Decodes a comma-separated variables (CSV) data format into a C++ data structure.
#include <jsoncons_ext/csv/csv.hpp>
template <typename T,class Source>
T decode_csv(const Source& s,
const basic_csv_decode_options<CharT>& options = basic_csv_decode_options<CharT>())); (1)
template <typename T,class CharT>
T decode_csv(std::basic_istream<CharT>& is,
const basic_csv_decode_options<CharT>& options = basic_csv_decode_options<CharT>())); (2)
template <typename T,class InputIt>
T decode_csv(InputIt first, InputIt last,
const basic_csv_decode_options<CharT>& options = basic_csv_decode_options<CharT>())); (3) (since 0.153.0)
template <typename T,typename Source,typename Allocator,typename TempAllocator>
T decode_csv(allocator_set<Allocator,TempAllocator> alloc_set,
const Source& s,
const basic_csv_decode_options<Source::value_type>& options = basic_csv_decode_options<Source::value_type>()); (4)
template <typename T,typename CharT,typename Allocator,typename TempAllocator>
T decode_csv(allocator_set<Allocator,TempAllocator> alloc_set,
std::basic_istream<CharT>& is,
const basic_csv_decode_options<CharT>& options = basic_csv_decode_options<CharT>()); (5)(1) Reads CSV data from a contiguous character sequence into a type T, using the specified (or defaulted) options. Type 'T' must be an instantiation of basic_json or support json_type_traits.
(2) Reads CSV data from an input stream into a type T, using the specified (or defaulted) options. Type 'T' must be an instantiation of basic_json or support json_type_traits.
(3) Reads CSV data from the range [first,last) into a type T, using the specified (or defaulted) options.
Type 'T' must be an instantiation of basic_json
or support json_type_traits.
Functions (4)-(5) are identical to (1)-(2) except an allocator_set is passed as an additional argument and provides allocators for result data and temporary allocations.
Returns a value of type T.
Throws a ser_error if parsing fails, and a conv_error if type conversion fails.
Example file (sales.csv)
customer_name,has_coupon,phone_number,zip_code,sales_tax_rate,total_amount
"John Roe",true,0272561313,01001,0.05,431.65
"Jane Doe",false,416-272-2561,55416,0.15,480.70
"Joe Bloggs",false,"4162722561","55416",0.15,300.70
"John Smith",FALSE,NULL,22313-1450,0.15,300.70
#include <jsoncons/json.hpp>
#include <jsoncons_ext/csv/csv.hpp>
#include <fstream>
using namespace jsoncons;
int main()
{
auto options = csv::csv_options{}
.assume_header(true)
.mapping_kind(csv::csv_mapping_kind::n_objects);
std::ifstream is1("input/sales.csv");
ojson j1 = csv::decode_csv<ojson>(is1,options);
std::cout << "\n(1)\n"<< pretty_print(j1) << "\n";
options.mapping_kind(csv::csv_mapping_kind::n_rows);
std::ifstream is2("input/sales.csv");
ojson j2 = csv::decode_csv<ojson>(is2,options);
std::cout << "\n(2)\n"<< pretty_print(j2) << "\n";
options.mapping_kind(csv::csv_mapping_kind::m_columns);
std::ifstream is3("input/sales.csv");
ojson j3 = csv::decode_csv<ojson>(is3,options);
std::cout << "\n(3)\n"<< pretty_print(j3) << "\n";
}Output:
(1)
[
{
"customer_name": "John Roe",
"has_coupon": true,
"phone_number": "0272561313",
"zip_code": "01001",
"sales_tax_rate": 0.05,
