docs.sheetjs.com/docz/docs/03-demos/09-cloud/02-aws.md

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Amazon Web Services	demos/local/index	demos/extensions/index

import current from '/version.js';

AWS is a Cloud Services platform which includes traditional virtual machine support, "Serverless Functions", cloud storage and much more.

:::caution

AWS iterates quickly and there is no guarantee that the referenced services will be available in the future.

:::

This demo focuses on two key offerings: cloud storage ("S3") and the "Serverless Function" platform ("Lambda").

The NodeJS Module can be shipped in a bundled Lambda function.

:::note

This was tested on 2023 April 24.

:::

AWS Lambda Functions

In this demo, the "Function URL" (automatic API Gateway management) features are used. Older deployments required special "Binary Media Types" to handle formats like XLSX. At the time of testing, the configuration was not required.

Reading Data

In the Lambda handler method, the event.body attribute is a Base64-encoded string. The busboy body parser can accept a decoded body.

Code Sample (click to hide)

This example takes the first uploaded file submitted with the key upload, parses the file and returns the CSV content of the first worksheet.

const XLSX = require('xlsx');
var Busboy = require('busboy');

exports.handler = function(event, context, callback) {
  /* set up busboy */
  var ctype = event.headers['Content-Type']||event.headers['content-type'];
  var bb = Busboy({headers:{'content-type':ctype}});

  /* busboy is evented; accumulate the fields and files manually */
  var fields = {}, files = {};
  bb.on('error', function(err) { callback(null, { body: err.message }); });
  bb.on('field', function(fieldname, val) {fields[fieldname] = val });
  // highlight-start
  bb.on('file', function(fieldname, file, filename) {
    /* concatenate the individual data buffers */
    var buffers = [];
    file.on('data', function(data) { buffers.push(data); });
    file.on('end', function() { files[fieldname] = [Buffer.concat(buffers), filename]; });
  });
  // highlight-end

  /* on the finish event, all of the fields and files are ready */
  bb.on('finish', function() {
    /* grab the first file */
    var f = files["upload"];
    if(!f) callback(new Error("Must submit a file for processing!"));

    /* f[0] is a buffer */
    // highlight-next-line
    var wb = XLSX.read(f[0]);

    /* grab first worksheet and convert to CSV */
    var ws = wb.Sheets[wb.SheetNames[0]];
    callback(null, { statusCode: 200, body: XLSX.utils.sheet_to_csv(ws) });
  });

  /* start the processing */
  // highlight-next-line
  bb.end(Buffer.from(event.body, "base64"));
};

Writing Data

For safely transmitting binary data, the base64 type should be used. Lambda callback response isBase64Encoded property forces a binary download.

Code Sample (click to hide)

This example generates a sample workbook and writes to a XLSX workbook.

var XLSX = require('xlsx');

exports.handler = function(event, context, callback) {
  /* make workbook */
  var wb = XLSX.read("S,h,e,e,t,J,S\n5,4,3,3,7,9,5", {type: "binary"});
  /* write to XLSX file in Base64 encoding */
  // highlight-next-line
  var body = XLSX.write(wb, { type: "base64", bookType: "xlsx" });
  /* mark as attached file */
  var headers = { "Content-Disposition": 'attachment; filename="SheetJSLambda.xlsx"'};
  /* Send back data */
  callback(null, {
    statusCode: 200,
    // highlight-next-line
    isBase64Encoded: true,
    body: body,
    headers: headers
  });
};

Demo

Complete Example (click to hide)

0. Review the quick start for JavaScript on AWS

1. Create a new folder and download index.js:

mkdir -p SheetJSLambda
cd SheetJSLambda
curl -LO https://docs.sheetjs.com/aws/index.js

2. Install dependencies to the current directory;

mkdir -p node_modules
npm install https://cdn.sheetjs.com/xlsx-latest/xlsx-latest.tgz busboy

3. Create a .zip package of the contents of the folder:

yes | zip -c ../SheetJSLambda.zip -r .

4. In the web interface for AWS Lambda, create a new Function with the options:

• Select "Author from scratch" (default choice when last verified)
• "Function Name": SheetJSLambda
• "Runtime": "Node.js" (select the version in the "Latest supported" block)
• Advanced Settings:
  • check "Enable function URL"
  • Auth type: NONE
  • Check "Configure cross-origin resource sharing (CORS)"

5. In the Interface, click "Upload from" and select ".zip file". Click the "Upload" button in the modal, select SheetJSLambda.zip, and click "Save".

When the demo was last tested, the ZIP was small enough that the Lambda code editor will load the package.

