Sep - Possibly the World's Fastest .NET CSV Parser

Modern, minimal, fast, zero allocation, reading and writing of separated values (csv, tsv etc.). Cross-platform, trimmable and AOT/NativeAOT compatible. Featuring an opinionated API design and pragmatic implementation targetted at machine learning use cases.

⭐ Please star this project if you like it. ⭐

• 🌃 Modern - utilizes features such as Span<T>, Generic Math (ISpanParsable<T>/ ISpanFormattable), ref struct, ArrayPool<T> and similar from .NET 7+ and C# 11+ for a modern and highly efficient implementation.
• 🔎 Minimal - a succinct yet expressive API with few options and no hidden changes to input or output. What you read/write is what you get. E.g. by default there is no "automatic" escaping/unescaping of quotes. For automatic unescaping of quotes see SepReaderOptions and Unescaping.
• 🚀 Fast - blazing fast with both architecture specific and cross-platform SIMD vectorized parsing incl. 64/128/256/512-bit paths e.g. AVX2, AVX-512 (.NET 8.0+), NEON. Uses csFastFloat for fast parsing of floating points. Reads or writes one row at a time efficiently with detailed benchmarks to prove it.
• 🌪️ Multi-threaded - unparalleled speed with highly efficient parallel CSV parsing that is up to 35x faster than CsvHelper, see ParallelEnumerate and benchmarks .
• 🗑️ Zero allocation - intelligent and efficient memory management allowing for zero allocations after warmup incl. supporting use cases of reading or writing arrays of values (e.g. features) easily without repeated allocations.
• ✅ Thorough tests - great code coverage and focus on edge case testing incl. randomized fuzz testing.
• 🌐 Cross-platform - works on any platform, any architecture supported by .NET. 100% managed and written in beautiful modern C#.
• ✂️ Trimmable and AOT/NativeAOT compatible - no problematic reflection or dynamic code generation. Hence, fully trimmable and Ahead-of-Time compatible. With a simple console tester program executable possible in just a few MBs. 💾
• 🗣️ Opinionated and pragmatic - conforms to the essentials of RFC-4180, but takes an opinionated and pragmatic approach towards this especially with regards to quoting and line ends. See section RFC-4180.

Example | Naming and Terminology | API | Limitations and Constraints | Comparison Benchmarks | Example Catalogue | RFC-4180 | FAQ | Public API Reference

Example

var text = """
           A;B;C;D;E;F
           Sep;🚀;1;1.2;0.1;0.5
           CSV;✅;2;2.2;0.2;1.5
           """;

using var reader = Sep.Reader().FromText(text);   // Infers separator 'Sep' from header
using var writer = reader.Spec.Writer().ToText(); // Writer defined from reader 'Spec'
                                                  // Use .FromFile(...)/ToFile(...) for files
var idx = reader.Header.IndexOf("B");
var nms = new[] { "E", "F" };

foreach (var readRow in reader)           // Read one row at a time
{
    var a = readRow["A"].Span;            // Column as ReadOnlySpan<char>
    var b = readRow[idx].ToString();      // Column to string (might be pooled)
    var c = readRow["C"].Parse<int>();    // Parse any T : ISpanParsable<T>
    var d = readRow["D"].Parse<float>();  // Parse float/double fast via csFastFloat
    var s = readRow[nms].Parse<double>(); // Parse multiple columns as Span<T>
                                          // - Sep handles array allocation and reuse
    foreach (ref var v in s) { v *= 10; }

    using var writeRow = writer.NewRow(); // Start new row. Row written on Dispose.
    writeRow["A"].Set(a);                 // Set by ReadOnlySpan<char>
    writeRow["B"].Set(b);                 // Set by string
    writeRow["C"].Set($"{c * 2}");        // Set via InterpolatedStringHandler, no allocs
    writeRow["D"].Format(d / 2);          // Format any T : ISpanFormattable
    writeRow[nms].Format(s);              // Format multiple columns directly
    // Columns are added on first access as ordered, header written when first row written
}

var expected = """
               A;B;C;D;E;F
               Sep;🚀;2;0.6;1;5
               CSV;✅;4;1.1;2;15
               
               """;                       // Empty line at end is for line ending,
                                          // which is always written.
Assert.AreEqual(expected, writer.ToString());

// Above example code is for demonstration purposes only.
// Short names and repeated constants are only for demonstration.

Naming and Terminology

Sep uses naming and terminology that is not based on RFC-4180, but is more tailored to usage in machine learning or similar. Additionally, Sep takes a pragmatic approach towards names by using short names and abbreviations where it makes sense and there should be no ambiguity given the context. That is, using Sep for Separator and Col for Column to keep code succinct.

Term	Description
Sep	Short for separator, also called delimiter. E.g. comma (,) is the separator for the separated values in a csv-file.
Header	Optional first row defining names of columns.
Row	A row is a collection of col(umn)s, which may span multiple lines. Also called record.
Col	Short for column, also called field.
Line	Horizontal set of characters until a line ending; \r\n, \r, \n.
Index	0-based that is RowIndex will be 0 for first row (or the header if present).
Number	1-based that is LineNumber will be 1 for the first line (as in notepad). Given a row may span multiple lines a row can have a From line number and a ToExcl line number matching the C# range indexing syntax [LineNumberFrom..LineNumberToExcl].

Application Programming Interface (API)

Besides being the succinct name of the library, Sep is both the main entry point to using the library and the container for a validated separator. That is, Sep is basically defined as:

public readonly record struct Sep(char Separator);

The separator char is validated upon construction and is guaranteed to be within a limited range and not being a char like " (quote) or similar. This can be seen in src/Sep/Sep.cs. The separator is constrained also for internal optimizations, so you cannot use any char as a separator.

⚠ Note that all types are within the namespace nietras.SeparatedValues and not Sep since it is problematic to have a type and a namespace with the same name.

To get started you can use Sep as the static entry point to building either a reader or writer. That is, for SepReader:

using var reader = Sep.Reader().FromFile("titanic.csv");

where .Reader() is a convenience method corresponding to:

using var reader = Sep.Auto.Reader().FromFile("titanic.csv");

where Sep? Auto => null; is a static property that returns null for a nullable Sep to signify that the separator should be inferred from the first row, which might be a header. If the first row does not contain any of the by default supported separators or there are no rows, the default separator will be used.

⚠ Note Sep uses ; as the default separator, since this is what was used in an internal proprietary library which Sep was built to replace. This is also to avoid issues with comma , being used as a decimal separator in some locales. Without having to resort to quoting.

If you want to specify the separator you can write:

using var reader = Sep.New(',').Reader().FromFile("titanic.csv");

or

var sep = new Sep(',');
using var reader = sep.Reader().FromFile("titanic.csv");

Similarly, for SepWriter:

using var writer = Sep.Writer().ToFile("titanic.csv");

or

using var writer = Sep.New(',').Writer().ToFile("titanic.csv");

where you have to specify a valid separator, since it cannot be inferred. To fascillitate easy flow of the separator and CultureInfo both SepReader and SepWriter expose a Spec property of type SepSpec that simply defines those two. This means you can write:

using var reader = Sep.Reader().FromFile("titanic.csv");
using var writer = reader.Spec.Writer().ToFile("titanic-survivors.csv");

where the writer then will use the separator inferred by the reader, for example.

API Pattern

In general, both reading and writing follow a similar pattern:

Sep/Spec => SepReaderOptions => SepReader => Row => Col(s) => Span/ToString/Parse
Sep/Spec => SepWriterOptions => SepWriter => Row => Col(s) => Set/Format

where each continuation flows fluently from the preceding type. For example, Reader() is an extension method to Sep or SepSpec that returns a SepReaderOptions. Similarly, Writer() is an extension method to Sep or SepSpec that returns a SepWriterOptions.

SepReaderOptions and SepWriterOptions are optionally configurable. That and the APIs for reader and writer is covered in the following sections.

For a complete example, see the example above or the ReadMeTest.cs.

⚠ Note that it is important to understand that Sep Row/Col/Cols are ref structs (please follow the ref struct link and understand how this limits the usage of those). This is due to these types being simple facades or indirections to the underlying reader or writer. That means you cannot use LINQ or create an array of all rows like reader.ToArray() as the reader is not IEnumerable<> either since ref structs cannot be used in interfaces, which is in fact the point. Hence, you need to parse or copy to different types instead. The same applies to Col/Cols which point to internal state that is also reused. This is to avoid repeated allocations for each row and get the best possible performance, while still defining a well structured and straightforward API that guides users to relevant functionality. See Why SepReader Is Not IEnumerable and LINQ Compatible for more.

⚠ For a full overview of public types and methods see Public API Reference.

SepReader API

SepReader API has the following structure (in pseudo-C# code):

using var reader = Sep.Reader(o => o).FromFile/FromText/From...;
var header = reader.Header;
var _ = header.IndexOf/IndicesOf/NamesStartingWith...;
foreach (var row in reader)
{
    var _ = row[colName/colNames].Span/ToString/Parse<T>...;
    var _ = row[colIndex/colIndices].Span/ToString/Parse<T>...;
}

That is, to use SepReader follow the points below:

1. Optionally define Sep or use default automatically inferred separator.
2. Specify reader with optional configuration of SepReaderOptions. For example, if a csv-file does not have a header this can be configured via:

   Sep.Reader(o => o with { HasHeader = false })

   For all options see SepReaderOptions.
3. Specify source e.g. file, text (string), TextWriter, etc. via From extension methods.
4. Optionally access the header. For example, to get all columns starting with GT_ use:

   var colNames = header.NamesStarting("GT_");
   var colIndices = header.IndicesOf(colNames);

5. Enumerate rows. One row at a time.
6. Access a column by name or index. Or access multiple columns with names and indices. Sep internally handles pooled allocation and reuse of arrays for multiple columns.
7. Use Span to access the column directly as a ReadOnlySpan<char>. Or use ToString to convert to a string. Or use Parse<T> where T : ISpanParsable<T> to parse the column chars to a specific type.

SepReaderOptions

The following options are available:

/// <summary>
/// Specifies the separator used, if `null` then automatic detection 
/// is used based on first row in source.
/// </summary>
public Sep? Sep { get; init; } = null;
/// <summary>
/// Specifies the culture used for parsing. 
/// May be `null` for default culture.
/// </summary>
public CultureInfo? CultureInfo { get; init; } = SepDefaults.CultureInfo;
/// <summary>
/// Indicates whether the first row is a header row.
/// </summary>
public bool HasHeader { get; init; } = true;
/// <summary>
/// Specifies <see cref="IEqualityComparer{T}" /> to use 
/// for comparing header column names and looking up index.
/// </summary>
public IEqualityComparer<string> ColNameComparer { get; init; } = SepDefaults.ColNameComparer;
/// <summary>
/// Specifies the method factory used to convert a column span 
/// of `char`s to a `string`.
/// </summary>
public SepCreateToString CreateToString { get; init; } = SepToString.Direct;
/// <summary>
/// Disables using [csFastFloat](https://github.com/CarlVerret/csFastFloat)
/// for parsing `float` and `double`.
/// </summary>
public bool DisableFastFloat { get; init; } = false;
/// <summary>
/// Disables checking if column count is the same for all rows.
/// </summary>
public bool DisableColCountCheck { get; init; } = false;
/// <summary>
/// Disables detecting and parsing quotes.
/// </summary>
public bool DisableQuotesParsing { get; init; } = false;
/// <summary>
/// Unescape quotes on column access.
/// </summary>
/// <remarks>
/// When true, if a column starts with a quote then the two outermost quotes
/// are removed and every second inner quote is removed. Note that
/// unquote/unescape happens in-place, which means the <see
/// cref="SepReader.Row.Span" /> will be modified and contain "garbage"
/// state after unescaped cols before next col. This is for efficiency to
/// avoid allocating secondary memory for unescaped columns. Header
/// columns/names will also be unescaped.
/// Requires <see cref="DisableQuotesParsing"/> to be false.
/// </remarks>
public bool Unescape { get; init; } = false;

Unescaping

While great care has been taken to ensure Sep unescaping of quotes is both correct and fast, there is always the question of how does one respond to invalid input.

The below table tries to summarize the behavior of Sep vs CsvHelper and Sylvan. Note that all do the same for valid input. There are differences for how invalid input is handled. For Sep the design choice has been based on not wanting to throw exceptions and to use a principle that is both reasonably fast and simple.

