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appedcsv

Linux	蘋果	視窗

appedcsv是一個易於使用的C ++ CSV解析器庫。它支持C ++ 11（後來），僅標題，並帶有基本的測試套件。

該圖書館在C ++ 20書中介紹了程序員。

示例用法

這是一個簡單的示例，讀取CSV文件並將“關閉”列作為浮子的向量。

colhdr.csv內容：

 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內容：

# 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;
}

有關更多示例，請參閱下面的更多示例。測試目錄還包含許多簡單的用法示例。

支持的平台

使用C ++ 11實施了MaparCSV，目的是要便攜。它已在：

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

安裝

只需將src/appapcsv.h複製到您的項目/包括目錄並包括該目錄。

也可以通過VCPKG和Conan軟件包經理獲得Maparcsv。

用列和行標頭讀取文件

默認情況下，Raptcsv將第一行視為列標題，第一行被視為數據。這允許使用其標籤訪問列，而不能使用行或單元格（僅使用指數）。為了將第一列視為行標頭，需要使用labelParams並將prownameidx設置為0。

列和行標頭

colrowhdr.csv內容：

 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內容：

# 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;
}

僅行標題

rowhdr.csv內容：

 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內容：

# 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;
}

沒有標題

nohdr.csv內容：

 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內容：

# 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;
}

使用自定義分離器讀取文件

為了讀取使用自定義分離器（即不是逗號）的文件，需要指定sameatorParams參數。以下示例使用半彩色作為分隔符讀取文件。

SEMI.CSV內容：

 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內容：

# 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;
}

支持的獲取/設置數據類型

文檔類中的內部單元格表示使用STD :: String，並且當請求其他類型時，使用標準轉換例程。所有標準轉換都是相對直接的，除了char的char以外，appcsv將單元格（第一個）字節解釋為字符。以下示例說明了受支持的數據類型。

colrowhdr.csv內容：

 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內容：

# 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;
}

全局自定義數據類型轉換

可以通過實現TOVAL（）和/或TOSTR（）來覆蓋轉換例程（或添加新的例程）。下面是一個示例覆蓋INT轉換，而是提供兩個小數點定點編號。另請參見測試/test035.cpp，以進行測試覆蓋TOVAL（）和TOSTR（）。

EX008.CPP內容：

# 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;
}

每個呼叫的自定義數據類型轉換

也可以按每句話覆蓋轉換，從而提高靈活性。以下示例中說明了這一點。可以在測試測試/test063.cpp中找到其他轉換替代用法

EX009.CPP內容：

# 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 " ;
}

從流或字符串讀取CSV數據

除了指定文件名外，MaparCSV還支持從流並通過StringStream間接構建文檔，並從字符串中間接構建文檔。與MappCSV一起使用的文件流應在std::ios::binary模式中打開，以啟用完整功能。這是一個簡單的示例，從字符串讀取CSV數據：

EX007.CPP內容：

# 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;
}

讀取具有無效數字（例如空單元）作為數字數據的文件

默認情況下，如果人們試圖將非數字數據訪問數字數據類型，則會引發異常，因為它基本上傳播了基礎轉換例程對調用應用程序的異常。

這樣做的原因是確保數據正確性。如果一個人希望能夠將具有無效數字的數據讀取為數字數據類型，則可以使用ConverterParams將轉換器配置為默認值為數字值。該值是可配置的，默認情況下它的std :: numeric_limits :: Signaling_nan（）用於float類型，而整數類型為0。例子：

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

檢查列是否存在

appedcsv提供方法getColumnNames（）和getRownames（）來檢索列和行名。要檢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());

處理引用的細胞

默認情況下，apparcsv會自動取消引用的單元格（IE刪除了"example quoted cell"中的"字符”）。該功能可以通過傳遞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 */ ));

跳動並評論線

默認情況下，Maparcsv讀取所有行，但可以被要求忽略以特定字符開頭的評論行，例如：

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

使用LinereaderParams也可以跳過空線，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對非ASCII文本的首選編碼是UTF-8。可以在存在CodeCvt標頭的系統上讀取和撰寫UTF-16 LE和UTF-16。在包含ropaipcsv.h之前定義has_codecvt，以啟用功能。 RapidCSV單元測試會自動檢測到codecvt的存在，並根據需要檢測has_codecvt的存在，請參見cmakelists.txt以獲取參考。啟用後，將自動檢測到任何加載文件的UTF-16編碼。

cmake提取

使用FetchContent的CMAKE項目中可能包括MaparCSV。請參閱cmake提取示例項目，尤其是其cmakelists.txt。

語言獨立解析

當默認情況下解析float值時，appedcsv使用LOCALE依賴性轉換函數。可以通過在ConverterParams中設置mNumericLocale來配置Maparcsv使用Locale Indepenlate解析，例如，請參見測試/test087.cpp

API文檔

以下類構成了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>

技術細節

Maparcsv使用Cmake進行測試。命令構建和執行測試套件：

 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文檔：

 doxygenmd src doc

Mappcsv使用不穩定來確保一致的代碼格式：

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

替代方案

例如，C ++有許多CSV解析器：

快速C ++ CSV解析器
文斯的CSV解析器

執照

MaparCSV根據BSD 3條規定許可分配。請參閱許可證文件。

貢獻

歡迎在GitHub項目頁面https://github.com/d99kris/rapidcsv上進行錯誤，PRS等

關鍵字

C ++，C ++ 11，CSV解析器，逗號分隔值，單頭庫。

展開

rapidcsv