How to load data from Trello to Google BigQuery

Blendo Team

This post helps you with loading your data from Trello to BigQuery. If you are looking to get analytics-ready data without the manual hassle you can integrate Trello to BigQuery with Blendo, so you can focus on what matters, getting value out of your data.

Extract your data from Trello

Trello exposes a very rich API to developers. It is the same API that is used internally to build the web and mobile Trello apps that we all use and love. It is possible to build a completely new application on top of the API using the different components and resources that it exposes, or just use it to pull out data as we plan to do in our case.

The Trello API follows the RESTful principles and it can be access through HTTP. As a RESTful API, interacting with it an be achieved by using tools like CURL or Postman or by using http clients for your favourite language or framework. A few suggestions:

Trello also offers an official Javascript client/wrapper for its API, that can be found here. It is also possible to find numerous other unofficial SDKs, all it takes is a quick search on Google or Github.

About Trello

Trello is a collaboration tool that organises your projects into visual boards. In one glance, Trello tells you what’s being worked on, who’s working on what, and where something is in progress. Trello is simple but flexible enough to allow you to organise your boards using any methodology that you like, for example many people use Trello to run Kanban.

Trello is simple on the surface, but cards have everything you need to get stuff done. You can post comments for instant feedback. Upload your files from Google Drive, Dropbox, Box, and OneDrive. Add checklists, labels, due dates, and more. Notifications make sure you always know when important stuff happens.

It offers a very simple pricing scheme:

  • Free: this first tier might cover the majority of users. You have access to all the basic functionalities that Trello

  • Business Class & Enterprise. Charged per seat and per month. the main difference between the two are the number of teams that are supported. Also app integration, team overview, increased file size allowed, file encryption, better support, restricted membership and enterprise grade security is provided compared to the Free

As more and more teams rely on Trello to run and track their projects, there is valuable data to be pulled from it that can help you to better understand the productivity of your company. For example by pulling data out from Trello and store it into Google BigQuery,  you can calculate numerous metrics about your sprint, like its current burndown rate. Identify projects with problems and figure out potential bottlenecks. In this article, we will find out how we can pull data from Trello to Google BigQuery for further analysis.

Trello API Authentication

Authentication and Authorisation is supported by the Trello API by implementing the oAuth protocol. It’s important to understand that the Authentication Token, obtained through the oAuth workflow execution,  gives your application the ability to make calls on behalf of your user, from their context. This token grants access to the authenticated user’s boards, lists, Cards, and other settings, depending on the permissions you requested in the authenticate method. So you have to handle it with care 🙂

Trello rate limiting

To help prevent strain on Trello’s servers, our API imposes rate limits per API key for all issued tokens. There is a limit of 300 requests per 10 seconds for each API key and no more than 100 requests per 10 second interval for each token. If a request exceeds the limit, Trello will return a 429 error.

Endpoints and available resources

The Trello API exposes a large number of resources together with their associated HTTP endpoints that allow the users to interact with the platform as the web and mobile applications of Trello do. The most important resources are the following:

  • Board: anything related to the boards a user can create and manage in Trello
  • Card: operations about the cards that can be created inside boards
  • Checklist: it allows the creation and manipulation of checklists inside cards
  • Label: operations related to labels that can be created inside cards
  • List: operations on lists
  • Member: operations related to members of a board
  • Notification: operations about the notification system of the platform
  • Organization: manage organisations inside Trello

So, let’s assume that you have a board that helps you track one of your projects, the methodology doesn’t matter at this points, what is important is that you most probably will have cards associate to tasks, and these cards are holding information that you would like to pull, store in a database like Google BigQuery and analyse it further. First we assume that we know the ID of our board,

  • our board id is 4eea4ffc91e31d1746000046

First we want to get all the lists that this board includes. To do that, we execute a GET request on the following URL:[application_key]&token=[optional_auth_token]

If the request is successful we will get back a response like the following:

    "id": "4eea4ffc91e31d174600004a",
    "name": "To Do Soon",
    "cards": [{
        "id": "4eea503791e31d1746000080",
        "name": "Finish my awesome application"
}, {
    "id": "4eea4ffc91e31d174600004b",
    "name": "Doing",
    "cards": [{
        "id": "4eea503d91e31d174600008f",
        "name": "Learn about the Trello API"
    }, {
        "id": "4eea522c91e31d174600027e",
        "name": "Figure out how to read a user's board list"
}, {
    "id": "4eea4ffc91e31d174600004c",
    "name": "Done",
    "cards": [{
        "id": "4eea501f91e31d1746000062",
        "name": "Get a key to use in my API requests"
    }, {
        "id": "4eea502b91e31d1746000071",
        "name": "Find out where the Trello API documentation is"

The above JSON response includes all the lists that our product has. Each least will contain cards with tasks and for example if we have a card inside the “Done” list it means that the associated task is completed.

