Question 1

How to parse a CSV file with custom delimiters in Swift using CodableCSV?

Accepted Answer

Use CSVReader or CSVDecoder and set the delimiters configuration property. For example, initialize CSVReader with a closure setting $0.delimiters.field = "	" for tab-separated values. This allows parsing non-comma delimited files easily.

Question 2

CodableCSV vs CSV.swift: which is better for handling large files?

Accepted Answer

CodableCSV offers lazy decoding and row-by-row processing with configurable buffering strategies, making it efficient for large files. CSV.swift also supports lazy parsing, but CodableCSV's dual interface and extensive configuration provide more flexibility for memory management.

Question 3

Can CodableCSV handle CSV files without headers?

Accepted Answer

Yes, by setting the headerStrategy to .none in CSVReader or CSVDecoder configuration. For Codable integration, you can use integer coding keys to map fields without headers, as shown in the tips section.

Question 4

How to encode a Swift struct to CSV using CodableCSV?

Accepted Answer

Conform your struct to Codable, create a CSVEncoder instance, and call encode() with the struct. Set headers configuration if needed, for example, $0.headers = ["name", "age"] to specify column names in the output.

Question 5

What are the performance implications of using Codable with CodableCSV?

Accepted Answer

Using Codable can introduce overhead for large datasets due to reflection and key mapping. CodableCSV mitigates this with buffering strategies like .sequential, but imperative parsing might be faster for performance-critical applications.

Question 6

Does CodableCSV support streaming from stdin or network?

Accepted Answer

Yes, it supports InputStream for reading, including stdin, and can write to various outputs. Configure CSVReader or CSVWriter with stream inputs, allowing real-time data processing from sources like network streams.

CodableCSV

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