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#ifndef TAKANE_CSV_DATA_FRAME_HPP
#define TAKANE_CSV_DATA_FRAME_HPP
#include "comservatory/comservatory.hpp"
#include "WrappedOption.hpp"
#include "data_frame.hpp"
#include "utils_csv.hpp"
#include <unordered_set>
#include <string>
#include <stdexcept>
/**
* @file csv_data_frame.hpp
* @brief Validation for CSV data frames.
*/
namespace takane {
/**
* @namespace takane::csv_data_frame
* @brief Definitions for CSV data frames.
*/
namespace csv_data_frame {
/**
* @brief Parameters for validating the CSV data frame.
*/
struct Parameters {
/**
* Number of rows in the data frame.
*/
size_t num_rows = 0;
/**
* Whether the data frame contains row names.
*/
bool has_row_names = false;
/**
* Details about the expected columns of the data frame, in order.
*/
WrappedOption<std::vector<data_frame::ColumnDetails> > columns;
/**
* Whether to load and parse the file in parallel, see `comservatory::ReadOptions` for details.
*/
bool parallel = false;
/**
* Version of the `data_frame` format.
*/
int df_version = 2;
};
/**
* @cond
*/
template<class ParseCommand>
CsvContents validate_base(ParseCommand parse, const Parameters& params, CsvFieldCreator* creator) {
DummyCsvFieldCreator default_creator;
if (creator == NULL) {
creator = &default_creator;
}
comservatory::Contents contents;
CsvContents output;
if (params.has_row_names) {
auto ptr = creator->string();
output.fields.emplace_back(ptr);
contents.fields.emplace_back(new CsvNameField(true, ptr));
}
const auto& columns = *(params.columns);
size_t ncol = columns.size();
std::unordered_set<std::string> present;
for (size_t c = 0; c < ncol; ++c) {
const auto& col = columns[c];
if (present.find(col.name) != present.end()) {
throw std::runtime_error("duplicate column name '" + col.name + "'");
}
present.insert(col.name);
if (col.type == data_frame::ColumnType::INTEGER) {
auto ptr = creator->integer();
output.fields.emplace_back(ptr);
contents.fields.emplace_back(new CsvIntegerField(c, ptr));
} else if (col.type == data_frame::ColumnType::NUMBER) {
output.fields.emplace_back(nullptr);
contents.fields.emplace_back(creator->number());
} else if (col.type == data_frame::ColumnType::STRING) {
if (col.string_format == data_frame::StringFormat::DATE) {
auto ptr = creator->string();
output.fields.emplace_back(ptr);
contents.fields.emplace_back(new CsvDateField(c, ptr));
} else if (col.string_format == data_frame::StringFormat::DATE_TIME) {
auto ptr = creator->string();
output.fields.emplace_back(ptr);
contents.fields.emplace_back(new CsvDateTimeField(c, ptr));
} else {
output.fields.emplace_back(nullptr);
contents.fields.emplace_back(creator->string());
}
} else if (col.type == data_frame::ColumnType::BOOLEAN) {
output.fields.emplace_back(nullptr);
contents.fields.emplace_back(creator->boolean());
} else if (col.type == data_frame::ColumnType::FACTOR) {
if (params.df_version == 1) {
auto ptr = creator->string();
output.fields.emplace_back(ptr);
contents.fields.emplace_back(new CsvFactorV1Field(c, col.factor_levels.get(), ptr));
} else {
auto ptr = creator->integer();
output.fields.emplace_back(ptr);
contents.fields.emplace_back(new CsvFactorV2Field(c, col.factor_levels->size(), ptr));
}
} else if (col.type == data_frame::ColumnType::OTHER) {
output.fields.emplace_back(nullptr);
contents.fields.emplace_back(new comservatory::UnknownField); // This can be anything.
} else {
throw std::runtime_error("unknown code for the expected column type");
}
}
comservatory::ReadOptions opt;
opt.parallel = params.parallel;
parse(contents, opt);
if (contents.num_records() != params.num_rows) {
throw std::runtime_error("number of records in the CSV file does not match the expected number of rows");
}
for (size_t c = 0; c < ncol; ++c) {
const auto& col = columns[c];
if (col.name != contents.names[c + params.has_row_names]) {
throw std::runtime_error("observed and expected header names do not match");
}
}
output.reconstitute(contents.fields);
return output;
}
/**
* @endcond
*/
/**
* Checks if a CSV data frame is correctly formatted.
* An error is raised if the file does not meet the specifications.
*
* @tparam Reader A **byteme** reader class.
*
* @param reader A stream of bytes from the CSV file.
* @param params Validation parameters.
* @param creator Factory to create objects for holding the contents of each CSV field.
* Defaults to a pointer to a `DummyFieldCreator` instance.
*
* @return Contents of the loaded CSV.
* Whether the `fields` member actually contains the CSV data depends on `creator`.
* Each entry of the `fields` member corresponds to an entry of `params.columns`,
* which an additional field at the start if `params.has_row_names = true`.
*/
template<class Reader>
CsvContents validate(Reader& reader, const Parameters& params, CsvFieldCreator* creator = NULL) {
return validate_base(
[&](comservatory::Contents& contents, const comservatory::ReadOptions& opt) -> void { comservatory::read(reader, contents, opt); },
params,
creator
);
}
/**
* Overload of `csv_data_frame::validate()` that accepts a file path.
*
* @param path Path to the CSV file.
* @param params Validation parameters.
* @param creator Factory to create objects for holding the contents of each CSV field.
* Defaults to a pointer to a `DummyFieldCreator` instance.
*
* @return Contents of the loaded CSV.
*/
inline CsvContents validate(const char* path, const Parameters& params, CsvFieldCreator* creator = NULL) {
return validate_base(
[&](comservatory::Contents& contents, const comservatory::ReadOptions& opt) -> void { comservatory::read_file(path, contents, opt); },
params,
creator
);
}
}
}
#endif
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