如何在 C++ 中读取和操作 CSV 文件数据?
时间：2022-11-21问题描述
不言自明，我试过谷歌并得到了很多可怕的专家交流，我也在这里搜索无济于事.最好是在线教程或示例.谢谢各位.
Pretty self-explanatory, I tried google and got a lot of the dreaded expertsexchange, I searched here as well to no avail. An online tutorial or example would be best. Thanks guys.
推荐答案
如果您真正要做的是操作 CSV 文件本身，那么 Nelson 的回答是有道理的.但是，我怀疑 CSV 只是您正在解决的问题的产物.在 C++ 中，这可能意味着您的数据模型是这样的:
If what you're really doing is manipulating a CSV file itself, Nelson's answer makes sense. However, my suspicion is that the CSV is simply an artifact of the problem you're solving. In C++, that probably means you have something like this as your data model:
struct Customer {
int id;
std::string first_name;
std::string last_name;
struct {
std::string street;
std::string unit;
} address;
char state[2];
int zip;
};
因此，当您处理一组数据时，使用 std::vector 或 std::set 是有意义的.
Thus, when you're working with a collection of data, it makes sense to have std::vector<Customer> or std::set<Customer>.
考虑到这一点，请将您的 CSV 处理视为两个操作:
With that in mind, think of your CSV handling as two operations:
// if you wanted to go nuts, you could use a forward iterator concept for both of these
class CSVReader {
public:
CSVReader(const std::string &inputFile);
bool hasNextLine();
void readNextLine(std::vector<std::string> &fields);
private:
/* secrets */
};
class CSVWriter {
public:
CSVWriter(const std::string &outputFile);
void writeNextLine(const std::vector<std::string> &fields);
private:
/* more secrets */
};
void readCustomers(CSVReader &reader, std::vector<Customer> &customers);
void writeCustomers(CSVWriter &writer, const std::vector<Customer> &customers);
一次读取和写入一行，而不是保留文件本身的完整内存表示.有几个明显的好处:
Read and write a single row at a time, rather than keeping a complete in-memory representation of the file itself. There are a few obvious benefits:
- 您的数据以对您的问题(客户)有意义的形式表示，而不是当前的解决方案(CSV 文件).
- 您可以轻松地为其他数据格式添加适配器，例如批量 SQL 导入/导出、Excel/OO 电子表格文件，甚至 HTML
渲染.
- 您的内存占用可能更小(取决于相对
sizeof(Customer)与单行中的字节数).CSVReader和CSVWriter可以作为内存模型(例如 Nelson 的)的基础而重复使用，而不会损失性能或功能.反之则不然.- Your data is represented in a form that makes sense for your problem (customers), rather than the current solution (CSV files).
- You can trivially add adapters for other data formats, such as bulk SQL import/export, Excel/OO spreadsheet files, or even an HTML
<table>rendering. - Your memory footprint is likely to be smaller (depends on relative
sizeof(Customer)vs. the number of bytes in a single row). CSVReaderandCSVWritercan be reused as the basis for an in-memory model (such as Nelson's) without loss of performance or functionality. The converse is not true.
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- 您的内存占用可能更小(取决于相对