Large Data Apps With Anvil’s Data Files Service
Easily Work with Large Datasets and ML Models with Anvil’s Python-based Data Files API.
Anvil’s New Data Files Service
Python has lots of great libraries for interacting with files, large datasets and machine learning models. And today we are happy to announce a new feature in Anvil to make it easier than ever to use large files and machine learning models in your Python code. We are launching Anvil’s new Data Files Service.
What are we releasing?
Data Files are files that you, as the app developer, can attach to your app. These files are available in your Server Modules. Data Files can be uploaded and accessed using the new built-in Data Files service.
There’s a new API to access and manage Data Files. Accessing files is as simple as using square brackets:
data = pandas.read_csv(data_files['my_spreadsheet.csv'])What can I use it for?
Any application that uses bulk static data! For example, you might build a dashboard that queries a CSV of static data using pandas. Or you might build an app around a machine-learning model, which loads a file of stored weights into PyTorch, Tensorflow or scikit-learn.
Get started right now
Check out our Quick Start guide to learn about using the Data Files Service.
Deploy a machine learning model
We’ve got a brand new tutorial to show you how to deploy an ML model and use it in your Anvil app:
More about Anvil
If you’re new here, welcome! Anvil is a platform for building full-stack web apps with nothing but Python. No need to wrestle with JS, HTML, CSS, Python, SQL and all their frameworks — just build it all in Python.
