stevetarver / excel-as-json

npm package that converts excel data to json
MIT License
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Convert Excel Files to JSON

What

Parse Excel xlsx files into a list of javascript objects and optionally write that list as a JSON encoded file.

You may organize Excel data by columns or rows where the first column or row contains object key names and the remaining columns/rows contain object values.

Expected use is offline translation of Excel data to JSON files, although all methods are exported for other uses.

Install

$ npm install excel-as-json --save-dev

Use

convertExcel = require('excel-as-json').processFile;
convertExcel(src, dst, options, callback);

NOTE If options are not specified, defaults are used.

With these arguments, you can:

Convert a row/col oriented Excel file to JSON as a development task and log errors:

convertExcel = require('excel-as-json').processFile

options = 
    sheet:'1'
    isColOriented: false
    omitEmtpyFields: false

convertExcel 'row.xlsx', 'row.json', options, (err, data) ->
    if err then console.log "JSON conversion failure: #{err}"

options = 
    sheet:'1'
    isColOriented: true
    omitEmtpyFields: false

convertExcel 'col.xlsx', 'col.json', options, (err, data) ->
    if err then console.log "JSON conversion failure: #{err}"

Convert Excel file to an object tree and use that tree. Note that properly formatted data will convert to the same object tree whether row or column oriented.

convertExcel = require('excel-as-json').processFile

convertExcel 'row.xlsx', undefined, undefined, (err, data) ->
    if err throw err
    doSomethingInteresting data

convertExcel 'col.xlsx', undefined, {isColOriented: true}, (err, data) ->
    if err throw err
    doSomethingInteresting data

Why?

What's the challenge?

Excel stores tabular data. Converting that to JSON using only a couple of assumptions is straight-forward. Most interesting JSON contains nested lists and objects. How do you map a flat data square that is easy for anyone to edit into these nested lists and objects?

Solving the challenge

Excel Data

What is the easiest way to organize and edit your Excel data? Lists of simple objects seem a natural fit for a row oriented sheets. Single objects with more complex structure seem more naturally presented as column oriented sheets. Doesn't really matter which orientation you use, the module allows you to speciy a row or column orientation; basically, where your keys are located: row 0 or column 0.

Keys and values:

Examples

A simple, row oriented key

firstName
Jihad

produces

[{
  "firstName": "Jihad"
}]

A dotted key name looks like

address.street
12 Beaver Court

and produces

[{
  "address": {
    "street": "12 Beaver Court"
    }
}]

An indexed array key name looks like

phones[0].number
123.456.7890

and produces

[{
  "phones": [{
      "number": "123.456.7890"
    }]
}]

An embedded array key name looks like this and has ';' delimited values

aliases[]
stormagedden;bob

and produces

[{
  "aliases": [
    "stormagedden",
    "bob"
  ]
}]

A more complete row oriented example

firstName lastName address.street address.city address.state address.zip
Jihad Saladin 12 Beaver Court Snowmass CO 81615
Marcus Rivapoli 16 Vail Rd Vail CO 81657

would produce

[{
    "firstName": "Jihad",
    "lastName": "Saladin",
    "address": {
      "street": "12 Beaver Court",
      "city": "Snowmass",
      "state": "CO",
      "zip": "81615"
    }
  },
  {
    "firstName": "Marcus",
    "lastName": "Rivapoli",
    "address": {
      "street": "16 Vail Rd",
      "city": "Vail",
      "state": "CO",
      "zip": "81657"
    }
  }]

You can do something similar in column oriented sheets. Note that indexed and flat arrays are added.

firstName Jihad Marcus
lastName Saladin Rivapoli
address.street 12 Beaver Court 16 Vail Rd
address.city Snowmass Vail
address.state CO CO
address.zip 81615 81657
phones[0].type home home
phones[0].number 123.456.7890 123.456.7891
phones[1].type work work
phones[1].number 098.765.4321 098.765.4322
aliases[] stormagedden;bob mac;markie

would produce

[
  {
    "firstName": "Jihad",
    "lastName": "Saladin",
    "address": {
      "street": "12 Beaver Court",
      "city": "Snowmass",
      "state": "CO",
      "zip": "81615"
    },
    "phones": [
      {
        "type": "home",
        "number": "123.456.7890"
      },
      {
        "type": "work",
        "number": "098.765.4321"
      }
    ],
    "aliases": [
      "stormagedden",
      "bob"
    ]
  },
  {
    "firstName": "Marcus",
    "lastName": "Rivapoli",
    "address": {
      "street": "16 Vail Rd",
      "city": "Vail",
      "state": "CO",
      "zip": "81657"
    },
    "phones": [
      {
        "type": "home",
        "number": "123.456.7891"
      },
      {
        "type": "work",
        "number": "098.765.4322"
      }
    ],
    "aliases": [
      "mac",
      "markie"
    ]
  }
]

Data Conversions

All values from the 'excel' package are returned as text. This module detects numbers and booleans and converts them to javascript types. Booleans must be text 'true' or 'false'. Excel FALSE and TRUE are provided from 'excel' as 0 and 1 - just too confusing.

Caveats

During install (mac), you may see compiler warnings while installing the excel dependency - although questionable, they appear to be benign.

Running tests

You can run tests after GitHub clone and npm install with:

ᐅ npm run-script test

> excel-as-json@2.0.1 test /Users/starver/code/makara/excel-as-json
> tools/test.sh

  assign
    ✓ should assign first level properties
    ✓ should assign second level properties
    ✓ should assign third level properties
#...

Bug Reports

To investigate bugs, we need to recreate the failure. In each bug report, please include:

Contributing

This project is small and simple and intends to remain that way. If you want to add functionality, please raise an issue as a place we can discuss it prior to doing any work.

You are always free to fork this repo and create your own version to do with as you will, or include this functionality in your projects and modify it to your heart's content.

TODO

Change History

2.0.2

2.0.1

2.0.0

1.0.0