Import a list output from Jupyter Notebook to Grasshopper?

[l.zhitnik]

Hey there!
I’ve been working on a project that produces massive amounts of data.
Obviously this is done in CPython (using Jupyter N). After filtering the data, I have a list of dictionaries that I would like to export from JN into GH, and to read that list as is in the Grasshopper Python module (in order to avoid creating heavy csv files and reading them with GH tools which is very heavy and time consuming).

Is that possible? Can I import a .py file with a list, or maybe even a .txt file straight into GH and have the Python component read it?

Thanks a lot,
Lev

[Kalpit_3d]

I think you should first import file using “get file” node then try with panels and other things for desired result.

[AndersDeleuran]

You can serialise the data using the native pickle module:

Serializing to file

Specifically to GHPython, I tend to structure RhinoCommon geometry data and more primitive types (floats, integers, strings, booleans) into a dictionary. And then pickle/unpickle (i.e. serialise) that to/from file using the standard pickle module: https://ironpython-test.readthedocs.io/en/latest/library/pickle.html Note that there’s also the cpickle standard module, and that not all data types will pickle. If you’re only interested in primitive types, I’d advice to use the standard json module…

And using native json for a more universal solution:

Python script to save/load GH Inputs (sliders, panels, etc)

Indeed, here’s a quick example of the first part (i.e. how to get and write slider/toggle/panel data to disk): 211117_WriteNamedObjectDataToDisk_01.gh (7.2 KB) (Edit: Added “pretty print” JSON formatting) For value lists, have a look at this example:

Edit: Assuming Jupyter Notebook can send/host raw textual data to a URL, you can also read that directly (i.e. skipping saving to file). Here’s a quick example demonstrating how to read a JSON file from a URL and casting that to a dictionary:

230623_ReadJsonFromUrl_00.gh (1.9 KB)

[Jacques_Gaudin]

You can run a Flask server from your Jupyter Notebook (to install Flask, just pip install Flask in your Jupyter environment).

To run the server and serve some data:

Flask_server.ipynb.py (1.1 KB)
I had to change the extension to upload the file, just get rid of the .py

Then to retrieve the data in Grasshopper:

client.gh (3.8 KB)

This way you don’t have to write to a file BUT I’m not sure how that will work with large data, you will need to segment it I believe, however I didn’t get that far.
Also the server needs a bit of work if you want to have decent security.