Rapidcsv
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Rapidcsv is a C++ header-only library for CSV parsing. While the name admittedly was inspired by the rapidjson project, the objectives are not the same. The goal of rapidcsv is to be an easy-to-use CSV library enabling rapid development. For optimal performance (be it CPU or memory usage) a CSV parser implemented for the specific use-case is likely to be more performant.
Example Usage
Here is a simple example reading a CSV file and getting 'Close' column as a vector of floats.
colhdr.csv content:
Open,High,Low,Close,Volume,Adj Close
64.529999,64.800003,64.139999,64.620003,21705200,64.620003
64.419998,64.730003,64.190002,64.620003,20235200,64.620003
64.330002,64.389999,64.050003,64.360001,19259700,64.360001
64.610001,64.949997,64.449997,64.489998,19384900,64.489998
64.470001,64.690002,64.300003,64.620003,21234600,64.620003
ex001.cpp content:
#include <iostream>
#include <vector>
#include "rapidcsv.h"
int main()
{
rapidcsv::Document doc("examples/colhdr.csv");
std::vector<float> col = doc.GetColumn<float>("Close");
std::cout << "Read " << col.size() << " values." << std::endl;
}
Refer to section More Examples below for more examples. The tests directory also contains many simple usage examples.
Supported Platforms
Rapidcsv is implemented using C++11 with the intention of being portable. It's been tested on:
- macOS Big Sur 11.0
- Ubuntu 20.04 LTS
- Windows 10 / Visual Studio 2019
Installation
Simply copy src/rapidcsv.h to your project/include directory and include it.
More Examples
Several of the following examples are also provided in the examples/
directory and can be executed directly under Linux and macOS. Example running
ex001.cpp:
./examples/ex001.cpp
Reading a File with Column and Row Headers
By default rapidcsv treats the first row as column headers, and the first column is treated as data. This allows accessing columns using their labels, but not rows or cells (only using indices). In order to treat the first column as row headers one needs to use LabelParams and set pRowNameIdx to 0.
Column and Row Headers
colrowhdr.csv content:
Date,Open,High,Low,Close,Volume,Adj Close
2017-02-24,64.529999,64.800003,64.139999,64.620003,21705200,64.620003
2017-02-23,64.419998,64.730003,64.190002,64.620003,20235200,64.620003
2017-02-22,64.330002,64.389999,64.050003,64.360001,19259700,64.360001
2017-02-21,64.610001,64.949997,64.449997,64.489998,19384900,64.489998
2017-02-17,64.470001,64.690002,64.300003,64.620003,21234600,64.620003
ex002.cpp content:
#include <iostream>
#include <vector>
#include "rapidcsv.h"
int main()
{
rapidcsv::Document doc("examples/colrowhdr.csv", rapidcsv::LabelParams(0, 0));
std::vector<float> close = doc.GetRow<float>("2017-02-22");
std::cout << "Read " << close.size() << " values." << std::endl;
long long volume = doc.GetCell<long long>("Volume", "2017-02-22");
std::cout << "Volume " << volume << " on 2017-02-22." << std::endl;
}
Row Headers Only
rowhdr.csv content:
2017-02-24,64.529999,64.800003,64.139999,64.620003,21705200,64.620003
2017-02-23,64.419998,64.730003,64.190002,64.620003,20235200,64.620003
2017-02-22,64.330002,64.389999,64.050003,64.360001,19259700,64.360001
2017-02-21,64.610001,64.949997,64.449997,64.489998,19384900,64.489998
2017-02-17,64.470001,64.690002,64.300003,64.620003,21234600,64.620003
ex003.cpp content:
#include <iostream>
#include <vector>
#include "rapidcsv.h"
int main()
{
rapidcsv::Document doc("examples/rowhdr.csv", rapidcsv::LabelParams(-1, 0));
std::vector<std::string> row = doc.GetRow<std::string>("2017-02-22");
std::cout << "Read " << row.size() << " values." << std::endl;
}
No Headers
nohdr.csv content:
64.529999,64.800003,64.139999,64.620003,21705200,64.620003
64.419998,64.730003,64.190002,64.620003,20235200,64.620003
64.330002,64.389999,64.050003,64.360001,19259700,64.360001
64.610001,64.949997,64.449997,64.489998,19384900,64.489998
64.470001,64.690002,64.300003,64.620003,21234600,64.620003
ex004.cpp content:
#include <iostream>
#include <vector>
#include "rapidcsv.h"
int main()
{
rapidcsv::Document doc("examples/nohdr.csv", rapidcsv::LabelParams(-1, -1));
std::vector<float> close = doc.GetColumn<float>(5);
std::cout << "Read " << close.size() << " values." << std::endl;
long long volume = doc.GetCell<long long>(4, 2);
std::cout << "Volume " << volume << " on 2017-02-22." << std::endl;
}
Reading a File with Custom Separator
For reading of files with custom separator (i.e. not comma), one need to specify the SeparatorParams argument. The following example reads a file using semi-colon as separator.
