title: Meteor-files s3 upload: insert is not a function on client side
body: <p>I'm trying to use ostrio:files aka Meteor-files with s3. When using the <a href="https://github.com/VeliovGroup/Meteor-Files/wiki/AWS-S3-Integration" rel="nofollow noreferrer">example s3 code</a> running Images.insert on the CLIENT returns insert is not a function. My code is exact to example on the s3 integration page other than changing the collection name. Is there additional code needed, or can someone post an example of client side code for the s3 path? I am not using templates, im using react for front-end, though this is basic js. Works perfectly fine if i swap the code in images.js with original non-s3 code for collection-fs, fyi.</p>
  
  <pre><code>import { FilesCollection } from 'meteor/ostrio:files';
  import Images from '../../../api/Images/Images'; //Server-side-file-store.js
  
  submitLogo() {
  var logo = document.getElementById('logoInput').files[0]
  const upload = Images.insert({
      file: logo,
      streams: 'dynamic',
      chunkSize: 'dynamic'
    }, false);
  
  
    upload.on('end', function (error, fileObj) {
      if (error) {
        alert('Error during upload: ' + error);
      } else {
        alert('File "' + fileObj.name + '" successfully uploaded');
      }
      template.currentUpload.set(false);
    });
  
    upload.start();
  }
  </code></pre>
  
  <p>s3 example code with collection name changed</p>
  
  <pre><code>import { Meteor } from 'meteor/meteor';
  import { _ } from 'meteor/underscore';
  import { Random } from 'meteor/random';
  import { FilesCollection } from 'meteor/ostrio:files';
  import stream from 'stream';
  
  import S3 from 'aws-sdk/clients/s3'; /* http://docs.aws.amazon.com/AWSJavaScriptSDK/latest/AWS/S3.html */
  /* See fs-extra and graceful-fs NPM packages */
  /* For better i/o performance */
  import fs from 'fs';
  
  /* Example: S3='{"s3":{"key": "xxx", "secret": "xxx", "bucket": "xxx", "region": "xxx""}}' meteor */
  if (process.env.S3) {
    Meteor.settings.s3 = JSON.parse(process.env.S3).s3;
  }
  
  const s3Conf = Meteor.settings.s3 || {};
  const bound  = Meteor.bindEnvironment((callback) =&gt; {
    return callback();
  });
  
  /* Check settings existence in `Meteor.settings` */
  /* This is the best practice for app security */
  if (s3Conf &amp;&amp; s3Conf.key &amp;&amp; s3Conf.secret &amp;&amp; s3Conf.bucket &amp;&amp; s3Conf.region) {
    // Create a new S3 object
    const s3 = new S3({
      secretAccessKey: s3Conf.secret,
      accessKeyId: s3Conf.key,
      region: s3Conf.region,
      // sslEnabled: true, // optional
      httpOptions: {
        timeout: 6000,
        agent: false
      }
    });
  
    // Declare the Meteor file collection on the Server
    const Images = new FilesCollection({
      debug: false, // Change to `true` for debugging
      storagePath: 'assets/app/uploads/uploadedFiles',
      collectionName: 'Images',
      // Disallow Client to execute remove, use the Meteor.method
      allowClientCode: false,
  
      // Start moving files to AWS:S3
      // after fully received by the Meteor server
      onAfterUpload(fileRef) {
        // Run through each of the uploaded file
        _.each(fileRef.versions, (vRef, version) =&gt; {
          // We use Random.id() instead of real file's _id
          // to secure files from reverse engineering on the AWS client
          const filePath = 'files/' + (Random.id()) + '-' + version + '.' + fileRef.extension;
  
          // Create the AWS:S3 object.
          // Feel free to change the storage class from, see the documentation,
          // `STANDARD_IA` is the best deal for low access files.
          // Key is the file name we are creating on AWS:S3, so it will be like files/XXXXXXXXXXXXXXXXX-original.XXXX
          // Body is the file stream we are sending to AWS
          s3.putObject({
            // ServerSideEncryption: 'AES256', // Optional
            StorageClass: 'STANDARD',
            Bucket: s3Conf.bucket,
            Key: filePath,
            Body: fs.createReadStream(vRef.path),
            ContentType: vRef.type,
          }, (error) =&gt; {
            bound(() =&gt; {
              if (error) {
                console.error(error);
              } else {
                // Update FilesCollection with link to the file at AWS
                const upd = { $set: {} };
                upd['$set']['versions.' + version + '.meta.pipePath'] = filePath;
  
                this.collection.update({
                  _id: fileRef._id
                }, upd, (updError) =&gt; {
                  if (updError) {
                    console.error(updError);
                  } else {
                    // Unlink original files from FS after successful upload to AWS:S3
                    this.unlink(this.collection.findOne(fileRef._id), version);
                  }
                });
              }
            });
          });
        });
      },
  