Input	Valid	CsvHelper	CsvHelper¹	Sylvan	Sep²
a	True	a	a	a	a
""	True
""""	True	"	"	"	"
""""""	True	""	""	""	""
"a"	True	a	a	a	a
"a""a"	True	a"a	a"a	a"a	a"a
"a""a""a"	True	a"a"a	a"a"a	a"a"a	a"a"a
a""a	False	EXCEPTION	a""a	a""a	a""a
a"a"a	False	EXCEPTION	a"a"a	a"a"a	a"a"a
·""·	False	EXCEPTION	·""·	·""·	·""·
·"a"·	False	EXCEPTION	·"a"·	·"a"·	·"a"·
·""	False	EXCEPTION	·""	·""	·""
·"a"	False	EXCEPTION	·"a"	·"a"	·"a"
a"""a	False	EXCEPTION	a"""a	a"""a	a"""a
"a"a"a"	False	EXCEPTION	aa"a"	a"a"a	aa"a
""·	False	EXCEPTION	·	"	·
"a"·	False	EXCEPTION	a·	a"	a·
"a"""a	False	EXCEPTION	aa	EXCEPTION	a"a
"a"""a"	False	EXCEPTION	aa"	a"a<NULL>	a"a"
""a"	False	EXCEPTION	a"	"a	a"
"a"a"	False	EXCEPTION	aa"	a"a	aa"
""a"a""	False	EXCEPTION	a"a""	"a"a"	a"a"
"""	False			EXCEPTION	"
"""""	False	"	"	EXCEPTION	""

· (middle dot) is whitespace to make this visible

¹ CsvHelper with BadDataFound = null

² Sep with Unescape = true in SepReaderOptions

SepReader Debuggability

Debuggability is an important part of any library and while this is still a work in progress for Sep, SepReader does have a unique feature when looking at it and it's row or cols in a debug context. Given the below example code:

var text = """
           Key;Value
           A;"1
           2
           3"
           B;"Apple
           Banana
           Orange
           Pear"
           """;
using var reader = Sep.Reader().FromText(text);
foreach (var row in reader)
{
    // Hover over reader, row or col when breaking here
    var col = row[1];
    if (Debugger.IsAttached && row.RowIndex == 2) { Debugger.Break(); }
    Debug.WriteLine(col.ToString());
}

and you are hovering over reader when the break is triggered then this will show something like:

String Length=55

That is, it will show information of the source for the reader, in this case a string of length 55.

SepReader.Row Debuggability

If you are hovering over row then this will show something like:

  2:[5..9] = "B;\"Apple\r\nBanana\r\nOrange\r\nPear\""

This has the format shown below.

<ROWINDEX>:[<LINENUMBERRANGE>] = "<ROW>"

Note how this shows line number range [FromIncl..ToExcl], as in C# range expression, so that one can easily find the row in question in notepad or similar. This means Sep has to track line endings inside quotes and is an example of a feature that makes Sep a bit slower but which is a price considered worth paying.

GitHub doesn't show line numbers in code blocks so consider copying the example text to notepad or similar to see the effect.

Additionally, if you expand the row in the debugger (e.g. via the small triangle) you will see each column of the row similar to below.

00:'Key'   = "B"
01:'Value' = "\"Apple\r\nBanana\r\nOrange\r\nPear\""

SepReader.Col Debuggability

If you hover over col you should see:

"\"Apple\r\nBanana\r\nOrange\r\nPear\""

Why SepReader Is Not IEnumerable and LINQ Compatible

As mentioned earlier Sep only allows enumeration and access to one row at a time and SepReader.Row is just a simple facade or indirection to the underlying reader. This is why it is defined as a ref struct. In fact, the following code:

using var reader = Sep.Reader().FromText(text);
foreach (var row in reader)
{ }

can also be rewritten as:

using var reader = Sep.Reader().FromText(text);
while (reader.MoveNext())
{
    var row = reader.Current;
}

where row is just a facade for exposing row specific functionality. That is, row is still basically the reader underneath. Hence, let's imagine if SepReader did implement IEnumerable<SepReader.Row> and the Row was not a ref struct. Then, you would be able to write something like below:

using var reader = Sep.Reader().FromText(text);
SepReader.Row[] rows = reader.ToArray();

Given Row is just a facade for the reader, this would be equivalent to writing:

using var reader = Sep.Reader().FromText(text);
SepReader[] rows = reader.ToArray();

which hopefully makes it clear why this is not a good thing. The array would effectively be the reader repeated several times. If this would have to be supported one would have to allocate memory for each row always, which would basically be no different than a ReadLine approach as benchmarked in Comparison Benchmarks.

This is perhaps also the reason why no other efficient .NET CSV parser (known to author) implements an API pattern like Sep, but instead let the reader define all functionality directly and hence only let's you access the current row and cols on that. This API, however, is in this authors opinion not ideal and can be a bit confusing, which is why Sep is designed like it is. The downside is the above caveat.

If you want to use LINQ or similar you have to first parse or transform the rows into some other type and enumerate it. This is easy to do and instead of counting lines you should focus on how such enumeration can be easily expressed using C# iterators (aka yield return). With local functions this can be done inside a method like:

var text = """
           Key;Value
           A;1.1
           B;2.2
           """;
var expected = new (string Key, double Value)[] {
    ("A", 1.1),
    ("B", 2.2),
};

using var reader = Sep.Reader().FromText(text);
var actual = Enumerate(reader).ToArray();

CollectionAssert.AreEqual(expected, actual);

static IEnumerable<(string Key, double Value)> Enumerate(SepReader reader)
{
    foreach (var row in reader)
    {
        yield return (row["Key"].ToString(), row["Value"].Parse<double>());
    }
}

Now if instead refactoring this to something LINQ-compatible by defining a common Enumerate or similar method it could be:

var text = """
           Key;Value
           A;1.1
           B;2.2
           """;
var expected = new (string Key, double Value)[] {
    ("A", 1.1),
    ("B", 2.2),
};

using var reader = Sep.Reader().FromText(text);
var actual = Enumerate(reader,
    row => (row["Key"].ToString(), row["Value"].Parse<double>()))
    .ToArray();

CollectionAssert.AreEqual(expected, actual);

static IEnumerable<T> Enumerate<T>(SepReader reader, SepReader.RowFunc<T> select)
{
    foreach (var row in reader)
    {
        yield return select(row);
    }
}

In fact, Sep now provides such a convenience extension method. And, discounting the Enumerate method, this does have less boilerplate, but not really more effective lines of code. The issue here is that this tends to favor factoring code in a way that can become very inefficient quickly. Consider if one wanted to only enumerate rows matching a predicate on Key which meant only 1% of rows were to be enumerated e.g.:

var text = """
           Key;Value
           A;1.1
           B;2.2
           """;
var expected = new (string Key, double Value)[] {
    ("B", 2.2),
};

using var reader = Sep.Reader().FromText(text);
var actual = reader.Enumerate(
    row => (row["Key"].ToString(), row["Value"].Parse<double>()))
    .Where(kv => kv.Item1.StartsWith('B'))
    .ToArray();

CollectionAssert.AreEqual(expected, actual);

This means you are still parsing the double (which is magnitudes slower than getting just the key) for all rows. Imagine if this was an array of floating points or similar. Not only would you then be parsing a lot of values you would also be allocated 99x arrays that aren't used after filtering with Where.

Instead, you should focus on how to express the enumeration in a way that is both efficient and easy to read. For example, the above could be rewritten as:

var text = """
           Key;Value
           A;1.1
           B;2.2
           """;
var expected = new (string Key, double Value)[] {
    ("B", 2.2),
};

using var reader = Sep.Reader().FromText(text);
var actual = Enumerate(reader).ToArray();

CollectionAssert.AreEqual(expected, actual);

static IEnumerable<(string Key, double Value)> Enumerate(SepReader reader)
{
    foreach (var row in reader)
    {
        var keyCol = row["Key"];
        if (keyCol.Span.StartsWith("B"))
        {
            yield return (keyCol.ToString(), row["Value"].Parse<double>());
        }
    }
}

To accomodate this Sep provides an overload for Enumerate that is similar to:

static IEnumerable<T> Enumerate<T>(this SepReader reader, SepReader.RowTryFunc<T> trySelect)
{
    foreach (var row in reader)
    {
        if (trySelect(row, out var value))
        {
            yield return value;
        }
    }
}

With this the above custom Enumerate can be replaced with:

var text = """
           Key;Value
           A;1.1
           B;2.2
           """;
var expected = new (string Key, double Value)[] {
    ("B", 2.2),
};

using var reader = Sep.Reader().FromText(text);
var actual = reader.Enumerate((SepReader.Row row, out (string Key, double Value) kv) =>
{
    var keyCol = row["Key"];
    if (keyCol.Span.StartsWith("B"))
    {
        kv = (keyCol.ToString(), row["Value"].Parse<double>());
        return true;
    }
    kv = default;
    return false;
}).ToArray();

CollectionAssert.AreEqual(expected, actual);

Note how this is pretty much the same length as the previous custom Enumerate. Also worse due to how C# requires specifying types for out parameters which then requires all parameter types for the lambda to be specified. Hence, in this case the custom Enumerate does not take significantly longer to write and is a lot more efficient than using LINQ .Where (also avoids allocating a string for key for each row) and is easier to debug and perhaps even read. All examples above can be seen in ReadMeTest.cs.

There is a strong case for having an enumerate API though and that is for parallelized enumeration, which will be discussed next.

ParallelEnumerate and Enumerate

As discussed in the previous section Sep provides Enumerate convenience extension methods, that should be used carefully. Alongside these there are ParallelEnumerate extension methods that provide very efficient multi-threaded enumeration. See benchmarks for numbers and Public API Reference.

ParallelEnumerate is build on top of LINQ AsParallel().AsOrdered() and will return exactly the same as Enumerate but with enumeration parallelized. This will use more memory during execution and as many threads as possible via the .NET thread pool. When using ParallelEnumerate one should, therefore (as always), be certain the provided delegate does not refer to or change any mutable state.

ParallelEnumerate comes with a lot of overhead compared to single-threaded foreach or Enumerate and should be used carefully based on measuring any potential benefit. Sep goes a long way to make this very efficient by using pooled arrays and parsing multiple rows in batches, but if the source only has a few rows then any benefit is unlikely.

Due to ParallelEnumerate being based on batches of rows it is also important not to "abuse" it in-place of LINQ AsParallel. The idea is to use it for parsing rows, not for doing expensive per row operations like loading an image or similar. In that case, you are better off using AsParallel() after ParallelEnumerate or Enumerate similarly to:

using var reader = Sep.Reader().FromFile("very-long.csv");
var results = reader.ParallelEnumerate(ParseRow)
                    .AsParallel().AsOrdered()
                    .Select(LoadData) // Expensive load
                    .ToList();

As a rule of thumb if the time per row exceeds 1 millisecond consider moving the expensive work to after ParallelEnumerate/Enumerate,

SepWriter API

SepWriter API has the following structure (in pseudo-C# code):

using var writer = Sep.Writer(o => o).ToFile/ToText/To...;
foreach (var data in EnumerateData())
{
    using var row = writer.NewRow();
    var _ = row[colName/colNames].Set/Format<T>...;
    var _ = row[colIndex/colIndices].Set/Format<T>...;
}

That is, to use SepWriter follow the points below:

1. Optionally define Sep or use default automatically inferred separator.
2. Specify writer with optional configuration of SepWriterOptions. For all options see SepWriterOptions.
3. Specify destination e.g. file, text (string via StringWriter), TextWriter, etc. via To extension methods.
4. MISSING: SepWriter currently does not allow you to define the header up front. Instead, header is defined by the order in which column names are accessed/created when defining the row.
5. Define new rows with NewRow. ⚠ Be sure to dispose any new rows before starting the next! For convenience Sep provides an overload for NewRow that takes a SepReader.Row and copies the columns from that row to the new row:

   using var reader = Sep.Reader().FromText(text);
   using var writer = reader.Spec.Writer().ToText();
   foreach (var readRow in reader)
   {   using var writeRow = writer.NewRow(readRow); }

6. Create a column by selecting by name or index. Or multiple columns via indices and names. Sep internally handles pooled allocation and reuse of arrays for multiple columns.
7. Use Set to set the column value either as a ReadOnlySpan<char>, string or via an interpolated string. Or use Format<T> where T : IFormattable to format T to the column value.
8. Row is written when Dispose is called on the row.

