normanlmfung

import asyncio
from datetime import datetime

def _log(msg : str):
    print(f"{datetime.utcnow()} {msg}")

async def dummy(name, delay_sec):
    _log(f"{name} entering ...")
    await asyncio.sleep(delay_sec)
    _log(f"{name} done for the day!")

normanlmfung

import asyncio

async def greet(name):
    await asyncio.sleep(1)
    print(f"Hello, {name}!")

async def main():
    task1 = asyncio.create_task(greet("Alice"))
    task2 = asyncio.create_task(greet("Bob"))
    await asyncio.gather(task1, task2)

normanlmfung

import asyncio
import concurrent.futures

def sync_function():
    return "Hello from a synchronous function!"

async def main():
    with concurrent.futures.ThreadPoolExecutor() as executor:
        result = await asyncio.get_running_loop().run_in_executor(executor, sync_function)
        print(result)

normanlmfung

import asyncio

async def my_coroutine():
    print("Hello,")
    await asyncio.sleep(1)
    print("world!")

def main():
    loop = asyncio.get_event_loop()
    try:

normanlmfung

from functools import reduce
numbers = [1, 2, 3, 4, 5]
sum_result = reduce(lambda x, y: x + y, numbers)
print("Sum of the numbers:", sum_result)

normanlmfung

nums = [ 1,2,3,4,5 ]
squares = []
for num in nums:
  squares.append(num**2)
# instead of loop, use 'map'
squares = list(map(lambda num: num ** 2, nums))

normanlmfung

'''
https://superfastpython.com/asyncio-semaphore/
https://superfastpython.com/thread-semaphore/
https://superfastpython.com/multiprocessing-semaphore-in-python/

There're three versions of Semaphore:
  from asyncio import Semaphore
  from threading import Semaphore
  from multiprocessing import Semaphore

normanlmfung

import concurrent.futures
import time

def background_task1():
  item_list = []
  for i in range(10):
    item_list.append(i)
    time.sleep(1)

  # Simulate an exception being thrown

normanlmfung

import concurrent.futures
import time

def background_task(task_id):
  item_list = []
  for i in range(3):
    item_list.append((task_id, i))
    time.sleep(1)
  return item_list

normanlmfung

# This is taken DIRECTLY from Geekforgeeks https://www.geeksforgeeks.org/heap-queue-or-heapq-in-python/
	import heapq

	li = [5, 7, 9, 1, 3]
	# If you call heapify, when you call heappop, order 1,3,5,7,8. If you comment out heapify call, heappop oder 5,7,9,1,3
	heapq.heapify(li) 
	while li:
		print(heapq.heappop(li))

	# Example 2 with tuples: (w, n) where w = weight, n = node id. Heapify uses 'w' to sort first, then 'n' as tie-breaker if there are two/more elements with same 'w'.