  
      // Intercept access to the file
      // And redirect request to AWS:S3
      interceptDownload(http, fileRef, version) {
        let path;
  
        if (fileRef &amp;&amp; fileRef.versions &amp;&amp; fileRef.versions[version] &amp;&amp; fileRef.versions[version].meta &amp;&amp; fileRef.versions[version].meta.pipePath) {
          path = fileRef.versions[version].meta.pipePath;
        }
  
        if (path) {
          // If file is successfully moved to AWS:S3
          // We will pipe request to AWS:S3
          // So, original link will stay always secure
  
          // To force ?play and ?download parameters
          // and to keep original file name, content-type,
          // content-disposition, chunked "streaming" and cache-control
          // we're using low-level .serve() method
          const opts = {
            Bucket: s3Conf.bucket,
            Key: path
          };
  
          if (http.request.headers.range) {
            const vRef  = fileRef.versions[version];
            let range   = _.clone(http.request.headers.range);
            const array = range.split(/bytes=([0-9]*)-([0-9]*)/);
            const start = parseInt(array[1]);
            let end     = parseInt(array[2]);
            if (isNaN(end)) {
              // Request data from AWS:S3 by small chunks
              end       = (start + this.chunkSize) - 1;
              if (end &gt;= vRef.size) {
                end     = vRef.size - 1;
              }
            }
            opts.Range   = `bytes=${start}-${end}`;
            http.request.headers.range = `bytes=${start}-${end}`;
          }
  
          const fileColl = this;
          s3.getObject(opts, function (error) {
            if (error) {
              console.error(error);
              if (!http.response.finished) {
                http.response.end();
              }
            } else {
              if (http.request.headers.range &amp;&amp; this.httpResponse.headers['content-range']) {
                // Set proper range header in according to what is returned from AWS:S3
                http.request.headers.range = this.httpResponse.headers['content-range'].split('/')[0].replace('bytes ', 'bytes=');
              }
  
              const dataStream = new stream.PassThrough();
              fileColl.serve(http, fileRef, fileRef.versions[version], version, dataStream);
              dataStream.end(this.data.Body);
            }
          });
  
          return true;
        }
        // While file is not yet uploaded to AWS:S3
        // It will be served file from FS
        return false;
      }
    });
  
    // Intercept FilesCollection's remove method to remove file from AWS:S3
    const _origRemove = Images.remove;
    Images.remove = function (search) {
      const cursor = this.collection.find(search);
      cursor.forEach((fileRef) =&gt; {
        _.each(fileRef.versions, (vRef) =&gt; {
          if (vRef &amp;&amp; vRef.meta &amp;&amp; vRef.meta.pipePath) {
            // Remove the object from AWS:S3 first, then we will call the original FilesCollection remove
            s3.deleteObject({
              Bucket: s3Conf.bucket,
              Key: vRef.meta.pipePath,
            }, (error) =&gt; {
              bound(() =&gt; {
                if (error) {
                  console.error(error);
                }
              });
            });
          }
        });
      });
  
      //remove original file from database
      _origRemove.call(this, search);
    };
  } else {
    throw new Meteor.Error(401, 'Missing Meteor file settings');
  }
  Further image (JPEG, PNG) processing with AWS Lambda
  The basic concept: you already have a S3 folder that you use for storage above. We are going to set a Lambda trigger on that folder and for each file saved into (plus any other condition you wish), we will save a thumb into another folder.
  
  First, sign in to your AWS console and select your region from the top bar. Go to your Lambda dashboard and create a new function.
  
  Add a trigger for S3, select your bucket, select "Object Created(All)", check Enable trigger and save (Add). Then add the "Function Code". The code will be your xxx.js file zipped together with the node_modules folder used by your xxx.js file. Please note that your Lambda function will need to have the same name as your xxx.js file (e.g. JS file name: ImageResizer.js will require the Lambda function name/handler ImageResizer.handler. Upload your ZIP file.
  
  Your resizer JS file
  We will be using two differents methods so please feel free to chose the one you prefer.
  
