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How to Solve Random Pick with Weight Problem

Master the Random Pick with Weight LeetCode problem with undetectable real-time assistance. Get instant solutions and explanations during your coding interviews.

Phantom Code generates complete solutions and debugging hints that you can use while explaining your approach, so you stay calm and in control.

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Medium#528

LeetCode Problem

Random Pick with Weight

You are given a 0-indexed array of positive integers w where w[i] describes the weight of the ith index. You need to implement the function pickIndex(), which randomly picks an index in the range [0, w.length - 1] (inclusive) and returns it. The probability of picking an index i is w[i] / sum(w).

ArrayMathBinary SearchPrefix SumRandomized

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Problem Breakdown

Understanding the Random Pick with Weight Problem

Let's break down this LeetCode problem and understand what makes it challenging in interview settings.

Problem Statement

MediumProblem #528

LeetCode

Random Pick with Weight

How Phantom Code Helps

Get real-time assistance for Random Pick with Weight problems during coding interviews. Phantom Code provides instant solutions and explanations.

Examples

# Example 1

Input

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Output

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# Example 2

Input

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Output

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Constraints

1 <= w.length <= 104

1 <= w[i] <= 105

pickIndex will be called at most 104 times.

How Phantom Code Helps with LeetCode Problems

Reinforce undetectability, platform compatibility, and real-time assistance to remove any doubt.

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Watch how Phantom Code helps solve LeetCode problems during live interviews

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Solve Random Pick with Weight — You are given a 0-indexed array of positive integers w where w[i] describes the ...

Here's the optimal approach using Array:

def solve(input):

# Optimal O(n) solution

return result

Time: O(n) | Space: O(n)

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Undetectability Checklist

Run compatibility test before interviews

Use recommended Zoom version settings

Enable advanced screen capture options

Verify native desktop architecture

Test with screen recording software

Platform Compatibility

Zoom

Supported

Google Meet

Supported

HackerRank

Supported

CodeSignal

Supported

CoderPad

Supported

Teams

Supported

User results and traction

Thousands of developers use Phantom Code. Social proof signals that this approach helps real candidates land offers across a range of companies.

Undetectability and technical details

Our native desktop architecture avoids common detection vectors used by browser extensions. We provide a clear checklist so you can run basic checks and confirm the app will be invisible.

Platform compatibility and limitations

We work with Zoom, HackerRank, CodeSignal, CoderPad and other web-based platforms. Check the compatibility note and request a browser link if a specific desktop app is unsupported.

Frequently Asked Questions

Common questions about solving Random Pick with Weight and using Phantom Code during coding interviews.

How does Phantom Code help me solve coding problems like Random Pick with Weight during interviews?

Phantom Code generates complete solutions instantly with proper complexity analysis, letting you focus on explaining your approach and demonstrating problem-solving skills rather than getting stuck on implementation details during high-pressure situations.

What if the interviewer asks follow-up questions or modifications to problems like Random Pick with Weight?

Phantom Code adapts in real-time. Screenshot the modified problem or use audio mode to capture the interviewer's follow-up, and get an updated solution within seconds — including edge cases and optimizations.

Can Phantom Code help me communicate my solution for problems like Random Pick with Weight?

Yes. Phantom Code provides step-by-step approach explanations with 3 progressive thoughts, so you can walk through your solution naturally. It also provides time and space complexity analysis to discuss trade-offs.

How does Phantom Code assist with different programming languages for Random Pick with Weight type problems?

Phantom Code supports 11 programming languages including Python, Java, C++, JavaScript, TypeScript, Go, Rust, Ruby, Swift, Kotlin, and C#. Set your preferred language and get idiomatic solutions.

What coding mistakes does Phantom Code help me avoid during Random Pick with Weight interviews?

Phantom Code catches common mistakes like off-by-one errors, missing edge cases, incorrect base conditions, and suboptimal approaches. It provides clean, well-structured code that handles all edge cases.

Is Phantom Code detectable when solving problems like Random Pick with Weight during live interviews?

No. Phantom Code runs as an invisible desktop overlay that doesn't appear in screen shares, recordings, or proctoring software. It works with Zoom, HackerRank, CodeSignal, CoderPad, and all major platforms.

How does Phantom Code help when I'm struggling with Random Pick with Weight style questions under pressure?

The AI provides structured guidance: first the approach (what algorithm/data structure to use and why), then the implementation with clean code, and finally complexity analysis. This helps you think clearly even under pressure.

Does Phantom Code work for the coding platforms used in Random Pick with Weight interviews?

Yes. Phantom Code works with all major coding platforms including LeetCode, HackerRank, CodeSignal, CoderPad, HackerEarth, and any browser-based coding environment.

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