"total_amount": 431.65
},
{
"customer_name": "Jane Doe",
"has_coupon": false,
"phone_number": "416-272-2561",
"zip_code": 55416,
"sales_tax_rate": 0.15,
"total_amount": 480.7
},
{
"customer_name": "Joe Bloggs",
"has_coupon": false,
"phone_number": "4162722561",
"zip_code": "55416",
"sales_tax_rate": 0.15,
"total_amount": 300.7
},
{
"customer_name": "John Smith",
"has_coupon": false,
"phone_number": null,
"zip_code": "22313-1450",
"sales_tax_rate": 0.15,
"total_amount": 300.7
}
]
(2)
[
["customer_name","has_coupon","phone_number","zip_code","sales_tax_rate","total_amount"],
["John Roe",true,"0272561313","01001",0.05,431.65],
["Jane Doe",false,"416-272-2561",55416,0.15,480.7],
["Joe Bloggs",false,"4162722561","55416",0.15,300.7],
["John Smith",false,null,"22313-1450",0.15,300.7]
]
(3)
{
"customer_name": ["John Roe","Jane Doe","Joe Bloggs","John Smith"],
"has_coupon": [true,false,false,false],
"phone_number": ["0272561313","416-272-2561",4162722561,null],
"zip_code": ["01001",55416,55416,"22313-1450"],
"sales_tax_rate": [0.05,0.15,0.15,0.15],
"total_amount": [431.65,480.7,300.7,300.7]
}#include <jsoncons/json.hpp>
#include <jsoncons_ext/csv/csv.hpp>
using namespace jsoncons;
int main()
{
std::string s = R"(employee-no,employee-name,dept,salary
00000001,"Smith,Matthew",sales,150000.00
00000002,"Brown,Sarah",sales,89000.00
)";
auto options = csv::csv_options{}
.assume_header(true)
.infer_types(false);
ojson j = csv::decode_csv<ojson>(s,options);
std::cout << pretty_print(j) << std::endl;
}Output:
[
{
"employee-no": "00000001",
"employee-name": "Smith,Matthew",
"dept": "sales",
"salary": "150000.00"
},
{
"employee-no": "00000002",
"employee-name": "Brown,Sarah",
"dept": "sales",
"salary": "89000.00"
}
]#include <jsoncons/json.hpp>
#include <jsoncons_ext/csv/csv.hpp>
using namespace jsoncons;
int main()
{
const std::string s = R"(Date,1Y,2Y,3Y,5Y
2017-01-09,0.0062,0.0075,0.0083,0.011
2017-01-08,0.0063,0.0076,0.0084,0.0112
2017-01-08,0.0063,0.0076,0.0084,0.0112
)";
auto options = csv::csv_options{}
.assume_header(true)
.column_types("string,float,float,float,float");
// csv_mapping_kind::n_objects
options.mapping_kind(csv::csv_mapping_kind::n_objects);
ojson j1 = csv::decode_csv<ojson>(s,options);
std::cout << "\n(1)\n"<< pretty_print(j1) << "\n";
// csv_mapping_kind::n_rows
options.mapping_kind(csv::csv_mapping_kind::n_rows);
ojson j2 = csv::decode_csv<ojson>(s,options);
std::cout << "\n(2)\n"<< pretty_print(j2) << "\n";
// csv_mapping_kind::m_columns
options.mapping_kind(csv::csv_mapping_kind::m_columns);
ojson j3 = csv::decode_csv<ojson>(s,options);
std::cout << "\n(3)\n" << pretty_print(j3) << "\n";
}Output:
(1)
[
{
"Date": "2017-01-09",
"1Y": 0.0062,
"2Y": 0.0075,
"3Y": 0.0083,
"5Y": 0.011
},
{
"Date": "2017-01-08",
"1Y": 0.0063,
"2Y": 0.0076,
"3Y": 0.0084,
"5Y": 0.0112
},
{
"Date": "2017-01-08",
"1Y": 0.0063,
"2Y": 0.0076,
"3Y": 0.0084,
"5Y": 0.0112
}
]
(2)
[
["Date","1Y","2Y","3Y","5Y"],
["2017-01-09",0.0062,0.0075,0.0083,0.011],
["2017-01-08",0.0063,0.0076,0.0084,0.0112],
["2017-01-08",0.0063,0.0076,0.0084,0.0112]
]
(3)
{
"Date": ["2017-01-09","2017-01-08","2017-01-08"],
"1Y": [0.0062,0.0063,0.0063],
