CsvParserSettings parserSettings = new CsvParserSettings(); // To get the values of all columns, use a column processor ColumnProcessor rowProcessor = new ColumnProcessor(); parserSettings.setRowProcessor(rowProcessor); CsvParser parser = new CsvParser(parserSettings); //This will kick in our column processor parser.parse(new FileReader(new File(copyUri))); //Finally, we can get the column values: Map<Integer, List<String>> columnValues = rowProcessor.getColumnValuesAsMapOfIndexes();
CsvParserSettings parserSettings = new CsvParserSettings(); // To get the values of all columns, use a column processor ColumnProcessor rowProcessor = new ColumnProcessor(); parserSettings.setRowProcessor(rowProcessor); CsvParser parser = new CsvParser(parserSettings); //This parses the entire file and triggers the column processor parser.parse(new FileReader(yourFile)); //Here we get the column values: Map<Integer, List<String>> columnValuesByIndex = rowProcessor.getColumnValuesAsMapOfIndexes(); Map<String, List<String>> columnValuesByName = rowProcessor.getColumnValuesAsMapOfNames();
//keys are possible headers, and values are the indexes where each header will be mapped to: Map<String, Integer> headerPositions = new LinkedHashMap<String, Integer>(); headerPositions.put("UniqueCode", 0); headerPositions.put("Name", 1); headerPositions.put("dogId", 2); headerPositions.put("catId", 2); headerPositions.put("cowId", 2); CsvParserSettings settings = new CsvParserSettings(); //we want headers settings.setHeaderExtractionEnabled(true); //let's use the custom row processor: MyBeanProcessor<MyPOJO> processor = new MyBeanProcessor<MyPOJO>(MyPOJO.class, headerPositions); settings.setRowProcessor(processor); CsvParser parser = new CsvParser(settings); parser.parse(<YOUR_INPUT_HERE>); List<MyPOJO> myPojos = processor.getBeans();
BeanListProcessor<TestBean> rowProcessor = new BeanListProcessor<TestBean>(TestBean.class); CsvParserSettings parserSettings = new CsvParserSettings(); parserSettings.setRowProcessor(rowProcessor); parserSettings.setHeaderExtractionEnabled(true); CsvParser parser = new CsvParser(parserSettings); //And parse! //this submits all rows parsed from the input to the BeanListProcessor parser.parse(new FileReader(new File("/examples/bean_test.csv"))); List<TestBean> beans = rowProcessor.getBeans();
BeanListProcessor<SUREDataBean> rowProcessor = new BeanListProcessor<SUREDataBean>(SUREDataBean.class); CsvParserSettings parserSettings = new CsvParserSettings(); settings.getFormat().setDelimiter('|'); parserSettings.setRowProcessor(rowProcessor); parserSettings.setHeaderExtractionEnabled(true); CsvParser parser = new CsvParser(parserSettings); //Parsing is started here. //this submits all rows parsed from the input to the BeanListProcessor parser.parse(new FileReader(new File("/examples/bean_test.csv"))); List<SUREDataBean> beans = rowProcessor.getBeans();
CsvParserSettings parserSettings = new CsvParserSettings(); //parser config with many options, check the tutorial parserSettings.setHeaderExtractionEnabled(true); // uses the first row as headers // To get the values of all columns, use a column processor ColumnProcessor rowProcessor = new ColumnProcessor(); parserSettings.setRowProcessor(rowProcessor); CsvParser parser = new CsvParser(parserSettings); //This will parse everything and pass the data to the column processor parser.parse(new FileReader(new File("/path/to/your/file.csv"))); //Finally, we can get the column values: Map<String, List<String>> columnValues = rowProcessor.getColumnValuesAsMapOfNames();
BeanListProcessor<Employee> rowProcessor = new BeanListProcessor<Employee>(Employee.class); CsvParserSettings parserSettings = new CsvParserSettings(); parserSettings.setRowProcessor(rowProcessor); parserSettings.setHeaderExtractionEnabled(true); CsvParser parser = new CsvParser(parserSettings); //And parse! //this submits all rows parsed from the input to the BeanListProcessor parser.parse(new FileReader(new File("/path/to/your.csv"))); List<Employee> beans = rowProcessor.getBeans();