   Note this is to allow a row to be defined flexibly with both column removal, moves and renames in the future. This is not yet supported.

SepWriterOptions

The following options are available:

/// <summary>
/// Specifies the separator used.
/// </summary>
public Sep Sep { get; init; }
/// <summary>
/// Specifies the culture used for parsing. 
/// May be `null` for default culture.
/// </summary>
public CultureInfo? CultureInfo { get; init; }
/// <summary>
/// Specifies whether to write a header row 
/// before data rows. Requires all columns 
/// to have a name. Otherwise, columns can be
/// added by indexing alone.
/// </summary>
public bool WriteHeader { get; init; } = true;

Limitations and Constraints

Sep is designed to be minimal and fast. As such, it has some limitations and constraints, since these are not needed for the initial intended usage:

• Automatic escaping and unescaping quotes is not supported. Use Trim extension method to remove surrounding quotes, for example.
• Comments # are not directly supported. You can skip a row by:

  foreach (var row in reader)
  {
       // Skip row if starts with #
       if (!row.Span.StartsWith("#"))
       {
            // ...
       }
  }

  This does not allow skipping a header row starting with # though.
• SepWriter is not yet fully featured and one cannot skip writing a header currently.

Comparison Benchmarks

To investigate the performance of Sep it is compared to:

• CsvHelper - the most commonly used CSV library with a staggering downloads on NuGet. Fully featured and battle tested.
• Sylvan - is well-known and has previously been shown to be the fastest CSV libraries for parsing (Sep changes that 😉).
• ReadLine/WriteLine - basic naive implementations that read line by line and split on separator. While writing columns, separators and line endings directly. Does not handle quotes or similar correctly.

All benchmarks are run from/to memory either with:

• StringReader or StreamReader + MemoryStream
• StringWriter or StreamWriter + MemoryStream

This to avoid confounding factors from reading from or writing to disk.

When using StringReader/StringWriter each char counts as 2 bytes, when measuring throughput e.g. MB/s. When using StreamReader/StreamWriter content is UTF-8 encoded and each char typically counts as 1 byte, as content usually limited to 1 byte per char in UTF-8. Note that in .NET for TextReader and TextWriter data is converted to/from char, but for reading such conversion can often be just as fast as Memmove.

By default only StringReader/StringWriter results are shown, if a result is based on StreamReader/StreamWriter it will be called out. Usually, results for StreamReader/StreamWriter are in line with StringReader/StringWriter but with half the throughput due to 1 byte vs 2 bytes. For brevity they are not shown here.

For all benchmark results, Sep has been defined as the Baseline in BenchmarkDotNet. This means Ratio will be 1.00 for Sep. For the others Ratio will then show how many times faster Sep is than that. Or how many times more bytes are allocated in Alloc Ratio.

Disclaimer: Any comparison made is based on a number of preconditions and assumptions. Sep is a new library written from the ground up to use the latest and greatest features in .NET. CsvHelper has a long history and has to take into account backwards compatibility and still supporting older runtimes, so may not be able to easily utilize more recent features. Same goes for Sylvan. Additionally, Sep has a different feature set compared to the two. Performance is a feature, but not the only feature. Keep that in mind when evaluating results.

Runtime and Platforms

The following runtime is used for benchmarking:

• NET 8.0.X

The following platforms are used for benchmarking:

• AMD 5950X X64 Platform Information

  OS=Windows 10 (10.0.19044.2846/21H2/November2021Update)
  AMD Ryzen 9 5950X, 1 CPU, 32 logical and 16 physical cores

• Intel Xeon Silver 4316 X64 Platform Information

  OS=Windows 10 (10.0.17763.3287/1809/October2018Update/Redstone5)
  Intel Xeon Silver 4316 CPU 2.30GHz, 1 CPU, 40 logical and 20 physical cores

• Neoverse N1 ARM64 Platform Information (cloud instance)

  OS=ubuntu 22.04
  Neoverse N1, ARM, 4 vCPU

Reader Comparison Benchmarks

The following reader scenarios are benchmarked:

• NCsvPerf from The fastest CSV parser in .NET
• Floats as for example in machine learning.

Details for each can be found in the following. However, for each of these 3 different scopes are benchmarked to better assertain the low-level performance of each library and approach and what parts of the parsing consume the most time:

• Row - for this scope only the row is enumerated. That is, for Sep all that is done is:

  foreach (var row in reader) { }

  this should capture parsing both row and columns but without accessing these. Note that some libraries (like Sylvan) will defer work for columns to when these are accessed.
• Cols - for this scope all rows and all columns are enumerated. If possible columns are accessed as spans, if not as strings, which then might mean a string has to be allocated. That is, for Sep this is:

  foreach (var row in reader)
  {
      for (var i = 0; i < row.ColCount; i++)
      {
          var span = row[i].Span;
      }
  }

• XYZ - finally the full scope is performed which is specific to each of the scenarios.

Additionally, as Sep supports multi-threaded parsing via ParallelEnumerate benchmarks results with _MT in the method name are multi-threaded. These show Sep provides unparalleled performance compared to any other CSV parser.

NCsvPerf PackageAssets Reader Comparison Benchmarks

NCsvPerf from The fastest CSV parser in .NET is a benchmark which in Joel Verhagen own words was defined with:

My goal was to find the fastest low-level CSV parser. Essentially, all I wanted was a library that gave me a string[] for each line where each field in the line was an element in the array.

What is great about this work is it tests a whole of 35 different libraries and approaches to this. Providing a great overview of those and their performance on this specific scenario. Given Sylvan is the fastest of those it is used as the one to beat here, while CsvHelper is used to compare to the most commonly used library.

The source used for this benchmark PackageAssetsBench.cs is a PackageAssets.csv with NuGet package information in 25 columns with rows like:

75fcf875-017d-4579-bfd9-791d3e6767f0,2020-11-28T01:50:41.2449947+00:00,Akinzekeel.BlazorGrid,0.9.1-preview,2020-11-27T22:42:54.3100000+00:00,AvailableAssets,RuntimeAssemblies,,,net5.0,,,,,,lib/net5.0/BlazorGrid.dll,BlazorGrid.dll,.dll,lib,net5.0,.NETCoreApp,5.0.0.0,,,0.0.0.0
75fcf875-017d-4579-bfd9-791d3e6767f0,2020-11-28T01:50:41.2449947+00:00,Akinzekeel.BlazorGrid,0.9.1-preview,2020-11-27T22:42:54.3100000+00:00,AvailableAssets,CompileLibAssemblies,,,net5.0,,,,,,lib/net5.0/BlazorGrid.dll,BlazorGrid.dll,.dll,lib,net5.0,.NETCoreApp,5.0.0.0,,,0.0.0.0
75fcf875-017d-4579-bfd9-791d3e6767f0,2020-11-28T01:50:41.2449947+00:00,Akinzekeel.BlazorGrid,0.9.1-preview,2020-11-27T22:42:54.3100000+00:00,AvailableAssets,ResourceAssemblies,,,net5.0,,,,,,lib/net5.0/de/BlazorGrid.resources.dll,BlazorGrid.resources.dll,.dll,lib,net5.0,.NETCoreApp,5.0.0.0,,,0.0.0.0
75fcf875-017d-4579-bfd9-791d3e6767f0,2020-11-28T01:50:41.2449947+00:00,Akinzekeel.BlazorGrid,0.9.1-preview,2020-11-27T22:42:54.3100000+00:00,AvailableAssets,MSBuildFiles,,,any,,,,,,build/Microsoft.AspNetCore.StaticWebAssets.props,Microsoft.AspNetCore.StaticWebAssets.props,.props,build,any,Any,0.0.0.0,,,0.0.0.0
75fcf875-017d-4579-bfd9-791d3e6767f0,2020-11-28T01:50:41.2449947+00:00,Akinzekeel.BlazorGrid,0.9.1-preview,2020-11-27T22:42:54.3100000+00:00,AvailableAssets,MSBuildFiles,,,any,,,,,,build/Akinzekeel.BlazorGrid.props,Akinzekeel.BlazorGrid.props,.props,build,any,Any,0.0.0.0,,,0.0.0.0

For Scope = Asset the columns are parsed into a PackageAsset class, which consists of 25 properties of which 22 are strings. Each asset is accumulated into a List<PackageAsset>. Each column is accessed as a string regardless.

This means this benchmark is dominated by turning columns into strings for the decently fast parsers. Hence, the fastest libraries in this test employ string pooling. That is, basically a custom dictionary from ReadOnlySpan<char> to string, which avoids allocating a new string for repeated values. And as can be seen in the csv-file there are a lot of repeated values. Both Sylvan and CsvHelper do this in the benchmark. So does Sep and as with Sep this is an optional configuration that has to be explicitly enable. For Sep this means the reader is created with something like:

using var reader = Sep.Reader(o => o with
{
    HasHeader = false,
    CreateToString = SepToString.PoolPerCol(maximumStringLength: 128),
})
.From(CreateReader());

What is unique for Sep is that it allows defining a pool per column e.g. via SepToString.PoolPerCol(...). This is based on the fact that often each column has its own set of values or strings that may be repeated without any overlap to other columns. This also allows one to define per column specific handling of ToString behavior. Whether to pool or not. Or even to use a statically defined pool.

Sep supports unescaping via an option, see SepReaderOptions and Unescaping. Therefore, Sep has two methods being tested. The default Sep without unescaping and Sep_Unescape where unescaping is enabled. Note that only if there are quotes will there be any unescaping, but to support unescape one has to track extra state during parsing which means there is a slight cost no matter what, most notably for the Cols scope. Sep is still the fastest of all (by far in many cases).

PackageAssets Benchmark Results

The results below show Sep is the fastest .NET CSV Parser (for this benchmark on these platforms and machines 😀). While for pure parsing allocating only a fraction of the memory due to extensive use of pooling and the ArrayPool<T>.

This is in many aspects due to Sep having extremely optimized string pooling and optimized hashing of ReadOnlySpan<char>, and thus not really due the the csv-parsing itself, since that is not a big part of the time consumed. At least not for a decently fast csv-parser.

With ParallelEnumerate (MT) Sep is >2x faster than Sylvan and up to 9x faster than CsvHelper.

AMD.Ryzen.9.5950X - PackageAssets Benchmark Results (Sep 0.4.6.0, Sylvan 1.3.7.0, CsvHelper 31.0.2.15)

Method	Scope	Rows	Mean	Ratio	MB	MB/s	ns/row	Allocated	Alloc Ratio
Sep______	Row	50000	2.326 ms	1.00	29	12544.5	46.5	1.01 KB	1.00
Sep_Unescape	Row	50000	2.387 ms	1.03	29	12226.3	47.7	1.02 KB	1.00
Sylvan___	Row	50000	3.014 ms	1.30	29	9682.9	60.3	7.21 KB	7.10
ReadLine_	Row	50000	12.914 ms	5.57	29	2259.6	258.3	88608.24 KB	87,329.01
CsvHelper	Row	50000	46.935 ms	20.17	29	621.7	938.7	20 KB	19.71
Sep______	Cols	50000	3.151 ms	1.00	29	9262.0	63.0	1.02 KB	1.00
Sep_Unescape	Cols	50000	3.773 ms	1.20	29	7734.6	75.5	1.02 KB	1.00
Sylvan___	Cols	50000	5.166 ms	1.64	29	5648.5	103.3	7.21 KB	7.09
ReadLine_	Cols	50000	13.021 ms	4.12	29	2241.0	260.4	88608.24 KB	87,077.58
CsvHelper	Cols	50000	72.451 ms	22.99	29	402.8	1449.0	445.76 KB	438.06
Sep______	Asset	50000	37.506 ms	1.00	29	778.0	750.1	13803.3 KB	1.00
Sep_MT___	Asset	50000	22.617 ms	0.60	29	1290.2	452.3	13992.22 KB	1.01
Sylvan___	Asset	50000	39.622 ms	1.06	29	736.5	792.4	13962.44 KB	1.01
ReadLine_	Asset	50000	105.490 ms	2.98	29	276.6	2109.8	102133.28 KB	7.40
CsvHelper	Asset	50000	87.642 ms	2.35	29	333.0	1752.8	13971.76 KB	1.01
Sep______	Asset	1000000	622.282 ms	1.00	583	938.1	622.3	266667.45 KB	1.00
Sep_MT___	Asset	1000000	249.164 ms	0.40	583	2343.0	249.2	268111.22 KB	1.01
Sylvan___	Asset	1000000	771.816 ms	1.23	583	756.4	771.8	266826.86 KB	1.00
ReadLine_	Asset	1000000	1,554.977 ms	2.43	583	375.4	1555.0	2038833.85 KB	7.65
CsvHelper	Asset	1000000	1,701.078 ms	2.67	583	343.2	1701.1	266838.3 KB	1.00

