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Streamlit-AgGrid is amazing. But there are 2 scenarios where its use is not recommended.
Hello there! I assume you are reading this blog post because you are aware of Streamlit and AgGrid. If, by chance, you are not familiar with either or want to dive into the technical details of AgGrid, I wrote a detailed blog post on how to create well-styled dataframes using the Streamlit-AgGrid component created by Pablo Fonseca.
In my opinion, st_aggrid is one of the best “extra” components in Streamlit. In fact, as of writing, it is the top recommended component in the dataframe section in the official Streamlit documentation. Because I have been extensively using AgGrid, I wanted to share with you 2 scenarios where AgGrid is not recommended. I will cover in detail:
- What happens if we are working with Polars?
- What happens if we are dealing with big datasets in our Streamlit app?
Disclaimer 1: I have no affiliation or partnership with AgGrid. I just find a lot of value in the open-source product. AgGrid does have a paid tiered product, but the blog post will only use the free components of AgGrid.
Disclaimer 2: All images and GIFs are authored by myself unless specified otherwise.
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