csv-string
v4.1.1
Published
PARSE and STRINGIFY for CSV strings. It's like JSON object but for CSV. It can also work row by row. And, if can parse strings, it can be use to parse files or streams too.
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Readme
Javascript CSV Strings
Parse and Stringify for CSV strings.
- API similar to the JSON parser (
CSV.parse
andCSV.stringify
). - Can also work row by row.
- Can also be used to parse strings from readable streams (e.g. file streams).
- Tolerant with the weird data
- Written in TypeScript
import * as CSV from 'csv-string';
// with String
const arr = CSV.parse('a,b,c\na,b,c');
const str = CSV.stringify(arr);
// with Stream
const stream = CSV.createStream();
stream.on('data', rows => {
process.stdout.write(CSV.stringify(rows, ','));
});
process.stdin.pipe(stream);
Contributors
- Kael Shipman
- Mehul Mohan
- Hossam Magdy
- Rich
- Rick Huizinga
- Nicolas Thouvenin
- Stéphane Gully
- J. Baumbach
- Sam Hauglustaine
- Rick Huizinga
- doleksy1
- François Parmentier
Installation
using npm:
npm install csv-string
or yarn
yarn add csv-string
API Documentation
parse(input: String, [options: Object]): Object
parse(input: string, [separator: string], [quote: string]): Object
Converts a CSV string input
to array output.
Options :
comma
String to indicate the CSV separator. (optional, default,
)quote
String to indicate the CSV quote if need. (optional, default"
)output
String choose 'objects' or 'tuples' to change output for Array or Object. (optional, defaulttuples
)
Example 1 :
const CSV = require('csv-string');
const parsedCsv = CSV.parse('a;b;c\nd;e;f', ';');
console.log(parsedCsv);
Output:
[
["a", "b", "c"],
["d", "e", "f"]
]
Example 2 :
const CSV = require('csv-string');
const parsedCsv = CSV.parse('a,b,c\n1,2,3\n4,5,6', { output: 'objects' });
console.log(parsedCsv);
Output:
[
{ a: '1', b: '2', c: '3' },
{ a: '4', b: '5', c: '6' }
]
If separator parameter is not provided, it is automatically detected.
stringify(input: Object, [separator: string]): string
Converts object input
to a CSV string.
import * as CSV from 'csv-string';
console.log(CSV.stringify(['a', 'b', 'c']));
console.log(
CSV.stringify([
['c', 'd', 'e'],
['c', 'd', 'e']
])
);
console.log(CSV.stringify({ a: 'e', b: 'f', c: 'g' }));
Output:
a,b,c
c,d,e
c,d,e
e,f,g
detect(input: string): string
Detects the best separator.
import * as CSV from 'csv-string';
console.log(CSV.detect('a,b,c'));
console.log(CSV.detect('a;b;c'));
console.log(CSV.detect('a|b|c'));
console.log(CSV.detect('a\tb\tc'));
Output:
,
;
|
\t
forEach(input: string, sep: string, quo: string, callback: function)
forEach(input: string, sep: string, callback: function)
forEach(input: string, callback: function)
callback(row: array, index: number): void
Calls callback
for each CSV row/line. The Array passed to callback contains the fields of the current row.
import * as CSV from 'csv-string';
const data = 'a,b,c\nd,e,f';
CSV.forEach(data, ',', function (row, index) {
console.log('#' + index + ' : ', row);
});
Output:
#0 : [ 'a', 'b', 'c' ]
#1 : [ 'd', 'e', 'f' ]
read(input: string, sep: string, quo: string, callback: function): number
read(input: string, sep: string, callback: function): number
read(input: string, callback: function): number
callback(row: array): void
Calls callback
when a CSV row is read. The Array passed to callback contains the fields of the row.
Returns the first offset after the row.
import * as CSV from 'csv-string';
const data = 'a,b,c\nd,e,f';
const index = CSV.read(data, ',', row => {
console.log(row);
});
console.log(data.slice(index));
Output:
[ 'a', 'b', 'c' ]
d,e,f
readAll(input: string, sep: string, quo: string, callback: function): number
readAll(input: string, sep: string, callback: function): number
readAll(input: string, callback: function): number
callback(rows: array): void
Calls callback
when all CSV rows are read. The Array passed to callback contains the rows of the file.
Returns the offset of the end of parsing (generally it's the end of the input string).
import * as CSV from 'csv-string';
const data = 'a,b,c\nd,e,f';
const index = CSV.readAll(data, row => {
console.log(row);
});
console.log('-' + data.slice(index) + '-');
Output:
[ [ 'a', 'b', 'c' ], [ 'd', 'e', 'f' ] ]
--
readChunk(input: string, sep: string, quo: string, callback: function): number
readChunk(input: string, sep: string, callback: function): number
readChunk(input: string, callback: function): number
callback(rows: array): void
Calls callback
when all CSV rows are read. The last row could be ignored, because the remainder could be in another chunk.
The Array passed to callback contains the rows of the file.
Returns the offset of the end of parsing. If the last row is ignored, the offset will point to the beginnning of the row.
import * as CSV from 'csv-string';
const data = 'a,b,c\nd,e';
const index = CSV.readChunk(data, row => {
console.log(row);
});
console.log('-' + data.slice(index) + '-');
Output:
[ [ 'a', 'b', 'c' ] ]
--
createStream(options: Object): WritableStream
createStream(): WritableStream
Create a writable stream for CSV chunk. Options are :
- separator : To indicate the CSV separator. By default is auto (see the detect function)
- quote** : To indicate the CSVquote.
Example : Read CSV file from the standard input.
const stream = CSV.createStream();
stream.on('data', row => {
console.log(row);
});
process.stdin.resume();
process.stdin.setEncoding('utf8');
process.stdin.pipe(stream);
Contribution
clone
yarn install
- ... do the changes, write tests
yarn test
(ensure all tests pass)yarn bench
(to check the performance impact)
Related projects
- https://npmjs.org/browse/keyword/csv
- http://www.uselesscode.org/js/csv/
- https://github.com/archan937/csonv.js
Benchmark
There is a quite basic benchmark to compare this project to other related ones, using file streams as input. See ./bench
for source code.
the test
yarn bench
the result
for a test file with 949,044 rows
| Package | Time | Output/Input similarity | | -------------- | --------- | ----------------------- | | a-csv | 6.01s | ~99% | | csv-stream | 6.64s | ~73% | | csv-streamer | 7.03s | ~79% | | csv-string | 6.53s | 100% | | fast-csv | 12.33s | 99.99% | | nodecsv | 7.10s | 100% |