"2Y": [0.0075,0.0076,0.0076],
"3Y": [0.0083,0.0084,0.0084],
"5Y": [0.011,0.0112,0.0112]
}#include <jsoncons/json.hpp>
#include <jsoncons_ext/csv/csv.hpp>
using namespace jsoncons;
int main()
{
const std::string s = R"(calculationPeriodCenters,paymentCenters,resetCenters
NY;LON,TOR,LON
NY,LON,TOR;LON
"NY";"LON","TOR","LON"
"NY","LON","TOR";"LON"
)";
auto print_options = json_options{}
.array_array_line_splits(line_split_kind::same_line);
auto options1 = csv::csv_options{}
.assume_header(true)
.subfield_delimiter(';');
json j1 = csv::decode_csv<json>(s,options1);
std::cout << "(1)\n" << pretty_print(j1,print_options) << "\n\n";
auto options2 = csv::csv_options{}
.mapping_kind(csv::csv_mapping_kind::n_rows)
.subfield_delimiter(';');
json j2 = csv::decode_csv<json>(s,options2);
std::cout << "(2)\n" << pretty_print(j2,print_options) << "\n\n";
auto options3 = csv::csv_options{}
assume_header(true)
.mapping_kind(csv::csv_mapping_kind::m_columns)
.subfield_delimiter(';');
json j3 = csv::decode_csv<json>(s,options3);
std::cout << "(3)\n" << pretty_print(j3,print_options) << "\n\n";
}Output:
(1)
[
{
"calculationPeriodCenters": ["NY","LON"],
"paymentCenters": "TOR",
"resetCenters": "LON"
},
{
"calculationPeriodCenters": "NY",
"paymentCenters": "LON",
"resetCenters": ["TOR","LON"]
},
{
"calculationPeriodCenters": ["NY","LON"],
"paymentCenters": "TOR",
"resetCenters": "LON"
},
{
"calculationPeriodCenters": "NY",
"paymentCenters": "LON",
"resetCenters": ["TOR","LON"]
}
]
(2)
[
["calculationPeriodCenters","paymentCenters","resetCenters"],
[["NY","LON"],"TOR","LON"],
["NY","LON",["TOR","LON"]],
[["NY","LON"],"TOR","LON"],
["NY","LON",["TOR","LON"]]
]
(3)
{
"calculationPeriodCenters": [["NY","LON"],"NY",["NY","LON"],"NY"],
"paymentCenters": ["TOR","LON","TOR","LON"],
"resetCenters": ["LON",["TOR","LON"],"LON",["TOR","LON"]]
}Convert a CSV source to a C++ data structure that satisfies json_type_traits requirements, and back
#include <jsoncons/json.hpp>
#include <jsoncons_ext/csv/csv.hpp>
#include <iostream>
using namespace jsoncons;
int main()
{
const std::string input = R"(Date,1Y,2Y,3Y,5Y
2017-01-09,0.0062,0.0075,0.0083,0.011
2017-01-08,0.0063,0.0076,0.0084,0.0112
2017-01-08,0.0063,0.0076,0.0084,0.0112
)";
auto ioptions = csv::csv_options{}
.header_lines(1)
.mapping_kind(csv::csv_mapping_kind::n_rows);
using table_type = std::vector<std::tuple<std::string,double,double,double,double>>;
table_type table = csv::decode_csv<table_type>(input,ioptions);
std::cout << "(1)\n";
for (const auto& row : table)
{
std::cout << std::get<0>(row) << ","
<< std::get<1>(row) << ","
<< std::get<2>(row) << ","
<< std::get<3>(row) << ","
<< std::get<4>(row) << "\n";
}
std::cout << "\n";
std::string output;
auto ooptions = csv::csv_options{}
.column_names("Date,1Y,2Y,3Y,5Y");
csv::encode_csv<table_type>(table, output, ooptions);
std::cout << "(2)\n";
std::cout << output << "\n";
}Output:
(1)
2017-01-09,0.0062,0.0075,0.0083,0.011
2017-01-08,0.0063,0.0076,0.0084,0.011
2017-01-08,0.0063,0.0076,0.0084,0.011
(2)
Date,1Y,2Y,3Y,5Y
2017-01-09,0.0062,0.0075,0.0083,0.011
2017-01-08,0.0063,0.0076,0.0084,0.0112
2017-01-08,0.0063,0.0076,0.0084,0.0112