就像每个人都把他的解决方案，这里是我的使用模板，lambda和tuple。

它可以将任何具有所需列的CSV转换为tuple的c++向量。

它通过在元组中定义每个CSV行元素类型来工作。

您还需要为每个元素定义std::string到类型转换Formatter lambda(例如使用std::atod)。

然后你就得到了这个结构的一个向量，对应于你的CSV数据。

您可以很容易地重用它来匹配任何CSV结构。

StringsHelpers.hpp

#include <string>
#include <fstream>
#include <vector>
#include <functional>

namespace StringHelpers
{
    template<typename Tuple>
    using Formatter = std::function<Tuple(const std::vector<std::string> &)>;

    std::vector<std::string> split(const std::string &string, const std::string &delimiter);

    template<typename Tuple>
    std::vector<Tuple> readCsv(const std::string &path, const std::string &delimiter, Formatter<Tuple> formatter);
};

StringsHelpers.cpp

#include "StringHelpers.hpp"

namespace StringHelpers
{
    /**
     * Split a string with the given delimiter into several strings
     *
     * @param string - The string to extract the substrings from
     * @param delimiter - The substrings delimiter
     *
     * @return The substrings
     */
    std::vector<std::string> split(const std::string &string, const std::string &delimiter)
    {
        std::vector<std::string> result;
        size_t                   last = 0,
                                 next = 0;

        while ((next = string.find(delimiter, last)) != std::string::npos) {
            result.emplace_back(string.substr(last, next - last));
            last = next + 1;
        }

        result.emplace_back(string.substr(last));

        return result;
    }

    /**
     * Read a CSV file and store its values into the given structure (Tuple with Formatter constructor)
     *
     * @tparam Tuple - The CSV line structure format
     *
     * @param path - The CSV file path
     * @param delimiter - The CSV values delimiter
     * @param formatter - The CSV values formatter that take a vector of strings in input and return a Tuple
     *
     * @return The CSV as vector of Tuple
     */
    template<typename Tuple>
    std::vector<Tuple> readCsv(const std::string &path, const std::string &delimiter, Formatter<Tuple> formatter)
    {
        std::ifstream      file(path, std::ifstream::in);
        std::string        line;
        std::vector<Tuple> result;

        if (file.fail()) {
            throw std::runtime_error("The file " + path + " could not be opened");
        }

        while (std::getline(file, line)) {
            result.emplace_back(formatter(split(line, delimiter)));
        }

        file.close();

        return result;
    }

    // Forward template declarations

    template std::vector<std::tuple<double, double, double>> readCsv<std::tuple<double, double, double>>(const std::string &, const std::string &, Formatter<std::tuple<double, double, double>>);
} // End of StringHelpers namespace

Main.cpp(一些用法)

#include "StringHelpers.hpp"

/**
 * Example of use with a CSV file which have (number,Red,Green,Blue) as line values. We do not want to use the 1st value
 * of the line.
 */
int main(int argc, char **argv)
{
    // Declare CSV line type, formatter and template type
    typedef std::tuple<double, double, double>                          CSV_format;
    typedef std::function<CSV_format(const std::vector<std::string> &)> formatterT;

    enum RGB { Red = 1, Green, Blue };

    const std::string COLOR_MAP_PATH = "/some/absolute/path";

    // Load the color map
    auto colorMap = StringHelpers::readCsv<CSV_format>(COLOR_MAP_PATH, ",", [](const std::vector<std::string> &values) {
        return CSV_format {
                // Here is the formatter lambda that convert each value from string to what you want
                std::strtod(values[Red].c_str(), nullptr),
                std::strtod(values[Green].c_str(), nullptr),
                std::strtod(values[Blue].c_str(), nullptr)
        };
    });

    // Use your colorMap as you  wish...
}

另一个类似于Loki Astari的答案的解决方案，在c++ 11中。这里的行是给定类型的std::元组。代码扫描一行，然后扫描到每个分隔符，然后将值直接转换并转储到元组中(使用一些模板代码)。

for (auto row : csv<std::string, int, float>(file, ',')) {
    std::cout << "first col: " << std::get<0>(row) << std::endl;
}

