Connectors / Helper / File Helpers

File Helpers

File Helpers

The File Helpers connector can be used to create files from content or from URLs as well as converting the character encoding of a file into UTF-8.


The File Helpers connector is a useful tool for creating file from ready made content, or from URLs themselves. It can also convert the character encoding of a file into UTF-8 format.

MANIPULATING FILE CONTENT: The File Helpers connector CANNOT manipulate file content, but other connectors within the Tray platform can. For CSV content refer to the CSV Editor docs and XML content refer to the XML Decoder docs.

Note on Operations usage


If you are unsure of the file encoding, but know it to be ANSI, within the properties panel in the field 'Original encoding', select: latin-1 from the dropdown options available.


Please be ware that you cannot convert ASCII to UTF-8 format due to the heritage of this type of encoding.

Mime type

When using certain connectors, like Google Drive, with File Helpers, we need to define the "mime_type." This field describes the type of media. For example, when doing the File Upload operation for Google Drive, the file object that is passed as input requires several fields like mime_type. By default, File Helpers will define mime_type as null, but Google Drive's File Upload operation doesn't accept null value for mime_type.

Therefore, to define mime_type, add a header called "mime_type" and for the value enter in the mime_type (e.g "application/pdf"). It is also important to make sure the filename's extension lines up with what you enter for mime_type (e.g .pdf).

Create File from Object

This example will demonstrate how to create a file from a Salesforce record and then upload the files to an S3 bucket.

The Create file from content operation can be used to pull records from services and extract specific data fields in order to create files based on this content.

This example shows the Create File from Content operation in action.

The complete workflow (using a Manual Trigger for testing purposes) looks like this:

What we will be doing here is:

  • Listing Accounts in Salesforce
  • Looping through each account one-by-one
  • Pulling the required data from each account to create a JSON file based on each account
  • Uploading each account as a file to an S3 bucket

Note that this example is suitable for working with a very small number of records. In a production environment where you might be working with large numbers you will need to use a pagination system to split the records into manageable batches.

1 - List Salesforce Accounts

Please see our Salesforce documentation for instructions on granting Tray access to your Salesforce instance.

With the first Salesforce connector, set the operation to Find Records, the Record Type to 'Account' and set 'Account ID' as the Field to be returned, as this is what we will use to locate each account in the second Salesforce step:

2 - Loop through the Accounts list

For the Loop connector set the operation as Loop List and then grab the list of records from the first Salesforce step using $.steps.salesforce-1.records:

3 - Grab the individual Account data from Salesforce

For each Account, use the second Salesforce step to pull the data needed to create each file by using the Find Records operation. The Record Type is set as Account and you can specify the fields to be returned which will make up the file. The key thing here is that you also set the Condition so that the Account ID is equal to $.steps.loop-1.value.Id:

4 - Create the File from the Account Data

For the File Helpers step set the operation to Create File from Content:

In this example we are setting the Name of the file to be auto-created using the Account ID. This is done using 'interpolation' where we can keep the field type as String and surround the json path in { }.

This is so that we can append '.json' to the filename.

The full entry is {$.steps.salesforce-2.records[0].Id}.json

Note that records[0].Id is used here because the output from salesforce-2 is in the format:

"total": 1,
"next_page_offset": null,
"records": [
"Id": "0014J000003GNllQAG",
"Name": "sForce",
"Type": null,
"Industry": null

So you can see that you are using [0] to get the first record in an array (of one!) and picking Id as the value from that record.

5 - Upload the file to an S3 bucket

Please see our AWS S3 documentation for instructions on granting Tray access to your S3 buckets.

For the AWS S3 step, set the operation to Put Object (File) and choose the Bucket name you wish to upload to. Set the Object Key as the file path including the file name (pulled from file-helpers-1) and set the file as $.steps.file-helpers-1.file:

6 - Check logs and S3 bucket for uploaded files

Once your workflow is correctly configured, click on 'Run workflow' and then check the 'Debug' tab to see if the run is successful:

Finally you can check in S3 to see the files succesfully uploaded:

Create File from URL

This example shows the Create File from URL operation in action by pulling a CSV file attached to an email.

