niceback
Tracebacks for Humans (in Jupyter notebooks) (by Tronic)
dash
Data Apps & Dashboards for Python. No JavaScript Required. (by plotly)
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The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
niceback
Posts with mentions or reviews of niceback.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-11-15.
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What features an ideal IDE for Python notebooks should have?
I solved this problem two years ago and tried to notify everyone. Looks like I am still the only person in the world using this: https://github.com/Tronic/niceback
dash
Posts with mentions or reviews of dash.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-13.
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Launch HN: Pynecone (YC W23) – Web Apps in Pure Python
Useful list. Dash & bokeh as two more in the space
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Python projects with best practices on Github?
I also heard of Dash which serves the same purpose I guess, but I think it has more to offer.
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4 Streamlit Alternatives for Building Python Data Apps
Plotly is a plotting library, and Dash is their open-source framework for building data apps with Python, R or Julia. (Dash also has an Enterprise version, but we'll focus on the open-source library here.)
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NiceGUI: Let any browser be the frontend for your Python code
Of course there are valid use cases for splitting frontend and backend technologies. NiceGUI is for those who don’t want to leave the Python ecosystem and like to reap the benefits of having all code in one place. There are other options like Streamlit, Dash, Anvil, JustPy, and Pynecone. But we initially created NiceGUI to easily handle the state of external hardware like LEDs, motors, and cameras. Additionally, we wanted to offer a gentle learning curve while still providing the ability to go all the way down to HTML, CSS, and JavaScript if needed.
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Containerizing Shiny for Python and Shinylive Applications
Shiny is a framework that makes it easy to build interactive web applications. Shiny was introduced 10 years ago as an R package. In his 10th anniversary keynote speech, Joe Cheng announced Shiny for Python at the 2022 RStudio Conference. Python programmers can now try out Shiny to create interactive data-driven web applications. Shiny comes as an alternative to other frameworks, like Dash, or Streamlit.
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How can I build interactive plots using Matplotlib/Numpy?
Take a look at streamlit and dash. Matplotlib widgets might also be of interest.
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Looking for web app generator from JSON data
Dash
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What are data apps?
There also are data application frameworks that are helpful here: tools like Plotly Dash and Streamlit make it possible to turn data scripts into shareable web applications without the need for front-end development.
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AAD auth for Plotly Dash
One particular interesting case is Dash by Plotly. While I myself have previously used Bokeh, I quickly made the transition to Dash since I felt it was more ready for usage as a deployed application. Additionally, having access to Plotly as a charting library is a big plus because it is such a successful open-source project with a strong community and a fantastic library.
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[Q] What industries use R over Python? Is it better to learn Python rather than R? I will be learning both, but want to know which I should focus on more.
Shiny is pretty great, but python has dash and streamlit, which in my opinion are nicer to use.
What are some alternatives?
When comparing niceback and dash you can also consider the following projects:
streamlit - Streamlit — The fastest way to build data apps in Python
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
panel - A high-level app and dashboarding solution for Python
uvicorn - An ASGI web server, for Python. 🦄
Flask - The Python micro framework for building web applications.
Jinja2 - A very fast and expressive template engine.
PyWebIO - Write interactive web app in script way.
ipywidgets - Interactive Widgets for the Jupyter Notebook
ttkthemes - A group of themes for the ttk extenstions for Tkinter
Chart.js - Simple HTML5 Charts using the <canvas> tag
three.js - JavaScript 3D Library.
Rust-Bio - This library provides implementations of many algorithms and data structures that are useful for bioinformatics. All provided implementations are rigorously tested via continuous integration.