我需要在c++中加载和使用CSV文件数据。在这一点上,它实际上只是一个以逗号分隔的解析器(即不用担心转义新行和逗号)。主要需要的是逐行解析器,它将在每次调用方法时为下一行返回一个向量。
我发现这篇文章看起来很有前途: http://www.boost.org/doc/libs/1_35_0/libs/spirit/example/fundamental/list_parser.cpp
我从未使用过Boost's Spirit,但我愿意尝试一下。但前提是我忽略了一个更直接的解决方案。
我需要在c++中加载和使用CSV文件数据。在这一点上,它实际上只是一个以逗号分隔的解析器(即不用担心转义新行和逗号)。主要需要的是逐行解析器,它将在每次调用方法时为下一行返回一个向量。
我发现这篇文章看起来很有前途: http://www.boost.org/doc/libs/1_35_0/libs/spirit/example/fundamental/list_parser.cpp
我从未使用过Boost's Spirit,但我愿意尝试一下。但前提是我忽略了一个更直接的解决方案。
当前回答
可以使用std::regex。
根据文件大小和可用内存,可以逐行读取,也可以完全在std::string中读取。
读取文件可以使用:
std::ifstream t("file.txt");
std::string sin((std::istreambuf_iterator<char>(t)),
std::istreambuf_iterator<char>());
然后你可以和这个相匹配,它实际上是根据你的需要定制的。
std::regex word_regex(",\\s]+");
auto what =
std::sregex_iterator(sin.begin(), sin.end(), word_regex);
auto wend = std::sregex_iterator();
std::vector<std::string> v;
for (;what!=wend ; wend) {
std::smatch match = *what;
v.push_back(match.str());
}
其他回答
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
}
}
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。
您需要做的第一件事是确保文件存在。来完成 这你只需要尝试打开文件流的路径。在你 打开文件流使用stream.fail()查看它是否如预期的那样工作, 与否。
bool fileExists(string fileName)
{
ifstream test;
test.open(fileName.c_str());
if (test.fail())
{
test.close();
return false;
}
else
{
test.close();
return true;
}
}
您还必须验证所提供的文件是正确的文件类型。 要做到这一点,您需要查看提供的文件路径直到 您可以找到文件扩展名。一旦你有了文件扩展名,请确保 它是一个。csv文件。
bool verifyExtension(string filename)
{
int period = 0;
for (unsigned int i = 0; i < filename.length(); i++)
{
if (filename[i] == '.')
period = i;
}
string extension;
for (unsigned int i = period; i < filename.length(); i++)
extension += filename[i];
if (extension == ".csv")
return true;
else
return false;
}
此函数将返回稍后在错误消息中使用的文件扩展名。
string getExtension(string filename)
{
int period = 0;
for (unsigned int i = 0; i < filename.length(); i++)
{
if (filename[i] == '.')
period = i;
}
string extension;
if (period != 0)
{
for (unsigned int i = period; i < filename.length(); i++)
extension += filename[i];
}
else
extension = "NO FILE";
return extension;
}
这个函数实际上会调用上面创建的错误检查,然后解析文件。
void parseFile(string fileName)
{
if (fileExists(fileName) && verifyExtension(fileName))
{
ifstream fs;
fs.open(fileName.c_str());
string fileCommand;
while (fs.good())
{
string temp;
getline(fs, fileCommand, '\n');
for (unsigned int i = 0; i < fileCommand.length(); i++)
{
if (fileCommand[i] != ',')
temp += fileCommand[i];
else
temp += " ";
}
if (temp != "\0")
{
// Place your code here to run the file.
}
}
fs.close();
}
else if (!fileExists(fileName))
{
cout << "Error: The provided file does not exist: " << fileName << endl;
if (!verifyExtension(fileName))
{
if (getExtension(fileName) != "NO FILE")
cout << "\tCheck the file extension." << endl;
else
cout << "\tThere is no file in the provided path." << endl;
}
}
else if (!verifyExtension(fileName))
{
if (getExtension(fileName) != "NO FILE")
cout << "Incorrect file extension provided: " << getExtension(fileName) << endl;
else
cout << "There is no file in the following path: " << fileName << endl;
}
}
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...
}
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);
}