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.
$ dotnet add package Sep
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. ⭐
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.Example | Naming and Terminology | API | Limitations and Constraints | Comparison Benchmarks | Example Catalogue | RFC-4180 | FAQ | Public API Reference
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.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 an ToExcl line number matching the C# range indexing syntax [LineNumberFrom..LineNumberToExcl]. |
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.
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 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:
Sep or use default automatically inferred separator.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.string), TextWriter, etc. via From
extension methods.GT_ use:
var colNames = header.NamesStarting("GT_");
var colIndices = header.IndicesOf(colNames);
Sep internally handles pooled allocation and reuse of arrays for
multiple columns.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.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 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>
/// 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.
/// </remarks>
public bool Unescape { get; init; } = false;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
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.
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\""
If you hover over col you should see:
"\"Apple\r\nBanana\r\nOrange\r\nPear\""
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", StringComparison.Ordinal))
.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.
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 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:
Sep or use default automatically inferred separator.SepWriterOptions.
For all options see SepWriterOptions.string via StringWriter),
TextWriter, etc. via To extension methods.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.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); }
Sep internally handles pooled allocation and reuse of
arrays for multiple columns.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.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.
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; }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:
Trim
extension method to remove surrounding quotes, for example.# 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.To investigate the performance of Sep it is compared to:
downloads on NuGet. Fully
featured and battle tested.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 + MemoryStreamStringWriter or StreamWriter + MemoryStreamThis 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.
The following runtime is used for benchmarking:
NET 8.0.XThe 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
The following reader scenarios are benchmarked:
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:
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.foreach (var row in reader)
{
for (var i = 0; i < row.ColCount; i++)
{
var span = row[i].Span;
}
}
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 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).
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.
| Method | Scope | Rows | Mean | Ratio | MB | MB/s | ns/row | Allocated | Alloc Ratio |
|---|---|---|---|---|---|---|---|---|---|
| Sep______ | Row | 50000 | 2.319 ms | 1.00 | 29 | 12581.3 | 46.4 | 967 B | 1.00 |
| Sep_Unescape | Row | 50000 | 2.335 ms | 1.01 | 29 | 12497.4 | 46.7 | 967 B | 1.00 |
| Sylvan___ | Row | 50000 | 2.985 ms | 1.29 | 29 | 9776.4 | 59.7 | 7381 B | 7.63 |
| ReadLine_ | Row | 50000 | 12.779 ms | 5.55 | 29 | 2283.6 | 255.6 | 90734838 B | 93,831.27 |
| CsvHelper | Row | 50000 | 43.702 ms | 18.84 | 29 | 667.7 | 874.0 | 21074 B | 21.79 |
| Sep______ | Cols | 50000 | 3.127 ms | 1.00 | 29 | 9331.2 | 62.5 | 970 B | 1.00 |
| Sep_Unescape | Cols | 50000 | 3.757 ms | 1.20 | 29 | 7766.9 | 75.1 | 972 B | 1.00 |
| Sylvan___ | Cols | 50000 | 5.353 ms | 1.71 | 29 | 5451.1 | 107.1 | 7385 B | 7.61 |
| ReadLine_ | Cols | 50000 | 12.753 ms | 4.07 | 29 | 2288.1 | 255.1 | 90734839 B | 93,541.07 |
| CsvHelper | Cols | 50000 | 69.377 ms | 22.20 | 29 | 420.6 | 1387.5 | 457060 B | 471.20 |
| Sep______ | Asset | 50000 | 35.112 ms | 1.00 | 29 | 831.1 | 702.2 | 14133938 B | 1.00 |
| Sep_MT___ | Asset | 50000 | 22.928 ms | 0.66 | 29 | 1272.8 | 458.6 | 14327404 B | 1.01 |
| Sylvan___ | Asset | 50000 | 39.254 ms | 1.11 | 29 | 743.4 | 785.1 | 14297119 B | 1.01 |
| ReadLine_ | Asset | 50000 | 106.311 ms | 3.04 | 29 | 274.5 | 2126.2 | 104584704 B | 7.40 |
| CsvHelper | Asset | 50000 | 83.844 ms | 2.39 | 29 | 348.0 | 1676.9 | 14306424 B | 1.01 |
| Sep______ | Asset | 1000000 | 658.125 ms | 1.00 | 583 | 887.0 | 658.1 | 273067600 B | 1.00 |
| Sep_MT___ | Asset | 1000000 | 305.092 ms | 0.46 | 583 | 1913.5 | 305.1 | 274288576 B | 1.00 |
| Sylvan___ | Asset | 1000000 | 794.169 ms | 1.21 | 583 | 735.1 | 794.2 | 273227616 B | 1.00 |
| ReadLine_ | Asset | 1000000 | 1,842.849 ms | 2.80 | 583 | 316.8 | 1842.8 | 2087764672 B | 7.65 |
| CsvHelper | Asset | 1000000 | 1,740.008 ms | 2.64 | 583 | 335.5 | 1740.0 | 273238000 B | 1.00 |
| 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 |
| 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 |
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.
