FlameCsv

High-performance RFC 4180-compliant CSV library for .NET 9/10 with trimming/AOT support

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• Download on nuget
• See the documentation

Features

• TL;DR: Blazingly fast, trimmable and easy-to-use feature-rich CSV library
• Ease of Use
  • Fluent API to read/write CSV from/to almost any source/destination
  • Built-in support for common CLR types and interfaces like I(Utf8)SpanParsable
  • Full feature parity with sync and async APIs
  • UTF-8/ASCII support to read/write bytes directly from a stream without additional transcoding
  • Hot reload support for internal caches
• High Performance
  • SIMD parsers tuned for each platform (AVX2, AVX512, ARM64)
  • Near-zero allocations
  • Parallel APIs to read/write records ordered or unordered with multiple threads
  • Low-level APIs to handle raw CSV field spans directly
• Deep Customization
  • Attribute configuration for header names, constructors, field order, etc.
  • Support for custom converters and converter factories (like System.Text.Json)
  • Read or write multiple CSV documents from/to a single data stream
• Source Generators
  • Library is fully annotated for NativeAOT and trimming
  • Source generated type maps for reflection-free reading and writing
  • Source generated enum converters with up to 10x better performance than Enum.TryParse/TryFormat

Examples

record User(int Id, string Name, DateTime LastLogin, int? Age = null);

string data = "id,name,lastlogin\n1,Bob,2010-01-01\n2,Alice,2024-05-22";

foreach (var user in Csv.From(data).Read<User>())
{
    Console.WriteLine(user);
}

Reflection-free reading using source generator

record User(int Id, string Name, DateTime LastLogin, int? Age = null);

[CsvTypeMap<char, User>]
partial class UserTypeMap;

foreach (var user in Csv.From(data).Read<User>(UserTypeMap.Default))
{
    Console.WriteLine(user);
}

Reading fields manually

string data = "id,name,lastlogin,age\n1,Bob,2010-01-01,42\n2,Alice,2024-05-22,\n";

CsvOptions<char> options = new()
{
    HasHeader = true,
    IgnoreHeaderCase = true,
    Converters = { new CustomDateTimeConverter() },
};

foreach (CsvRecord<char> record in Csv.From(data).Enumerate(options))
{
    var u1 = new User(
        Id:        record.GetField<int>("Id"),
        Name:      record.GetField<string>("Name"),
        LastLogin: record.GetField<DateTime>("LastLogin"),
        Age:       record.FieldCount >= 3 ? record.GetField<int?>("Age") : null);

    // fields can also be fetched via index
    var u2 = new User(
        Id:        record.GetField<int>(0),
        Name:      record.GetField<string>(1),
        LastLogin: record.GetField<DateTime>(2),
        Age:       record.FieldCount >= 3 ? record.GetField<int?>(3) : null);
    
    // or get them once and reuse
    int nameIndex = record.Header["Name"];
}

Writing records

// write to a stringbuilder
StringBuilder builder = new StringBuilder();
Csv.To(builder).Write(data);

// write to stream
await Csv.To(stream).WithUtf8Encoding().WriteAsync(data);

// write to file in parallel
Csv.ToFile("output.csv").AsParallel(cancellationToken).Write(data);

Writing manually

using (CsvWriter<char> writer = CsvWriter.Create(TextWriter.Null))
{
    writer.WriteRecord(new User(1, "Bob", DateTime.Now, 42));
    writer.NextRecord();
    writer.Flush();

    writer.WriteField(1);
    writer.WriteField("Alice");
    writer.WriteField(DateTime.UnixEpoch);
    writer.WriteField((int?)null);
    writer.NextRecord();
}

Benchmarks

See detailed benchmarks in the documentation page.