KUkushalkolar·Mar 13, 2025
I just commented above, see this: https://github.com/vispy/jupyter_rfb/issues/95#issuecomment-...
In Fastplotlib: GPU-accelerated, fast, and interactive plotting libraryvispy
jupyter_rfb
Python2024–2025
vispy / jupyter_rfb
jupyter_rfb
Remote Frame Buffer for Python notebooks
3Distinct people
6Mentions
0Explicit recommenders
88GitHub stars
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What it is
Remote Frame Buffer for Python notebooks
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No documented product use has been verified yet.
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- pyqtgraph/pyqtgraph · linked in 2 of the same discussions
Mentioned in the same Hacker News threads. That is not proof they are substitutes.
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| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
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| Mar 2025 | 2025-03-01 00:00:00 UTC | 2025-04-01 00:00:00 UTC | 4 | 0 | 4 |
What Hacker News says
6 sourcesI just remembered, I think there is something weird with Google's servers or the network because performance was very poor even with a custom Google Cloud instance running jupyterlab, see this: https://github.com/vispy/jupyter_rfb/issues/95#issuecomment-...
In Fastplotlib: GPU-accelerated, fast, and interactive plotting libraryThanks Ivo!
Just to add on, colab is weird and not performant, this PR outlines our attempts to get jupyter-rfb working on colab: https://github.com/vispy/jupyter_rfb/pull/77
In Fastplotlib: GPU-accelerated, fast, and interactive plotting libraryFastplotlib definitely works in Jupyterlab through jupyter-rfb
https://github.com/vispy/jupyter_rfb
I believe the performance is pretty decent, especially if you run the kernel locally
Their docs also cover this as mentioned by @clewis7 below: https://www.fastplotlib.org/ver/dev/user_guide/faq.html#what...
In Fastplotlib: GPU-accelerated, fast, and interactive plotting libraryFrom "Show HN: We open-sourced our [rpi CSV] compost monitoring tech" https://news.ycombinator.com/item?id=42201207 :
Nagios, Collectd, [Prometheus], Grafana
From "Preview of Explore Logs, a new way to browse your logs without writing LogQL"
https://news.ycombinator.com/item?id=39981805 :
> Grafana supports SQL, PromQL, InfluxQL, and LogQL.
From https://news.ycombinator.com/item?id=40164993 :
> But that's not a GUI, that's notebooks. For Jupyter integration, TIL pyqtgraph has jupyter_rfb, Remote Frame Buffer: https://github.com/vispy/jupyter_rfb
pyqtgraph:
https://github.com/pyqtgraph/pyqtgraph
Matplotlib can generate GIF and WEBM (and .mp4) animations, but not realtime.
ManimCE might work in notebooks, but IDK about realtime
Genesis is fast enough by FPS for faster than realtime 3D with Python (LuisaRender) and a GPU:
https://github.
Read the rest
FWICS pyqtwebgraph has a TableWidget:
https://pyqtgraph.readthedocs.io/en/latest/api_reference/wid... https://github.com/pyqtgraph/pyqtgraph/blob/master/pyqtgraph... :
> Extends QTableWidget with some useful functions for automatic data handling and copy / export context menu. Can automatically format and display a variety of data types (see setData() for more information
DataTreeWidget handles nested structs: https://pyqtgraph.readthedocs.io/en/latest/api_reference/wid...
SO says it's better to extend Qt QTableView and do pagination for larger datasets: https://stackoverflow.com/questions/61517220/pyqt-pandas-fas... https://www.pythonguis.com/tutorials/qtableview-modelviews-n...
pyqtgraph mentions CUDA and NumPy support, but not pandas. Hard to believe there's not yet specific support for drawing spreadsheets of pandas dataframes in qt
Read the rest
or pyqtgraph yet.
dask.DataFrame and dask-CuDF also support CUDA. sympy's lambdify function compiles readable symbolic algebra to fast code for various libraries and GPUs.
The Dataframe Protocol __dataframe__ interface spec Purpose and Scope doc mentions the NumPy __array_interface__ protocol; which may do sufficient auto-casting to a NumPy array before trying to draw a data table with formatting derived from then-removed columnar metadata:
https://data-apis.org/dataframe-protocol/latest/purpose_and_...
Practically, pd.DataFrame(,dtype_backend="arrow") may be a quick performance boost.
Jupyter kernels with Papermill or cron and templated parameters at the top of a notebook with a dated filename in a (repo2docker compatible) git repo also solve for interactive reports. To provision a temporary container for a user editing report notebooks, there's Voila on binderhub / jupyterhub, https://github.com/binder-examples/voila
or repo2jupyterlite in WASM with MathTex and Pyodide's NumPy/pandas/sympy: https://github.com/jupyterlite/repo2jupyterlite
But that's not a GUI, that's notebooks. For Jupyter integration, TIL pyqtgraph has jupyter_rfb, Remote Frame Buffer: https://github.com/vispy/jupyter_rfb