[Bug] Virtual text wrap for pandas

[Lun4m]

• OS: Ubuntu 23.10
• NeoVim Version: 0.9.1
• Python Version: 3.11.6
• Python is installed with: apt
• Health checks

`:checkhealth molten`

==============================================================================
molten: require("molten.health").check()

molten-nvim ~

• OK NeoVim >=0.9
• OK Python >=3.10
• OK Python module pynvim found
• OK Python module jupyter-client found
• OK Python module cairosvg found
• WARNING Optional python module pnglatex not found
  • ADVICE:
    • pip install pnglatex
• WARNING Optional python module plotly not found
  • ADVICE:
    • pip install plotly
• WARNING Optional python module kaleido not found
  • ADVICE:
    • pip install kaleido
• OK Python module pyperclip found
• OK Python module nbformat found

Description

Not that big of a deal, but pandas Dataframe virtual text outputs wrap even if vim.g.molten_wrap_output = false.
I'm using molten as the REPL provider for NotebookNavigator.

Reproduction Steps

This wraps

import numpy as np
import pandas as pd
columns = ["sourceId", "referenceTime", "elementId", "value", "unit", "timeOffset", "someother", "another", "anotheroneone", "verylongname"]
df = pd.DataFrame(
    data={col: np.linspace(0, 10, 20) for col in columns},
)
print(df.head())

This does not wrap

print(100 * "-!-")

My molten config

{
  "benlubas/molten-nvim",
  version = "^1.0.0", -- use version <2.0.0 to avoid breaking changes
  dependencies = { "3rd/image.nvim" },
  build = ":UpdateRemotePlugins",
  init = function()
    vim.g.molten_image_provider = "image.nvim"
    vim.g.molten_virt_text_output = true
    vim.g.molten_virt_text_max_lines = 40
    vim.g.molten_wrap_output = false
  end,
}

Expected Behavior

In both cases output text should not be wrapped.

[benlubas]

this is the way pandas formats it's output, not an issue with molten

[Lun4m]

Do you know if it's specifically for the jupyter protocol? Because if I put that snippet in a script and run it in the terminal the output doesn't wrap 🤔

Edit:
It seeems so, I just found out you need to add this for it to work in Jupyter

pd.set_option("display.expand_frame_repr", False)