semi.csv content:
Date;Open;High;Low;Close;Volume;Adj Close
2017-02-24;64.529999;64.800003;64.139999;64.620003;21705200;64.620003
2017-02-23;64.419998;64.730003;64.190002;64.620003;20235200;64.620003
2017-02-22;64.330002;64.389999;64.050003;64.360001;19259700;64.360001
2017-02-21;64.610001;64.949997;64.449997;64.489998;19384900;64.489998
2017-02-17;64.470001;64.690002;64.300003;64.620003;21234600;64.620003
ex005.cpp content:
#include <iostream>
#include <vector>
#include "rapidcsv.h"
int main()
{
rapidcsv::Document doc("examples/semi.csv", rapidcsv::LabelParams(0, 0),
rapidcsv::SeparatorParams(';'));
std::vector<float> close = doc.GetColumn<float>("Close");
std::cout << "Read " << close.size() << " values." << std::endl;
long long volume = doc.GetCell<long long>("Volume", "2017-02-22");
std::cout << "Volume " << volume << " on 2017-02-22." << std::endl;
}
Supported Get/Set Data Types
The internal cell representation in the Document class is using std::string
and when other types are requested, standard conversion routines are used.
All standard conversions are relatively straight-forward, with the
exception of char
for which rapidcsv interprets the cell's (first) byte
as a character. The following example illustrates the supported data types.
colrowhdr.csv content:
Date,Open,High,Low,Close,Volume,Adj Close
2017-02-24,64.529999,64.800003,64.139999,64.620003,21705200,64.620003
2017-02-23,64.419998,64.730003,64.190002,64.620003,20235200,64.620003
2017-02-22,64.330002,64.389999,64.050003,64.360001,19259700,64.360001
2017-02-21,64.610001,64.949997,64.449997,64.489998,19384900,64.489998
2017-02-17,64.470001,64.690002,64.300003,64.620003,21234600,64.620003
ex006.cpp content:
#include <iostream>
#include <vector>
#include "rapidcsv.h"
int main()
{
rapidcsv::Document doc("examples/colrowhdr.csv", rapidcsv::LabelParams(0, 0));
std::cout << doc.GetCell<std::string>("Volume", "2017-02-22") << std::endl;
std::cout << doc.GetCell<int>("Volume", "2017-02-22") << std::endl;
std::cout << doc.GetCell<long>("Volume", "2017-02-22") << std::endl;
std::cout << doc.GetCell<long long>("Volume", "2017-02-22") << std::endl;
std::cout << doc.GetCell<unsigned>("Volume", "2017-02-22") << std::endl;
std::cout << doc.GetCell<unsigned long>("Volume", "2017-02-22") << std::endl;
std::cout << doc.GetCell<unsigned long long>("Volume", "2017-02-22") << std::endl;
std::cout << doc.GetCell<float>("Volume", "2017-02-22") << std::endl;
std::cout << doc.GetCell<double>("Volume", "2017-02-22") << std::endl;
std::cout << doc.GetCell<long double>("Volume", "2017-02-22") << std::endl;
std::cout << doc.GetCell<char>("Volume", "2017-02-22") << std::endl;
}
Global Custom Data Type Conversion
One may override conversion routines (or add new ones) by implementing ToVal() and/or ToStr(). Below is an example overriding int conversion, to instead provide two decimal fixed-point numbers. Also see tests/test035.cpp for a test overriding ToVal() and ToStr().
