jstocsv

0.1.2 • Public • Published

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JStoCSV

A small, versatile, dependency free module to convert an array of JavaScript objects to CSV.

  • Handles basic nesting, e.g. field.nested.inAnother or myArray[4]
  • Support alternative delimiters (e.g. TAB delimted) and end of lines.
  • Powerful user function option for "tricky stuff".

Usage

const labelledFields = [
  { path: "name.given", label: "First Name" },  // example of nested data
  { path: "name.surname", label: "Last Name" }
  { path: "birth_day", label: "Date of Birth" },
...
];

data = [
 { name: { given: "John", surname: "Doe" }, birth_day: "06 March 2003" },
  ...
]

const jstocsv = new JStoCSV(labelledFields);
jstocsv.stream(data, someWriteableStream); // or
let result = jstocsv.generateString(data);

Output / Result
First Name,Last Name,Date of Birth
John,Doe, 06 March 2003
...

API

JStoCSV(fields, options) constructor

  • fields is usually an array of {}

    • path: a string, route to get the data, e.g. "name" or "name.first"
    • label: label for header line (defaults to path)
    • fn: optional user function to apply afterwards (usually null, see Notes at end)
  • fields may be an array of strings

    • if so, they are used for the path (and the header label)
    • fn option is unavailable

If fields is not provided, JStoCSV will use all keys from the first data value.

  • options
    • delimiter defaults to ',', you can use '\t' etc.
    • eol defaults to '\n'
    • quoteEmpties put quotes around all empty fields
    • quoteAll put quotes around all fields
    • noHeaderLine don't write out a header line

generateLines(data)

Creates an array of Strings, one per line of the CSV file.

  • data is an array of objects.

generateString(data, appendEOL)

Joins the lines with the eol character.

  • data is an array of objects.
  • appendEOL at end (default is false)

Both of those require that all the CSV file fit in memory. If your data is huge, consider

stream(data, writeStream)

  • data is an array of objects.
  • writeStream note: caller must end() or close() etc...

For the ultimate in control

reduce(data, reducer, acc)

  • data is an array of objects
  • reducer(acc, line) called for each line in the csv file
  • acc the initial accumulator

For convenience, you can use (see tests)

  • _stringReducer();
  • _streamReducer()

Notes, Todos, and Caveats

Supplying a user function fn in fields

This module is short because it just does the basics for output. If you need to "do something very special", supply a user function fn to fields. For each value, it will be called with

fn(value, datum, index, array)

  • value is the value within datum (as determined by path)
  • datum is the entire object in the data array
  • index is the 0-based index of the object within the data array
  • array is the full data array

For example, in the unit test "userfn", we generate an artificial column based on the difference between successive values in the field .number, via

fn: function(val, datum, index, array) {
  return index ? val-array[index-1].number : val;
}

Caveats

  • The _quoteValue() method is pretty basic. Pathological data may break it.
  • a new field, .splitpath, will be added to each of the fields you pass in.

Alternatives. Most are larger.

json-csv

  • works very similarly, even has a user function (caller "filter") but less versatile

simple-csv-writer

  • works with arrays of arrays (not objects)

csv-writer

  • looks good but more complex.

fast-csv

  • looks powerful
  • the headers are confusing

Readme

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Install

npm i jstocsv

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Version

0.1.2

License

MIT

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Collaborators

  • morganconrad