Streamlit-AgGrid is wonderful. However there are 2 eventualities the place its use shouldn’t be really helpful.
Whats up there! I assume you’re studying this weblog publish since you are conscious of Streamlit and AgGrid. If, by probability, you aren’t accustomed to both or need to dive into the technical particulars of AgGrid, I wrote an in depth weblog publish on learn how to create well-styled dataframes utilizing the Streamlit-AgGrid part created by Pablo Fonseca.
For my part, st_aggrid is without doubt one of the greatest “additional” elements in Streamlit. In reality, as of writing, it’s the high really helpful part within the dataframe part within the official Streamlit documentation. As a result of I’ve been extensively utilizing AgGrid, I needed to share with you 2 eventualities the place AgGrid shouldn’t be really helpful. I’ll cowl intimately:
- What occurs if we’re working with Polars?
- What occurs if we’re coping with large datasets in our Streamlit app?
Disclaimer 1: I’ve no affiliation or partnership with AgGrid. I simply discover lots of worth within the open-source product. AgGrid does have a paid tiered product, however the weblog publish will solely use the free elements of AgGrid.
Disclaimer 2: All pictures and GIFs are authored on my own until specified in any other case.