| /* |
| * Licensed to the Apache Software Foundation (ASF) under one |
| * or more contributor license agreements. See the NOTICE file |
| * distributed with this work for additional information |
| * regarding copyright ownership. The ASF licenses this file |
| * to you 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 org.apache.jena.sparql.resultset; |
| |
| import java.io.InputStream ; |
| import java.util.ArrayList ; |
| import java.util.Iterator ; |
| import java.util.List ; |
| import java.util.function.Function; |
| |
| import org.apache.jena.atlas.csv.CSVParser ; |
| import org.apache.jena.atlas.iterator.Iter ; |
| import org.apache.jena.atlas.logging.FmtLog ; |
| import org.apache.jena.graph.Node ; |
| import org.apache.jena.graph.NodeFactory ; |
| import org.apache.jena.query.ResultSet ; |
| import org.apache.jena.sparql.ARQException ; |
| import org.apache.jena.sparql.core.Var ; |
| import org.apache.jena.sparql.engine.ResultSetStream ; |
| import org.apache.jena.sparql.engine.binding.Binding ; |
| import org.apache.jena.sparql.engine.binding.BindingFactory ; |
| import org.apache.jena.sparql.engine.binding.BindingMap ; |
| import org.slf4j.Logger ; |
| import org.slf4j.LoggerFactory ; |
| |
| /** Convenient comma separated values - see also TSV (tab separated values) |
| * which outputs full RDF terms (in Turtle-style). |
| * |
| * The CSV format supported is: |
| * <ul> |
| * <li>First row is variable names without '?'</li> |
| * <li>Strings, quoted if necessary and numbers output only. |
| * No language tags, or datatypes. |
| * URIs are send without $lt;> |
| * </li> |
| * CSV is RFC 4180, but there are many variations. |
| * </ul> |
| * This code reads the file and treats everything as strings. |
| * <p> |
| * The code also allows for parsing boolean results where we expect the header to be a single string |
| * from the set: true yes false no |
| * </p> |
| * <p> |
| * Any other value is considered an error for parsing a boolean results and anything past the first line is ignored |
| * </p> |
| */ |
| public class CSVInput |
| { |
| // This code exists to support the SPARQL WG tests. |
| private static Logger log = LoggerFactory.getLogger(CSVInput.class) ; |
| public static ResultSet fromCSV(InputStream in) |
| { |
| CSVParser parser = CSVParser.create(in) ; |
| final List<Var> vars = vars(parser) ; |
| List<String> varNames = Var.varNames(vars) ; |
| Function<List<String>, Binding> transform = new Function<List<String>, Binding>(){ |
| private int count = 1 ; |
| @Override |
| public Binding apply(List<String> row) { |
| if ( row.size() != vars.size() ) |
| FmtLog.warn(log, "Row %d: Length=%d: expected=%d", count, row.size(), vars.size()) ; |
| |
| BindingMap binding = BindingFactory.create() ; |
| // Check. |
| for (int i = 0 ; i < vars.size() ; i++ ) { |
| Var v = vars.get(i) ; |
| String field = (i<row.size()) ? row.get(i) : "" ; |
| Node n = NodeFactory.createLiteral(field) ; |
| binding.add(v, n); |
| } |
| count++ ; |
| return binding ; |
| }} ; |
| Iterator<Binding> bindings = Iter.map(parser.iterator(), transform) ; |
| |
| //Generate an instance of ResultSetStream using TSVInputIterator |
| //This will parse actual result rows as needed thus minimising memory usage |
| return new ResultSetStream(varNames, null, bindings); |
| } |
| |
| private static List<Var> vars(CSVParser parser) { |
| final List<Var> vars = new ArrayList<>(); |
| List<String> varNames = parser.parse1() ; |
| if ( varNames == null ) |
| throw new ARQException("SPARQL CSV Results malformed, input is empty"); |
| for ( String vn : varNames ) { |
| vars.add(Var.alloc(vn)) ; |
| } |
| return vars ; |
| } |
| |
| public static boolean booleanFromCSV(InputStream in) |
| { |
| CSVParser parser = CSVParser.create(in) ; |
| final List<Var> vars = vars(parser) ; |
| if ( vars.size() != 1 ) { |
| throw new ARQException("CSV Boolean Results malformed: variables line='"+vars+"'") ; |
| } |
| if ( ! vars.get(0).getName().equals("_askResult")) { |
| FmtLog.warn(log, "Boolean result variable is '%s', not '_askResult'", vars.get(0).getName()) ; |
| } |
| |
| List<String> line = parser.parse1() ; |
| if ( line.size() != 1 ) { |
| throw new ARQException("CSV Boolean Results malformed: data line='"+line+"'") ; |
| } |
| String str = line.get(0) ; |
| boolean b ; |
| if ( str.equalsIgnoreCase("true") || str.equalsIgnoreCase("yes") ) |
| b = true ; |
| else if (str.equalsIgnoreCase("false") || str.equalsIgnoreCase("no")) |
| b = false; |
| else { |
| throw new ARQException("CSV Boolean Results malformed, expected one of - true yes false no - but got " + str); |
| } |
| |
| List<String> line2 = parser.parse1() ; |
| if ( line2 != null ) { |
| FmtLog.warn(log, "Extra rows: first is "+line2) ; |
| } |
| return b ; |
| } |
| } |