The Create file from URL operation can be used to import a file from a URL and subsequently pass it to another service.

The workflow snippet looks like this:

1 - Email Trigger

The workflow is kicked off by an email trigger, whereby you can send an email with a file (such as a CSV) attached to your worflow, as explained in our Email Trigger documentation.

2 - Create file from URL

Now, for the File Helpers step you can set the operation to Create file from url and use the connector snake to pick up the $.steps.trigger.attachments[0].url jsonpath, which will get the file from the temporary url which Tray has made for the attachment:

3 - Use the created file

The next step is to start using the created file with our CSV Editor or CSV Reader.

The Create CSV from file operation can use the $.steps.file-helpers-1.file.url jsonpath to get the file created by the file helpers step:

For further instructions on how to read and work with CSV files, please see the documentation for our CSV Editor or CSV Reader.

Convert to UTF-8 from URL

Please see the above 'Notes on Operations usage' section for information on ANSI, ASCII and Mime type

It is now possible to convert various types of encoded files (such as Base-64), into UTF-8. Below is a good example of how to convert an ANSI encoded file from Google Drive, into a UTF-8 encoded one.

USER TIP: This connector and operation is ideally paired with the [CSV editor](/platform/connectors/docs/core/csv-processor/) connector as it requires the UTF-8 charset to function!

The completed workflow will look similar to the following:

Step 1 - Setup Manual Trigger & Get URL

Once you have clicked 'Create new workflow' from your main dashboard (and named said new workflow), select the Manual trigger from the trigger options available:

This particular File Helpers operation requires a URL for the document you wish to convert to UTF-8.

The easiest way to get this is by using a connector type that is relevant to the source of your document - in this case we are using a Google document, therefore the Google Drive connector will be needed (as this example is showcasing an ANSI encoded file within a Google drive account, that needs to be converted into UTF-8).

By using its available 'Download file' operation we are able to return the URL of the file needed. This should also be true of other documentation connectors should you wish to utilise them.

Note that the Google Drive connector is needed NOT the Google Docs connector. For more details see their relevant docs pages.

With that said, once you have been redirected to the workflow dashboard, from the connectors panel on the left add a Google Drive connector as your second step. Set the operation to 'Download File'.

Feel free to re-name your steps as you go along to make things clearer for yourself and other users.

Step 2 - Collect & Convert File

Once the properties panel for Google Drive is highlighted, add the 'File ID' of the document that needs converting. You can get this from the URL of the file itself.

Open the document you intend to convert in your browser window, and copy the hash displayed within the address bar.

Add a 'File Helpers' connector, as your second step. Set the operation to 'Convert to UTF-8 from URL'

This is an ANSI encoded file, and because ANSI is a term used to describe a subset of encodings, for this operation make sure to set the 'Original encoding' field to 'latin-1'. Now lets run the workflow. The 'URL' field can be generated using the connector-snake and jsonpathing methods.

In order to specify the information you want, start by using the 'URL' mapping icon (found next to the list input field, within the properties panel) to generate the connector-snake.

While hovering over the 'Download File' step (with the tail end of the connector-snake), select URL from the list of output properties displayed. This will auto-populate a jsonpath within your 'URL' input field, and update the type selector to jsonpath as well.

For more clarification on the pathways you have available, open the Debug panel to view your step's Input and Output.

JSONPATHS: For more information on what jsonpaths are and how to use jsonpaths with, please see our Intro page and Data Guide for more details.
CONNECTOR-SNAKE: The simplest and easiest way to generate your jsonpaths is to use our feature called the Connector-snake. Please see the main page for more details.

As the rest of the fields are not mandatory you need not worry about filling them in at this stage, though feel free to do so depending on your use case.

Step 3 - Display Output

Once you have completed setup, run your workflow by clicking on the green button in the bottom right hand corner named 'Run workflow'.

Open the Debug panel to view your results:

Tadah! Through the magic of you now have a beautiful flawless newly UTF-8 encoded file!

BEST PRACTICES: Whenever you do decide to create your own workflow, please make sure you take a look at our Managing data best practices guide.

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