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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 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;

import javax.annotation.concurrent.Immutable;
import java.io.IOException;
import java.io.Reader;

@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) {
                bytesCache = CharStreams.toString(reader).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);
        } 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 getTypes(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.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()); } }





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