ex008.cpp content:
#include <iostream>
#include <vector>
#include "rapidcsv.h"
namespace rapidcsv
{
template<>
void Converter<int>::ToVal(const std::string& pStr, int& pVal) const
{
pVal = static_cast<int>(roundf(100.0f * std::stof(pStr)));
}
}
int main()
{
rapidcsv::Document doc("examples/colrowhdr.csv", rapidcsv::LabelParams(0, 0));
std::vector<int> close = doc.GetColumn<int>("Close");
std::cout << "close[0] = " << close[0] << std::endl;
std::cout << "close[1] = " << close[1] << std::endl;
}
Custom Data Type Conversion Per Call
It is also possible to override conversions on a per-call basis, enabling more flexibility. This is illustrated in the following example. Additional conversion override usage can be found in the test tests/test063.cpp
ex009.cpp content:
#include <iostream>
#include <vector>
#include "rapidcsv.h"
void ConvFixPoint(const std::string& pStr, int& pVal)
{
pVal = static_cast<int>(roundf(100.0f * std::stof(pStr)));
}
struct MyStruct
{
int val = 0;
};
void ConvMyStruct(const std::string& pStr, MyStruct& pVal)
{
pVal.val = static_cast<int>(roundf(100.0f * std::stof(pStr)));
}
int main()
{
rapidcsv::Document doc("examples/colrowhdr.csv", rapidcsv::LabelParams(0, 0));
std::cout << "regular = " << doc.GetCell<int>("Close", "2017-02-21") << "\n";
std::cout << "fixpointfunc = " << doc.GetCell<int>("Close", "2017-02-21", ConvFixPoint) << "\n";
auto convFixLambda = [](const std::string& pStr, int& pVal) { pVal = static_cast<int>(roundf(100.0f * stof(pStr))); };
std::cout << "fixpointlambda = " << doc.GetCell<int>("Close", "2017-02-21", convFixLambda) << "\n";
std::cout << "mystruct = " << doc.GetCell<MyStruct>("Close", "2017-02-21", ConvMyStruct).val << "\n";
}
Reading CSV Data from a Stream or String
In addition to specifying a filename, rapidcsv supports constructing a Document
from a stream and, indirectly through stringstream, from a string. File streams
used with rapidcsv should be opened in std::ios::binary
mode to enable full
functionality. Here is a simple example reading CSV data from a string:
ex007.cpp content:
#include <iostream>
#include <vector>
#include "rapidcsv.h"
int main()
{
const std::string& csv =
"Date,Open,High,Low,Close,Volume,Adj Close\n"
"2017-02-24,64.529999,64.800003,64.139999,64.620003,21705200,64.620003\n"
"2017-02-23,64.419998,64.730003,64.190002,64.620003,20235200,64.620003\n"
"2017-02-22,64.330002,64.389999,64.050003,64.360001,19259700,64.360001\n"
"2017-02-21,64.610001,64.949997,64.449997,64.489998,19384900,64.489998\n"
"2017-02-17,64.470001,64.690002,64.300003,64.620003,21234600,64.620003\n"
;
std::stringstream sstream(csv);
rapidcsv::Document doc(sstream, rapidcsv::LabelParams(0, 0));
std::vector<float> close = doc.GetColumn<float>("Close");
std::cout << "Read " << close.size() << " values." << std::endl;
long long volume = doc.GetCell<long long>("Volume", "2017-02-22");
std::cout << "Volume " << volume << " on 2017-02-22." << std::endl;
}
Reading a File with Invalid Numbers (e.g. Empty Cells) as Numeric Data
By default rapidcsv throws an exception if one tries to access non-numeric data as a numeric data type, as it basically propagates the underlying conversion routines' exceptions to the calling application.