Intel.Xeon.Silver.4316.2.30GHz - PackageAssets Benchmark Results (Sep 0.4.0.0, Sylvan 1.3.5.0, CsvHelper 30.0.1.0)

Method	Scope	Rows	Mean	Ratio	MB	MB/s	ns/row	Allocated	Alloc Ratio
Sep______	Row	50000	5.118 ms	1.00	29	5701.4	102.4	1.18 KB	1.00
Sep_Unescape	Row	50000	5.146 ms	1.01	29	5670.6	102.9	1.18 KB	1.00
Sylvan___	Row	50000	5.953 ms	1.16	29	4901.9	119.1	7.21 KB	6.12
ReadLine_	Row	50000	25.973 ms	5.07	29	1123.5	519.5	88608.26 KB	75,111.64
CsvHelper	Row	50000	90.063 ms	17.60	29	324.0	1801.3	20.69 KB	17.54
Sep______	Cols	50000	7.123 ms	1.00	29	4096.5	142.5	1.19 KB	1.00
Sep_Unescape	Cols	50000	7.943 ms	1.12	29	3673.9	158.9	1.19 KB	1.00
Sylvan___	Cols	50000	10.124 ms	1.42	29	2882.3	202.5	7.22 KB	6.09
ReadLine_	Cols	50000	25.928 ms	3.64	29	1125.5	518.6	88608.24 KB	74,678.88
CsvHelper	Cols	50000	140.614 ms	19.74	29	207.5	2812.3	446.45 KB	376.26
Sep______	Asset	50000	53.901 ms	1.00	29	541.4	1078.0	13802.75 KB	1.00
Sep_MT___	Asset	50000	30.484 ms	0.57	29	957.3	609.7	14030.67 KB	1.02
Sylvan___	Asset	50000	67.354 ms	1.25	29	433.2	1347.1	13961.77 KB	1.01
ReadLine_	Asset	50000	149.924 ms	2.78	29	194.6	2998.5	102133.61 KB	7.40
CsvHelper	Asset	50000	158.310 ms	2.94	29	184.3	3166.2	13970.8 KB	1.01
Sep______	Asset	1000000	1,122.212 ms	1.00	583	520.2	1122.2	266672.93 KB	1.00
Sep_MT___	Asset	1000000	378.388 ms	0.34	583	1542.8	378.4	267505.55 KB	1.00
Sylvan___	Asset	1000000	1,408.440 ms	1.26	583	414.5	1408.4	266826.38 KB	1.00
ReadLine_	Asset	1000000	2,962.035 ms	2.63	583	197.1	2962.0	2038832.76 KB	7.65
CsvHelper	Asset	1000000	3,379.135 ms	3.00	583	172.8	3379.1	266833.95 KB	1.00

Neoverse.N1 - PackageAssets Benchmark Results (Sep 0.4.0.0, Sylvan 1.3.5.0, CsvHelper 30.0.1.0)

Method	Scope	Rows	Mean	Ratio	MB	MB/s	ns/row	Allocated	Alloc Ratio
Sep______	Row	50000	12.72 ms	1.00	29	2287.5	254.3	1020 B	1.00
Sep_Unescape	Row	50000	12.75 ms	1.00	29	2281.2	255.0	1020 B	1.00
Sylvan___	Row	50000	31.29 ms	2.46	29	929.4	625.9	6269 B	6.15
ReadLine_	Row	50000	37.12 ms	2.92	29	783.5	742.5	90734916 B	88,955.80
CsvHelper	Row	50000	91.34 ms	7.18	29	318.4	1826.9	21272 B	20.85
Sep______	Cols	50000	15.00 ms	1.00	29	1938.6	300.1	1032 B	1.00
Sep_Unescape	Cols	50000	16.05 ms	1.07	29	1811.8	321.1	1035 B	1.00
Sylvan___	Cols	50000	35.43 ms	2.36	29	821.0	708.6	6288 B	6.09
ReadLine_	Cols	50000	41.72 ms	2.78	29	697.2	834.3	90734929 B	87,921.44
CsvHelper	Cols	50000	137.46 ms	9.16	29	211.6	2749.3	457144 B	442.97
Sep______	Asset	50000	68.24 ms	1.00	29	426.2	1364.9	14134756 B	1.00
Sep_MT___	Asset	50000	38.78 ms	0.57	29	750.1	775.5	14191876 B	1.00
Sylvan___	Asset	50000	100.82 ms	1.48	29	288.5	2016.5	14295846 B	1.01
ReadLine_	Asset	50000	157.86 ms	2.31	29	184.2	3157.2	104585308 B	7.40
CsvHelper	Asset	50000	167.11 ms	2.43	29	174.1	3342.2	14309064 B	1.01
Sep______	Asset	1000000	1,357.03 ms	1.00	581	428.8	1357.0	273070824 B	1.00
Sep_MT___	Asset	1000000	648.57 ms	0.48	581	897.2	648.6	277540480 B	1.02
Sylvan___	Asset	1000000	1,990.02 ms	1.47	581	292.4	1990.0	273234920 B	1.00
ReadLine_	Asset	1000000	3,137.22 ms	2.32	581	185.5	3137.2	2087767336 B	7.65
CsvHelper	Asset	1000000	3,391.21 ms	2.50	581	171.6	3391.2	273241296 B	1.00

PackageAssets Benchmark Results (SERVER GC)

The package assets benchmark (Scope Asset) has a very high base load in the form of the accumulated instances of PackageAsset and since Sep is so fast the GC becomes a significant bottleneck for the benchmark, especially for multi-threaded parsing. Switching to SERVER GC can, therefore, provide significant speedup as can be seen below.

With ParallelEnumerate and server GC Sep is >4x faster than Sylvan and up to 18x faster than CsvHelper. Breaking 4 GB/s parsing speed on package assets on 5950X.

AMD.Ryzen.9.5950X - PackageAssets Benchmark Results (SERVER GC) (Sep 0.4.6.0, Sylvan 1.3.7.0, CsvHelper 31.0.2.15)

Method	Scope	Rows	Mean	Ratio	MB	MB/s	ns/row	Allocated	Alloc Ratio
Sep______	Asset	50000	21.051 ms	1.00	29	1386.2	421.0	13.48 MB	1.00
Sep_MT___	Asset	50000	5.993 ms	0.29	29	4869.4	119.9	13.64 MB	1.01
Sylvan___	Asset	50000	29.301 ms	1.39	29	995.9	586.0	13.63 MB	1.01
ReadLine_	Asset	50000	33.868 ms	1.60	29	861.6	677.4	99.74 MB	7.40
CsvHelper	Asset	50000	76.599 ms	3.64	29	381.0	1532.0	13.64 MB	1.01
Sep______	Asset	1000000	425.355 ms	1.00	583	1372.5	425.4	260.41 MB	1.00
Sep_MT___	Asset	1000000	109.917 ms	0.26	583	5311.1	109.9	261.49 MB	1.00
Sylvan___	Asset	1000000	588.226 ms	1.38	583	992.4	588.2	260.57 MB	1.00
ReadLine_	Asset	1000000	581.137 ms	1.37	583	1004.6	581.1	1991.04 MB	7.65
CsvHelper	Asset	1000000	1,535.431 ms	3.60	583	380.2	1535.4	260.58 MB	1.00

Intel.Xeon.Silver.4316.2.30GHz - PackageAssets Benchmark Results (SERVER GC) (Sep 0.4.0.0, Sylvan 1.3.5.0, CsvHelper 30.0.1.0)

Method	Scope	Rows	Mean	Ratio	RatioSD	MB	MB/s	ns/row	Allocated	Alloc Ratio
Sep______	Asset	50000	41.669 ms	1.00	0.00	29	700.3	833.4	13.48 MB	1.00
Sep_MT___	Asset	50000	9.802 ms	0.24	0.00	29	2977.1	196.0	13.68 MB	1.01
Sylvan___	Asset	50000	56.608 ms	1.36	0.01	29	515.5	1132.2	13.63 MB	1.01
ReadLine_	Asset	50000	47.549 ms	1.14	0.01	29	613.7	951.0	99.74 MB	7.40
CsvHelper	Asset	50000	153.359 ms	3.68	0.02	29	190.3	3067.2	13.64 MB	1.01
Sep______	Asset	1000000	822.268 ms	1.00	0.00	583	710.0	822.3	260.41 MB	1.00
Sep_MT___	Asset	1000000	161.654 ms	0.20	0.00	583	3611.3	161.7	261.31 MB	1.00
Sylvan___	Asset	1000000	1,120.677 ms	1.36	0.00	583	520.9	1120.7	260.57 MB	1.00
ReadLine_	Asset	1000000	1,081.121 ms	1.31	0.00	583	540.0	1081.1	1991.05 MB	7.65
CsvHelper	Asset	1000000	3,051.024 ms	3.71	0.00	583	191.3	3051.0	260.58 MB	1.00

Neoverse.N1 - PackageAssets Benchmark Results (SERVER GC) (Sep 0.4.0.0, Sylvan 1.3.5.0, CsvHelper 30.0.1.0)

Method	Scope	Rows	Mean	Ratio	RatioSD	MB	MB/s	ns/row	Allocated	Alloc Ratio
Sep______	Asset	50000	56.29 ms	1.00	0.00	29	516.7	1125.8	13.48 MB	1.00
Sep_MT___	Asset	50000	20.66 ms	0.37	0.02	29	1407.7	413.2	13.53 MB	1.00
Sylvan___	Asset	50000	88.70 ms	1.58	0.08	29	327.9	1773.9	13.63 MB	1.01
ReadLine_	Asset	50000	67.01 ms	1.19	0.04	29	434.1	1340.1	99.74 MB	7.40
CsvHelper	Asset	50000	158.71 ms	2.83	0.10	29	183.3	3174.2	13.64 MB	1.01
Sep______	Asset	1000000	1,110.22 ms	1.00	0.00	581	524.1	1110.2	260.41 MB	1.00
Sep_MT___	Asset	1000000	402.71 ms	0.36	0.00	581	1444.9	402.7	265.42 MB	1.02
Sylvan___	Asset	1000000	1,759.98 ms	1.58	0.01	581	330.6	1760.0	260.57 MB	1.00
ReadLine_	Asset	1000000	1,575.08 ms	1.43	0.07	581	369.4	1575.1	1991.05 MB	7.65
CsvHelper	Asset	1000000	3,167.05 ms	2.85	0.01	581	183.7	3167.1	260.58 MB	1.00

PackageAssets with Quotes Benchmark Results

NCsvPerf does not examine performance in the face of quotes in the csv. This is relevant since some libraries like Sylvan will revert to a slower (not SIMD vectorized) parsing code path if it encounters quotes. Sep was designed to always use SIMD vectorization no matter what.

Since there are two extra chars to handle per column, it does have a significant impact on performance, no matter what though. This is expected when looking at the numbers. For each row of 25 columns, there are 24 separators (here ,) and one set of line endings (here \r\n). That's 26 characters. Adding quotes around each of the 25 columns will add 50 characters or almost triple the total to 76.