6. Enable external access to the function.

Under Configuration > Function URL, click "Edit" and ensure that Auth type is set to NONE. If it is not, select NONE and click Save.

Under Configuration > Permissions, scroll down to "Resource-based policy". If no policy statements are defined, select "Add Permission" with the options:

• Select "Function URL" at the top
• Auth type: NONE
• Ensure that Statement ID is set to FunctionURLAllowPublicAccess
• Ensure that Principal is set to *
• Ensure that Action is set to lambda:InvokeFunctionUrl

Click "Save" and a new Policy statement should be created.

7. Find the Function URL (It is in the "Function Overview" section).

Try to access that URL in a web browser and the site will try to download SheetJSLambda.xlsx. Save and open the file to confirm it is valid.

To test parsing, download https://sheetjs.com/pres.numbers and make a POST request to the public function URL (change FUNCTION_URL in the command):

curl -X POST -F "upload=@pres.numbers" FUNCTION_URL

The result should be a CSV output of the first sheet.

S3 Storage

The main module for S3 and all AWS services is aws-sdk.

Reading Data

The s3#getObject method returns an object with a createReadStream method. Buffers can be concatenated and passed to XLSX.read.

Demo (click to hide)

This sample fetches a buffer from S3 and parses the workbook.

1. Save the following script to SheetJSReadFromS3.js:

var XLSX = require("xlsx");
var AWS = require('aws-sdk');

/* replace these constants */
var accessKeyId = "<REPLACE WITH ACCESS KEY ID>";
var secretAccessKey = "<REPLACE WITH SECRET ACCESS KEY>";
var Bucket = "<REPLACE WITH BUCKET NAME>";

var Key = "pres.numbers";

/* Get stream */
var s3 = new AWS.S3({
  apiVersion: '2006-03-01',
  credentials: {
    accessKeyId: accessKeyId,
    secretAccessKey: secretAccessKey
  }
});
var f = s3.getObject({ Bucket: Bucket, Key: Key }).createReadStream();

/* collect data */
var bufs = [];
f.on('data', function(data) { bufs.push(data); });
f.on('end', function() {
  /* concatenate and parse */
  var wb = XLSX.read(Buffer.concat(bufs));
  console.log(XLSX.utils.sheet_to_csv(wb.Sheets[wb.SheetNames[0]]));
});

2. Create a new bucket (or get the name of an existing bucket).

3. Download https://sheetjs.com/pres.numbers

In the S3 site, open the bucket and click "Upload". In the Upload page, click and drag the pres.numbers file into the browser window and click "Upload".

4. Edit SheetJSReadFromS3.js and replace the marked constants:

• accessKeyId: access key for the AWS account
• secretAccessKey: secret access key for the AWS account
• Bucket: name of the bucket

5. Run the script:

node SheetJSReadFromS3.js

The program will display the data in CSV format.

Writing Data

S3#upload directly accepts a Buffer.

Demo (click to hide)

This sample creates a simple workbook, generates a NodeJS buffer, and uploads the buffer to S3.

1. Save the following script to SheetJSWriteToS3.js:

var XLSX = require("xlsx");
var AWS = require('aws-sdk');

/* replace these constants */
var accessKeyId = "<REPLACE WITH ACCESS KEY ID>";
var secretAccessKey = "<REPLACE WITH SECRET ACCESS KEY>";
var Bucket = "<REPLACE WITH BUCKET NAME>";

var Key = "test.xlsx";

/* Create a simple workbook and write XLSX to buffer */
var ws = XLSX.utils.aoa_to_sheet(["SheetJS".split(""), [5,4,3,3,7,9,5]]);
var wb = XLSX.utils.book_new(); XLSX.utils.book_append_sheet(wb, ws, "Sheet1");
var Body = XLSX.write(wb, {type: "buffer", bookType: "xlsx"});

/* upload buffer */
var s3 = new AWS.S3({
  apiVersion: '2006-03-01',
  credentials: {
    accessKeyId: accessKeyId,
    secretAccessKey: secretAccessKey
  }
});
s3.upload({ Bucket: Bucket, Key: Key, Body: Body }, function(err, data) {
  if(err) throw err;
  console.log("Uploaded to " + data.Location);
});

2. Create a new bucket (or get the name of an existing bucket).

3. Edit SheetJSWriteToS3.js and replace the marked constants:

• accessKeyId: access key for the AWS account
• secretAccessKey: secret access key for the AWS account
• Bucket: name of the bucket

4. Run the script:

node SheetJSWriteToS3.js

5. In the S3 site, select the bucket and download the object named test.xlsx. Open the file in a spreadsheet editor.