CSV Operations using OpenCSV
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Join For FreeOpenCSV is one of the best tools for CSV operations. We will see how to use OpenCSV for basic reading and writing operations.
How to Use
The Maven dependency for OpenCSV is as follows:
<dependency> <groupId>net.sf.opencsv</groupId> <artifactId>opencsv</artifactId> <version>2.3</version> </dependency>
What it provides
- CSVReader: Provides the operations to read the CSV file as a list of String array. It can used along with CsvToBean to read the data as list of beans
- CSVWriter: Allows us to write the data to a CSV file.
- CsvToBean: Reads the CSV data and coverts to a bean using MappingStrategy.
- MappingStrategy: It's an interface to define the mapping between the data being written to the header of the CSV. It's been implemented by HeaderColumnNameMappingStrategy, ColumnPositionMappingStrategy and HeaderColumnNameTranslateMappingStrategy for respective mapping formats.
Writing to a CSV file
See below an example of writing a CSV file using CSVWriter
String csv = "/tmp/employee.csv"; CSVWriter writer = new CSVWriter(new FileWriter(csv)); String[] header= new String[]{"Name","Age","Salary","Address"}; writer.writeNext(header); List<String[]> allData = new ArrayList<String[]>(); for(int i=0;i<3;i++) { String[] data = new String[]{"Blogger"+i,"20"+i,"20.0002",i+" World Wide Web"}; allData.add(data); } writer.writeAll(allData); writer.close();
Points to be noted
- CSVWriter can write line by line using writeNext
- writeAll can used to write full CSV data at once.
- By default, the separator will be a comma(,). If you want to make another character as a separator we can pass it as an argument.
- The maximum possible signature of the constructor is :
public CSVWriter(Writer writer, char separator, char quotechar, char escapechar)
Output
"Name","Age","Salary","Address" "Blogger0","200","20.0002","0 World Wide Web" "Blogger1","201","20.0002","1 World Wide Web" "Blogger2","202","20.0002","2 World Wide Web"
Reading from a CSV File
Reading a csv can be done in two ways. One as a list of string array or as a bean.
Reading as an array
CSVReader csvReader = new CSVReader(new FileReader("/tmp/employee.csv")); List<String[]> allData = csvReader.readAll(); for(String[] data : allData) { for(String s : data) { System.out.print(s+";"); } System.out.println(); } csvReader.close();
Points to be noted
- As CSVWriter, CSVReader also provides readNext and readAll methods to read one line or full data respectively and the delimiter can be specified while reading the file (Other than comma(,)).
- Adding to that, we can set the ignore spaces, default skip lines, special quote character etc.. while reading a CSV file
- When we read as an array of string, header will not ignored. So we need to skip the first element in the list or we can specify start line while creating CSVReader. See the output below
Output
Name;Age;Salary;Address; Blogger0;200;20.0002;0 World Wide Web; Blogger1;201;20.0002;1 World Wide Web; Blogger2;202;20.0002;2 World Wide Web;
Reading as a Bean
The CSV data can be read into a bean, but we need to define the mapping strategy and pass the strategy to CsvToBean to parse the data into a bean.
Map<String, String> mapping = new HashMap<String, String>(); mapping.put("Name", "name"); mapping.put("Age", "age"); mapping.put("Salary", "salary"); mapping.put("address", "Address"); HeaderColumnNameTranslateMappingStrategy<Employee> strategy = new HeaderColumnNameTranslateMappingStrategy<Employee>(); strategy.setType(Employee.class); strategy.setColumnMapping(mapping); CSVReader csvReader = new CSVReader(new FileReader("/tmp/employee.csv")); CsvToBean<Employee> csvToBean = new CsvToBean<Employee>(); List<Employee> list = csvToBean.parse(strategy, csvReader); for(Employee e : list) { System.out.println(e); }
Points to be noted
- Here we used HeaderColumnNameTranslateMappingStrategy which maps the column id to the bean property.
- CSV Reader and strategy to be passed to CsvToBean to read the data into the bean. When we parse, we get the list of bean as a result.
Output
Name : Blogger0; Age : 200; Salary : 20.0002; Addresss : 0 World Wide Web Name : Blogger1; Age : 201; Salary : 20.0002; Addresss : 1 World Wide Web Name : Blogger2; Age : 202; Salary : 20.0002; Addresss : 2 World Wide Web
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