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appedcsv

Linux	苹果	视窗

appedcsv是一个易于使用的C ++ CSV解析器库。它支持C ++ 11（后来），仅标题，并带有基本的测试套件。

该图书馆在C ++ 20书中介绍了程序员。

示例用法

这是一个简单的示例，读取CSV文件并将“关闭”列作为浮子的向量。

colhdr.csv内容：

 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内容：

# 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;
}

有关更多示例，请参阅下面的更多示例。测试目录还包含许多简单的用法示例。

支持的平台

使用C ++ 11实施了MaparCSV，目的是要便携。它已在：

Macos Ventura 13.0
Ubuntu 22.04 Lts
Windows 10 / Visual Studio 2019

安装

只需将src/appapcsv.h复制到您的项目/包括目录并包括该目录。

也可以通过VCPKG和Conan软件包经理获得Maparcsv。

用列和行标头读取文件

默认情况下，Raptcsv将第一行视为列标题，第一行被视为数据。这允许使用其标签访问列，而不能使用行或单元格（仅使用指数）。为了将第一列视为行标头，需要使用labelParams并将prownameidx设置为0。

列和行标头

colrowhdr.csv内容：

 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内容：

# 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;
}

仅行标题

rowhdr.csv内容：

 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内容：

# 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;
}

没有标题

nohdr.csv内容：

 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内容：

# 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;
}

使用自定义分离器读取文件

为了读取使用自定义分离器（即不是逗号）的文件，需要指定sameatorParams参数。以下示例使用半彩色作为分隔符读取文件。

SEMI.CSV内容：

 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内容：

# 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;
}

支持的获取/设置数据类型

文档类中的内部单元格表示使用STD :: String，并且当请求其他类型时，使用标准转换例程。所有标准转换都是相对直接的，除了char的char以外，appcsv将单元格（第一个）字节解释为字符。以下示例说明了受支持的数据类型。

colrowhdr.csv内容：

 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内容：

# 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;
}

全局自定义数据类型转换

可以通过实现TOVAL（）和/或TOSTR（）来覆盖转换例程（或添加新的例程）。下面是一个示例覆盖INT转换，而是提供两个小数点定点编号。另请参见测试/test035.cpp，以进行测试覆盖TOVAL（）和TOSTR（）。

EX008.CPP内容：

# 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;
}

每个呼叫的自定义数据类型转换

也可以按每句话覆盖转换，从而提高灵活性。以下示例中说明了这一点。可以在测试测试/test063.cpp中找到其他转换替代用法

EX009.CPP内容：

# 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 " ;
}

从流或字符串读取CSV数据

除了指定文件名外，MaparCSV还支持从流并通过StringStream间接构建文档，并从字符串中间接构建文档。与MappCSV一起使用的文件流应在std::ios::binary模式中打开，以启用完整功能。这是一个简单的示例，从字符串读取CSV数据：

EX007.CPP内容：

# 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;
}

读取具有无效数字（例如空单元）作为数字数据的文件

默认情况下，如果人们试图将非数字数据访问数字数据类型，则会引发异常，因为它基本上传播了基础转换例程对调用应用程序的异常。

这样做的原因是确保数据正确性。如果一个人希望能够将具有无效数字的数据读取为数字数据类型，则可以使用ConverterParams将转换器配置为默认值为数字值。该值是可配置的，默认情况下它的std :: numeric_limits :: Signaling_nan（）用于float类型，而整数类型为0。例子：

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

检查列是否存在

appedcsv提供方法getColumnNames（）和getRownames（）来检索列和行名。要检查特定列名是否存在，例如：

rapidcsv::Document doc ( " file.csv " );
std::vector<std::string> columnNames = doc.GetColumnNames();
bool columnExists =
  (std::find(columnNames.begin(), columnNames.end(), " A " ) != columnNames.end());

处理引用的细胞

默认情况下，apparcsv会自动取消引用的单元格（IE删除了"example quoted cell"中的"字符”）。该功能可以通过传递pAutoQuote = false在SeparatorParams中被禁用，示例：示例：

rapidcsv::Document doc ( " file.csv " , rapidcsv::LabelParams(),
                       rapidcsv::SeparatorParams( ' , ' /* pSeparator */ ,
                                                 false /* pTrim */ ,
                                                 rapidcsv:: sPlatformHasCR /* pHasCR */ ,
                                                 false /* pQuotedLinebreaks */ ,
                                                 false /* pAutoQuote */ ));

跳动并评论线

默认情况下，Maparcsv读取所有行，但可以被要求忽略以特定字符开头的评论行，例如：

rapidcsv::Document doc ( " file.csv " , rapidcsv::LabelParams(), rapidcsv::SeparatorParams(),
                       rapidcsv::ConverterParams(),
                       rapidcsv::LineReaderParams( true /* pSkipCommentLines */ ,
                                                  ' # ' /* pCommentPrefix */ ));

使用LinereaderParams也可以跳过空线，例如：

rapidcsv::Document doc ( " file.csv " , rapidcsv::LabelParams(), rapidcsv::SeparatorParams(),
                       rapidcsv::ConverterParams(),
                       rapidcsv::LineReaderParams( false /* pSkipCommentLines */ ,
                                                  ' # ' /* pCommentPrefix */ ,
                                                  true /* pSkipEmptyLines */ ));

UTF-16和UTF-8

appcsv对非ASCII文本的首选编码是UTF-8。可以在存在CodeCvt标头的系统上读取和撰写UTF-16 LE和UTF-16。在包含ropaipcsv.h之前定义has_codecvt，以启用功能。 RapidCSV单元测试会自动检测到codecvt的存在，并根据需要检测has_codecvt的存在，请参见cmakelists.txt以获取参考。启用后，将自动检测到任何加载文件的UTF-16编码。

cmake提取

使用FetchContent的CMAKE项目中可能包括MaparCSV。请参阅cmake提取示例项目，尤其是其cmakelists.txt。

语言独立解析

当默认情况下解析float值时，appedcsv使用LOCALE依赖性转换函数。可以通过在ConverterParams中设置mNumericLocale来配置Maparcsv使用Locale Indepenlate解析，例如，请参见测试/test087.cpp

API文档

以下类构成了appcsv接口：

Class Maparcsv :: Document
Class Maparcsv :: LabelParams
Class Maparcsv :: saparatorParams
Class Maparcsv :: ConverterParams
Class Maparcsv :: LinereaderParams
Class Maparcsv :: no_converter
Class Maparcsv :: Converter <t>

技术细节

Maparcsv使用Cmake进行测试。命令构建和执行测试套件：

 mkdir -p build && cd build && cmake -DRAPIDCSV_BUILD_TESTS=ON .. && make && ctest -C unit --output-on-failure && ctest -C perf --verbose ; cd -

MaparcSV使用doxygenmd生成其Markdown API文档：

 doxygenmd src doc

Mappcsv使用不稳定来确保一致的代码格式：

 uncrustify -c uncrustify.cfg --no-backup src/rapidcsv.h

替代方案

例如，C ++有许多CSV解析器：

快速C ++ CSV解析器
文斯的CSV解析器

执照

MaparCSV根据BSD 3条规定许可分配。请参阅许可证文件。

贡献

欢迎在GitHub项目页面https://github.com/d99kris/rapidcsv上进行错误，PRS等

关键字

C ++，C ++ 11，CSV解析器，逗号分隔值，单头库。

展开

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