优势：

非常干净，使用简单，只有c++ 11。 自动类型转换为std::tuple<t1，…>通过算子>>。

缺少什么:

转义和引用 没有错误处理的情况下畸形的CSV。

主要代码:

#include <iterator>
#include <sstream>
#include <string>

namespace csvtools {
    /// Read the last element of the tuple without calling recursively
    template <std::size_t idx, class... fields>
    typename std::enable_if<idx >= std::tuple_size<std::tuple<fields...>>::value - 1>::type
    read_tuple(std::istream &in, std::tuple<fields...> &out, const char delimiter) {
        std::string cell;
        std::getline(in, cell, delimiter);
        std::stringstream cell_stream(cell);
        cell_stream >> std::get<idx>(out);
    }

    /// Read the @p idx-th element of the tuple and then calls itself with @p idx + 1 to
    /// read the next element of the tuple. Automatically falls in the previous case when
    /// reaches the last element of the tuple thanks to enable_if
    template <std::size_t idx, class... fields>
    typename std::enable_if<idx < std::tuple_size<std::tuple<fields...>>::value - 1>::type
    read_tuple(std::istream &in, std::tuple<fields...> &out, const char delimiter) {
        std::string cell;
        std::getline(in, cell, delimiter);
        std::stringstream cell_stream(cell);
        cell_stream >> std::get<idx>(out);
        read_tuple<idx + 1, fields...>(in, out, delimiter);
    }
}

/// Iterable csv wrapper around a stream. @p fields the list of types that form up a row.
template <class... fields>
class csv {
    std::istream &_in;
    const char _delim;
public:
    typedef std::tuple<fields...> value_type;
    class iterator;

    /// Construct from a stream.
    inline csv(std::istream &in, const char delim) : _in(in), _delim(delim) {}

    /// Status of the underlying stream
    /// @{
    inline bool good() const {
        return _in.good();
    }
    inline const std::istream &underlying_stream() const {
        return _in;
    }
    /// @}

    inline iterator begin();
    inline iterator end();
private:

    /// Reads a line into a stringstream, and then reads the line into a tuple, that is returned
    inline value_type read_row() {
        std::string line;
        std::getline(_in, line);
        std::stringstream line_stream(line);
        std::tuple<fields...> retval;
        csvtools::read_tuple<0, fields...>(line_stream, retval, _delim);
        return retval;
    }
};

/// Iterator; just calls recursively @ref csv::read_row and stores the result.
template <class... fields>
class csv<fields...>::iterator {
    csv::value_type _row;
    csv *_parent;
public:
    typedef std::input_iterator_tag iterator_category;
    typedef csv::value_type         value_type;
    typedef std::size_t             difference_type;
    typedef csv::value_type *       pointer;
    typedef csv::value_type &       reference;

    /// Construct an empty/end iterator
    inline iterator() : _parent(nullptr) {}
    /// Construct an iterator at the beginning of the @p parent csv object.
    inline iterator(csv &parent) : _parent(parent.good() ? &parent : nullptr) {
        ++(*this);
    }

    /// Read one row, if possible. Set to end if parent is not good anymore.
    inline iterator &operator++() {
        if (_parent != nullptr) {
            _row = _parent->read_row();
            if (!_parent->good()) {
                _parent = nullptr;
            }
        }
        return *this;
    }

    inline iterator operator++(int) {
        iterator copy = *this;
        ++(*this);
        return copy;
    }

    inline csv::value_type const &operator*() const {
        return _row;
    }

    inline csv::value_type const *operator->() const {
        return &_row;
    }

    bool operator==(iterator const &other) {
        return (this == &other) or (_parent == nullptr and other._parent == nullptr);
    }
    bool operator!=(iterator const &other) {
        return not (*this == other);
    }
};

template <class... fields>
typename csv<fields...>::iterator csv<fields...>::begin() {
    return iterator(*this);
}

template <class... fields>
typename csv<fields...>::iterator csv<fields...>::end() {
    return iterator();
}

