After weeks of preparation, we’re proud to finally announce Terality hosted demo notebook - the fastest way to take Terality for a test ride, completely free of charge. We wanted to lower the time needed for you to realize what Terality is all about to 1 click! There’s no better way than running a pre-written tutorial on our infrastructure to experience our pandas lightning-fast serverless data processing
As a result, you can see the benefits of using Terality instead of pandas in minutes. Indeed, Terality scales pandas in one line of code. All you have to do is open and run the notebook - we handle the rest. There’s no need to load or upload massive datasets to Amazon or Azure, nor to go through the account authentication process.
You can access the hosted tutorial here, but we suggest reading this article until the end to get the full picture.
Until now, to test Terality, you had to go through the whole process. It’s not very long, but still can take 5 to 10 minutes the first time to do it: you had to create an account, install the Terality Python library, configure and authenticate your account through your terminal, find a dataset if you don’t have one ready, create a notebook, manage the library and dataset imports, and start writing code. It’s a lot of time and steps if you just wanted to see if Terality is the right match for you.
Please note that from the second time you use Terality, you won’t have to go through this whole process as Terality would have been installed and configured already on your local machine. You’d just have to open your notebook and import terality, the exact same way you’d import pandas.
As of now, you only have to open our hosted notebook and run the pre-written code. That’s it! You can even run your own code. Please note that this notebook is not designed for production usage yet. The only purpose, for now, is to allow our future users to test Terality in 1 click.
You can reference the illustration below to get a clearer picture of the steps needed and approximated time for each step:
That’s correct - you can now get started with Terality in seconds! Keep in mind that your mileage may vary for local setup, mostly depending on the Internet speed.
But that’s not something you should worry about with the test notebook. It comes in two flavors, so let’s discuss the differences next.
Our hosted notebook walks you through the process of working with Reddit’s comments dataset from May 2015. The dataset takes 5 GB in RAM. Processing it with pandas would be really slow. We have a 40 GB notebook version if you want to further compare Pandas and Terality. Keep in mind that only the 5 GB version is hosted in our demo environment. In both cases, the goal of this demo notebook is to show you how Terality scales pandas and makes pandas faster by just changing the import line of your notebook.
The notebook opens up in Jupyter Lab, which we’re sure will feel familiar.
So what are you waiting for? There’s even no need to set up an account, just go through the notebook below.
What are your thoughts on our hosted notebook? Are you ready to include Terality in your data science/engineering pipeline? Let us know:
As of today, you can use Terality in your favorite data science online notebook environment - Google Colab. A lot of Google Colab users have been experiencing the pain of getting memory errors and speed issues with Pandas. Indeed, Pandas doesn’t scale well when it comes to processing large datasets above 5 or 10GB.