Azure Data Factory Code Explainer

def quick_sort(arr):
    if len(arr) <= 1:
        return arr
    pivot = arr[len(arr) // 2]
    left = [x for x in arr if x < pivot]
    middle = [x for x in arr if x == pivot]
    right = [x for x in arr if x > pivot]
    return quick_sort(left) + middle + quick_sort(right)

class Car:
    def __init__(self, brand, model, year):
        self.brand = brand
        self.model = model
        self.year = year
    def age(self, current_year):
        return current_year - self.year
    def __str__(self):
        return f'{self.brand} {self.model}'

l = [x**2 for x in range(5)]

SELECT Employees.LastName, COUNT(Orders.OrderID) AS NumberOfOrders FROM Orders
    INNER JOIN Employees ON Orders.EmployeeID = Employees.EmployeeID
    GROUP BY LastName
    HAVING COUNT(Orders.OrderID) > 10
    ORDER BY NumberOfOrders DESC;

import multiprocessing
import os
def worker():
     print(f'Worker process id: {os.getpid()}')
if __name__ == '__main__':
     jobs = []
     for i in range(5):
         p = multiprocessing.Process(target=worker)
         jobs.append(p)
         p.start()

import asyncio
def factorial(name, number):
    f = 1
    for i in range(2, number+1):
        print(f'Task {name}: Compute factorial({i})...')
        await asyncio.sleep(1)
        f *= i
    print(f'Task {name}: factorial({number}) = {f}')
asyncio.run(factorial('A', 3))

=VLOOKUP(B2,$G$3:$H$10,2,FALSE)

ind <- c('TB', 'AD', 'OB', 'MA', 'TB', 'MA')
count <- c(8, 14, 6, 12, 5, 9)
df <- data.frame(ind, count)
std_df <- df %>% group_by(ind) %>% summarise(mean = mean(count), sd = sd(count))

PREDICT(<model>, [ColumnName1, ColumnName2, ..., ColumnNameN])

mssg = 'Hello, World!'
print(''.join(format(ord(x), 'b') for x in mssg))