## Round 1 - Coding ## Problem Given the contents of a CSV file as a string, implement a query engine that supports `SELECT`, `WHERE` (with `=` and `>` conditions), and `ORDER BY`. No external CSV or database libraries allowed. ```python class CSVQuery: def __init__(self, csv_data: str): ... def select(self, columns: list[str]) -> list[dict]: ... def where(self, column: str, op: str, value: str) -> 'CSVQuery': # op: "=", ">", " 'CSVQuery': ... def execute(self) -> list[dict]: ... ``` ## Example ``` csv = """name,age,dept Alice,30,Eng Bob,25,Sales Carol,35,Eng""" q = CSVQuery(csv) result = q.where("dept", "=", "Eng").order_by("age").select(["name","age"]).execute() # -> [{"name":"Alice","age":"30"},{"name":"Carol","age":"35"}] ``` ## Follow-ups 1. How do you handle quoted fields that contain commas, e.g. `"Smith, John"`? 2. How would you support numeric comparison for integer and float columns? 3. Add support for `LIMIT N` — where in the chain does it apply? 4. How would you handle missing or empty values in a column used for sorting or filtering?

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CSV Queries: Parse and Query a CSV File Without External Libraries

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Round 1 - Coding Problem Given the contents of a CSV file as a string, implement a query engine that supports SELECT, WHERE (with = and > conditions), and ORDER BY. No external CSV or database libraries allowed. Example Follow-ups How do you handle quoted fields that contain commas, e.g. "Smith, John"? How would you support numeric comparison for integer and float columns? Add support for LIMIT N — where in the chain does it apply? How would you handle missing or empty values in a column used fo…

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

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

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CSV Queries: Parse and Query a CSV File Without External Libraries

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