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Streamlit, a popular app framework for computer science and machine learning, has reached its milestone in version 1.0. The open source project is curated by a company of the same name that offers a commercial service built on the platform. To date, the project has had more than 4.5 million GitHub downloads and is used by more than 10,000 organizations.
The framework fills an important gap between computer scientists who want to develop a new analysis widget or app and computer technology that is typically required to implement these on a large scale. Data researchers can build web apps to access and explore machine learning models, advanced algorithms and complex data types without having to master back-end computer engineering tasks.
Streamlit co-founder and CEO Adrien Treuille told VentureBeat that “the combination of the sleek simplicity of the Streamlit library and the fact that it’s all in Python means developers can do things in hours that normally took weeks.”
The crowded landscape with data science apps
The tools are used by everyone from computer science students to large companies. The company is experiencing the fastest growth in tech-focused companies with a large number of Python users and a need to quickly experiment with new apps and analytics.
“All companies have the same problems with lots of data, lots of questions and too little time to answer them all,” Treuille said.
Improvements in v1.0 include faster app speed and responsiveness, improved customization, and statefulness support. The company plans to improve its widget library, enhance the developer experience and make it easier for data researchers to share code, components, apps and answers next year in 2022.
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