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Streamlit

Streamlit

Software Development

San Francisco, CA 107,069 followers

A faster way to build and share data apps

About us

Streamlit is an open-source Python framework for data scientists and AI/ML engineers to deliver dynamic data apps in only a few lines of code

Website
http://streamlit.io
Industry
Software Development
Company size
11-50 employees
Headquarters
San Francisco, CA
Type
Privately Held
Founded
2018

Locations

Employees at Streamlit

Updates

  • 🚀 See what's new in the 1.64 release! Highlights: 📊 Introducing st.echarts_chart, a new command that renders Apache ECharts options with Streamlit theming, accepting dicts, JSON strings, or pyecharts charts. ⏳ Streamlit now supports async/await in app code, making it easy to use async libraries like httpx, aiohttp, and asyncpg directly. 📝 Announcing live updates for st.text_input: set live=True and the widget commits while the user types, after a short pause. ...And from 1.63: event-scoped fragment reruns, on_change="ignore" mode for widgets, new type="step" for st.expander & st.status, + more! 📄 Full release notes: https://lnkd.in/gjxTnMKh 🎈 Explore the 1.63 + 1.64 demo app: https://lnkd.in/gXD_f2MY

  • Streamlit reposted this

    Ever tried adding a molecule editor to a Streamlit app? 🧪 The popular JSME molecule editor was written in JavaScript and doesn't just drop into a Python app. So I built streamlit-jsme. 🚀 This is a personal first for me. Sure, I've used Streamlit components countless times before, but this was the first one I've ever built. Using coding agent and the Streamlit v2 component API made it far more approachable than I expected. 🙌 It wraps JSME as a Streamlit v2 component that runs directly in the page. You draw the structure or paste a SMILES notation (a text string that depicts the chemical structure), hit Apply, and get the result back in Python as SMILES, stereo-stripped SMILES, or a MOL file. 🔬 From there, the molecule is ready for whatever's next: use with the RDKit library, property prediction, similarity search, or compute features for an ML model. 🤖 📦 Setup is only a pip install away: pip install streamlit-jsme 👇 Using it is only a few lines of code: from streamlit_jsme import st_jsme smiles = st_jsme("CC(=O)Oc1ccccc1C(=O)O") st.write(f"SMILES: {smiles}") If it's useful to you, a GitHub star goes a long way. ⭐ 🐙 GitHub https://lnkd.in/g2KfyD44 P.S. I’ve also used AI to help create this video, would love to hear your thoughts on what you think! It definitely opens up new avenues for content creation. #Streamlit #Cheminformatics #Bioinformatics #Python #DrugDiscovery #OpenSource

  • View organization page for Streamlit

    107,069 followers

    🎈 The latest 1.62 release is here! Highlights: 🔍 Introducing client-side validation (validate) and specialized email, URL, phone, and search types (type) for st.text_input, with smart defaults for validation, autofill, mobile keyboards, icons, and placeholders. 🎁 Introducing a new wrap parameter, letting you choose whether horizontal layouts, widgets, and labels wrap or remain on one scrollable or truncated row. ⌨️ Announcing a public streamlit.typing namespace for stable imports of Streamlit-owned types including fully typed selection and data editor state values. 📖 Read the full release notes: https://lnkd.in/gjxTnMKh 👀 Explore more in the 1.61 + 1.62 demo app: https://lnkd.in/gXXXMAWu

  • View organization page for Streamlit

    107,069 followers

    🎈 Check out the 1.61 release! Highlights: 📊 Introducing lazy loading for st.dataframe: large dataframes now load rows on demand automatically so the browser stays responsive. A new lazy parameter lets you turn this on or off explicitly, and Polars LazyFrame objects are supported natively. 🔄 st.cache_data and st.cache_resource have a new refresh_mode="background" option that refreshes expired cache values in the background so your app serves the previous value without waiting. 🔢 st.metric has new icon parameter letting you display an icon next to the metric label. ⏰ st.time_input got a major revamp with editable time segments, a new format parameter (12h/24h/localized), seconds granularity, paste support, and improved form behavior with Enter-to-submit. Explore more in the full release notes: https://lnkd.in/gaTuSu2d

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  • View organization page for Streamlit

    107,069 followers

    Hear a little about the Streamlit Creators program from O.G. Creator Fanilo Andrianasolo! 🤩 🎈 Learn more here: https://lnkd.in/gSUFMxjv Official application window opens this Fall.

    🌸 My hidden career hack level up --- I joined the Streamlit Creators/Ambassadors program a few years ago and got a lot of career benefits from it: - Goodies! I had people come to me during conferences just because I was wearing a Streamlit shirt - Network: I joined a group of other Streamlit DataFans on a private Slack channel, ending up sharing a lot of different perspectives. Oh, and maybe we did share hidden job opportunities 👀 - Speaking: most company ambassador program provide resources to get you to speak at conferences/meetups. They may share their hidden roadmap updates, coaching on speaking and call for papers, a budget for travel/accomodation. You get the speaking event on your resume, they get bigger reach, it's a win-win If you can, definitely join one! Like Streamlit's: https://lnkd.in/dNB8CSuE

  • View organization page for Streamlit

    107,069 followers

    🤩 Brand new custom component built by Carlos D. Serrano! Check it out. 👇

    New Streamlit custom component Streamlit Avatar Stack. Build a customizable Avatar Stack in your UI. Version 0.1.0 features: • Supports Names, Material icons, Image URLs and Local images • Selectable • Optional labels and tooltips • Overlapping or side-by-side layouts • Automatic wrapping and expandable groups • Left or right alignment • Query-parameter binding --------------------------------- pip install streamlit-avatar-stack Link in the first comment.

  • Streamlit reposted this

    🌸 Streamlit 1.59 release from a month ago. Better late than never! --- - Dataframe ButtonColumn lets you drop Streamlit buttons into dataframe cells, wired up to on_click callbacks - Every dataframe column now has a stats menu built in: click it to get a histogram plus the key numbers like mean or 75% percentile - st.skeleton() gives you an animated loading placeholder, to use similarly to st.empty() - Mermaid diagrams now render inside the app wherever Markdown is supported --- IMO We're seeing more and more dataframe related changes. I wonder if Streamlit is planning to make their Dataframe one of the best Python interactive web spreadsheets editable by coding agents 👀

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