Garbage collection and array references in NumPy - Step-by-Step Execution

Concept Flow - Garbage collection and array references

Create array A

↓

Assign B = A (reference)

↓

Modify B affects A

↓

Delete A

↓

B still holds reference

↓

Delete B

↓

No references left -> Garbage collected

This flow shows how arrays share references, how deleting one reference doesn't delete the data until all references are gone, triggering garbage collection.

Execution Sample

NumPy

import numpy as np
A = np.array([1, 2, 3])
B = A
B[0] = 10
del A
del B

This code creates a numpy array, assigns it to another variable, modifies it, then deletes references to show when garbage collection happens.

Execution Table

Step	Action	Array A	Array B	Reference Count	Garbage Collection
1	Create A	[1, 2, 3]	None	1	No
2	Assign B = A	[1, 2, 3]	[1, 2, 3]	2 (shared)	No
3	Modify B[0] = 10	[10, 2, 3]	[10, 2, 3]	2 (shared)	No
4	Delete A	Deleted	[10, 2, 3]	1	No
5	Delete B	Deleted	Deleted	0	Yes

💡 All references deleted at step 5, array memory is garbage collected.

Variable Tracker

Variable	Start	After Step 2	After Step 3	After Step 4	After Step 5
A	[1, 2, 3]	[1, 2, 3]	[10, 2, 3]	Deleted	Deleted
B	None	[1, 2, 3]	[10, 2, 3]	[10, 2, 3]	Deleted
Reference Count	1	2	2	1	0

Key Moments - 3 Insights

Why does modifying B also change A's values?

Because B is just another name (reference) for the same array as A, so changes via B affect the same data (see execution_table step 3).

Why isn't the array deleted when we delete A?

Deleting A only removes one reference; B still points to the array, so it stays in memory (see execution_table step 4).

When does garbage collection actually happen?

Garbage collection happens only when all references are deleted, here after deleting B at step 5 (see exit_note).

Visual Quiz - 3 Questions

Look at the execution_table at step 3, what is the value of array A?

A [1, 2, 3]

B Deleted

C [10, 2, 3]

D None

💡 Hint

Check the 'Array A' column at step 3 in execution_table.

At which step does the reference count drop to zero?

A Step 4

B Step 5

C Step 3

D Step 2

💡 Hint

Look at the 'Reference Count' column in variable_tracker after each step.

If we did not delete B at step 5, what would happen to the array?

A It would remain in memory

B It would be garbage collected anyway

C It would cause an error

D It would be copied automatically

💡 Hint

See explanation in key_moments about when garbage collection happens.

Concept Snapshot

Garbage collection in numpy depends on references.
Assigning one array to another shares the same data.
Modifying one reference changes the original array.
Deleting a reference removes one pointer.
Data is freed only when all references are deleted.
Use del to remove references and trigger garbage collection.

Full Transcript

This lesson shows how numpy arrays are managed in memory using references. When you assign one array to another variable, both variables point to the same data. Changing the array through one variable changes it for the other too. Deleting one variable only removes one reference; the data stays as long as another reference exists. Garbage collection happens only when all references are deleted, freeing the memory. This is important to understand to avoid unexpected changes and memory leaks.