AMD.Ryzen.9.5950X - PackageAssets with Quotes Benchmark Results (Sep 0.4.6.0, Sylvan 1.3.7.0, CsvHelper 31.0.2.15)

Method	Scope	Rows	Mean	Ratio	MB	MB/s	ns/row	Allocated	Alloc Ratio
Sep______	Row	50000	6.401 ms	1.00	33	5214.3	128.0	1.03 KB	1.00
Sep_Unescape	Row	50000	6.785 ms	1.06	33	4919.3	135.7	1.03 KB	1.00
Sylvan___	Row	50000	18.566 ms	2.91	33	1797.8	371.3	7.23 KB	7.04
ReadLine_	Row	50000	14.481 ms	2.26	33	2304.8	289.6	108778.74 KB	105,883.49
CsvHelper	Row	50000	52.862 ms	8.26	33	631.4	1057.2	20 KB	19.47
Sep______	Cols	50000	7.238 ms	1.00	33	4611.2	144.8	1.03 KB	1.00
Sep_Unescape	Cols	50000	8.971 ms	1.23	33	3720.6	179.4	1.03 KB	1.00
Sylvan___	Cols	50000	21.286 ms	2.94	33	1568.0	425.7	7.24 KB	7.02
ReadLine_	Cols	50000	14.900 ms	2.06	33	2240.1	298.0	108778.74 KB	105,482.42
CsvHelper	Cols	50000	83.563 ms	11.54	33	399.4	1671.3	445.76 KB	432.25
Sep______	Asset	50000	39.372 ms	1.00	33	847.8	787.4	13802.4 KB	1.00
Sep_MT___	Asset	50000	24.035 ms	0.61	33	1388.7	480.7	13985.88 KB	1.01
Sylvan___	Asset	50000	50.022 ms	1.26	33	667.2	1000.4	13962.17 KB	1.01
ReadLine_	Asset	50000	120.676 ms	3.07	33	276.6	2413.5	122304.18 KB	8.86
CsvHelper	Asset	50000	96.420 ms	2.44	33	346.2	1928.4	13971.94 KB	1.01
Sep______	Asset	1000000	703.318 ms	1.00	667	949.4	703.3	266667.29 KB	1.00
Sep_MT___	Asset	1000000	332.798 ms	0.47	667	2006.3	332.8	267969.09 KB	1.00
Sylvan___	Asset	1000000	1,075.648 ms	1.53	667	620.7	1075.6	266824.34 KB	1.00
ReadLine_	Asset	1000000	2,409.387 ms	3.34	667	277.1	2409.4	2442315.91 KB	9.16
CsvHelper	Asset	1000000	2,087.482 ms	2.96	667	319.9	2087.5	266832.87 KB	1.00

Intel.Xeon.Silver.4316.2.30GHz - PackageAssets with Quotes Benchmark Results (Sep 0.4.0.0, Sylvan 1.3.5.0, CsvHelper 30.0.1.0)

Method	Scope	Rows	Mean	Ratio	MB	MB/s	ns/row	Allocated	Alloc Ratio
Sep______	Row	50000	13.60 ms	1.00	33	2453.9	272.0	1.21 KB	1.00
Sep_Unescape	Row	50000	12.79 ms	0.94	33	2610.7	255.7	1.2 KB	1.00
Sylvan___	Row	50000	33.79 ms	2.49	33	987.8	675.8	7.26 KB	6.01
ReadLine_	Row	50000	30.72 ms	2.26	33	1086.5	614.4	108778.76 KB	90,048.06
CsvHelper	Row	50000	102.72 ms	7.55	33	324.9	2054.3	20.69 KB	17.13
Sep______	Cols	50000	15.89 ms	1.00	33	2100.0	317.9	1.21 KB	1.00
Sep_Unescape	Cols	50000	16.99 ms	1.07	33	1964.6	339.8	1.22 KB	1.00
Sylvan___	Cols	50000	39.57 ms	2.53	33	843.6	791.3	7.27 KB	5.99
ReadLine_	Cols	50000	31.03 ms	1.95	33	1075.5	620.7	108778.74 KB	89,613.38
CsvHelper	Cols	50000	160.67 ms	10.11	33	207.7	3213.4	446.45 KB	367.79
Sep______	Asset	50000	64.27 ms	1.00	33	519.4	1285.3	13804.23 KB	1.00
Sep_MT___	Asset	50000	36.01 ms	0.56	33	926.9	720.2	14020.14 KB	1.02
Sylvan___	Asset	50000	96.43 ms	1.50	33	346.1	1928.5	13962.36 KB	1.01
ReadLine_	Asset	50000	198.74 ms	3.10	33	167.9	3974.7	122304.04 KB	8.86
CsvHelper	Asset	50000	179.60 ms	2.79	33	185.8	3591.9	13970.63 KB	1.01
Sep______	Asset	1000000	1,325.26 ms	1.00	667	503.8	1325.3	266667.79 KB	1.00
Sep_MT___	Asset	1000000	573.47 ms	0.45	667	1164.3	573.5	267685.55 KB	1.00
Sylvan___	Asset	1000000	1,983.93 ms	1.50	667	336.6	1983.9	266834.56 KB	1.00
ReadLine_	Asset	1000000	3,804.46 ms	2.87	667	175.5	3804.5	2442323.66 KB	9.16
CsvHelper	Asset	1000000	3,767.71 ms	2.84	667	177.2	3767.7	266840.59 KB	1.00

Neoverse.N1 - PackageAssets with Quotes Benchmark Results (Sep 0.4.0.0, Sylvan 1.3.5.0, CsvHelper 30.0.1.0)

Method	Scope	Rows	Mean	Ratio	MB	MB/s	ns/row	Allocated	Alloc Ratio
Sep______	Row	50000	25.14 ms	1.00	33	1323.9	502.8	1.04 KB	1.00
Sep_Unescape	Row	50000	24.79 ms	0.99	33	1342.6	495.8	1.04 KB	1.00
Sylvan___	Row	50000	39.92 ms	1.59	33	833.7	798.4	6.14 KB	5.88
ReadLine_	Row	50000	44.29 ms	1.76	33	751.5	885.8	108778.83 KB	104,199.74
CsvHelper	Row	50000	106.65 ms	4.24	33	312.1	2133.0	20.77 KB	19.90
Sep______	Cols	50000	27.56 ms	1.00	33	1207.5	551.3	1.06 KB	1.00
Sep_Unescape	Cols	50000	29.35 ms	1.06	33	1133.8	587.1	1.06 KB	1.00
Sylvan___	Cols	50000	45.55 ms	1.65	33	730.7	911.0	6.17 KB	5.82
ReadLine_	Cols	50000	45.78 ms	1.66	33	727.1	915.5	108778.83 KB	102,663.15
CsvHelper	Cols	50000	152.23 ms	5.52	33	218.6	3044.5	446.61 KB	421.50
Sep______	Asset	50000	80.29 ms	1.00	33	414.5	1605.8	13804.89 KB	1.00
Sep_MT___	Asset	50000	49.12 ms	0.61	33	677.5	982.4	13858.29 KB	1.00
Sylvan___	Asset	50000	110.68 ms	1.38	33	300.7	2213.6	13961.37 KB	1.01
ReadLine_	Asset	50000	196.34 ms	2.44	33	169.5	3926.7	122305.09 KB	8.86
CsvHelper	Asset	50000	180.62 ms	2.24	33	184.3	3612.4	13974.57 KB	1.01
Sep______	Asset	1000000	1,619.19 ms	1.00	665	411.2	1619.2	266671.09 KB	1.00
Sep_MT___	Asset	1000000	830.09 ms	0.52	665	802.1	830.1	269668.23 KB	1.01
Sylvan___	Asset	1000000	2,185.17 ms	1.35	665	304.7	2185.2	266828.83 KB	1.00
ReadLine_	Asset	1000000	3,986.74 ms	2.46	665	167.0	3986.7	2442318.74 KB	9.16
CsvHelper	Asset	1000000	3,682.98 ms	2.27	665	180.8	3683.0	266841.98 KB	1.00

PackageAssets with Quotes Benchmark Results (SERVER GC)

Here again are benchmark results with server garbage collection, which provides significant speedup over workstation garbage collection.

AMD.Ryzen.9.5950X - PackageAssets with Quotes Benchmark Results (SERVER GC) (Sep 0.4.6.0, Sylvan 1.3.7.0, CsvHelper 31.0.2.15)

Method	Scope	Rows	Mean	Ratio	MB	MB/s	ns/row	Allocated	Alloc Ratio
Sep______	Asset	50000	25.84 ms	1.00	33	1291.8	516.7	13.48 MB	1.00
Sep_MT___	Asset	50000	10.97 ms	0.42	33	3041.8	219.5	13.64 MB	1.01
Sylvan___	Asset	50000	45.45 ms	1.70	33	734.3	909.1	13.63 MB	1.01
ReadLine_	Asset	50000	40.09 ms	1.59	33	832.6	801.7	119.44 MB	8.86
CsvHelper	Asset	50000	92.69 ms	3.59	33	360.1	1853.8	13.64 MB	1.01
Sep______	Asset	1000000	546.80 ms	1.00	667	1221.1	546.8	260.41 MB	1.00
Sep_MT___	Asset	1000000	212.94 ms	0.39	667	3135.7	212.9	261.47 MB	1.00
Sylvan___	Asset	1000000	960.19 ms	1.75	667	695.4	960.2	260.57 MB	1.00
ReadLine_	Asset	1000000	678.16 ms	1.24	667	984.6	678.2	2385.07 MB	9.16
CsvHelper	Asset	1000000	1,900.80 ms	3.47	667	351.3	1900.8	260.58 MB	1.00

Intel.Xeon.Silver.4316.2.30GHz - PackageAssets with Quotes Benchmark Results (SERVER GC) (Sep 0.4.0.0, Sylvan 1.3.5.0, CsvHelper 30.0.1.0)

Method	Scope	Rows	Mean	Ratio	RatioSD	MB	MB/s	ns/row	Allocated	Alloc Ratio
Sep______	Asset	50000	52.58 ms	1.00	0.00	33	634.7	1051.7	13.48 MB	1.00
Sep_MT___	Asset	50000	17.79 ms	0.34	0.00	33	1875.9	355.9	13.67 MB	1.01
Sylvan___	Asset	50000	86.54 ms	1.65	0.01	33	385.7	1730.8	13.63 MB	1.01
ReadLine_	Asset	50000	55.36 ms	1.05	0.01	33	602.9	1107.1	119.44 MB	8.86
CsvHelper	Asset	50000	176.28 ms	3.35	0.02	33	189.3	3525.6	13.64 MB	1.01
Sep______	Asset	1000000	1,043.85 ms	1.00	0.00	667	639.7	1043.9	260.41 MB	1.00
Sep_MT___	Asset	1000000	336.86 ms	0.32	0.00	667	1982.1	336.9	261.35 MB	1.00
Sylvan___	Asset	1000000	1,697.87 ms	1.63	0.00	667	393.3	1697.9	260.57 MB	1.00
ReadLine_	Asset	1000000	1,177.60 ms	1.13	0.00	667	567.0	1177.6	2385.07 MB	9.16
CsvHelper	Asset	1000000	3,478.19 ms	3.33	0.01	667	192.0	3478.2	260.58 MB	1.00

Neoverse.N1 - PackageAssets with Quotes Benchmark Results (SERVER GC) (Sep 0.4.0.0, Sylvan 1.3.5.0, CsvHelper 30.0.1.0)

Method	Scope	Rows	Mean	Ratio	RatioSD	MB	MB/s	ns/row	Allocated	Alloc Ratio
Sep______	Asset	50000	70.05 ms	1.00	0.00	33	475.1	1400.9	13.48 MB	1.00
Sep_MT___	Asset	50000	32.78 ms	0.47	0.02	33	1015.2	655.7	13.53 MB	1.00
Sylvan___	Asset	50000	98.67 ms	1.41	0.06	33	337.3	1973.5	13.63 MB	1.01
ReadLine_	Asset	50000	79.84 ms	1.14	0.08	33	416.8	1596.9	119.44 MB	8.86
CsvHelper	Asset	50000	173.86 ms	2.48	0.09	33	191.4	3477.2	13.64 MB	1.01
Sep______	Asset	1000000	1,382.02 ms	1.00	0.00	665	481.8	1382.0	260.41 MB	1.00
Sep_MT___	Asset	1000000	589.55 ms	0.43	0.00	665	1129.3	589.6	260.97 MB	1.00
Sylvan___	Asset	1000000	1,962.01 ms	1.42	0.00	665	339.3	1962.0	260.57 MB	1.00
ReadLine_	Asset	1000000	1,744.55 ms	1.26	0.01	665	381.6	1744.6	2385.08 MB	9.16
CsvHelper	Asset	1000000	3,454.73 ms	2.50	0.01	665	192.7	3454.7	260.58 MB	1.00

Floats Reader Comparison Benchmarks

The FloatsReaderBench.cs benchmark demonstrates what Sep is built for. Namely parsing 32-bit floating points or features as in machine learning. Here a simple CSV-file is randomly generated with N ground truth values, N predicted result values and nothing else (note this was changed from version 0.3.0, prior to that there were some extra leading columns). N = 20 here. For example:

