st-airtable-connection 0.0.4

Streamlit Connection for Airtable.

Airtable ⚡ Streamlit Connection

This repo includes a st.connection for Airtable which wraps the popular community created and maintained pyAirtable library.

The initial focus of this connector is on read-only operations: specifically listing records and retrieving the schema of an Airtable base. Write-back support may be added in the future.

👀 Live demo w/ AI ✨

A live demo of the code example in examples/explore.py can be accessed on Streamlit Cloud at http://marks-airtable-connection-demo.streamlit.app [demo video]. Provide your Open AI API key to be able to ask questions about the data in the selected Airtable table. The underlying data can be viewed and cloned here.

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Minimal example: retrieve all records from base's first table

See examples/ for additional examples

.streamlit/secrets.toml

[connections.your_connection_name]
personal_access_token = "patXXX" # REQUIRED
base_id = "appXXX" # optional
table_id = "tblXXX" # optional

ℹ️ The Airtable personal access token you use should have both data.records:read and schema.bases:read scopes to use all functionality of this connector.

minimal_example.py

import streamlit as st
from streamlit_airtable import AirtableConnection

# Create connection
conn = st.connection("your_connection_name", type=AirtableConnection)

# Retrieve base schema
base_schema = conn.get_base_schema()
with st.expander("Base schema"):
    st.json(base_schema)

# Get the first table's ID
first_table = base_schema["tables"][0]
st.markdown(f"First table ID: `{first_table['id']}` (named `{first_table['name']}`)")

# Retrieve all records for the first table (pyAirtable paginates automatically)
# (Note you can also pass in parameters supported by pyAirtable
# (https://pyairtable.readthedocs.io/en/stable/api.html#parameters) such as as
# max_records, view, sort, and formula into conn.query() like so:
# table_records = conn.query(first_table["id"], max_records=25, view='viwXXX')
table_records = conn.query(table_id=first_table["id"])
st.markdown(f"{len(table_records)} records retrieved")
st.dataframe(table_records)

Steps to replicate the minimal example

1. Clone/download this repo
2. Install the connector (pip install -e .)
3. Move into the examples/ dir (cd examples/)
4. Copy .streamlit/secrets.toml.example to .streamlit/secrets.toml and provide your own values
5. Run streamlit run minimal_example.py

Acknowledgements & thank yous

• Streamlit connection examples: Google Sheets & DuckDB
• pyAirtable