tech.tablesaw.io.csv.CsvReader Maven / Gradle / Ivy
/*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package tech.tablesaw.io.csv;
import com.google.common.io.CharStreams;
import com.univocity.parsers.common.AbstractParser;
import com.univocity.parsers.csv.CsvFormat;
import com.univocity.parsers.csv.CsvParser;
import com.univocity.parsers.csv.CsvParserSettings;
import java.io.IOException;
import java.io.Reader;
import javax.annotation.concurrent.Immutable;
import org.apache.commons.math3.util.Pair;
import tech.tablesaw.api.ColumnType;
import tech.tablesaw.api.Table;
import tech.tablesaw.io.DataReader;
import tech.tablesaw.io.FileReader;
import tech.tablesaw.io.ReaderRegistry;
import tech.tablesaw.io.Source;
@Immutable
public class CsvReader extends FileReader implements DataReader {
private static final CsvReader INSTANCE = new CsvReader();
static {
register(Table.defaultReaderRegistry);
}
public static void register(ReaderRegistry registry) {
registry.registerExtension("csv", INSTANCE);
registry.registerMimeType("text/csv", INSTANCE);
registry.registerOptions(CsvReadOptions.class, INSTANCE);
}
/** Constructs a CsvReader */
public CsvReader() {
super();
}
/**
* Determines column types if not provided by the user Reads all input into memory unless File was
* provided
*/
private Pair getReaderAndColumnTypes(Source source, CsvReadOptions options)
throws IOException {
ColumnType[] types = options.columnTypes();
byte[] bytesCache = null;
if (types == null) {
Reader reader = source.createReader(bytesCache);
if (source.file() == null) {
String s = CharStreams.toString(reader);
bytesCache = source.getCharset() != null ? s.getBytes(source.getCharset()) : s.getBytes();
// create a new reader since we just exhausted the existing one
reader = source.createReader(bytesCache);
}
types = detectColumnTypes(reader, options);
}
return Pair.create(source.createReader(bytesCache), types);
}
public Table read(CsvReadOptions options) throws IOException {
return read(options, false);
}
private Table read(CsvReadOptions options, boolean headerOnly) throws IOException {
Pair pair = getReaderAndColumnTypes(options.source(), options);
Reader reader = pair.getKey();
ColumnType[] types = pair.getValue();
AbstractParser parser = csvParser(options);
try {
return parseRows(options, headerOnly, reader, types, parser, options.sampleSize());
} finally {
if (options.source().reader() == null) {
// if we get a reader back from options it means the client opened it, so let the client
// close it
// if it's null, we close it here.
parser.stopParsing();
reader.close();
}
}
}
/**
* Returns a string representation of the column types in file {@code csvFilename}, as determined
* by the type-detection algorithm
*
* This method is intended to help analysts quickly fix any erroneous types, by printing out
* the types in a format such that they can be edited to correct any mistakes, and used in an
* array literal
*
*
For example:
*
*
LOCAL_DATE, // 0 date SHORT, // 1 approval STRING, // 2 who
*
*
Note that the types are array separated, and that the index position and the column name are
* printed such that they would be interpreted as comments if you paste the output into an array:
*
*
*
* @throws IOException if file cannot be read
*/
public String printColumnTypes(CsvReadOptions options) throws IOException {
Table structure = read(options, true).structure();
return getTypeString(structure);
}
/**
* Estimates and returns the type for each column in the delimited text file {@code file}
*
*
The type is determined by checking a sample of the data in the file. Because only a sample
* of the data is checked, the types may be incorrect. If that is the case a Parse Exception will
* be thrown.
*
*
The method {@code printColumnTypes()} can be used to print a list of the detected columns
* that can be corrected and used to explicitly specify the correct column types.
*/
protected ColumnType[] detectColumnTypes(Reader reader, CsvReadOptions options) {
boolean header = options.header();
int linesToSkip = header ? 1 : 0;
CsvParser parser = csvParser(options);
try {
return getColumnTypes(reader, options, linesToSkip, parser);
} finally {
parser.stopParsing();
// we don't close the reader since we didn't create it
}
}
private CsvParser csvParser(CsvReadOptions options) {
CsvParserSettings settings = new CsvParserSettings();
settings.setLineSeparatorDetectionEnabled(options.lineSeparatorDetectionEnabled());
settings.setFormat(csvFormat(options));
settings.setMaxCharsPerColumn(options.maxCharsPerColumn());
if (options.maxNumberOfColumns() != null) {
settings.setMaxColumns(options.maxNumberOfColumns());
}
return new CsvParser(settings);
}
private CsvFormat csvFormat(CsvReadOptions options) {
CsvFormat format = new CsvFormat();
if (options.quoteChar() != null) {
format.setQuote(options.quoteChar());
}
if (options.escapeChar() != null) {
format.setQuoteEscape(options.escapeChar());
}
if (options.separator() != null) {
format.setDelimiter(options.separator());
}
if (options.lineEnding() != null) {
format.setLineSeparator(options.lineEnding());
}
if (options.commentPrefix() != null) {
format.setComment(options.commentPrefix());
}
return format;
}
@Override
public Table read(Source source) throws IOException {
return read(CsvReadOptions.builder(source).build());
}
}