该解决方案检测这4种情况

完整的课程在

https://github.com/pedro-vicente/csv-parser

1,field 2,field 3,
1,field 2,"field 3 quoted, with separator",
1,field 2,"field 3
with newline",
1,field 2,"field 3
with newline and separator,",

它一个字符一个字符地读取文件，每次读取一行到一个向量(字符串)，因此适合于非常大的文件。

使用

迭代直到返回空行(文件结束)。行是一个向量，其中每个条目都是一个CSV列。

read_csv_t csv;
csv.open("../test.csv");
std::vector<std::string> row;
while (true)
{
  row = csv.read_row();
  if (row.size() == 0)
  {
    break;
  }
}

类声明

class read_csv_t
{
public:
  read_csv_t();
  int open(const std::string &file_name);
  std::vector<std::string> read_row();
private:
  std::ifstream m_ifs;
};

实现

std::vector<std::string> read_csv_t::read_row()
{
  bool quote_mode = false;
  std::vector<std::string> row;
  std::string column;
  char c;
  while (m_ifs.get(c))
  {
    switch (c)
    {
      /////////////////////////////////////////////////////////////////////////////////////////////////////
      //separator ',' detected. 
      //in quote mode add character to column
      //push column if not in quote mode
      /////////////////////////////////////////////////////////////////////////////////////////////////////

    case ',':
      if (quote_mode == true)
      {
        column += c;
      }
      else
      {
        row.push_back(column);
        column.clear();
      }
      break;

      /////////////////////////////////////////////////////////////////////////////////////////////////////
      //quote '"' detected. 
      //toggle quote mode
      /////////////////////////////////////////////////////////////////////////////////////////////////////

    case '"':
      quote_mode = !quote_mode;
      break;

      /////////////////////////////////////////////////////////////////////////////////////////////////////
      //line end detected
      //in quote mode add character to column
      //return row if not in quote mode
      /////////////////////////////////////////////////////////////////////////////////////////////////////

    case '\n':
    case '\r':
      if (quote_mode == true)
      {
        column += c;
      }
      else
      {
        return row;
      }
      break;

      /////////////////////////////////////////////////////////////////////////////////////////////////////
      //default, add character to column
      /////////////////////////////////////////////////////////////////////////////////////////////////////

    default:
      column += c;
      break;
    }
  }

  //return empty vector if end of file detected 
  m_ifs.close();
  std::vector<std::string> v;
  return v;
}

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);
    }

我写了一个很好的解析CSV文件的方法，我认为我应该把它作为一个答案:

#include <algorithm>
#include <fstream>
#include <iostream>
#include <stdlib.h>
#include <stdio.h>

struct CSVDict
{
  std::vector< std::string > inputImages;
  std::vector< double > inputLabels;
};

/**
\brief Splits the string

\param str String to split
\param delim Delimiter on the basis of which splitting is to be done
\return results Output in the form of vector of strings
*/
std::vector<std::string> stringSplit( const std::string &str, const std::string &delim )
{
  std::vector<std::string> results;

  for (size_t i = 0; i < str.length(); i++)
  {
    std::string tempString = "";
    while ((str[i] != *delim.c_str()) && (i < str.length()))
    {
      tempString += str[i];
      i++;
    }
    results.push_back(tempString);
  }

  return results;
}

/**
\brief Parse the supplied CSV File and obtain Row and Column information. 

Assumptions:
1. Header information is in first row
2. Delimiters are only used to differentiate cell members

\param csvFileName The full path of the file to parse
\param inputColumns The string of input columns which contain the data to be used for further processing
\param inputLabels The string of input labels based on which further processing is to be done
\param delim The delimiters used in inputColumns and inputLabels
\return Vector of Vector of strings: Collection of rows and columns
*/
std::vector< CSVDict > parseCSVFile( const std::string &csvFileName, const std::string &inputColumns, const std::string &inputLabels, const std::string &delim )
{
  std::vector< CSVDict > return_CSVDict;
  std::vector< std::string > inputColumnsVec = stringSplit(inputColumns, delim), inputLabelsVec = stringSplit(inputLabels, delim);
  std::vector< std::vector< std::string > > returnVector;
  std::ifstream inFile(csvFileName.c_str());
  int row = 0;
  std::vector< size_t > inputColumnIndeces, inputLabelIndeces;
  for (std::string line; std::getline(inFile, line, '\n');)
  {
    CSVDict tempDict;
    std::vector< std::string > rowVec;
    line.erase(std::remove(line.begin(), line.end(), '"'), line.end());
    rowVec = stringSplit(line, delim);

    // for the first row, record the indeces of the inputColumns and inputLabels
    if (row == 0)
    {
      for (size_t i = 0; i < rowVec.size(); i++)
      {
        for (size_t j = 0; j < inputColumnsVec.size(); j++)
        {
          if (rowVec[i] == inputColumnsVec[j])
          {
            inputColumnIndeces.push_back(i);
          }
        }
        for (size_t j = 0; j < inputLabelsVec.size(); j++)
        {
          if (rowVec[i] == inputLabelsVec[j])
          {
            inputLabelIndeces.push_back(i);
          }
        }
      }
    }
    else
    {
      for (size_t i = 0; i < inputColumnIndeces.size(); i++)
      {
        tempDict.inputImages.push_back(rowVec[inputColumnIndeces[i]]);
      }
      for (size_t i = 0; i < inputLabelIndeces.size(); i++)
      {
        double test = std::atof(rowVec[inputLabelIndeces[i]].c_str());
        tempDict.inputLabels.push_back(std::atof(rowVec[inputLabelIndeces[i]].c_str()));
      }
      return_CSVDict.push_back(tempDict);
    }
    row++;
  }

  return return_CSVDict;
}

我需要一个易于使用的c++库来解析CSV文件，但找不到任何可用的库，所以我最终构建了一个。 Rapidcsv是一个c++ 11的纯头库，它可以直接访问已解析的列(或行)，作为选择的数据类型的向量。例如:

#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;
}

使用Boost Tokenizer的解决方案:

std::vector<std::string> vec;
using namespace boost;
tokenizer<escaped_list_separator<char> > tk(
   line, escaped_list_separator<char>('\\', ',', '\"'));
for (tokenizer<escaped_list_separator<char> >::iterator i(tk.begin());
   i!=tk.end();++i) 
{
   vec.push_back(*i);
}

另一个CSV I/O库可以在这里找到:

http://code.google.com/p/fast-cpp-csv-parser/

#include "csv.h"

int main(){
  io::CSVReader<3> in("ram.csv");
  in.read_header(io::ignore_extra_column, "vendor", "size", "speed");
  std::string vendor; int size; double speed;
  while(in.read_row(vendor, size, speed)){
    // do stuff with the data
  }
}