  Official Lambda resizer by AWS: full documentation here. This is based on sharp.js, claimed to be 4-5 times faster than ImageMagick. Just download the ZIP from the Amazon documentation and follow the steps above. You might want to make sure that the packages in the package.json file are at the toppes version. If not, please run an npm install to latest versions in order to generate the updated node_modules before you zip your index.js and node_modules folder together.
  Resizer based on ImageMagic (example shows a resize to output JPG, 420px width, 85% quality, with a meta attached for CachControl set to 10 days).
  package.json
  {
    "name": "amazon-lambda-resizer",
    "version": "0.0.1",
    "description": "Resizer for lambda images in a S3 bucket from a source_folder to target_folder",
    "main": "index.js",
    "scripts": {
      "start": "node index.js"
    },
    "dependencies": {
      "async": "^2.6.0",
      "aws-sdk": "^2.240.1",
      "gm": "^1.23.1",
      "path": "^0.12.7"
    },
    "keywords": [
      "node",
      "lambda",
      "aws"
    ]
  }
  index.js
  Change to something like ImageResizer.js and make sure this has the same name as your Lambda function / handler
  
  /* Dependencies: */
  const async = require('async');
  const AWS   = require('aws-sdk');
  const gm    = require('gm');
  const util  = require('util');
  const path  = require('path');
  const imageMagick = gm.subClass({ imageMagick: true });
  
  const WEB_WIDTH_MAX = 420;
  const WEB_Q_MAX = 85;
  const FOLDER_DEST = 'thumb/';
  
  AWS.config.update({
    accessKeyId: 'xxxxxxxxxxx',
    secretAccessKey: 'xxxxxxxxxxxxxxxxxxxx'
  });
  
  const s3 = new AWS.S3();
  
  exports.handler = (event, context, callback) =&gt; {
    // Read options from the event.
    // console.log('Reading options from event:\n', util.inspect(event, {depth: 5}));
    const srcBucket = event.Records[0].s3.bucket.name;
  
    // Object key may have spaces or unicode non-ASCII characters.
    const srcKey = decodeURIComponent(event.Records[0].s3.object.key.replace(/\+/g, ' '));
    const dstBucket = srcBucket;
    const imageName = path.basename(srcKey);
  
    // Infer the image type.
    const typeMatch = srcKey.match(/\.([^.]*)$/);
    if (!typeMatch) {
      callback('Could not determine the image type.');
      return;
    }
    const imageType = typeMatch[1];
    if (imageType.toUpperCase() !== 'jpg'.toUpperCase() &amp;&amp; imageType.toUpperCase() !== 'png'.toUpperCase() &amp;&amp; imageType.toUpperCase() !== 'jpeg'.toUpperCase()) {
      callback(`Unsupported image type: ${imageType}`);
      return;
    }
  
    // ****************before async******************
    // Download the image from S3, transform, and upload to a different S3 bucket.
    async.waterfall([
      function download (next) {
        // Download the image from S3 into a buffer.
        s3.getObject({
          Bucket: srcBucket,
          Key: srcKey
        }, next);
      },
      function transformWebMax (response, next) {
        imageMagick(response.Body)
          .resize(WEB_WIDTH_MAX)
          .quality(WEB_Q_MAX)
          // .gravity('Center')
          .strip()
          // .crop(WEB_WIDTH_MAX, WEB_HEIGHT_MAX)
          .toBuffer('jpg', (err, buffer) =&gt; {
            if (err) {
              console.log('An error occurred while saving IM to buffer: ', err)
              return false /* stop the remaining sequence and prevent sending an empty or invalid buffer to AWS */
            } else {
              next(null, response, buffer)
            }
          })
      },
      function uploadWebMax (response, buffer, next) {
        // Stream the transformed image to a different S3 bucket.
        const dstKeyResized = FOLDER_DEST + imageName;
        s3.putObject({
          Bucket: dstBucket,
          Key: dstKeyResized,
          Body: buffer,
          ContentType: response.ContentType,
          CacheControl: 'max-age=864000'
        }, (err, data) =&gt; {
          if (err) {
            console.error(err, err.stack);
          } else {
            console.log('uploaded to web-max Successfully !!');
            next(null, response, buffer);
          }
        });
      }
    ], err =&gt; {
      if (err) {
        console.error('Unable to resize image');
      } else {
        console.log('Successfully resized image');
      }
      callback(null, 'message');
    });
  };
  
  
  export { Images }
  </code></pre>