We were toying with this simple setup to autocomplete python with deep learning

https://github.com/vpj/python_autocomplete

The metric we used to measure the performance was the number of keystrokes saved. That is the model gives a single suggestion of length L and L-1 keystrokes are saved if it matches actual code. It performs pretty well saving around 30-50% key strokes despite being naive.

Next we want to try different architectures and improve inference performance. Right now it’s too slow for any actual usage.

If you have any ideas or suggestions please do share.