Rapidcsv

Linux + Mac	Windows

Rapidcsv is a simple 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, and an example of getting a specific cell as well.

    #include <iostream>
    #include <vector>
    #include <rapidcsv.h>

    int main()
    {
      rapidcsv::Document doc("../tests/msft.csv");

      std::vector<float> close = doc.GetColumn<float>("Close");
      std::cout << "Read " << close.size() << " values." << std::endl;

      long long volume = doc.GetCell<long long>("Volume", "2011-03-09");
      std::cout << "Volume " << volume << " on 2011-03-09." << std::endl;

      // ...
    }

The below section More Examples contains more examples(!), and additionally the tests directory contains many simple usage examples as well.

Supported Platforms

Rapidcsv is implemented using C++11 with the intention of being portable. It's been tested on:

OS X El Capitan 10.11
Ubuntu 16.04 LTS
Windows 7 / Visual Studio 2015

Installation

Simply copy src/rapidcsv.h to your project/include directory and include it.

More Examples

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 line reads file.csv using semi-colon as separator.

    rapidcsv::Document doc("file.csv", rapidcsv::LabelParams(), rapidcsv::SeparatorParams(';'));

Reading a File without Headers

By default rapidcsv treats the first row as column headers, and the first column as row headers. This allows accessing rows/columns/cells using their labels, for example GetCell("Close", "2011-03-09") to get the cell from column labelled "Close", at row labelled "2011-03-09". Sometimes one may prefer to be able to access first row and column as data, and only access cells by their row and column index. In order to do so one need use LabelParams and set pColumnNameIdx and pRowNameIdx to -1 (disabled). Example:

    rapidcsv::Document doc("file.csv", rapidcsv::LabelParams(-1, -1));

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 datatype, 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 datatypes, one can use ConverterParams to configure the converter to default to a numeric value. The value is configurable, but 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));

Custom Data Conversion

The internal cell representation in the Document class is using std::string and when other types are requested, standard conversion routines are used. One may override conversion routines (or add new ones) by implementing ToVal() and ToStr(). Here is an example overriding int conversion, to instead provide two decimal fixed-point numbers. See tests/test035.cpp for a complete program example.

    namespace rapidcsv
    {
      template<>
      void Converter<int>::ToVal(const std::string& pStr, int& pVal) const
      {
        pVal = roundf(100.0 * stof(pStr));
      }
    
      template<>
      void Converter<int>::ToStr(const int& pVal, std::string& pStr) const
      {
        std::ostringstream out;
        out << std::fixed << std::setprecision(2) << static_cast<float>(pVal) / 100.0f;
        pStr = out.str();
      }
    }

API Documentation

The following classes makes up the Rapidcsv interface:

Technical Details

Rapidcsv uses cmake for its tests. Commands to build and execute the test suite:

mkdir -p build && cd build && cmake .. && make && ctest --output-on-failure ; cd -

Rapidcsv uses doxyman2md to generate its API documentation:

doxyman2md src doc

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.

werkamsus/rapidcsv