GT_Feature0;GT_Feature1;GT_Feature2;GT_Feature3;GT_Feature4;GT_Feature5;GT_Feature6;GT_Feature7;GT_Feature8;GT_Feature9;GT_Feature10;GT_Feature11;GT_Feature12;GT_Feature13;GT_Feature14;GT_Feature15;GT_Feature16;GT_Feature17;GT_Feature18;GT_Feature19;RE_Feature0;RE_Feature1;RE_Feature2;RE_Feature3;RE_Feature4;RE_Feature5;RE_Feature6;RE_Feature7;RE_Feature8;RE_Feature9;RE_Feature10;RE_Feature11;RE_Feature12;RE_Feature13;RE_Feature14;RE_Feature15;RE_Feature16;RE_Feature17;RE_Feature18;RE_Feature19
0.52276427;0.16843422;0.26259267;0.7244084;0.51292276;0.17365117;0.76125056;0.23458846;0.2573214;0.50560355;0.3202332;0.3809696;0.26024464;0.5174511;0.035318818;0.8141374;0.57719684;0.3974705;0.15219308;0.09011261;0.70515215;0.81618196;0.5399706;0.044147138;0.7111546;0.14776127;0.90621275;0.6925897;0.5164137;0.18637845;0.041509967;0.30819967;0.5831603;0.8210651;0.003954861;0.535722;0.8051845;0.7483589;0.3845737;0.14911908
0.6264564;0.11517637;0.24996082;0.77242833;0.2896067;0.6481459;0.14364648;0.044498358;0.6045593;0.51591337;0.050794687;0.42036617;0.7065823;0.6284636;0.21844554;0.013253775;0.36516154;0.2674384;0.06866083;0.71817476;0.07094294;0.46409357;0.012033525;0.7978093;0.43917948;0.5134962;0.4995968;0.008952909;0.82883793;0.012896823;0.0030740085;0.063773096;0.6541431;0.034539033;0.9135142;0.92897075;0.46119377;0.37533295;0.61660606;0.044443816
0.7922863;0.5323656;0.400699;0.29737252;0.9072584;0.58673894;0.73510516;0.019412167;0.88168067;0.9576787;0.33283427;0.7107;0.1623628;0.10314285;0.4521515;0.33324885;0.7761104;0.14854911;0.13469358;0.21566042;0.59166247;0.5128394;0.98702157;0.766223;0.67204326;0.7149494;0.2894748;0.55206;0.9898286;0.65083236;0.02421702;0.34540752;0.92906284;0.027142895;0.21974725;0.26544374;0.03848049;0.2161237;0.59233844;0.42221397
0.10609442;0.32130885;0.32383907;0.7511514;0.8258279;0.00904226;0.0420841;0.84049565;0.8958947;0.23807365;0.92621964;0.8452882;0.2794469;0.545344;0.63447595;0.62532926;0.19230893;0.29726416;0.18304513;0.029583583;0.23084833;0.93346167;0.98742676;0.78163713;0.13521992;0.8833956;0.18670778;0.29476836;0.5599867;0.5562107;0.7124796;0.121927656;0.5981778;0.39144602;0.88092715;0.4449142;0.34820423;0.96379805;0.46364686;0.54301775

For Scope=Floats the benchmark will parse the features as two spans of floats; one for ground truth values and one for predicted result values. Then calculates the mean squared error (MSE) of those as an example. For Sep this code is succinct and still incredibly efficient:

using var reader = Sep.Reader().From(Reader.CreateReader());

var groundTruthColNames = reader.Header.NamesStartingWith("GT_");
var resultColNames = groundTruthColNames.Select(n =>
    n.Replace("GT_", "RE_", StringComparison.Ordinal))
    .ToArray();

var sum = 0.0;
var count = 0;
foreach (var row in reader)
{
    var gts = row[groundTruthColNames].Parse<float>();
    var res = row[resultColNames].Parse<float>();

    sum += MeanSquaredError(gts, res);
    ++count;
}
return sum / count;

Note how one can access and parse multiple columns easily while there are no repeated allocations for the parsed floating points. Sep internally handles a pool of arrays for handling multiple columns and returns spans for them.

The benchmark is based on an assumption of accessing columns by name per row. Ideally, one would look up the indices of the columns by name before enumerating rows, but this is a repeated nuisance to have to handle and Sep was built to avoid this. Hence, the comparison is based on looking up by name for each, even if this ends up adding a bit more code in the benchmark for other approaches.

As can be seen below, the actual low level parsing of the separated values is a tiny part of the total runtime for Sep for which the runtime is dominated by parsing the floating points. Since Sep uses csFastFloat for an integrated fast floating point parser, it is >2x faster than Sylvan for example. If using Sylvan one may consider using csFastFloat if that is an option. With the multi-threaded (MT) ParallelEnumerate implementation Sep is up to 23x faster than Sylvan.

CsvHelper suffers from the fact that one can only access the column as a string so this has to be allocated for each column (ReadLine by definition always allocates a string per column). Still CsvHelper is significantly slower than the naive ReadLine approach. With Sep being >4x faster than CsvHelper and up to 35x times faster when using ParallelEnumerate.

Note that ParallelEnumerate provides significant speedup over single-threaded parsing even though the source is only about 20 MB. This underlines how efficient ParallelEnumerate is, but bear in mind that this is for the case of repeated micro-benchmark runs.

It is a testament to how good the .NET and the .NET GC is that the ReadLine is pretty good compared to CsvHelper regardless of allocating a lot of strings.

AMD.Ryzen.9.5950X - FloatsReader Benchmark Results (Sep 0.4.6.0, Sylvan 1.3.7.0, CsvHelper 31.0.2.15)

Method	Scope	Rows	Mean	Ratio	MB	MB/s	ns/row	Allocated	Alloc Ratio
Sep______	Row	25000	2.061 ms	1.00	20	9857.0	82.5	1.25 KB	1.00
Sylvan___	Row	25000	2.448 ms	1.19	20	8299.1	97.9	10.02 KB	8.02
ReadLine_	Row	25000	11.663 ms	5.66	20	1742.2	466.5	73489.64 KB	58,791.71
CsvHelper	Row	25000	26.409 ms	12.82	20	769.4	1056.3	20 KB	16.00
Sep______	Cols	25000	2.696 ms	1.00	20	7537.1	107.8	1.25 KB	1.00
Sylvan___	Cols	25000	4.017 ms	1.49	20	5058.7	160.7	10.02 KB	8.00
ReadLine_	Cols	25000	11.638 ms	4.33	20	1746.0	465.5	73489.64 KB	58,654.24
CsvHelper	Cols	25000	27.323 ms	10.14	20	743.7	1092.9	21340.22 KB	17,032.26
Sep______	Floats	25000	22.268 ms	1.00	20	912.5	890.7	8 KB	1.00
Sep_MT___	Floats	25000	3.396 ms	0.15	20	5983.3	135.8	182.55 KB	22.83
Sylvan___	Floats	25000	66.977 ms	3.01	20	303.4	2679.1	18.2 KB	2.28
ReadLine_	Floats	25000	72.970 ms	3.27	20	278.5	2918.8	73493.12 KB	9,190.01
CsvHelper	Floats	25000	105.666 ms	4.75	20	192.3	4226.6	22061.92 KB	2,758.75

Intel.Xeon.Silver.4316.2.30GHz - FloatsReader Benchmark Results (Sep 0.4.0.0, Sylvan 1.3.5.0, CsvHelper 30.0.1.0)

Method	Scope	Rows	Mean	Ratio	MB	MB/s	ns/row	Allocated	Alloc Ratio
Sep______	Row	25000	4.012 ms	1.00	20	5064.2	160.5	1.41 KB	1.00
Sylvan___	Row	25000	4.607 ms	1.15	20	4410.6	184.3	10.02 KB	7.11
ReadLine_	Row	25000	21.873 ms	5.46	20	929.0	874.9	73489.67 KB	52,114.56
CsvHelper	Row	25000	57.624 ms	14.36	20	352.6	2305.0	20.77 KB	14.73
Sep______	Cols	25000	5.841 ms	1.00	20	3478.9	233.6	1.42 KB	1.00
Sylvan___	Cols	25000	7.398 ms	1.27	20	2746.5	295.9	10.03 KB	7.06
ReadLine_	Cols	25000	21.529 ms	3.69	20	943.8	861.2	73489.67 KB	51,756.14
CsvHelper	Cols	25000	60.610 ms	10.38	20	335.3	2424.4	21340.82 KB	15,029.57
Sep______	Floats	25000	43.612 ms	1.00	20	465.9	1744.5	8.22 KB	1.00
Sep_MT___	Floats	25000	6.159 ms	0.14	20	3299.0	246.4	213.54 KB	25.96
Sylvan___	Floats	25000	142.246 ms	3.26	20	142.8	5689.8	18.43 KB	2.24
ReadLine_	Floats	25000	155.347 ms	3.56	20	130.8	6213.9	73493.3 KB	8,935.78
CsvHelper	Floats	25000	215.336 ms	4.94	20	94.4	8613.4	22062.78 KB	2,682.53

Neoverse.N1 - FloatsReader Benchmark Results (Sep 0.4.0.0, Sylvan 1.3.5.0, CsvHelper 30.0.1.0)

Method	Scope	Rows	Mean	Ratio	MB	MB/s	ns/row	Allocated	Alloc Ratio
Sep______	Row	25000	9.537 ms	1.00	20	2125.7	381.5	1.21 KB	1.00
Sylvan___	Row	25000	30.832 ms	3.23	20	657.5	1233.3	9.74 KB	8.02
ReadLine_	Row	25000	33.938 ms	3.56	20	597.3	1357.5	73489.73 KB	60,493.16
CsvHelper	Row	25000	59.210 ms	6.21	20	342.4	2368.4	20.71 KB	17.04
Sep______	Cols	25000	11.460 ms	1.00	20	1768.9	458.4	1.23 KB	1.00
Sylvan___	Cols	25000	34.857 ms	3.04	20	581.6	1394.3	9.75 KB	7.91
ReadLine_	Cols	25000	35.410 ms	3.09	20	572.5	1416.4	73489.72 KB	59,630.33
CsvHelper	Cols	25000	64.828 ms	5.65	20	312.7	2593.1	21341.07 KB	17,316.37
Sep______	Floats	25000	52.297 ms	1.00	20	387.6	2091.9	8.12 KB	1.00
Sep_MT___	Floats	25000	15.271 ms	0.29	20	1327.5	610.9	65.28 KB	8.04
Sylvan___	Floats	25000	168.664 ms	3.23	20	120.2	6746.6	18.2 KB	2.24
ReadLine_	Floats	25000	166.356 ms	3.18	20	121.9	6654.3	73493.46 KB	9,052.97
CsvHelper	Floats	25000	218.131 ms	4.17	20	92.9	8725.2	22063.34 KB	2,717.78

Writer Comparison Benchmarks

Writer benchmarks are still pending, but Sep is unlikely to be the fastest here since it is explicitly designed to make writing more convenient and flexible. Still efficient, but not necessarily fastest. That is, Sep does not require writing header up front and hence having to keep header column order and row values column order the same. This means Sep does not write columns directly upon definition but defers this until a new row has been fully defined and then is ended.

Example Catalogue

The following examples are available in ReadMeTest.cs.

Example - Copy Rows

var text = """
           A;B;C;D;E;F
           Sep;🚀;1;1.2;0.1;0.5
           CSV;✅;2;2.2;0.2;1.5
           
           """; // Empty line at end is for line ending

using var reader = Sep.Reader().FromText(text);
using var writer = reader.Spec.Writer().ToText();
foreach (var readRow in reader)
{
    using var writeRow = writer.NewRow(readRow);
}
Assert.AreEqual(text, writer.ToString());

Example - Skip Empty Rows

var text = """
           A
           1
           2

           3


           4
           
           """; // Empty line at end is for line ending
var expected = new[] { 1, 2, 3, 4 };

// Disable col count check to allow empty rows
using var reader = Sep.Reader(o => o with { DisableColCountCheck = true }).FromText(text);
var actual = new List<int>();
foreach (var row in reader)
{
    // Skip empty row
    if (row.Span.Length == 0) { continue; }

    actual.Add(row["A"].Parse<int>());
}
CollectionAssert.AreEqual(expected, actual);

Example - Use Extension Method Enumerate within async/await Context

Since SepReader.Row is a ref struct as covered above, one has to avoid referencing it directly in async context. This can be done in a number of ways, but one way is to use Enumerate extension method to parse/extract data from row like shown below.

var text = """
           C
           1
           2
           """;

using var reader = Sep.Reader().FromText(text);
var squaredSum = 0;
// Use Enumerate to avoid referencing SepReader.Row in async context
foreach (var value in reader.Enumerate(row => row["C"].Parse<int>()))
{
    squaredSum += await Task.Run(() => value * value);
}
Assert.AreEqual(5, squaredSum);

Example - Use Local Function within async/await Context

Another way to avoid referencing SepReader.Row directly in async context is to use custom iterator via yield return to parse/extract data from row like shown below.

var text = """
           C
           1
           2
           """;

using var reader = Sep.Reader().FromText(text);
var squaredSum = 0;
// Use custom local function Enumerate to avoid referencing
// SepReader.Row in async context
foreach (var value in Enumerate(reader))
{
    squaredSum += await Task.Run(() => value * value);
}
Assert.AreEqual(5, squaredSum);

static IEnumerable<int> Enumerate(SepReader reader)
{
    foreach (var r in reader) { yield return r["C"].Parse<int>(); }
}

RFC-4180

While the RFC-4180 requires \r\n (CR,LF) as line ending, the well-known line endings (\r\n, \n and \r) are supported similar to .NET. Environment.NewLine is used when writing. Quoting is supported by simply matching pairs of quotes, no matter what.

