Merge already sorted inputs into one lazy sorted stream.
What You Will Learn
merge(*iterables, key=None, reverse=False) assumes every input is already sorted. It does not sort each input and returns an iterator.
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.
from heapq import merge
print(list(merge([1, 4, 7], [2, 3, 8])))How the Example Works
- The imports provide the standard-library tools used in the demonstration: heapq.
- 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 list(merge([1, 4, 7], [2, 3, 8])) prints [1, 2, 3, 4, 7, 8]. Compare that result with the rule above before you change the argument.
Expected output from the example:
[1, 2, 3, 4, 7, 8]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
Merge chronological streams from two log files.
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
- Passing unsorted inputs and expecting merge() to repair the ordering.
- Overlooking this documented constraint: it does not sort each input and returns an iterator.
Key Takeaways
- Merge already sorted inputs into one lazy sorted stream.
- merge(*iterables, key=None, reverse=False) assumes every input is already sorted.
- Apply this operation only after checking the assumptions and input conditions shown in the example.