np.random.default_rng() modern approach in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is np.random.default_rng() used for?

np.random.default_rng() creates a new random number generator object. It is the modern way to generate random numbers in NumPy, replacing older functions like np.random.rand().

beginner

How do you generate 5 random integers between 0 and 10 using default_rng()?

rng = np.random.default_rng()
random_ints = rng.integers(0, 10, size=5)

This creates 5 random integers from 0 up to (but not including) 10.

intermediate

Why is default_rng() preferred over older NumPy random functions?

It provides better randomness quality, is easier to control with a seed, and avoids global state issues. It also supports new features and is the recommended approach since NumPy 1.17.

beginner

How do you set a seed with default_rng() to get repeatable results?

rng = np.random.default_rng(42)

Using the same seed will produce the same sequence of random numbers every time.

beginner

What method would you use with default_rng() to generate random floats between 0 and 1?

Use rng.random(size) to generate random floats in the range [0, 1).

What does np.random.default_rng() return?

A A random integer

B A random float between 0 and 1

C A new random number generator object

D A global random seed

default_rng() returns a new random number generator object to generate random numbers.

How do you generate 10 random floats between 0 and 1 using default_rng()?

A rng.integers(0, 1, size=10)

B rng.uniform(0, 1)

C np.random.rand(10)

D rng.random(10)

rng.random(10) generates 10 random floats between 0 and 1.

Why should you use default_rng() instead of np.random.rand()?

A It is slower but more compatible

B It provides better randomness and control

C It uses global state

D It does not support seeding

default_rng() offers better randomness quality and easier control with seeds.

How do you make random results repeatable with default_rng()?

A Use <code>rng = np.random.default_rng(seed=123)</code>

B Use <code>rng = np.random.default_rng()</code> without arguments

C Call <code>rng.seed(123)</code> after creation

D Set a global seed with <code>np.random.seed(123)</code>

Passing a seed to default_rng() ensures repeatable random sequences.

Which method generates random integers with default_rng()?

A rng.integers()

B rng.random()

C rng.randint()

D rng.uniform()

rng.integers() generates random integers in a specified range.

Explain how to create a random number generator with a fixed seed using np.random.default_rng() and generate 3 random floats.

Think about how to pass a seed and call the method for floats.

Describe the advantages of using np.random.default_rng() over older NumPy random functions.

Focus on quality, control, and best practice.