com.conveyal.gtfs.loader.ColorField Maven / Gradle / Ivy
package com.conveyal.gtfs.loader;
import com.conveyal.gtfs.error.NewGTFSError;
import com.conveyal.gtfs.error.NewGTFSErrorType;
import com.conveyal.gtfs.storage.StorageException;
import java.sql.JDBCType;
import java.sql.PreparedStatement;
import java.sql.SQLType;
import java.util.Set;
import static com.conveyal.gtfs.loader.Field.cleanString;
/**
* Represents a six-digit hex color code. Should be parsed as hex text and less than OxFFFFFF.
*
* Created by abyrd on 2017-03-30
*/
public class ColorField extends Field {
public ColorField(String name, Requirement requirement) {
super(name, requirement);
}
/** Check that a string can be properly parsed and is in range. */
public ValidateFieldResult validateAndConvert (String string) {
ValidateFieldResult result = new ValidateFieldResult<>(string);
try {
if (string.length() != 6) {
result.errors.add(NewGTFSError.forFeed(NewGTFSErrorType.COLOR_FORMAT, string));
}
int integer = Integer.parseInt(string, 16);
return result; // Could also store the integer.
} catch (Exception ex) {
throw new StorageException(NewGTFSErrorType.COLOR_FORMAT, string);
}
}
public Set setParameter(PreparedStatement preparedStatement, int oneBasedIndex, String string) {
try {
ValidateFieldResult result = validateAndConvert(string);
preparedStatement.setString(oneBasedIndex, result.clean);
return result.errors;
} catch (Exception ex) {
throw new StorageException(ex);
}
}
/**
* From the Postgres manual, on character types:
* There is no performance difference among these three types, apart from increased storage space when using
* the blank-padded type, and a few extra CPU cycles to check the length when storing into a length-constrained
* column. While character(n) has performance advantages in some other database systems, there is no such advantage
* in PostgreSQL; in fact character(n) is usually the slowest of the three because of its additional storage costs.
*
* Arguably colors are integers expressed in hex though.
*/
@Override
public SQLType getSqlType() {
return JDBCType.VARCHAR;
}
}