Contents

streamlit 1.33.0

0

A faster way to build and share data apps

A faster way to build and share data apps

Stars: 31252, Watchers: 31252, Forks: 2760, Open Issues: 796

The streamlit/streamlit repo was created 4 years ago and the last code push was 2 hours ago.
The project is extremely popular with a mindblowing 31252 github stars!

How to Install streamlit

You can install streamlit using pip

pip install streamlit

or add it to a project with poetry

poetry add streamlit

Package Details

Author
Snowflake Inc
License
Apache License 2.0
Homepage
https://streamlit.io
PyPi:
https://pypi.org/project/streamlit/
Documentation:
https://docs.streamlit.io/
GitHub Repo:
https://github.com/streamlit/streamlit

Classifiers

  • Database/Front-Ends
  • Office/Business/Financial/Spreadsheet
  • Scientific/Engineering/Information Analysis
  • Scientific/Engineering/Visualization
  • Software Development/Libraries/Application Frameworks
  • Software Development/Widget Sets
No  streamlit  pypi packages just yet.

Errors

A list of common streamlit errors.

Code Examples

Here are some streamlit code examples and snippets.

GitHub Issues

The streamlit package has 796 open issues on GitHub

  • inconsistent type returned by number_input
  • inconsistent behaviour with key of st.number_input in combination with disabled
  • Feature/st user
  • Use primaryColor for st.spinner
  • Provide way to run with the WSGI/ASGI protocols
  • ISBNLibHTTPError
  • [Pure design change] Make checkbox/radio only show focus when tabbing, not when clicked.
  • Bump nanoid from 3.1.20 to 3.2.0 in /frontend
  • Overflow LaTeX formulas
  • Remove focus lock on stateful popover
  • User's session_state is reset on websocket close
  • st.radio with DataFrame fails on rerun
  • Height option for st.container and st.expander
  • [WIP] Better exception formatting with rich
  • Remove some remaining usage of the term "report"

See more issues on GitHub

Related Packages & Articles

spacy 3.7.4

Industrial-strength Natural Language Processing (NLP) in Python

keras 3.2.0

Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow. The core data structures of Keras are layers and models. The philosophy is to keep simple things simple, while allowing the user to be fully in control when they need to (the ultimate control being the easy extensibility of the source code via subclassing).

pandas 2.2.1

Powerful data structures for data analysis, time series, and statistics

nlp 0.4.0

HuggingFace/NLP is an open library of NLP datasets.

gensim 4.3.2

Python framework for fast Vector Space Modelling