Install PocketCsvReader. This complete console example reads a small customer export without requiring a file on disk.
Input
Id,Name
1,Ada
2,Grace
Read rows
using System.Text;
using PocketCsvReader.Configuration;
var csv = new CsvReaderBuilder()
.WithDialect(d => d.WithHeader().WithLineTerminator("\n"))
.Build();
using var stream = new MemoryStream(Encoding.UTF8.GetBytes("Id,Name\n1,Ada\n2,Grace\n"));
using var reader = csv.ToDataReader(stream);
while (reader.Read())
{
var id = reader.GetInt32(reader.GetOrdinal("Id"));
var name = reader.GetString(reader.GetOrdinal("Name"));
Console.WriteLine($"{id}: {name}");
}
1: Ada
2: Grace
WithHeader() uses the first row for column names. For headerless data use WithoutHeader() and access columns by position. The line terminator is explicit here because the input uses LF. See CSV and TSV for quoting, comments, presets, and dialect defaults.
To read a file, replace csv.ToDataReader(stream) with csv.ToDataReader("customers.csv"). The data reader owns its supplied stream and closes it on disposal. A filename overload streams input too; choosing a filename does not itself load the whole file.
Map to objects
The default CSV object mapper requires a public constructor whose parameter count and order match the data columns, such as public record Customer(int Id, string Name). A property-only class is insufficient. Use csv.To<Customer>("customers.csv") and enumerate it while its input is available.
Column names do not bind constructor parameters. Map rows to objects contains a complete order import, custom parsers, and a selected-column mapper.
Next steps
- Choose an output model for arrays, dictionaries, dynamic rows, tables, or typed objects.
- Configure schemas and cultures when values need explicit types or formats.
- Read asynchronously and understand stream lifetimes.
- Handle optional fields and malformed input.
