What is the fast and slow pointer technique? | Interview Question

Q: What is the fast and slow pointer technique?

**Target Audience:** Beginners preparing for coding interviews — no prior algorithms knowledge assumed **Difficulty:** Easy **Language:** Python 3 > **How to read this doc:** Every idea is explained in plain language first, then tagged with `📌 Interview term:` so you also learn the exact word an interviewer expects. All code is Python, and every output block in the **Verified** section was copied from a real run of the examples on this page. ## 1. Why This Even Matters — A Story First A tortoise and a hare start a race at the same spot. The hare runs twice as fast. - If the course is a **straight road**, the hare reaches the finish line first, and at that exact moment the tortoise is precisely **halfway** along the road. You found the middle of the road without ever measuring it. - If the course is secretly a **circular track**, the hare never finishes. It keeps going round, and sooner or later it comes up behind the tortoise and **laps** it. The moment they are side by side prove

The problem

Question presented to candidate: "What is the fast and slow pointer technique? Explain how it works and show me, in Python, two problems it solves on a linked list."

What a strong answer should cover:

Two pointers start at the same place; the slow one moves one step and the fast one moves two steps per round.
Use 1, the middle: when the fast pointer reaches the end, the slow pointer is halfway.
Use 2, cycles (Floyd's algorithm): inside a loop the fast pointer gains one node per round, so the two must meet; if the fast one reaches the end, there is no cycle.
O(n) time and O(1) extra space, compared with O(n) space for a hash set of visited nodes.
It also works on any sequence where each value determines the next (happy numbers, find the duplicate number).
Python specifics: comparing nodes with is (not == or values), the fast is not None and fast.next is not None order, and a set as the O(n)-space alternative.

Code / implementation expected: Optional — a short Python function for the middle or for cycle detection; the explanation of why the pointers meet matters more.

dsa
linked-list
two-pointers

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Solution

Target Audience: Beginners preparing for coding interviews — no prior algorithms knowledge assumed Difficulty: Easy Language: Python 3

How to read this doc: Every idea is explained in plain language first, then tagged with 📌 Interview term: so you also learn the exact word an interviewer expects. All code is Python, and every output block in the Verified section was copied from a real run of the examples on this page.

1. Why This Even Matters — A Story First

A tortoise and a hare start a race at the same spot. The hare runs twice as fast.

If the course is a straight road, the hare reaches the finish line first, and at that exact moment the tortoise is precisely halfway along the road. You found the middle of the road without ever measuring it.
If the course is secretly a circular track, the hare never finishes. It keeps going round, and soo

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11 min read · 9 sections

Python code

Edit the code and run it here. Each printed line with an expected value becomes a test.

PythonMiddle of a list and cycle detection with one pattern

Practice

PythonFast and slow pointers on a number sequence (happy numbers)

Practice

Discussion

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