Write arguments to the app.
This is the Swiss Army knife of Streamlit commands: it does different things depending on what you throw at it. Unlike other Streamlit commands, write() has some unique properties:
- You can pass in multiple arguments, all of which will be written.
- Its behavior depends on the input types as follows.
- It returns None, so its "slot" in the App cannot be reused.
Function signature | |
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st.write(*args, **kwargs) | |
Parameters | |
*args (any) | One or many objects to print to the App. Arguments are handled as follows:
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unsafe_allow_html (bool) | This is a keyword-only argument that defaults to False. By default, any HTML tags found in strings will be escaped and therefore treated as pure text. This behavior may be turned off by setting this argument to True. That said, we strongly advise against it. It is hard to write secure HTML, so by using this argument you may be compromising your users' security. For more information, see: https://github.com/streamlit/streamlit/issues/152 Also note that `unsafe_allow_html` is a temporary measure and may be removed from Streamlit at any time. If you decide to turn on HTML anyway, we ask you to please tell us your exact use case here: https://discuss.streamlit.io/t/96 . This will help us come up with safe APIs that allow you to do what you want. |
Example
Its basic use case is to draw Markdown-formatted text, whenever the input is a string:
write('Hello, *World!* :sunglasses:')(view standalone Streamlit app)As mentioned earlier, st.write() also accepts other data formats, such as numbers, data frames, styled data frames, and assorted objects:
st.write(1234) st.write(pd.DataFrame({ 'first column': [1, 2, 3, 4], 'second column': [10, 20, 30, 40], }))(view standalone Streamlit app)Finally, you can pass in multiple arguments to do things like:
st.write('1 + 1 = ', 2) st.write('Below is a DataFrame:', data_frame, 'Above is a dataframe.')(view standalone Streamlit app)Oh, one more thing: st.write accepts chart objects too! For example:
import pandas as pd import numpy as np import altair as alt df = pd.DataFrame( np.random.randn(200, 3), columns=['a', 'b', 'c']) c = alt.Chart(df).mark_circle().encode( x='a', y='b', size='c', color='c', tooltip=['a', 'b', 'c']) st.write(c)(view standalone Streamlit app)