magic-csv

magic-csv is an automagic CSV parser designed to handle whatever you throw at it




__Usage__
``javascript
MagicCSV = require("magic-csv");
csv = new MagicCSV({trim: true});

// file example
csv.readFile("example.csv", function(err, stats) {
csv.getCols(); // ['First', 'Last', 'Pain']
csv.getRow(0); // ['Brian', 'Regan', '8']
csv.getObject(0); // {First: 'Brian', Last: 'Regan', Pain: '8'}
csv.getStats(); // stats object, detailing how the file was parsed
csv.getRowCount(); // same as stats.row_count
});

// objects example
var ob1 = {Name: 'Jimmy', Phone: 5552497, Gender: 'M'};
var ob2 = {Name: 'Justin', Phone: 5553546, Phone2: 5557951, Gender: 'M'};
csv.readObjects([ob1, ob2], function(err, stats) {
csv.getCols(); // ['Name', 'Phone', 'Phone2', 'Gender']
csv.getRow(0); // ['Jimmy', '5552497', '', 'M']
csv.getRow(1); // ['Justin', '5553546', '5557951', 'M']
csv.getCol('Phone'); // ['5552497', '5553546']
});

// raw example
csv.parse(str, function(err, stats) {
csv.getRow(-1); // last row
csv.getRows(); // all rows
csv.getObjects(); // all objects
csv.getColCount(); // same as stats.col_count
});

// write methods
csv.writeToStream(stream);
csv.writeToRes(res, 'out.csv'); // express response
csv.writeToFile('out.csv');
`


__Options__
`javascript
// passed to MagicCSV at instantiation (defaults shown)
{
trim: true, // trim values
drop_bad_rows: false, // drop rows with extra fields
drop_empty_rows: true, // drop rows with no data
drop_duplicate_rows: false, // drop duplicate rows
drop_empty_cols: false, // drop columns with no data
allow_single_col: false, // allow input with only one column
default_col_name: 'Unknown' // name for generated columns
}
`


__Stats__
`javascript
// example object returned by csv.getStats()
{
line_ending: 'LF', // LF, CR, CRLF, n/a, unknown
delimiter: 'comma', // comma, tab, pipe, n/a, unknown
col_count: 14,
row_count: 1893,
empty_cols: ['Middle Name', 'Alt_Email'],
duplicate_cols: {Zip: ['Zip 2']}, // repeat occurance of Zip renamed Zip 2
bad_row_indexes: [234, 759], // column shifting may have occurred here
valid_col_count: 13, // column names found
blank_col_count: 2, // blank column names repaired
added_col_count: 1, // columns added to cover extra fields
dropped_col_count: 0,
dropped_row_count: 2
}
`


__Errors__

All err objects have a code` property. Possible values are:
* INPUT
* READ
* WRITE
* PARSE