Note that some libraries will claim conformance but the RFC is, perhaps naturally, quite strict e.g. only comma is supported as separator/delimiter. Sep defaults to using ; as separator if writing, while auto-detecting supported separators when reading. This is decidedly non-conforming.

The RFC defines the following condensed ABNF grammar:

file = [header CRLF] record *(CRLF record) [CRLF]
header = name *(COMMA name)
record = field *(COMMA field)
name = field
field = (escaped / non-escaped)
escaped = DQUOTE *(TEXTDATA / COMMA / CR / LF / 2DQUOTE) DQUOTE
non-escaped = *TEXTDATA
COMMA = %x2C
CR = %x0D ;as per section 6.1 of RFC 2234 [2]
DQUOTE =  %x22 ;as per section 6.1 of RFC 2234 [2]
LF = %x0A ;as per section 6.1 of RFC 2234 [2]
CRLF = CR LF ;as per section 6.1 of RFC 2234 [2]
TEXTDATA =  %x20-21 / %x23-2B / %x2D-7E

Note how TEXTDATA is restricted too, yet many will allow any character incl. emojis or similar (which Sep supports), but is not in conformance with the RFC.

Quotes inside an escaped field e.g. "fie""ld" are only allowed to be double quotes. Sep currently allows any pairs of quotes and quoting doesn't need to be at start of or end of field (col or column in Sep terminology).

All in all Sep takes a pretty pragmatic approach here as the primary use case is not exchanging data on the internet, but for use in machine learning pipelines or similar.

Frequently Asked Questions (FAQ)

Ask questions on GitHub and this section will be expanded. :)

• Does Sep support object mapping like CsvHelper? No, Sep is a minimal library and does not support object mapping. First, this is usually supported via reflection, which Sep avoids. Second, object mapping often only works well in a few cases without actually writing custom mapping for each property, which then basically amounts to writing the parsing code yourself. If object mapping is a must have, consider writing your own source generator for it if you want to use Sep. Maybe some day Sep will have a built-in source generator, but not in the foreseeable future.