我在GitHub上放了一个小的工作示例;我一直用它来解析一些数值数据，它达到了它的目的。

如果你确实关心正确解析CSV，这将做它…相对较慢，因为它一次只处理一个字符。

 void ParseCSV(const string& csvSource, vector<vector<string> >& lines)
    {
       bool inQuote(false);
       bool newLine(false);
       string field;
       lines.clear();
       vector<string> line;

       string::const_iterator aChar = csvSource.begin();
       while (aChar != csvSource.end())
       {
          switch (*aChar)
          {
          case '"':
             newLine = false;
             inQuote = !inQuote;
             break;

          case ',':
             newLine = false;
             if (inQuote == true)
             {
                field += *aChar;
             }
             else
             {
                line.push_back(field);
                field.clear();
             }
             break;

          case '\n':
          case '\r':
             if (inQuote == true)
             {
                field += *aChar;
             }
             else
             {
                if (newLine == false)
                {
                   line.push_back(field);
                   lines.push_back(line);
                   field.clear();
                   line.clear();
                   newLine = true;
                }
             }
             break;

          default:
             newLine = false;
             field.push_back(*aChar);
             break;
          }

          aChar++;
       }

       if (field.size())
          line.push_back(field);

       if (line.size())
          lines.push_back(line);
    }

下面是读取矩阵的代码，注意你在matlab中也有一个csvwrite函数

void loadFromCSV( const std::string& filename )
{
    std::ifstream       file( filename.c_str() );
    std::vector< std::vector<std::string> >   matrix;
    std::vector<std::string>   row;
    std::string                line;
    std::string                cell;

    while( file )
    {
        std::getline(file,line);
        std::stringstream lineStream(line);
        row.clear();

        while( std::getline( lineStream, cell, ',' ) )
            row.push_back( cell );

        if( !row.empty() )
            matrix.push_back( row );
    }

    for( int i=0; i<int(matrix.size()); i++ )
    {
        for( int j=0; j<int(matrix[i].size()); j++ )
            std::cout << matrix[i][j] << " ";

        std::cout << std::endl;
    }
}

你可能想看看我的自由/开源软件项目CSVfix(更新链接)，这是一个用c++编写的CSV流编辑器。CSV解析器不是什么好东西，但它完成了工作，整个包可以在不编写任何代码的情况下满足您的需要。

CSV解析器请参见alib/src/a_csv.cpp，使用示例请参见csvlib/src/csved_ioman.cpp (IOManager::ReadCSV)。

你可以使用这个库: https://github.com/vadamsky/csvworker

代码示例:

#include <iostream>
#include "csvworker.h"

using namespace std;

int main()
{
    //
    CsvWorker csv;
    csv.loadFromFile("example.csv");
    cout << csv.getRowsNumber() << "  " << csv.getColumnsNumber() << endl;

    csv.getFieldRef(0, 2) = "0";
    csv.getFieldRef(1, 1) = "0";
    csv.getFieldRef(1, 3) = "0";
    csv.getFieldRef(2, 0) = "0";
    csv.getFieldRef(2, 4) = "0";
    csv.getFieldRef(3, 1) = "0";
    csv.getFieldRef(3, 3) = "0";
    csv.getFieldRef(4, 2) = "0";

    for(unsigned int i=0;i<csv.getRowsNumber();++i)
    {
        //cout << csv.getRow(i) << endl;
        for(unsigned int j=0;j<csv.getColumnsNumber();++j)
        {
            cout << csv.getField(i, j) << ".";
        }
        cout << endl;
    }

    csv.saveToFile("test.csv");

    //
    CsvWorker csv2(4,4);

    csv2.getFieldRef(0, 0) = "a";
    csv2.getFieldRef(0, 1) = "b";
    csv2.getFieldRef(0, 2) = "r";
    csv2.getFieldRef(0, 3) = "a";
    csv2.getFieldRef(1, 0) = "c";
    csv2.getFieldRef(1, 1) = "a";
    csv2.getFieldRef(1, 2) = "d";
    csv2.getFieldRef(2, 0) = "a";
    csv2.getFieldRef(2, 1) = "b";
    csv2.getFieldRef(2, 2) = "r";
    csv2.getFieldRef(2, 3) = "a";

    csv2.saveToFile("test2.csv");

    return 0;
}