After we got a list of all the lists we can start fetching the cards of each list. Again we do that by executing a GET request to the appropriate endpoint, using the IDs of the lists that we have extracted from the previous response. A typical URL for fetching the cards of a list looks like the following:[application_key]&token=[optional_auth_token]

And the result of a successful request to the above endpoint will result to something with the following structure:

    "id": "4eea503791e31d1746000080",
    "badges": {
        "votes": 0,
        "viewingMemberVoted": false,
        "subscribed": false,
        "fogbugz": "",
        "checkItems": 0,
        "checkItemsChecked": 0,
        "comments": 0,
        "attachments": 0,
        "description": false,
        "due": null
    "checkItemStates": [],
    "closed": false,
    "dateLastActivity": "2011-12-15T19:53:27.228Z",
    "desc": "",
    "descData": null,
    "due": null,
    "email": null,
    "idAttachmentCover": null,
    "idBoard": "4eea4ffc91e31d1746000046",
    "idChecklists": [],
    "idLabels": [],
    "idList": "4eea4ffc91e31d174600004a",
    "idMembers": [],
    "idMembersVoted": [],
    "idShort": 3,
    "labels": [],
    "manualCoverAttachment": false,
    "name": "Finish my awesome application",
    "pos": 65536,
    "shortLink": "XlG8S7ll",
    "shortUrl": "",
    "subscribed": null,
    "url": ""

We have retrieved all the relevant to our project information from our board. We just need to remodel our data in an appropriate way for us to query it on a database like Google BigQuery and of course ensure that we properly load the data to it. After we do that we are ready start querying our Trello data and learning everything related to the performance of our teams and projects.

Prepare your data to be sent from Trello to Google BigQuery

Before you load your data into BigQuery, you should make sure that it is presented in a format supported by it, so for example if the API you pull data from returns XML you have to first transform it into a serialisation that BigQuery understands. Currently two data formats are supported:

You also need to make sure that the data types you are using are the ones supported by BigQuery, which are the following:


for more information please check the Preparing Data for BigQuery page on the documentation.

About Google BigQuery

BigQuery is the data warehousing solution of Google. It’s part of the Google Cloud Platform and it also speaks SQL like Redshift does. Queries are executed against append-only tables using the processing power of Google’s infrastructure. It is also fully managed and is offered as a service over the cloud. You can interact with it through its web UI, using a command line tool while a variety of client libraries exist so you can interact with it through your application.

Load Data from Trello to Google BigQuery

If you want to load data from Trello to Google BigQuery, you have to use one of the following supported data sources.

  1. Google Cloud Storage
  2. Sent data directly to BigQuery with a POST request
  3. Google Cloud Datastore Backup
  4. Streaming insert
  5. App Engine log files
  6. Cloud Storage logs

From the above list of sources, 5 and 6 are not applicable in our case.

For Google Cloud Storage, you first have to load your data into it, there are a few options on how to do this, for example you can use the console directly as it is described here and do not forget to follow the best practices. Another option is to post your data through the JSON API, as we see again APIs play an important role in both the extraction but also the loading of data into our data warehouse.. In it’s simplest case it’s just a matter of one HTTP POST request using a tool like CURL or Postman. It should look like the following example.

POST /upload/storage/v1/b/myBucket/o?uploadType=media&name=myObject HTTP/1.1
Content-Type: application/text
Content-Length: number_of_bytes_in_file
Authorization: Bearer your_auth_token your Trello data

and if everything went ok, you should get something like the following as a response from the server:

HTTP/1.1 200
Content-Type: application/json
"name": "myObject"

Working with Curl or Postman, is good only for testing, if you would like to automate the process of loading your data into Google Bigquery, you should write some code to send your data to Google Cloud Storage. In case you are developing on the Google App Engine you can use the library that is available for the languages that are supported by it:

  1. Python
  2. Java
  3. PHP
  4. Go

If you are using one of the above languages and you are not coding for the Google App Engine, you can use it to access the Cloud Storage from your environment. Interacting such a feature rich product like Google Cloud Storage can become quite complicated depending on your use case, for more details on the different options that exist you can check Google Cloud Storage documentation. If you are looking for a less engaged and more neutral way of using Cloud Storage, you can consider a solution like Blendo.

After you have loaded your data into Google Cloud Storage, you have to create a Load Job for BigQuery to actually load the data into it, this Job should point to the source data in Cloud Storage that have to be imported, this happens by providing source URIs that point to the appropriate objects.

The previous method described, used a POST request to the Google Cloud Storage API for storing the data there and then load it into BigQuery. Another way to go is to do a direct HTTP POST request to BigQuery with the data you would like to query. This approach is similar to how we loaded the data to Google Cloud Storage through the JSON API, but it uses the appropriate end-points of BigQuery to load the data there directly. The way to interact with it is quite similar, for more information can be found on the Google BigQuery API Reference and on the page that describes how to load data into BigQuery using POST. You can interact with it using the HTTP client library of the language or framework of your choice, a few options are:

The best way to load data from Trello to BigQuery

So far we just scraped the surface of what you can do with BigQuery and how to load data into it. Things can get even more complicated if you want to integrate data coming from different sources.

Are you striving to achieve results right now?

Instead of writing, hosting and maintaining a flexible data infrastructure use Blendo that can handle everything automatically for you.

Blendo with one click integrates with sources or services, creates analytics-ready data and syncs your Trello to BigQuery right away.