Row

Row operations consist of the filters, transformers, and bufferings. Each of these are described in Basics and Reference documentation. Pnyx will automatically Shim Line operations (filters and transformers) whenever calling Line methods while in Row state. In addition to these operations, the following operations are available: The rest of this page illustrates some usages these operations.

Shim Examples

By default, when shimming Line filters, a boolean OR operation is performed. This means that a Row will be matched, if any column matches the ILineFilter. To match each column, use the shimAnd method. An example of both are shown below.
Shim OR: 
            
const String input = @"Line one,a,,c
Line two,a,b,c
Line three,,,c
"; 
await using (Pnyx p = new Pnyx())
{
    p.readString(input);
    p.parseCsv();
    p.hasLine();
    p.writeStdout();
}                        
// outputs:
// "Line one",a,,c
// "Line two",a,b,c
// "Line three",,,c
Shim AND: 
const String input = @"Line one,a,,c
Line two,a,b,c
Line three,,,c
"; 
await using (Pnyx p = new Pnyx())
{
    p.readString(input);
    p.parseCsv();
    p.shimAnd(p2 => p2.hasLine());
    p.writeStdout();
}                        
// outputs:
// "Line two",a,b,c

Custom Operations

The built-in Row opertions for Pnyx only cover the very basics. For any advanced application, custom operations will be used extensively. In this case, each Row interface is simple to implement and easily tested with Unit Tests. In addition to implementing interfaces, Pnyx supports using Lambda expression for quicker, more flexible usage. The following examples shows the two Row operations with Lambda expressions.

rowFilter (lambda): 
const String input = @"Line one,KEEPER
Line two,Loser
"; 
await using (Pnyx p = new Pnyx())
{
    p.readString(input);
    p.parseCsv();
    p.rowFilter(x => x[1].isUpperCase());
    p.writeStdout();
}                        
// outputs:         
// "Line one",KEEPER
rowTransformer (lambda): 
const String input = @"Line one,KEEPER
Line two,LOSER
"; 
await using (Pnyx p = new Pnyx())
{
    p.readString(input);
    p.parseCsv();
    p.rowTransformer(x => new List<string?> {x[1].toTitleCase()});
    p.writeStdout();
}                        
// outputs:            
// Keeper
// Loser

Convert To Line

To convert Row data to Line data, there are several methods available. These methods: print, printDelimiter, and printTab are documented in Reference, Conversion. For advanced formatting, IRowConverter should be implemented and used with rowToLine method. Below are some examples of converting Row data to Line data.
print 
const String input = "Socialism,Communism,Fascism"; 
await using (Pnyx p = new Pnyx())
{
    p.readString(input);
    p.parseCsv();
    p.print("Failed Systems: $1, $2, and $3");
    p.writeStdout();
}                        
// outputs: Failed Systems: Socialism, Communism, and Fascism
printDelimiter 
const String input = "col1,\"Column, zwei\""; 
await using (Pnyx p = new Pnyx())
{
    p.readString(input);
    p.parseCsv();
    p.printDelimiter("|");
    p.writeStdout();
}                        
// outputs: col1|Column, zwei

Column Operation

IRowFilters and IRowTransformers are designed to work with all columns. When shimming ILineFilters or ILineTransformers, every column is affected. In many cases, you may want to operate on only one column. For this, use rowFilterColumn and rowTransformerColumn methods. These methods take a column index (zero-based) and a line filter or transformer. An example of both are shown below.

rowFilterColumn 
const String input = @"
Line one,Atlanta,City located in the southwestern United States.
Line two,New York,The most populous city in the United States.
Line three,Tampa,Sunny and warm city on the west coast of Florida.
";

await using Pnyx p = new Pnyx();
p.readString(input);
p.parseCsv();
p.rowFilterColumn(RowConstants.B, new Grep("a"));
p.writeStdout();
// outputs:
// Line one,Atlanta,City located in the southwestern United States.
// Line three,Tampa,Sunny and warm city on the west coast of Florida.

rowTransformerColumn 
const String input = @"
Line one,Atlanta
Line two,New York
Line three,Tampa
";
await using Pnyx p = new Pnyx();
p.readString(input);
p.parseCsv();
p.rowTransformerColumn(RowConstants.B, new SedReplace(".*", @"City of \0"));
p.writeStdout();
// outputs:
// Line one,City of Atlanta
// Line two,City of New York
// Line three,City of Tampa

Columns Operation

IRowFilters and IRowTransformers are designed to work with all columns. To apply to one column, see Column Operation. To apply to multiple columns, use withColumns method. This works by wrapping a lamba expression. Every row operation performed within the lamba is restricted to operate on the specified column(s). Here is an example of filters and transforms that are only applied to a column.
withColumns (filter) 
const String input = @"
Line one,Atlanta,City located in the southwestern United States.
Line two,New York,The most populous city in the United States.
Line three,Tampa,Sunny and warm city on the west coast of Florida.
";
await using Pnyx p = new Pnyx();
p.readString(input);
p.parseCsv();
p.withColumns(p2 => p2.grep("a"), RowConstants.B);
p.writeStdout();
// outputs:
// Line one,Atlanta,City located in the southwestern United States.
// Line three,Tampa,Sunny and warm city on the west coast of Florida.

withColumns (transform) 
const String input = @"
Line one,Atlanta
Line two,New York
Line three,Tampa
";
await using Pnyx p = new Pnyx();
p.readString(input);
p.parseCsv();
p.withColumns(p2 => p2.sed(".*", @"City of \0"), RowConstants.B);
p.writeStdout();
// outputs:
// Line one,City of Atlanta
// Line two,City of New York
// Line three,City of Tampa

Next

Suggested next steps:
  • Line, learn more about Line operations
  • Object, examples of Object operations
  • NameValuePair, examples of Name-Value Pair operations
  • Input, learn more about Input operations
  • Output, learn more about Output operations