| Method | Scope | Rows | Mean | Ratio | RatioSD | MB | MB/s | ns/row | Allocated | Alloc Ratio |
|---|---|---|---|---|---|---|---|---|---|---|
| Sep______ | Asset | 50000 | 22.138 ms | 1.00 | 0.00 | 29 | 1318.2 | 442.8 | 13.48 MB | 1.00 |
| Sep_MT___ | Asset | 50000 | 7.222 ms | 0.32 | 0.00 | 29 | 4040.6 | 144.4 | 13.64 MB | 1.01 |
| Sylvan___ | Asset | 50000 | 30.112 ms | 1.36 | 0.02 | 29 | 969.1 | 602.2 | 13.63 MB | 1.01 |
| ReadLine_ | Asset | 50000 | 39.837 ms | 1.86 | 0.41 | 29 | 732.5 | 796.7 | 99.74 MB | 7.40 |
| CsvHelper | Asset | 50000 | 79.581 ms | 3.59 | 0.02 | 29 | 366.7 | 1591.6 | 13.64 MB | 1.01 |
| Sep______ | Asset | 1000000 | 450.151 ms | 1.00 | 0.00 | 583 | 1296.9 | 450.2 | 260.41 MB | 1.00 |
| Sep_MT___ | Asset | 1000000 | 135.709 ms | 0.30 | 0.01 | 583 | 4301.7 | 135.7 | 261.36 MB | 1.00 |
| Sylvan___ | Asset | 1000000 | 598.959 ms | 1.33 | 0.01 | 583 | 974.7 | 599.0 | 260.57 MB | 1.00 |
| ReadLine_ | Asset | 1000000 | 654.982 ms | 1.46 | 0.02 | 583 | 891.3 | 655.0 | 1991.04 MB | 7.65 |
| CsvHelper | Asset | 1000000 | 1,592.052 ms | 3.53 | 0.03 | 583 | 366.7 | 1592.1 | 260.58 MB | 1.00 |
| 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 |
| 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 |
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.