// BeanListProcessor converts each parsed row to an instance of a given class, then stores each instance into a list. BeanListProcessor<SubscriberPackages> rowProcessor = new BeanListProcessor<SubscriberPackages>(SubscriberPackages.class); CsvParserSettings parserSettings = new CsvParserSettings(); //many options here, check the tutorial. parserSettings.setRowProcessor(rowProcessor); //uses the bean processor to handle your input rows parserSettings.setHeaderExtractionEnabled(true); // extracts header names from the input file. CsvParser parser = new CsvParser(parserSettings); //creates a parser with your settings. parser.parse(new FileReader(new File("/path/to/file.csv"))); //all rows parsed here go straight to the bean processor // The BeanListProcessor provides a list of objects extracted from the input. List<SubscriberPackages> beans = rowProcessor.getBeans();
CsvParserSettings parserSettings = new CsvParserSettings(); // Let's extract headers parserSettings.setHeaderExtractionEnabled(true); // To get the values of all columns, use a column processor ColumnProcessor rowProcessor = new ColumnProcessor(); parserSettings.setRowProcessor(rowProcessor); CsvParser parser = new CsvParser(parserSettings); //This will kick in our column processor parser.parse(new FileReader("path/to/file.csv")); //Finally, we can get the column values: Map<String, List<String>> columnValues = rowProcessor.getColumnValuesAsMapOfNames();
public <T> List<T> parseBeans(Class<T> beanType, File inputFile){ BeanListProcessor<T> rowProcessor = new BeanListProcessor<T>(beanType); CsvParserSettings parserSettings = new CsvParserSettings(); parserSettings.setRowProcessor(rowProcessor); parserSettings.setHeaderExtractionEnabled(true); //will get headers from the input file CsvParser parser = new CsvParser(parserSettings); //this will read your file and submit all rows to the row processor defined above parser.parse(new FileReader(inputFile)); List<T> beans = rowProcessor.getBeans(); return beans; }
// BeanListProcessor converts each parsed row to an instance of a given class, then stores each instance into a list. BeanListProcessor<TestBean> rowProcessor = new BeanListProcessor<TestBean>(TestBean.class); CsvParserSettings parserSettings = new CsvParserSettings(); parserSettings.setRowProcessor(rowProcessor); //Uses the first valid row of the CSV to assign names to each column parserSettings.setHeaderExtractionEnabled(true); CsvParser parser = new CsvParser(parserSettings); parser.parse(new FileReader(yourFile)); // The BeanListProcessor provides a list of objects extracted from the input. List<TestBean> beans = rowProcessor.getBeans();
BeanListProcessor<TestBean> rowProcessor = new BeanListProcessor<TestBean>(TestBean.class); CsvParserSettings parserSettings = new CsvParserSettings(); parserSettings.setRowProcessor(rowProcessor); parserSettings.setHeaderExtractionEnabled(true); CsvParser parser = new CsvParser(parserSettings); parser.parse(new FileReader(Paths.get("list2.csv").toFile()); // The BeanListProcessor provides a list of objects extracted from the input. List<TestBean> beans = rowProcessor.getBeans();
public void parseCsvToBeanWithList() { final BeanListProcessor<Client> clientProcessor = new BeanListProcessor<Client>(Client.class); CsvParserSettings settings = new CsvParserSettings(); settings.getFormat().setLineSeparator("\n"); settings.setRowProcessor(clientProcessor); CsvParser parser = new CsvParser(settings); parser.parse(new StringReader(CSV_INPUT)); List<Client> rows = clientProcessor.getBeans(); }
BeanListProcessor<TestBean> rowProcessor = new BeanListProcessor<TestBean>(TestBean.class); CsvParserSettings parserSettings = new CsvParserSettings(); parserSettings.setRowProcessor(rowProcessor); parserSettings.setHeaderExtractionEnabled(true); CsvParser parser = new CsvParser(parserSettings); parser.parse(getReader("/examples/bean_test.csv")); List<TestBean> beans = rowProcessor.getBeans();
