Python Stack push() pop()

stack = []

def push(val):

    stack.append(val)

def pop():

    val = stack[-1]

    del stack[-1]

    return val

push(3)

push(2)

push(1)

print(pop())

print(pop())

print(pop())

Covert python .py file to .exe

pip install pyinstaller

pyinstaller --onefile -w filename.py

Python Multiprocessing : Run Code in Parallel Using the Multiprocessing Module

import concurrent.futures
	import time
	start = time.perf_counter()
	def do_something(seconds):
	print(f'Sleeping {seconds} second(s)...')
	time.sleep(seconds)
	return f'Done Sleeping...{seconds}'
	with concurrent.futures.ProcessPoolExecutor() as executor:
	secs = [5, 4, 3, 2, 1]
	results = executor.map(do_something, secs)
	# for result in results:
	# print(result)
	finish = time.perf_counter()
	print(f'Finished in {round(finish-start, 2)} second(s)')

Python Threading : Run Code Concurrently Using the Threading Module

import concurrent.futures import time start = time.perf_counter() def do_something(seconds): print(f'Sleeping {seconds} second(s)...') time.sleep(seconds) return f'Done Sleeping...{seconds}' with concurrent.futures.ThreadPoolExecutor() as executor: secs = [5, 4, 3, 2, 1] results = executor.map(do_something, secs) # for result in results: # print(result) # threads = [] # for _ in range(10): # t = threading.Thread(target=do_something, args=[1.5]) # t.start() # threads.append(t) # for thread in threads: # thread.join() finish = time.perf_counter() print(f'Finished in {round(finish-start, 2)} second(s)')

Ansible to convert extra variable into lowercase or uppercase

{{ ansible_var | lower }}

{{ ansible_var | upper }}

python Math Function

import math

def sin(x):

    if 2 * x == pi:

        return 0.99999999

    else:

        return None

pi = 3.14

print(sin(pi/2))

print(math.sin(math.pi/2))

Python Pandas to read excel .csv file and get all values under specific column and skip null value

import os
from selenium import webdriver
import time
import pandas as pd
from pandas import ExcelWriter
from pandas import ExcelFile

df = pd.read_csv(r"xxx.csv")
queue = df["Messages"].dropna().tolist()
print (queue)