
External Data Sources: Adding clarity to cargo tracking
The new External Data Sources feature allows Vortexa users to distinguish between BoLs, port and fixtures data that underpin product and grade information.

Vortexa launch easy-accessible Jupyter Notebooks throughout PythonSDK documentation.
Behind me stands a wall that encircles the techies of this world, part of a vast system of barriers that divides the professional workforce between those who code, and those who do not.
It is unfortunate that learning to code often begins with the barrier-to-entry that is creating venvs, hosting servers, writing lockfiles?
To achieve our goals in this changing energy industry, we must tear down this wall. It must be trivially easy for experts in all fields to start writing scripts, with the same comfort they're accustomed to when writing word documents, slide decks, or spreadsheets.
Brilliant ideas are spawned at the intersection of different disciplines. By removing the barrier to entry we allow domain experts to exercise the power of Python.
Brilliant things come from the spreading of ideas. Source: https://xkcd.com/
It was this thinking that led us to embed Jupyter Notebooks throughout our PythonSDK documentation.
Step 1. Open the PythonSDK docs
Step 2. Click any 'try-me-out' button to launch a Jupyter Notebook in your browser.
That's it!
You'll then have a notebook in your browser, pre-populated with all the requirements to explore the world's global waterborne oil & gas data.
Click here to launch this notebook in your browser.
Keep an eye out for 'try-me-out' buttons like these in the SDK docs.
Buttons like these throughout the SDK docs will open up Jupyter Notebooks in your browser.
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