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The built-in Python function dir() is an essential tool when exploring a module’s attributes. It returns an alphabetically sorted list of all the functions, constants, and other attributes available in a module. For example, if you want to see what the math module offers, you can use the following code: 
import math
print(dir(math))
This command outputs a list similar to: 
['__doc__', '__loader__', '__name__', '__package__', 'acos', 'acosh', 'asin', 'asinh', 'atan', 'atan2', 'atanh', 'ceil', 'comb', 'copysign', 'cos', 'cosh', 'degrees', 'dist', 'e', 'erf', 'erfc', 'exp', 'exp1', 'fabs', 'factorial', 'floor', 'fmod', 'frexp', 'fsum', 'gamma', 'gcd', 'hypot', 'inf', 'isclose', 'isfinite', 'isinf', 'isnan', 'isqrt', 'ldexp', 'lgamma', 'log', 'log10', 'log1p', 'log2', 'modf', 'nan', 'perm', 'pi', 'pow', 'pprint', 'radians', 'remainder', 'sin', 'sinh', 'sqrt', 'tan', 'tanh', 'tau', 'trunc']
For detailed information on each attribute, refer to the official Python documentation. Python’s random module provides a variety of functions to generate pseudo-random numbers. Although these numbers seem random, they are produced by deterministic algorithms, and their outcomes can be reproduced if you set a specific seed.

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Generating Random Floats

To obtain a random floating-point number in the range [0.0, 1.0), you can use the random() function: 
from random import random
print(random())
When the module is imported, Python automatically seeds the random number generator using the current system time. To generate reproducible results, you can explicitly set the seed using the seed() function: 
from random import random, seed

seed(10)  # Set a fixed seed for reproducibility
for i in range(5):
    print(random())
This will consistently produce the following sequence: 
0.5714025946899135
0.4288890546751146
0.3781625196021736
0.1770104802442504
0.3867352020073605
For consistent results across executions, always set a fixed seed when generating random numbers.

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Generating Random Integers

If you need random integers, you can choose between the randint and randrange functions:
  • The randint(a, b) function returns an integer N such that a ≤ N ≤ b. For example, to generate a random integer between 0 and 9:
from random import randint
for i in range(3):
    print(randint(0, 9))
  • The randrange() function follows Python’s range semantics. When given a single parameter, it returns a random integer from 0 up to (but not including) that number:
from random import randrange

for i in range(5):
    print(randrange(10))
You can also use randrange(start, stop, step) to define a specific step interval. For example, generating a number from the values 0, 3, 6, or 9 within the range 0 to 10 is done as follows: 
from random import randrange
for i in range(5):
    print(randrange(0, 10, 3))

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Random Selection from a List

In addition to generating random numbers, the random module includes functions to select items from collections:
  • Use choice() to pick a single random element from a list.
  • Use sample(population, k) to retrieve a list of k unique elements from the given list.
from random import choice, sample

students = ["Anne", "Bob", "Max", "John", "Peter"]
print("Random choice:", choice(students))
print("Random sample (2 students):", sample(students, 2))
For more details on these functions, consult the Python random module documentation. That’s it for our guide on the math and random modules in Python. Start experimenting with these functions to better understand the power of Python’s standard library and enhance your coding projects. Happy coding!

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