Python heapq.heappush() Function: Usage and Examples

Push an item onto a heap while maintaining its invariant.

What You Will Learn

heappush(heap, item) changes a list in place and returns None. Each push costs O(log n).

Time complexity assumes a specific input structure. Include setup work such as sorting or building a lookup table when comparing complete solutions.

Step-by-Step Example

The example below makes the behavior visible with small input values that you can change safely.

import heapq
priority_queue = [2, 5]
heapq.heapify(priority_queue)
heapq.heappush(priority_queue, 1)
print(priority_queue[0])

How the Example Works

• The imports provide the standard-library tools used in the demonstration: heapq.
• The variable priority_queue holds the result of [2, 5]. Later lines use that value or inspect how it changes.
• The print() calls make the return values or state visible so you can compare them with the explanation and check your prediction.

For the chosen input, the expression priority_queue[0] prints 1. Compare that result with the rule above before you change the argument.

Expected output from the example:

1

Another Example: Compare the Results

Try a second input and compare it with the first. Notice whether the result changes in type, value, order, or number of items.

from heapq import heappush, heappop
q = [2, 5]
heappush(q, 1)
print(heappop(q))

Expected output:

1

When You Would Use This

This technique matters when a program handles larger queues, sorted records, or repeated lookups. Choose the data structure based on actual operations and the preconditions the algorithm requires. Verify boundary inputs before optimizing for speed.

Practice: Modify the Code

Add tasks with numeric priorities to a heap.

Verify the changed output against the behavior described above, including the relevant invalid or boundary case.

For complete parameters and version details, consult the official Python documentation.

Common Beginner Mistakes

• Appending to the internal list directly and assuming the heap invariant is preserved.
• Assuming the input is correctly sorted or arranged without checking the algorithm’s preconditions.

Key Takeaways

• Push an item onto a heap while maintaining its invariant.
• heappush(heap, item) changes a list in place and returns None.
• Apply this operation only after checking the assumptions and input conditions shown in the example.