SepReader FAQ

SepWriter FAQ

Links

• Publishing a NuGet package using GitHub and GitHub Actions

Public API Reference

[assembly: System.CLSCompliant(false)]
[assembly: System.Reflection.AssemblyMetadata("IsTrimmable", "True")]
[assembly: System.Reflection.AssemblyMetadata("RepositoryUrl", "https://github.com/nietras/Sep/")]
[assembly: System.Resources.NeutralResourcesLanguage("en")]
[assembly: System.Runtime.CompilerServices.InternalsVisibleTo("Sep.Benchmarks")]
[assembly: System.Runtime.CompilerServices.InternalsVisibleTo("Sep.ComparisonBenchmarks")]
[assembly: System.Runtime.CompilerServices.InternalsVisibleTo("Sep.Test")]
[assembly: System.Runtime.Versioning.TargetFramework(".NETCoreApp,Version=v8.0", FrameworkDisplayName=".NET 8.0")]
namespace nietras.SeparatedValues
{
    public readonly struct Sep : System.IEquatable<nietras.SeparatedValues.Sep>
    {
        public Sep() { }
        public Sep(char separator) { }
        public char Separator { get; init; }
        public static nietras.SeparatedValues.Sep? Auto { get; }
        public static nietras.SeparatedValues.Sep Default { get; }
        public static nietras.SeparatedValues.Sep New(char separator) { }
        public static nietras.SeparatedValues.SepReaderOptions Reader() { }
        public static nietras.SeparatedValues.SepReaderOptions Reader(System.Func<nietras.SeparatedValues.SepReaderOptions, nietras.SeparatedValues.SepReaderOptions> configure) { }
        public static nietras.SeparatedValues.SepWriterOptions Writer() { }
        public static nietras.SeparatedValues.SepWriterOptions Writer(System.Func<nietras.SeparatedValues.SepWriterOptions, nietras.SeparatedValues.SepWriterOptions> configure) { }
    }
    public delegate nietras.SeparatedValues.SepToString SepCreateToString(nietras.SeparatedValues.SepReaderHeader? maybeHeader, int colCount);
    public static class SepDefaults
    {
        public static System.StringComparer ColNameComparer { get; }
        public static System.Globalization.CultureInfo CultureInfo { get; }
        public static char Separator { get; }
    }
    [System.Diagnostics.DebuggerDisplay("{DebuggerDisplay,nq}")]
    public sealed class SepReader : nietras.SeparatedValues.SepReaderState
    {
        public nietras.SeparatedValues.SepReader.Row Current { get; }
        public bool HasHeader { get; }
        public bool HasRows { get; }
        public nietras.SeparatedValues.SepReaderHeader Header { get; }
        public bool IsEmpty { get; }
        public nietras.SeparatedValues.SepSpec Spec { get; }
        public nietras.SeparatedValues.SepReader GetEnumerator() { }
        public bool MoveNext() { }
        public string ToString(int index) { }
        [System.Diagnostics.DebuggerDisplay("{DebuggerDisplay}")]
        [System.Obsolete("Types with embedded references are not supported in this version of your compiler" +
            ".", true)]
        [System.Runtime.CompilerServices.CompilerFeatureRequired("RefStructs")]
        [System.Runtime.CompilerServices.IsByRefLike]
        public readonly struct Col
        {
            public System.ReadOnlySpan<char> Span { get; }
            public T Parse<T>()
                where T : System.ISpanParsable<T> { }
            public override string ToString() { }
            public T? TryParse<T>()
                where T :  struct, System.ISpanParsable<T> { }
            public bool TryParse<T>(out T value)
                where T : System.ISpanParsable<T> { }
        }
        [System.Obsolete("Types with embedded references are not supported in this version of your compiler" +
            ".", true)]
        [System.Runtime.CompilerServices.CompilerFeatureRequired("RefStructs")]
        [System.Runtime.CompilerServices.IsByRefLike]
        public readonly struct Cols
        {
            public int Count { get; }
            public nietras.SeparatedValues.SepReader.Col this[int index] { get; }
            public System.Span<T> Parse<T>()
                where T : System.ISpanParsable<T> { }
            public void Parse<T>(System.Span<T> span)
                where T : System.ISpanParsable<T> { }
            public T[] ParseToArray<T>()
                where T : System.ISpanParsable<T> { }
            public System.Span<T> Select<T>(method selector) { }
            public System.Span<T> Select<T>(nietras.SeparatedValues.SepReader.ColFunc<T> selector) { }
            public System.Span<string> ToStrings() { }
            public string[] ToStringsArray() { }
            public System.Span<T?> TryParse<T>()
                where T :  struct, System.ISpanParsable<T> { }
            public void TryParse<T>(System.Span<T?> span)
                where T :  struct, System.ISpanParsable<T> { }
        }
        [System.Diagnostics.DebuggerDisplay("{DebuggerDisplayPrefix,nq}{Span}")]
        [System.Diagnostics.DebuggerTypeProxy(typeof(nietras.SeparatedValues.SepReader.Row.DebugView))]
        [System.Obsolete("Types with embedded references are not supported in this version of your compiler" +
            ".", true)]
        [System.Runtime.CompilerServices.CompilerFeatureRequired("RefStructs")]
        [System.Runtime.CompilerServices.IsByRefLike]
        public readonly struct Row
        {
            public int ColCount { get; }
            public nietras.SeparatedValues.SepReader.Col this[int index] { get; }
            public nietras.SeparatedValues.SepReader.Col this[System.Index index] { get; }
            public nietras.SeparatedValues.SepReader.Col this[string colName] { get; }
            public nietras.SeparatedValues.SepReader.Cols this[System.Range range] { get; }
            public nietras.SeparatedValues.SepReader.Cols this[System.ReadOnlySpan<int> indices] { get; }
            public nietras.SeparatedValues.SepReader.Cols this[System.Collections.Generic.IReadOnlyList<int> indices] { get; }
            public nietras.SeparatedValues.SepReader.Cols this[int[] indices] { get; }
            public nietras.SeparatedValues.SepReader.Cols this[System.ReadOnlySpan<string> colNames] { get; }
            public nietras.SeparatedValues.SepReader.Cols this[System.Collections.Generic.IReadOnlyList<string> colNames] { get; }
            public nietras.SeparatedValues.SepReader.Cols this[string[] colNames] { get; }
            public int LineNumberFrom { get; }
            public int LineNumberToExcl { get; }
            public int RowIndex { get; }
            public System.ReadOnlySpan<char> Span { get; }
            public System.Func<int, string> UnsafeToStringDelegate { get; }
            public override string ToString() { }
        }
        public delegate void ColAction(nietras.SeparatedValues.SepReader.Col col);
        public delegate T ColFunc<T>(nietras.SeparatedValues.SepReader.Col col);
        public delegate void ColsAction(nietras.SeparatedValues.SepReader.Cols col);
        public delegate void RowAction(nietras.SeparatedValues.SepReader.Row row);
        public delegate T RowFunc<T>(nietras.SeparatedValues.SepReader.Row row);
        public delegate bool RowTryFunc<T>(nietras.SeparatedValues.SepReader.Row row, out T value);
    }
    public static class SepReaderExtensions
    {
        public static System.Collections.Generic.IEnumerable<T> Enumerate<T>(this nietras.SeparatedValues.SepReader reader, nietras.SeparatedValues.SepReader.RowFunc<T> select) { }
        public static System.Collections.Generic.IEnumerable<T> Enumerate<T>(this nietras.SeparatedValues.SepReader reader, nietras.SeparatedValues.SepReader.RowTryFunc<T> trySelect) { }
        public static nietras.SeparatedValues.SepReader From(this nietras.SeparatedValues.SepReaderOptions options, byte[] buffer) { }
        public static nietras.SeparatedValues.SepReader From(this nietras.SeparatedValues.SepReaderOptions options, System.IO.Stream stream) { }
        public static nietras.SeparatedValues.SepReader From(this nietras.SeparatedValues.SepReaderOptions options, System.IO.TextReader reader) { }
        public static nietras.SeparatedValues.SepReader From(this nietras.SeparatedValues.SepReaderOptions options, string name, System.Func<string, System.IO.Stream> nameToStream) { }
        public static nietras.SeparatedValues.SepReader From(this nietras.SeparatedValues.SepReaderOptions options, string name, System.Func<string, System.IO.TextReader> nameToReader) { }
        public static nietras.SeparatedValues.SepReader FromFile(this nietras.SeparatedValues.SepReaderOptions options, string filePath) { }
        public static nietras.SeparatedValues.SepReader FromText(this nietras.SeparatedValues.SepReaderOptions options, string text) { }
        public static System.Collections.Generic.IEnumerable<T> ParallelEnumerate<T>(this nietras.SeparatedValues.SepReader reader, nietras.SeparatedValues.SepReader.RowFunc<T> select) { }
        public static System.Collections.Generic.IEnumerable<T> ParallelEnumerate<T>(this nietras.SeparatedValues.SepReader reader, nietras.SeparatedValues.SepReader.RowTryFunc<T> trySelect) { }
        public static System.Collections.Generic.IEnumerable<T> ParallelEnumerate<T>(this nietras.SeparatedValues.SepReader reader, nietras.SeparatedValues.SepReader.RowFunc<T> select, int degreeOfParallism) { }
        public static System.Collections.Generic.IEnumerable<T> ParallelEnumerate<T>(this nietras.SeparatedValues.SepReader reader, nietras.SeparatedValues.SepReader.RowTryFunc<T> trySelect, int degreeOfParallism) { }
        public static nietras.SeparatedValues.SepReaderOptions Reader(this nietras.SeparatedValues.Sep sep) { }
        public static nietras.SeparatedValues.SepReaderOptions Reader(this nietras.SeparatedValues.Sep? sep) { }
        public static nietras.SeparatedValues.SepReaderOptions Reader(this nietras.SeparatedValues.SepSpec spec) { }
        public static nietras.SeparatedValues.SepReaderOptions Reader(this nietras.SeparatedValues.Sep sep, System.Func<nietras.SeparatedValues.SepReaderOptions, nietras.SeparatedValues.SepReaderOptions> configure) { }
        public static nietras.SeparatedValues.SepReaderOptions Reader(this nietras.SeparatedValues.Sep? sep, System.Func<nietras.SeparatedValues.SepReaderOptions, nietras.SeparatedValues.SepReaderOptions> configure) { }
        public static nietras.SeparatedValues.SepReaderOptions Reader(this nietras.SeparatedValues.SepSpec spec, System.Func<nietras.SeparatedValues.SepReaderOptions, nietras.SeparatedValues.SepReaderOptions> configure) { }
    }
    public sealed class SepReaderHeader
    {
        public System.Collections.Generic.IReadOnlyList<string> ColNames { get; }
        public bool IsEmpty { get; }
        public static nietras.SeparatedValues.SepReaderHeader Empty { get; }
        public int IndexOf(string colName) { }
        public int[] IndicesOf(System.Collections.Generic.IReadOnlyList<string> colNames) { }
        public int[] IndicesOf(System.ReadOnlySpan<string> colNames) { }
        public int[] IndicesOf(params string[] colNames) { }
        public void IndicesOf(System.ReadOnlySpan<string> colNames, System.Span<int> colIndices) { }
        public System.Collections.Generic.IReadOnlyList<string> NamesStartingWith(string prefix, System.StringComparison comparison = 4) { }
        public override string ToString() { }
        public bool TryIndexOf(string colName, out int colIndex) { }
    }
    public readonly struct SepReaderOptions : System.IEquatable<nietras.SeparatedValues.SepReaderOptions>
    {
        public SepReaderOptions() { }
        public SepReaderOptions(nietras.SeparatedValues.Sep? sep) { }
        public System.Collections.Generic.IEqualityComparer<string> ColNameComparer { get; init; }
        public nietras.SeparatedValues.SepCreateToString CreateToString { get; init; }
        public System.Globalization.CultureInfo? CultureInfo { get; init; }
        public bool DisableColCountCheck { get; init; }
        public bool DisableFastFloat { get; init; }
        public bool DisableQuotesParsing { get; init; }
        public bool HasHeader { get; init; }
        public nietras.SeparatedValues.Sep? Sep { get; init; }
        public bool Unescape { get; init; }
    }
    public class SepReaderState : System.IDisposable
    {
        public void Dispose() { }
    }
    public static class SepReaderWriterExtensions
    {
        public static void CopyTo(this nietras.SeparatedValues.SepReader.Row readerRow, nietras.SeparatedValues.SepWriter.Row writerRow) { }
        public static nietras.SeparatedValues.SepWriter.Row NewRow(this nietras.SeparatedValues.SepWriter writer, nietras.SeparatedValues.SepReader.Row rowToCopy) { }
    }
    public readonly struct SepSpec : System.IEquatable<nietras.SeparatedValues.SepSpec>
    {
        public SepSpec() { }
        public SepSpec(nietras.SeparatedValues.Sep sep, System.Globalization.CultureInfo? cultureInfo) { }
        public System.Globalization.CultureInfo? CultureInfo { get; init; }
        public nietras.SeparatedValues.Sep Sep { get; init; }
    }
    public abstract class SepToString : System.IDisposable
    {
        protected SepToString() { }
        public virtual bool IsThreadSafe { get; }
        public static nietras.SeparatedValues.SepCreateToString Direct { get; }
        public void Dispose() { }
        protected virtual void Dispose(bool disposing) { }
        public abstract string ToString(System.ReadOnlySpan<char> colSpan, int colIndex);
        public static nietras.SeparatedValues.SepCreateToString OnePool(int maximumStringLength = 32, int initialCapacity = 64, int maximumCapacity = 4096) { }
        public static nietras.SeparatedValues.SepCreateToString PoolPerCol(int maximumStringLength = 32, int initialCapacity = 64, int maximumCapacity = 4096) { }
        public static nietras.SeparatedValues.SepCreateToString PoolPerColThreadSafe(int maximumStringLength = 32, int initialCapacity = 64, int maximumCapacity = 4096) { }
        public static nietras.SeparatedValues.SepCreateToString PoolPerColThreadSafeFixedCapacity(int maximumStringLength = 32, int capacity = 2048) { }
    }
    public sealed class SepWriter : System.IDisposable
    {
        public nietras.SeparatedValues.SepWriterHeader Header { get; }
        public nietras.SeparatedValues.SepSpec Spec { get; }
        public void Dispose() { }
        public void Flush() { }
        public nietras.SeparatedValues.SepWriter.Row NewRow() { }
        public override string ToString() { }
        [System.Obsolete("Types with embedded references are not supported in this version of your compiler" +
            ".", true)]
        [System.Runtime.CompilerServices.CompilerFeatureRequired("RefStructs")]
        [System.Runtime.CompilerServices.IsByRefLike]
        public struct Row
        {
            public nietras.SeparatedValues.SepWriter.Col this[int colIndex] { get; }
            public nietras.SeparatedValues.SepWriter.Col this[string colName] { get; }
            public nietras.SeparatedValues.SepWriter.Cols this[System.ReadOnlySpan<int> indices] { get; }
            public nietras.SeparatedValues.SepWriter.Cols this[System.ReadOnlySpan<string> colNames] { get; }
            public nietras.SeparatedValues.SepWriter.Cols this[System.Collections.Generic.IReadOnlyList<string> colNames] { get; }
            public nietras.SeparatedValues.SepWriter.Cols this[string[] colNames] { get; }
            public void Dispose() { }
        }
        [System.Obsolete("Types with embedded references are not supported in this version of your compiler" +
            ".", true)]
        [System.Runtime.CompilerServices.CompilerFeatureRequired("RefStructs")]
        [System.Runtime.CompilerServices.IsByRefLike]
        public readonly struct Col
        {
            public void Format<T>(T value)
                where T : System.ISpanFormattable { }
            public void Set(System.ReadOnlySpan<char> span) { }
            public void Set([System.Runtime.CompilerServices.InterpolatedStringHandlerArgument("")] ref nietras.SeparatedValues.SepWriter.Col.FormatInterpolatedStringHandler handler) { }
            public void Set(System.IFormatProvider? provider, [System.Runtime.CompilerServices.InterpolatedStringHandlerArgument(new string?[]?[] {
                    "",
                    "provider"})] ref nietras.SeparatedValues.SepWriter.Col.FormatInterpolatedStringHandler handler) { }
            [System.Runtime.CompilerServices.InterpolatedStringHandler]
            public readonly struct FormatInterpolatedStringHandler
            {
                public FormatInterpolatedStringHandler(int literalLength, int formattedCount, nietras.SeparatedValues.SepWriter.Col col) { }
                public FormatInterpolatedStringHandler(int literalLength, int formattedCount, nietras.SeparatedValues.SepWriter.Col col, System.IFormatProvider? provider) { }
                public void AppendFormatted(System.ReadOnlySpan<char> value) { }
                public void AppendFormatted(string? value) { }
                public void AppendFormatted(System.ReadOnlySpan<char> value, int alignment = 0, string? format = null) { }
                public void AppendFormatted(object? value, int alignment = 0, string? format = null) { }
                public void AppendFormatted(string? value, int alignment = 0, string? format = null) { }
                public void AppendFormatted<T>(T value) { }
                public void AppendFormatted<T>(T value, int alignment) { }
                public void AppendFormatted<T>(T value, string? format) { }
                public void AppendFormatted<T>(T value, int alignment, string? format) { }
                public void AppendLiteral(string value) { }
            }
        }
        [System.Obsolete("Types with embedded references are not supported in this version of your compiler" +
            ".", true)]
        [System.Runtime.CompilerServices.CompilerFeatureRequired("RefStructs")]
        [System.Runtime.CompilerServices.IsByRefLike]
        public readonly struct Cols
        {
            public int Count { get; }
            public nietras.SeparatedValues.SepWriter.Col this[int colIndex] { get; }
            public void Format<T>(System.Collections.Generic.IReadOnlyList<T> values)
                where T : System.ISpanFormattable { }
            public void Format<T>(System.ReadOnlySpan<T> values)
                where T : System.ISpanFormattable { }
            public void Format<T>(System.Span<T> values)
                where T : System.ISpanFormattable { }
            public void Format<T>(T[] values)
                where T : System.ISpanFormattable { }
            public void Format<T>(System.ReadOnlySpan<T> values, nietras.SeparatedValues.SepWriter.ColAction<T> format) { }
            public void Set(System.Collections.Generic.IReadOnlyList<string> values) { }
            public void Set(System.ReadOnlySpan<string> values) { }
            public void Set(string[] values) { }
            public void Set(nietras.SeparatedValues.SepReader.Cols cols) { }
        }
        public delegate void ColAction(nietras.SeparatedValues.SepWriter.Col col);
        public delegate void ColAction<T>(nietras.SeparatedValues.SepWriter.Col col, T value);
        public delegate void RowAction(nietras.SeparatedValues.SepWriter.Row row);
    }
    public static class SepWriterExtensions
    {
        public static nietras.SeparatedValues.SepWriter To(this nietras.SeparatedValues.SepWriterOptions options, System.IO.Stream stream) { }
        public static nietras.SeparatedValues.SepWriter To(this nietras.SeparatedValues.SepWriterOptions options, System.IO.TextWriter writer) { }
        public static nietras.SeparatedValues.SepWriter To(this nietras.SeparatedValues.SepWriterOptions options, System.IO.Stream stream, bool leaveOpen) { }
        public static nietras.SeparatedValues.SepWriter To(this nietras.SeparatedValues.SepWriterOptions options, System.IO.TextWriter writer, bool leaveOpen) { }
        public static nietras.SeparatedValues.SepWriter ToFile(this nietras.SeparatedValues.SepWriterOptions options, string filePath) { }
        public static nietras.SeparatedValues.SepWriter ToText(this nietras.SeparatedValues.SepWriterOptions options) { }
        public static nietras.SeparatedValues.SepWriter ToText(this nietras.SeparatedValues.SepWriterOptions options, int capacity) { }
        public static nietras.SeparatedValues.SepWriterOptions Writer(this nietras.SeparatedValues.Sep sep) { }
        public static nietras.SeparatedValues.SepWriterOptions Writer(this nietras.SeparatedValues.SepSpec spec) { }
        public static nietras.SeparatedValues.SepWriterOptions Writer(this nietras.SeparatedValues.Sep sep, System.Func<nietras.SeparatedValues.SepWriterOptions, nietras.SeparatedValues.SepWriterOptions> configure) { }
        public static nietras.SeparatedValues.SepWriterOptions Writer(this nietras.SeparatedValues.SepSpec spec, System.Func<nietras.SeparatedValues.SepWriterOptions, nietras.SeparatedValues.SepWriterOptions> configure) { }
    }
    [System.Diagnostics.DebuggerDisplay("{DebuggerDisplay,nq}")]
    [System.Diagnostics.DebuggerTypeProxy(typeof(nietras.SeparatedValues.SepWriterHeader.DebugView))]
    public sealed class SepWriterHeader
    {
        public void Add(System.Collections.Generic.IReadOnlyList<string> colNames) { }
        public void Add(System.ReadOnlySpan<string> colNames) { }
        public void Add(string colName) { }
        public void Add(string[] colNames) { }
        public void Write() { }
    }
    public readonly struct SepWriterOptions : System.IEquatable<nietras.SeparatedValues.SepWriterOptions>
    {
        public SepWriterOptions() { }
        public SepWriterOptions(nietras.SeparatedValues.Sep sep) { }
        public System.Globalization.CultureInfo? CultureInfo { get; init; }
        public nietras.SeparatedValues.Sep Sep { get; init; }
        public bool WriteHeader { get; init; }
    }
}