read-excel-file-forwps v4.0.2

read-excel-file

Read *.xlsx files in a browser or Node.js. Parse to JSON with a strict schema.

Demo

Install

npm install read-excel-file --save

Browser

<input type="file" id="input" />

import readXlsxFile from 'read-excel-file'

const input = document.getElementById('input')

input.addEventListener('change', () => {
  readXlsxFile(input.files[0]).then((rows) => {
    // `rows` is an array of rows
    // each row being an array of cells.
  })
})

Node.js

const readXlsxFile = require('read-excel-file/node');

// File path.
readXlsxFile('/path/to/file').then((rows) => {
  // `rows` is an array of rows
  // each row being an array of cells.
})

// Readable Stream.
readXlsxFile(fs.createReadStream('/path/to/file')).then((rows) => {
  ...
})

Dates

XLSX format has no dedicated "date" type so dates are stored internally as simply numbers along with a "format" (e.g. "MM/DD/YY"). When using readXlsx() with schema parameter all dates get parsed correctly in any case. But if using readXlsx() without schema parameter (to get "raw" data) then this library attempts to guess whether a cell value is a date or not by examining the cell "format" (e.g. "MM/DD/YY"), so in most cases dates are detected and parsed automatically. For exotic cases one can pass an explicit dateFormat parameter (e.g. "MM/DD/YY") to instruct the library to parse numbers with such "format" as dates.

JSON

To convert rows to JSON pass schema option to readXlsxFile(). It will return { rows, errors } object instead of just rows.

// An example *.xlsx document:
// -----------------------------------------------------------------------------
// | START DATE | NUMBER OF STUDENTS | IS FREE | COURSE TITLE |    CONTACT     |
// -----------------------------------------------------------------------------
// | 03/24/2018 |         123        |   true  |  Chemistry   | (123) 456-7890 |
// -----------------------------------------------------------------------------

const schema = {
  'START DATE': {
    prop: 'date',
    type: Date
    // Excel stores dates as integers.
    // E.g. '24/03/2018' === 43183.
    // Such dates are parsed to UTC+0 timezone with time 12:00 .
  },
  'NUMBER OF STUDENTS': {
    prop: 'numberOfStudents',
    type: Number,
    required: true
  },
  'COURSE': {
    prop: 'course',
    type: {
      'IS FREE': {
        prop: 'isFree',
        type: Boolean
        // Excel stored booleans as numbers:
        // `1` is `true` and `0` is `false`.
        // Such numbers are parsed to booleans.
      },
      'COURSE TITLE': {
        prop: 'title',
        type: String
      }
    }
  },
  'CONTACT': {
    prop: 'contact',
    required: true,
    parse(value) {
      const number = parsePhoneNumber(value)
      if (!number) {
        throw new Error('invalid')
      }
      return number
    }
  }
}

readXlsxFile(file, { schema }).then(({ rows, errors }) => {
  // `errors` have shape `{ row, column, error, value }`.
  errors.length === 0

  rows === [{
    date: new Date(2018, 2, 24),
    numberOfStudents: 123,
    course: {
      isFree: true,
      title: 'Chemistry'
    },
    contact: '+11234567890',
  }]
})

There are also some additional exported types:

• "Integer" for parsing integer Numbers.
• "URL" for parsing URLs.
• "Email" for parsing email addresses.

A schema entry for a column can also have a validate(value) function for validating the parsed value. It must throw an Error if the value is invalid.

A React component for displaying error info could look like this:

import { parseExcelDate } from 'read-excel-file'

function ParseExcelError({ children: error }) {
  // Human-readable value.
  let value = error.value
  if (error.type === Date) {
    value = parseExcelDate(value).toString()
  }
  // Error summary.
  return (
    <div>
      <code>"{error.error}"</code>
      {' for value '}
      <code>"{value}"</code>
      {' in column '}
      <code>"{error.column}"</code>
      {error.type && ' of type '}
      {error.type && <code>"{error.type.name}"</code>}
      {' in row '}
      <code>"{error.row}"</code>
    </div>
  )
}

When using a schema there's also an optional transformData(data) parameter which can be used for the cases when the spreadsheet rows/columns aren't in the correct format. For example, the heading row may be missing, or there may be some purely presentational or empty rows. Example:

readXlsxFile(file, {
  schema,
  transformData(data) {
    // Adds header row to the data.
    return ['ID', 'NAME', ...].concat(data)
    // Removes empty rows.
    return data.filter(rows => row.filter(column => column !== null).length > 0)
  }
})

Browser compatibility

Node.js *.xlxs parser uses xpath and xmldom packages for XML parsing. The same packages could be used in a browser because all modern browsers (except IE 11) have native DOMParser built-in which could is used instead (meaning smaller footprint and better performance) but since Internet Explorer 11 support is still required the browser version doesn't use the native DOMParser and instead uses xpath and xmldom packages for XML parsing just like the Node.js version.

Advanced

By default it reads the first sheet in the document. If you have multiple sheets in your spreadsheet then pass either sheet: number (sheet index, starting from 1) or sheet: string (sheet name) as part of the options argument (options.sheet is 1 by default):

readXlsxFile(file, { sheet: 2 }).then((data) => {
  ...
})

readXlsxFile(file, { sheet: 'Sheet1' }).then((data) => {
  ...
})

To get the list of sheets one can pass getSheets: true option:

readXlsxFile(file, { getSheets: true }).then((sheets) => {
  // sheets === [{ name: 'Sheet1' }, { name: 'Sheet2' }]
})

References

For XML parsing xmldom and xpath are used.

License

MIT