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An efficient dBase DBF file parser written in pure JavaScript

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node-dbf

This is an event-based dBase file parser for very efficiently reading data from *.dbf files.

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The codebase is written in CoffeeScript but compiled in the npm module so CoffeeScript is not a dependency in production.

To get started, simply install the module using npm:

npm install node-dbf

and then require it:

var Parser = require('node-dbf');

#Classes

There are two classes - the Parser and the Header. The Parser is the most interesting class.

##Parser

This class is the main interface for reading data from dBase files. It extends EventEmitter and its output is via events.

###new Parser(path, options)

  • path String The full path to the DBF file to parse
  • options Object An object containing options for the parser.

The support options are:

  • encoding String The character encoding to use (default = utf-8)

Creates a new Parser and attaches it to the specified filename.

var Parser = require('node-dbf');

var parser = new Parser('/path/to/my/dbase/file.dbf');

###parser.on(event, listener)

  • event String The event name to listen for (see below for details)
  • listener Function The callback to bind to the event

This method is inherited from the EventEmitter class.

###parser.parse()

Call this method once you have bound to the events you are interested in. Although it returns the parser object (for chaining), all the dBase data is outputted via events.

parser.parse();

###Event: 'start'

  • parser Parser The parser object

This event is emitted as soon as the parser.parse() method has been invoked.

###Event: 'header'

  • header Header The header object as parsed from the dBase file

This event is emitted once the header has been parsed from the dBase file

###Event: 'record'

  • record Object An object representing the record that has been found

The record object will have a key for each field within the record, named after the field. It is trimmed (leading and trailing) of any blank characters (dBase files use \x20 for padding).

In addition to the fields, the object contains two special keys:

  • @sequenceNumber Number indicates the order in which it was extracted
  • @deleted Boolean whether this record has been deleted or not

This object may look like:

{
    "@sequenceNumber": 123,
    "@deleted": false,
    "firstName": "John",
    "lastName": "Smith
}

###Event: 'end'

  • parser Parser The parser object

This event is fired once the dBase parsing is complete and there are no more records remaining.

##Usage

The following code example illustrates a very simple usage for this module:

var Parser = require('node-dbf');

var parser = new Parser('/path/to/my/dbase/file.dbf');

parser.on('start', function(p) {
    console.log('dBase file parsing has started');
});

parser.on('header', function(h) {
    console.log('dBase file header has been parsed');
});

parser.on('record', function(record) {
    console.log('Name: ' + record.firstName + ' ' + record.lastName); // Name: John Smith
});

parser.on('end', function(p) {
    console.log('Finished parsing the dBase file');
});

parser.parse();

#Command-Line Interface (CLI)

The parser also supports a command-line interface (CLI) for converting DBF files to CSV. You can invoke it as follows:

$ node-dbf convert /path/to/file.dbf

This will write the converted rows to stdout and metadata about the process (e.g. number of rows, etc) to stderr. This allows you to write stdout directly to an output file, for example:

$ node-dbf convert file.dbf > file.csv

For more help information on using the command line options, use the integrated help:

$ node-dbf help

#Tests

Tests are written in Mocha using Chai BDD for the expectations. Data on San Francisco zip codes was used as a reference test file - downloaded from SF OpenData and included in the ./test/fixtures/bayarea_zipcodes.dbf file within the repository.

#TODO

  • Add more tests
  • Add support for field types other than Character and Numeric
  • Use fs.readStream instead of fs.readFile for increased performance
  • Add a CLI interface for converting to CSV, etc
  • Improve error handling to emit an error event

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  • JavaScript 68.3%
  • CoffeeScript 31.7%