## Problem You are given a string representing a custom config file. The format uses indentation (2 spaces per level) to represent nesting, and `key: value` pairs. Values may be strings or nested sections. Parse it into a nested Python dict. ```python def parse_config(text: str) -> dict: ``` ## Example ``` text = """ database: host: localhost port: 5432 credentials: user: admin password: secret server: port: 8080 """ Output: { "database": { "host": "localhost", "port": "5432", "credentials": {"user": "admin", "password": "secret"} }, "server": {"port": "8080"} } ``` ## Follow-ups 1. How do you handle tabs vs. spaces, or mixed indentation? 2. What if values can be lists (lines starting with `- `)? 3. Write a `serialize(d: dict) -> str` function that is the inverse of `parse_config`. 4. How would you add line-number error reporting for malformed input?

InterviewDB Experience

File Parsing - Parse a Custom Config Format into a Nested Dict

phone

Interview Experience

Problem You are given a string representing a custom config file. The format uses indentation (2 spaces per level) to represent nesting, and key: value pairs. Values may be strings or nested sections. Parse it into a nested Python dict. Example Follow-ups How do you handle tabs vs. spaces, or mixed indentation? What if values can be lists (lines starting with - )? Write a serialize(d: dict) -> str function that is the inverse of parse_config. How would you add line-number error reporting for mal…

Full Details

🔒

Unlock all Affirm questions

Full insider details, leaked discussions, and candidate experiences.

Get full access — $100 a year, unlimited access

About This Question

This is a candidate experience report from a affirm interview during the phone round.

It covers the following topics: Strings, Phone, Sql, Coding, Onsite .

Topics

Strings Phone Sql Coding Onsite

File Parsing - Parse a Custom Config Format into a Nested Dict

Interview Experience

Full Details

About This Question

Topics

More Affirm Interview Questions