dash
Rust-Bio
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dash | Rust-Bio | |
---|---|---|
56 | 9 | |
20,434 | 1,494 | |
1.3% | 2.3% | |
9.6 | 6.7 | |
7 days ago | 11 days ago | |
Python | Rust | |
MIT License | 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.
dash
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dash VS solara - a user suggested alternative
2 projects | 13 Oct 2023
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[Python] NiceGUI: Lassen Sie jeden Browser das Frontend für Ihren Python-Code sein
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.
- Visualizing parquet in s3 bucket for data analysis?
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Little guidance of a python newbie
You could use something like Streamlit or Dash. In any case you will be accessing your app through the browser.
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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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Sharing interactive Plotly graphs
looks like you can get it manually (albeit with a loss of interactivity) https://github.com/plotly/dash/issues/145
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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.
Rust-Bio
- Bioinformatics Data Structures in Rust
- Bioinformatics with Rust
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bioinformatic libraries and zig?
Does anyone know of zig native libraries for bioinformatics (here is a Rust example https://rust-bio.github.io/ )? It seems as though one could pull in a lot of bioinformatics C libraries such as done with https://github.com/brentp/hts-zig.
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Proteomics search engine written in Rust
e.g. Rust-Bio
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What are your top 3-5 programming languages and why?
I would start with the book and then rust-bio library. Rust is a pretty low level language compared to R/Python. It’s an especially good fit for writing efficient tools that make use of the kinds of algorithms / data structures that are implemented in rust-bio.
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I have to admit. The free code camp course is a bit more sparing than I would have preferred. How did everyone learn Rust?
Absolutely! It already is, e.g., https://github.com/rust-bio/rust-bio. I'm moving from the academia/nonprofit world into industry bioinformatics, and I intend to use Rust as much as possible. I've already replaced as much of my Python as possible with Rust. I feel I'm able to create larger, more complex programs with Rust because I have the compiler to keep me from making common mistakes that are so easy to make in dynamically typed languages like Perl and Python. It might take longer to write a program initially, but I've started to create a library of functions I can paste together to do things like parse a positive integer, find a bunch of files with a certain file extension, search through data for a pattern, parse CSV files, etc. Writing my latest book has provided even more common patterns I keep finding I use over and over.
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Is learning Rust and systems programming through the books Rust in Action and Crafting Interpreters a good idea?
I think there is huge potential for Rust in bioinformatics, and there are already some great projects like https://rust-bio.github.io/. It seems industry is also hiring for these skills. This Nature article is a little old, but also covers why people in the field are looking for greater safety and performance. It's relatively easy to write a Python program to do bio stuff, but it's also very easy to get lots of things wrong or for the resulting program to be slow and/or impossible to extend and maintain. In the long run, I think it makes sense to write in Rust. Perl was king in biofx when I started, and I would not have predicted it being displaced by Python, so there's good reason to believe that Python may one day be eclipsed by Rust.
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Whats your favourite open source Rust project that needs more recognition?
Well, someone mentioned https://rust-bio.github.io/
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How can one make Rust excel in the Sciences
So generally stuff in this maths/numerical space. The term is a bit deceptive because it rarely means domain-specific science libraries like rust-bio even thought that might be what you think when you hear "scientific computing".
What are some alternatives?
streamlit - Streamlit — A faster way to build and share data apps.
kanidm - Kanidm: A simple, secure and fast identity management platform
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
clickhouse-rs - Asynchronous ClickHouse client library for Rust programming language.
panel - Panel: The powerful data exploration & web app framework for Python
GeoRust - Geospatial primitives and algorithms for Rust
uvicorn - An ASGI web server, for Python. 🦄
Rhai - Rhai - An embedded scripting language for Rust.
Flask - The Python micro framework for building web applications.
cycle - Modern and safe symbolic mathematics
nicegui - Create web-based user interfaces with Python. The nice way.
easy_rust - Rust explained using easy English