VisPy
diagrams
VisPy | diagrams | |
---|---|---|
4 | 110 | |
3,230 | 35,065 | |
0.9% | - | |
8.6 | 6.2 | |
3 days ago | about 1 month ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
VisPy
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Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
VisPy - High-performance scientific visualization based on OpenGL.
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Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/vispy/vispy
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Seeking library recommendation for 3D visualization of crystal structure
Two similar alternatives you could look at are PyVista which is based on the same framework as Mayavi and VisPy. Mayavi is strongly dependent on the whole Enthought suite which can be a disadvantage if you don’t really use its abilities.
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Show HN: MPL Plotter – Python library to make technical plots more efficiently
2. I recommend Datashader (https://datashader.org/) (HoloViz is super cool) and Vispy (https://vispy.org/). I found Vispy's documentation a bit lacking some time ago, but they probably have improved it since then, and it's very capable. Lastly, check Taichi (https://taichi.graphics/), might not be a conventional data representation library (or rather, not only), but it's amazing and worth a look.
To add some more depth to the Seaborn comparison, and not being an expert Seaborn user, I'd say:
1. MPL Plotter is lighter (but also with less wide-ranging plot options)
diagrams
- Diagrams as Code
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Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
diagrams - Diagram as Code.
- How to draw beautiful software architecture diagrams
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Top 9 Architecture diagram software for cloud infrastructure
Mingrammer is an intriguing tool for individuals who prefer coding diagrams rather than creating them through graphical interfaces. It operates using Python code and offers a relatively quick setup process. It is compatible with AWS, Azure, GCP, Alibaba, and Oracle. Notably, the project is open source and has garnered significant attention on GitHub with over 31K stars.
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Pravljenje AWS strukturnog diagrama
Ja sam koristio ovo: https://diagrams.mingrammer.com/
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Dynamically generate Cloud System Architecture diagram
That’s another option: https://diagrams.mingrammer.com Guessing with IaC done with Pulumi (Python) and this, it could pretty powerful and automatically generated.
- [Golang] Diagrammes comme code avec Go?
- Network diagram Tool
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Top 7 diagrams as code tools for software architecture
Diagrams allow you to draw cloud system architectures using Python code.
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Do you like to draw while explaining stuff?
I use excalidraw a lot for short conversations. If I have to go into major detail I use diagrams https://diagrams.mingrammer.com
What are some alternatives?
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
c4-draw.io - Draw.io template/diagram containing C4 Model shapes. Drawio Diagrams.net
matplotlib - matplotlib: plotting with Python
Graphviz - Simple Python interface for Graphviz
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
obsidian-excalidraw-plugin - A plugin to edit and view Excalidraw drawings in Obsidian
pyrender - Easy-to-use glTF 2.0-compliant OpenGL renderer for visualization of 3D scenes.
pygraphviz - Python interface to Graphviz graph drawing package
bokeh - Interactive Data Visualization in the browser, from Python
excalidraw - Virtual whiteboard for sketching hand-drawn like diagrams
Flask JSONDash - :snake: :bar_chart: :chart_with_upwards_trend: Build complex dashboards without any front-end code. Use your own endpoints. JSON config only. Ready to go.
vscode-drawio - This unofficial extension integrates Draw.io (also known as diagrams.net) into VS Code.