The reason for this is to ensure data correctness. If one wants to be able to read data with invalid numbers as numeric data types, one can use ConverterParams to configure the converter to default to a numeric value. The value is configurable and by default it's std::numeric_limits::signaling_NaN() for float types, and 0 for integer types. Example:
rapidcsv::Document doc("file.csv", rapidcsv::LabelParams(),
rapidcsv::SeparatorParams(),
rapidcsv::ConverterParams(true));
Check if a Column Exists
Rapidcsv provides the methods GetColumnNames() and GetRowNames() to retrieve the column and row names. To check whether a particular column name exists one can for example do:
rapidcsv::Document doc("file.csv");
std::vector<std::string> columnNames = doc.GetColumnNames();
bool columnExists =
(std::find(columnNames.begin(), columnNames.end(), "A") != columnNames.end());
Handling Quoted Cells
By default rapidcsv automatically dequotes quoted cells (i.e. removes the encapsulating
"
characters from "example quoted cell"
). This functionality may be disabled by
passing pAutoQuote = false
in SeparatorParams
, example:
rapidcsv::Document doc("file.csv", rapidcsv::LabelParams(),
rapidcsv::SeparatorParams(',' /* pSeparator */,
false /* pTrim */,
rapidcsv::sPlatformHasCR /* pHasCR */,
false /* pQuotedLinebreaks */,
false /* pAutoQuote */));
Skipping Empty and Comment Lines
Rapidcsv reads all lines by default, but may be called to ignore comment lines starting with a specific character, example:
rapidcsv::Document doc("file.csv", rapidcsv::LabelParams(), rapidcsv::SeparatorParams(),
rapidcsv::ConverterParams(),
rapidcsv::LineReaderParams(true /* pSkipCommentLines */,
'#' /* pCommentPrefix */));
Using LineReaderParams it is also possible to skip empty lines, example:
rapidcsv::Document doc("file.csv", rapidcsv::LabelParams(), rapidcsv::SeparatorParams(),
rapidcsv::ConverterParams(),
rapidcsv::LineReaderParams(false /* pSkipCommentLines */,
'#' /* pCommentPrefix */,
true /* pSkipEmptyLines */));
UTF-16 and UTF-8
Rapidcsv's preferred encoding for non-ASCII text is UTF-8. UTF-16 LE and UTF-16 BE can be read and written by rapidcsv on systems where codecvt header is present. Define HAS_CODECVT before including rapidcsv.h in order to enable the functionality. Rapidcsv unit tests automatically detects the presence of codecvt and sets HAS_CODECVT as needed, see CMakeLists.txt for reference. When enabled, the UTF-16 encoding of any loaded file is automatically detected.
CMake FetchContent
Rapidcsv may be included in a CMake project using FetchContent. Refer to the CMake FetchContent Example Project and in particular its CMakeLists.txt.
Locale Independent Parsing
Rapidcsv uses locale-dependent conversion functions when parsing float values
by default. It is possible to configure rapidcsv to use locale independent
parsing by setting mNumericLocale
in ConverterParams
, see for example
tests/test087.cpp
API Documentation
The following classes makes up the Rapidcsv interface:
- class rapidcsv::Document
- class rapidcsv::LabelParams
- class rapidcsv::SeparatorParams
- class rapidcsv::ConverterParams
- class rapidcsv::LineReaderParams
- class rapidcsv::no_converter
- class rapidcsv::Converter< T >
Technical Details
Rapidcsv uses cmake for its tests. Commands to build and execute the test suite:
mkdir -p build && cd build && cmake -DRAPIDCSV_BUILD_TESTS=ON .. && make && ctest -C unit --output-on-failure && ctest -C perf --verbose ; cd -
Rapidcsv uses doxygenmd to generate its Markdown API documentation:
doxygenmd src doc
Rapidcsv uses Uncrustify to ensure consistent code formatting:
uncrustify -c uncrustify.cfg --no-backup src/rapidcsv.h
Alternatives
There are many CSV parsers for C++, for example:
License
Rapidcsv is distributed under the BSD 3-Clause license. See LICENSE file.
Contributions
Bugs, PRs, etc are welcome on the GitHub project page https://github.com/d99kris/rapidcsv
Keywords
c++, c++11, csv parser, comma separated values, single header library.