Voilà VS Plotly

Voilà Reviews

Plotly Reviews

Voilà mentions (11)

• Evidence – Business Intelligence as Code

  > Works with CI/CD out of the box. Deploy to vercel, netlify, your own infra. Jupyter is suited for whatever you want to do with it. Voila exists to enable the use case of re-generating notebooks on a CI/CD system: https://github.com/voila-dashboards/voila Anyways, seems like the templating is more powerful than the one being offered by Jupyter Notebooks.... - Source: Hacker News / about 1 year ago

• Warning, Streamlit collects a lot of data!

  I don't understand why everyone isn't just using voila. it's so much better than streamlit or gradio. But that's just my opinion I guess. Source: about 1 year ago

• Mercury – Turn Python Notebooks to Web Apps

  Ill have to check it out and see how it compares to voilà and holoviz panel. What I like about Holoviz panel is you can create a data web app from code that resides in a notebook or create a completely standalone app from just plain py scripts, and it supports many different visualization backends. I have found it to be the more flexible and generalizable data web app framework among the others I have come... Source: about 1 year ago

• Turn Jupyter Notebook to Web App with open-source Mercury framework and Python only

  Any insights what the differences between this and Voila are? Https://github.com/voila-dashboards/voila. Source: about 1 year ago

• New library to develop streamlit apps in jupyter

  A nifty little alternative to voila, one might say. - Source: dev.to / over 1 year ago

Plotly mentions (29)

• Python equivalent to power bi/power query?

  For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: 5 months ago

• Junior Developer asked to make Saaas in first month.

  If your CEO wants you to solo build an alternative to Tableau, PowerBi, or even Plotly then consider him/her delusional. Source: 12 months ago

• PSA: You don't need fancy stuff to do good work.

  Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: 12 months ago

• Wait, but I thought they were the same thing?

  I use plotly and like it a lot. It is slower though. Noticeable if you want to batch-generate a bunch of images and dump them into a folder. But that probably isn't the case most times. Source: about 1 year ago

• Storing your data in a Plotly Dash data dashboard

  Plotly Dash is a great framework for developing interactive data dashboards using Python, R, and Javascript. It works alongside Plotly to bring your beautiful visualizations to the masses. - Source: dev.to / over 1 year ago