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    excel-2-json

    1.0.1 • Public • Published

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    Convert Excel Files to JSON

    Install

    Expected use is offline translation of Excel data to JSON files, although async facilities are provided.

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

    Use

    convertExcel = require('excel-as-json').processFile;
    convertExcel(<src>, <dst>, isColOriented, callback);
    • src: path to source Excel file (xlsx only) - will read sheet 0
    • dst: path to destination JSON file. If null, simply return the parsed object tree
    • isColOriented: is an Excel row an object, or is a column an object (Default: false)
    • callback(err, data): callback for completion notification

    With these arguments, you can:

    • convertExcel(src, dst) will write a row oriented xlsx to file with no notification
    • convertExcel(src, dst, true) will write a col oriented xlsx to file with no notification
    • convertExcel(src, dst, true, callback) will write a col oriented xlsx to file and notify with errors and data
    • convertExcel(src, null, true, callback) will return errors and the parsed object tree in the callback

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

    convertExcel = require('excel-as-json').processFile
     
    convertExcel 'row.xlsx', 'row.json', false, (err, data) ->
        if err then console.log "JSON conversion failure: #{err}"
    convertExcel 'col.xlsx', 'col.json', true, (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, false, (err, data) ->
        if err throw err
        doSomethingInteresting data
    convertExcel 'col.xlsx', undefined, true, (err, data) ->
        if err throw err
        doSomethingInteresting data

    Why?

    • Your application serves static data obtained as Excel reports from another application
    • Whoever manages your static data finds Excel more pleasant than editing JSON
    • Your data is the result of calculations or formatting that is more simply done in Excel

    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

    • Use a key row to name JSON keys
    • Allow data to be stored in row or column orientation.
    • Use javascript notation for keys and arrays
      • Allow dotted key path notation
      • Allow arrays of objects and literals

    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:

    • Row or column 0 contains JSON key paths
    • Remaining rows/columns contain values for those keys
    • Multiple value rows/columns represent multiple objects stored as a list
    • Within an object, lists of objects have keys like phones[1].type
    • Within an object, flat lists have keys like aliases[]

    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.

    TODO

    • provide processSync - using 'async' module
    • Detect and convert dates
    • Make 1 column values a single object?

    Change History

    1.0.0

    • Changed process() to processFile() to avoid name collision with node's process object
    • Automatically convert text numbers and booleans to native values
    • Create destination directory if it does not exist

    Install

    npm i excel-2-json

    DownloadsWeekly Downloads

    2

    Version

    1.0.1

    License

    MIT

    Last publish

    Collaborators

    • lxxyx