Review Python geodata code
Company: Airbnb
Role: Software Engineer
Category: Coding & Algorithms
Difficulty: medium
Interview Round: Onsite
##### Question
You are given a Python codebase that performs geolocation data processing. Conduct a thorough code review: identify readability, correctness, performance, and scalability issues, and propose concrete refactors or optimizations (e.g., data structures, vectorization, caching, modularization).
Quick Answer: This question evaluates proficiency in Python code review and geolocation data-processing, including competencies in readability, correctness, performance optimization, and architectural scalability.
Given a list of GPS points as (latitude, longitude) and an integer precision p, partition the plane into a uniform grid where each cell spans 10^-p degrees in both latitude and longitude. Map each point to its grid cell using integer tile indices i = floor(lat * 10^p + 1e-12) and j = floor(lon * 10^p + 1e-12). Return the number of distinct grid cells visited by the points. If the list is empty, return 0.
Constraints
- 0 <= n <= 200000
- -90.0 <= latitude <= 90.0
- -180.0 <= longitude <= 180.0
- 0 <= precision <= 6
- Quantization uses i = floor(lat * 10^precision + 1e-12), j = floor(lon * 10^precision + 1e-12)
- Return the count of unique (i, j) pairs
Hints
- Convert each point to integer tile indices and use a set to track uniqueness.
- Precompute scale = 10**precision and avoid Python's round; use math.floor with a tiny epsilon to counter floating-point noise.
- If many identical points appear, caching their tile result can reduce repeated computation.