| Method | Scope | Rows | Mean | Ratio | MB | MB/s | ns/row | Allocated | Alloc Ratio |
|---|---|---|---|---|---|---|---|---|---|
| Sep______ | Row | 50000 | 6.867 ms | 1.00 | 33 | 4860.2 | 137.3 | 983 B | 1.00 |
| Sep_Unescape | Row | 50000 | 6.749 ms | 0.98 | 33 | 4945.8 | 135.0 | 981 B | 1.00 |
| Sylvan___ | Row | 50000 | 17.676 ms | 2.57 | 33 | 1888.3 | 353.5 | 7406 B | 7.53 |
| ReadLine_ | Row | 50000 | 15.002 ms | 2.19 | 33 | 2224.9 | 300.0 | 111389433 B | 113,315.80 |
| CsvHelper | Row | 50000 | 52.772 ms | 7.68 | 33 | 632.5 | 1055.4 | 21081 B | 21.45 |
| Sep______ | Cols | 50000 | 7.753 ms | 1.00 | 33 | 4305.2 | 155.1 | 986 B | 1.00 |
| Sep_Unescape | Cols | 50000 | 8.778 ms | 1.13 | 33 | 3802.3 | 175.6 | 987 B | 1.00 |
| Sylvan___ | Cols | 50000 | 20.304 ms | 2.63 | 33 | 1643.9 | 406.1 | 7411 B | 7.52 |
| ReadLine_ | Cols | 50000 | 15.319 ms | 1.99 | 33 | 2178.8 | 306.4 | 111389433 B | 112,971.03 |
| CsvHelper | Cols | 50000 | 84.141 ms | 10.86 | 33 | 396.7 | 1682.8 | 457060 B | 463.55 |
| Sep______ | Asset | 50000 | 39.890 ms | 1.00 | 33 | 836.7 | 797.8 | 14134252 B | 1.00 |
| Sep_MT___ | Asset | 50000 | 24.580 ms | 0.61 | 33 | 1357.9 | 491.6 | 14320647 B | 1.01 |
| Sylvan___ | Asset | 50000 | 51.352 ms | 1.29 | 33 | 650.0 | 1027.0 | 14296619 B | 1.01 |
| ReadLine_ | Asset | 50000 | 118.667 ms | 2.91 | 33 | 281.3 | 2373.3 | 125239088 B | 8.86 |
| CsvHelper | Asset | 50000 | 96.789 ms | 2.42 | 33 | 344.8 | 1935.8 | 14307820 B | 1.01 |
| Sep______ | Asset | 1000000 | 752.314 ms | 1.00 | 667 | 887.5 | 752.3 | 273070272 B | 1.00 |
| Sep_MT___ | Asset | 1000000 | 403.912 ms | 0.54 | 667 | 1653.1 | 403.9 | 274538768 B | 1.01 |
| Sylvan___ | Asset | 1000000 | 1,095.609 ms | 1.46 | 667 | 609.4 | 1095.6 | 273233808 B | 1.00 |
| ReadLine_ | Asset | 1000000 | 2,550.179 ms | 3.38 | 667 | 261.8 | 2550.2 | 2500931696 B | 9.16 |
| CsvHelper | Asset | 1000000 | 2,031.309 ms | 2.70 | 667 | 328.7 | 2031.3 | 273236600 B | 1.00 |
| 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 |
| 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 |
Here again are benchmark results with server garbage collection, which provides significant speedup over workstation garbage collection.
| Method | Scope | Rows | Mean | Ratio | RatioSD | MB | MB/s | ns/row | Allocated | Alloc Ratio |
|---|---|---|---|---|---|---|---|---|---|---|
| Sep______ | Asset | 50000 | 26.83 ms | 1.00 | 0.00 | 33 | 1243.9 | 536.6 | 13.48 MB | 1.00 |
| Sep_MT___ | Asset | 50000 | 12.95 ms | 0.48 | 0.01 | 33 | 2576.6 | 259.1 | 13.64 MB | 1.01 |
| Sylvan___ | Asset | 50000 | 44.44 ms | 1.66 | 0.01 | 33 | 751.1 | 888.8 | 13.63 MB | 1.01 |
| ReadLine_ | Asset | 50000 | 46.86 ms | 1.71 | 0.48 | 33 | 712.3 | 937.2 | 119.44 MB | 8.86 |
| CsvHelper | Asset | 50000 | 93.47 ms | 3.48 | 0.02 | 33 | 357.1 | 1869.5 | 13.64 MB | 1.01 |
| Sep______ | Asset | 1000000 | 552.21 ms | 1.00 | 0.00 | 667 | 1209.2 | 552.2 | 260.41 MB | 1.00 |
| Sep_MT___ | Asset | 1000000 | 230.71 ms | 0.42 | 0.00 | 667 | 2894.2 | 230.7 | 261.6 MB | 1.00 |
| Sylvan___ | Asset | 1000000 | 928.39 ms | 1.68 | 0.01 | 667 | 719.2 | 928.4 | 260.57 MB | 1.00 |
| ReadLine_ | Asset | 1000000 | 750.83 ms | 1.36 | 0.02 | 667 | 889.3 | 750.8 | 2385.07 MB | 9.16 |
| CsvHelper | Asset | 1000000 | 1,852.26 ms | 3.35 | 0.01 | 667 | 360.5 | 1852.3 | 260.58 MB | 1.00 |
| 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 |
| 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 |
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 run time 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.
