Question 1

How to parse a CSV file with custom delimiters in Rust using rust-csv?

Accepted Answer

Use the `ReaderBuilder` to set a custom delimiter, like `csv::ReaderBuilder::new().delimiter(b';').from_reader(io::stdin())` for semicolon-separated values. This is part of the flexible reader/writer features documented in the examples.

Question 2

rust-csv vs csv-core: which one should I use?

Accepted Answer

rust-csv is higher-level with Serde integration and more features, ideal for data serialization and complex tasks. csv-core is lower-level and lighter, better for simple parsing without dependencies. Choose based on your need for convenience vs minimalism.

Question 3

How to handle large CSV files efficiently with rust-csv?

Accepted Answer

Leverage the iterator-based API to stream records one by one, such as using `for result in rdr.records()` to minimize memory overhead. This is emphasized in the key features for streaming processing of large files.

Question 4

Can I write Rust structs to CSV with rust-csv?

Accepted Answer

Yes, by deriving `serde::Serialize` on your struct and using `csv::Writer` to serialize data. The README includes an example with Serde for reading, and writing follows a similar pattern documented in the cookbook.

Question 5

What are common errors in rust-csv and how to fix them?

Accepted Answer

Common errors include header mismatches or malformed quotes; the library provides detailed error messages. Ensure your CSV conforms to set delimiters and quoting rules, and check the error types for debugging.

Question 6

Is rust-csv good for real-time data streaming?

Accepted Answer

Yes, with its iterator-based API, it can handle streaming data efficiently. However, for ultra-high-throughput scenarios, benchmark performance as the library's focus is on correctness and flexibility over raw speed in edge cases.

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