run(
            f"ping {ip} -n 1", stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL
        ).returncode,
    )


executor = ThreadPoolExecutor(4)
print(*executor.map(ping, ips))

    park = file.readlines()
    
    #executor = ThreadPoolExecutor(4)
    with ThreadPoolExecutor(4) as executor:
        for result in executor.map(ping, park):
            print(result)

import subprocess
from concurrent.futures import ThreadPoolExecutor


ips = ["10.0.0.5", "127.0.0.1", "::1"]


def ping(ip):
    return (
        ip,
        subprocess.run(
            f"ping {ip} -n 1", stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL
        ).returncode,
    )


executor = ThreadPoolExecutor(4)
for result in executor.map(ping, ips):
    print(result[0], "is down" if result[1] else "is up")

Output:
10.0.0.5 is down
127.0.0.1 is up
::1 is up

import subprocess
from concurrent.futures import ThreadPoolExecutor
import pandas as pd

ips = ["10.0.0.5", "127.0.0.1", "::1"]


def ping(ip):
    return (
        ip,
        subprocess.run(
            f"ping {ip} -n 1", stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL
        ).returncode,
    )


executor = ThreadPoolExecutor(4)
df = pd.DataFrame(executor.map(ping, ips), columns=["address", "state"])
print(df)

Output:
     address  state
0   10.0.0.5      1
1  127.0.0.1      0
2        ::1      0

            address  state
0  www.google.com\n      1
1   www.abc13.com\n      1
2   www.yahoo.com\n      1
3     www.cnn.com\n      1
4   www.walmart.com      0
0.17187809944152832

www.google.com
,down
www.abc13.com
,down
www.yahoo.com
,down
www.cnn.com
,down
www.walmart.com,up

import time
import subprocess
from concurrent.futures import ThreadPoolExecutor
import pandas as pd

def ping(ip):
    return (
        ip,
        subprocess.run(
            f"ping {ip} -n 1", stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL
        ).returncode,
    )

start = time.time()

with open("ip_list.txt") as file:
    park = file.readlines()
    with ThreadPoolExecutor(4) as executor:
        for result in executor.map(ping, park):
            if result[1] == 0:
           	    f = open("ip_output.txt","a")
           	    f.write(str(result[0]) + ',up' + '\n')
           	    f.close() 
            else:
           	    f = open("ip_output.txt","a")
           	    f.write(str(result[0] + ',down' +'\n'))
           	    f.close()   

import time
import subprocess
from concurrent.futures import ThreadPoolExecutor
import pandas as pd

def ping(ip):
    return (
        ip,
        subprocess.run(
            f"ping {ip} -n 1", stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL
        ).returncode,
    )

start = time.time()

with open("ip_list.txt") as file:
    park = file.readlines()
 
    executor = ThreadPoolExecutor(4)
    df = pd.DataFrame(executor.map(ping, park), columns=["address", "state"])
    print(df)

with open("ip_list.txt") as file:
    park = file.readlines()
 
    executor = ThreadPoolExecutor(5)
    df = pd.DataFrame(executor.map(ping, park), columns=['address', 'state'])
    df.to_csv(r'ip_output.csv',header=False, index=False) 

"www.google.com
",1
"www.abc13.com
",1
"www.yahoo.com
",1
"www.cnn.com
",1
www.walmart.com,0