Garbage collection and array references in NumPy - Mini Project: Build & Apply

Garbage Collection and Array References with NumPy

📖 Scenario: You are working with numerical data in Python using NumPy arrays. Understanding how array references and garbage collection work helps you manage memory efficiently when handling large datasets.

🎯 Goal: Build a small program that creates a NumPy array, assigns it to multiple variables, modifies one reference, and then deletes references to observe how garbage collection affects the array.

📋 What You'll Learn

Create a NumPy array with specific values

Assign the array to a second variable (reference)

Modify the array through one reference

Delete one reference and observe the remaining reference

Delete all references to allow garbage collection

💡 Why This Matters

🌍 Real World

Managing memory efficiently is important when working with large datasets in data science or machine learning projects.

💼 Career

Understanding references and garbage collection helps developers write efficient code that avoids memory leaks and unexpected bugs.

1

Create a NumPy array

Import the numpy module as np and create a NumPy array called arr with the values [10, 20, 30, 40, 50].

NumPy

# Import numpy and create the array arr with values [10, 20, 30, 40, 50]
# Your code here

Need a hint?

Use np.array([...]) to create the array.

2

Assign the array to a second variable

Create a new variable called ref_arr and assign it to reference the existing array arr.

NumPy

import numpy as np
arr = np.array([10, 20, 30, 40, 50])
# Assign ref_arr to reference arr
# Your code here

Need a hint?

Just assign ref_arr = arr to create a reference.

3

Modify the array through one reference

Change the second element (index 1) of the array using the ref_arr variable to the value 25.

NumPy

import numpy as np
arr = np.array([10, 20, 30, 40, 50])
ref_arr = arr
# Change the second element of ref_arr to 25
# Your code here

Need a hint?

Use indexing like ref_arr[1] = 25 to modify the array.

4

Delete references to allow garbage collection

Delete the variable arr using the del statement. Then delete ref_arr using del to remove all references to the array.

NumPy

import numpy as np
arr = np.array([10, 20, 30, 40, 50])
ref_arr = arr
ref_arr[1] = 25
# Delete arr and ref_arr to remove references
# Your code here

Need a hint?

Use del arr and del ref_arr to delete the variables.