| Method | Scope | Rows | Mean | Ratio | MB | MB/s | ns/row | Allocated | Alloc Ratio |
|---|---|---|---|---|---|---|---|---|---|
| Sep______ | Row | 25000 | 1.936 ms | 1.00 | 20 | 10498.4 | 77.4 | 1.18 KB | 1.00 |
| Sylvan___ | Row | 25000 | 2.259 ms | 1.17 | 20 | 8995.4 | 90.4 | 10.02 KB | 8.50 |
| ReadLine_ | Row | 25000 | 11.063 ms | 5.69 | 20 | 1836.8 | 442.5 | 73489.64 KB | 62,295.85 |
| CsvHelper | Row | 25000 | 25.135 ms | 12.99 | 20 | 808.4 | 1005.4 | 20.58 KB | 17.45 |
| Sep______ | Cols | 25000 | 2.566 ms | 1.00 | 20 | 7918.8 | 102.6 | 1.18 KB | 1.00 |
| Sylvan___ | Cols | 25000 | 3.821 ms | 1.49 | 20 | 5318.1 | 152.8 | 10.03 KB | 8.48 |
| ReadLine_ | Cols | 25000 | 11.675 ms | 4.54 | 20 | 1740.5 | 467.0 | 73489.64 KB | 62,141.53 |
| CsvHelper | Cols | 25000 | 27.400 ms | 10.67 | 20 | 741.6 | 1096.0 | 21340.81 KB | 18,045.40 |
| Sep______ | Floats | 25000 | 21.852 ms | 1.00 | 20 | 929.9 | 874.1 | 7.93 KB | 1.00 |
| Sep_MT___ | Floats | 25000 | 3.916 ms | 0.18 | 20 | 5188.4 | 156.7 | 178.87 KB | 22.56 |
| Sylvan___ | Floats | 25000 | 71.861 ms | 3.29 | 20 | 282.8 | 2874.4 | 18.2 KB | 2.30 |
| ReadLine_ | Floats | 25000 | 73.981 ms | 3.39 | 20 | 274.7 | 2959.2 | 73493.12 KB | 9,271.52 |
| CsvHelper | Floats | 25000 | 102.224 ms | 4.68 | 20 | 198.8 | 4089.0 | 22062.55 KB | 2,783.30 |
| 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 |
| 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 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.
The following examples are available in ReadMeTest.cs.
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());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.
Ask questions on GitHub and this section will be expanded. :)
[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=v7.0", FrameworkDisplayName=".NET 7.0")]
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.SepHeader? maybeHeader, int colCount);
public static class SepDefaults
{
public static System.Globalization.CultureInfo CultureInfo { get; }
public static char Separator { get; }
}
public sealed class SepHeader
{
public SepHeader(string row, System.Collections.Generic.Dictionary<string, int> colNameToIndex) { }
public System.Collections.Generic.IReadOnlyList<string> ColNames { get; }
public bool IsEmpty { get; }
public static nietras.SeparatedValues.SepHeader 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() { }
}
[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.SepHeader 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 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 readonly struct SepReaderOptions : System.IEquatable<nietras.SeparatedValues.SepReaderOptions>
{
public SepReaderOptions() { }
public SepReaderOptions(nietras.SeparatedValues.Sep? sep) { }
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 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 class SepWriter : System.IDisposable
{
public SepWriter(nietras.SeparatedValues.SepWriterOptions options, System.IO.TextWriter writer) { }
public nietras.SeparatedValues.SepSpec Spec { get; }
public void Dispose() { }
protected virtual void Dispose(bool disposing) { }
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 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) { }
}
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; }
}
}