Our great sponsors
tuna | VisPy | |
---|---|---|
4 | 4 | |
1,263 | 3,217 | |
- | 0.8% | |
0.0 | 8.6 | |
about 2 months ago | 12 days ago | |
Python | Python | |
GNU General Public License v3.0 only | GNU General Public License v3.0 or later |
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.
tuna
-
Is AWS Lambda Cold Start Still an Issue?
Every minor detail matters and adds to the total import time as part of the cold start. We need to optimize our code and imports. If you use Python, you can analyze your code with a tool like Tuna and optimize your libraries (perhaps replace slower ones) and your imports.
- Make Python Run Faster
- Scanning Function calls in a script - is there a tool?
-
Creating a Python CLI with Go(lang)-comparable startup times
I started to examine the output of python -X importtime -m gefyra 2> import.log just to check the imports. There is an awesome tool to analyze the Python imports: tuna (see: https://github.com/nschloe/tuna). tuna allows analyzing the import times from the log. Run it like so tuna import.log. It opens a browser window and visualizes the import times. With that I was able to manually move all imports to the functions in which they are needed (and bring in some other optimizations). This greatly violates PEP 8 (https://peps.python.org/pep-0008/#imports) but leads to very fast startup times.
VisPy
-
Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
VisPy - High-performance scientific visualization based on OpenGL.
-
Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/vispy/vispy
-
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.
-
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)
What are some alternatives?
SnakeViz - An in-browser Python profile viewer
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
Altair - Declarative statistical visualization library for Python
matplotlib - matplotlib: plotting with Python
ggplot - ggplot port for python
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
seaborn - Statistical data visualization in Python
pyrender - Easy-to-use glTF 2.0-compliant OpenGL renderer for visualization of 3D scenes.
vincent
bokeh - Interactive Data Visualization in the browser, from Python
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
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.