from statistics import median, mean, mode

def print_stats(array):
  print(array)
  print("median =", median(array))
  print("mean   =", mean(array))
  print("mode   =", mode(array))
  print()

print_stats([1, 2, 3, 3, 4])
print_stats([1, 2, 3, 3])

import calendar
from datetime import datetime

# Get the UTC timestamp
a = calendar.timegm(datetime.utcnow().utctimetuple())

print(a)

#Original
def output_json_log_data_to_file(filename, record_dictionary_list):
    with open(filename, 'w') as outputFile:
        for record in record_dictionary_list:
            json.dump(record, outputFile)
            outputFile.write('\n')


#Atomic
def output_json_log_data_to_file(filename, record_dictionary_list):
    # Use atomic file operations to prevent race conditions with readers
    # Write to temporary file first, then atomically rename to target file
    tmp_filename = filename + '.tmp'
    with open(tmp_filename, 'w') as outputFile:
        for record in record_dictionary_list:
            json.dump(record, outputFile)
            outputFile.write('\n')
    # Atomic rename - this prevents readers from seeing partial writes
    shutil.move(tmp_filename, filename)

color2 = (60, 74, 172)
color1 = (19, 28, 87)

percent = 1.0
for i in range(101):
    resultRed = round(color1[0] + percent * (color2[0] - color1[0]))
    resultGreen = round(color1[1] + percent * (color2[1] - color1[1]))
    resultBlue = round(color1[2] + percent * (color2[2] - color1[2]))
    print((resultRed, resultGreen, resultBlue))
    percent -= 0.01

def print_pyramid_pattern(n):
     
    # outer loop to handle number of rows
    # n in this case
    for i in range(0, n):
     
        # inner loop to handle number of columns
        # values changing acc. to outer loop
        for j in range(0, i+1):
         
            # printing stars
            print("* ",end="")
      
        # ending line after each row
        print("\r")
 
print_pyramid_pattern(10)

bytes_data = b'Hello, World!'
string_data = bytes_data.decode('utf-8')
print("String:", string_data)