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。

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;
    }
}

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。

使用Spirit来解析csv并不过分。Spirit非常适合微解析任务。例如，使用Spirit 2.1，它就像:

bool r = phrase_parse(first, last,

    //  Begin grammar
    (
        double_ % ','
    )
    ,
    //  End grammar

    space, v);

向量v被值填满了。在刚刚与Boost 1.41一起发布的新的Spirit 2.1文档中，有一系列教程涉及到这一点。

本教程从简单到复杂。CSV解析器呈现在中间的某个位置，并涉及使用Spirit的各种技术。生成的代码与手写代码一样紧凑。检查生成的汇编程序!

不管怎样，下面是我的实现。它处理wstring输入，但是可以很容易地调整为string。它不处理字段中的换行符(因为我的应用程序也不这样做，但添加它的支持并不太难)，它不符合RFC中的“\r\n”行尾(假设您使用std::getline)，但它确实正确地处理空格修剪和双引号(希望如此)。

using namespace std;

// trim whitespaces around field or double-quotes, remove double-quotes and replace escaped double-quotes (double double-quotes)
wstring trimquote(const wstring& str, const wstring& whitespace, const wchar_t quotChar)
{
    wstring ws;
    wstring::size_type strBegin = str.find_first_not_of(whitespace);
    if (strBegin == wstring::npos)
        return L"";

    wstring::size_type strEnd = str.find_last_not_of(whitespace);
    wstring::size_type strRange = strEnd - strBegin + 1;

    if((str[strBegin] == quotChar) && (str[strEnd] == quotChar))
    {
        ws = str.substr(strBegin+1, strRange-2);
        strBegin = 0;
        while((strEnd = ws.find(quotChar, strBegin)) != wstring::npos)
        {
            ws.erase(strEnd, 1);
            strBegin = strEnd+1;
        }

    }
    else
        ws = str.substr(strBegin, strRange);
    return ws;
}

pair<unsigned, unsigned> nextCSVQuotePair(const wstring& line, const wchar_t quotChar, unsigned ofs = 0)
{
    pair<unsigned, unsigned> r;
    r.first = line.find(quotChar, ofs);
    r.second = wstring::npos;
    if(r.first != wstring::npos)
    {
        r.second = r.first;
        while(((r.second = line.find(quotChar, r.second+1)) != wstring::npos)
            && (line[r.second+1] == quotChar)) // WARNING: assumes null-terminated string such that line[r.second+1] always exist
            r.second++;

    }
    return r;
}

unsigned parseLine(vector<wstring>& fields, const wstring& line)
{
    unsigned ofs, ofs0, np;
    const wchar_t delim = L',';
    const wstring whitespace = L" \t\xa0\x3000\x2000\x2001\x2002\x2003\x2004\x2005\x2006\x2007\x2008\x2009\x200a\x202f\x205f";
    const wchar_t quotChar = L'\"';
    pair<unsigned, unsigned> quot;

    fields.clear();

    ofs = ofs0 = 0;
    quot = nextCSVQuotePair(line, quotChar);
    while((np = line.find(delim, ofs)) != wstring::npos)
    {
        if((np > quot.first) && (np < quot.second))
        { // skip delimiter inside quoted field
            ofs = quot.second+1;
            quot = nextCSVQuotePair(line, quotChar, ofs);
            continue;
        }
        fields.push_back( trimquote(line.substr(ofs0, np-ofs0), whitespace, quotChar) );
        ofs = ofs0 = np+1;
    }
    fields.push_back( trimquote(line.substr(ofs0), whitespace, quotChar) );

    return fields.size();
}

您可以使用仅头文件的Csv::Parser库。

它完全支持RFC 4180，包括字段值中的引号、转义引号和换行。 它只需要标准的c++ (c++ 17)。 它支持在编译时从std::string_view读取CSV数据。 它使用Catch2进行了广泛的测试。