BeanListProcessor<TestBean> rowProcessor = new BeanListProcessor<TestBean>(TestBean.class); CsvParserSettings parserSettings = new CsvParserSettings(); parserSettings.setRowProcessor(rowProcessor); parserSettings.setHeaderExtractionEnabled(true); CsvParser parser = new CsvParser(parserSettings); parser.parse(getReader("/examples/bean_test.csv")); List<TestBean> beans = rowProcessor.getBeans();
ObjectRowListProcessor rowProcessor = new ObjectRowListProcessor(); rowProcessor.convertFields(Conversions.toBoolean("yes", "no")).set("metformin-rosiglitazone","metformin-pioglitazone","change","diabetesMed","readmitted")); //and all other fields where this makes sense. rowProcessor.convertFields(Conversions.toLowerCase(), Conversions.toNull("none", "?")).set("another field", "and another field"); CsvParserSettings parserSettings = new CsvParserSettings(); parserSettings.setRowProcessor(rowProcessor); parserSettings.setHeaderExtractionEnabled(true); CsvParser parser = new CsvParser(parserSettings); //the rowProcessor will be executed here. parser.parse(YOUR_INPUT_HERE); List<Object[]> rows = rowProcessor.getRows();
CsvParserSettings settings = new CsvParserSettings(); //Create a row processor to process input rows. In this case we want //multiple instances of different classes: MultiBeanListProcessor processor = new MultiBeanListProcessor(TestBean.class, AmountBean.class, QuantityBean.class); // we also need to grab the headers from our input file settings.setHeaderExtractionEnabled(true); // configure the parser to use the MultiBeanProcessor settings.setRowProcessor(processor); // create the parser and run CsvParser parser = new CsvParser(settings); parser.parse(new File("/path/to/your.csv")); // get the beans: List<TestBean> testBeans = processor.getBeans(TestBean.class); List<AmountBean> amountBeans = processor.getBeans(AmountBean.class); List<QuantityBean> quantityBeans = processor.getBeans(QuantityBean.class);
// BeanListProcessor converts each parsed row to an instance of a given class, then stores each instance into a list. BeanListProcessor<TestBean> rowProcessor = new BeanListProcessor<TestBean>(TestBean.class); CsvParserSettings parserSettings = new CsvParserSettings(); parserSettings.setRowProcessor(rowProcessor); parserSettings.setHeaderExtractionEnabled(true); CsvParser parser = new CsvParser(parserSettings); parser.parse(getReader("/examples/bean_test.csv")); // The BeanListProcessor provides a list of objects extracted from the input. List<TestBean> beans = rowProcessor.getBeans();
CsvParserSettings parserSettings = new CsvParserSettings(); //many options here, check the documentation. parserSettings.setHeaderExtractionEnabled(true); // gets the headers from the first row // To get the values of all columns, use a column processor ColumnProcessor rowProcessor = new ColumnProcessor(); parserSettings.setRowProcessor(rowProcessor); CsvParser parser = new CsvParser(parserSettings); //This will parse all rows and submit them to the column processor parser.parse(newFileReader("test.csv")); //Finally, we can get the column values: Map<String, List<String>> columnValues = rowProcessor.getColumnValuesAsMapOfNames();
CsvParserSettings parserSettings = new CsvParserSettings(); parserSettings.getFormat().setLineSeparator("\n"); parserSettings.getFormat().setDelimiter('$'); parserSettings.setHeaderExtractionEnabled(true); // To get the values of all columns, use a column processor ColumnProcessor rowProcessor = new ColumnProcessor(); parserSettings.setRowProcessor(rowProcessor); CsvParser parser = new CsvParser(parserSettings); //This will kick in our column processor parser.parse(new FileReader("testing.cvs")); //Finally, we can get the column values: Map<String, List<String>> columnValues = rowProcessor.getColumnValuesAsMapOfNames();