Bigquery-Streamlit
This project demonstrates running SQL queries on BigQuery public datasets and rendering results into an interactive Streamlit app.
Blog post: https://imadelhanafi.com/posts/bigquery_dashboard/
Live version: https://bigquery.imadelhanafi.com
Running on cloud/local machine
To run the application, build the docker image and run it using the following commands
docker build -t app .
docker run --rm -p 8080:8080 app:latest
The application will be available on http://0.0.0.0:8080.
Note:
In order to use BigQuery API in python, we need to create a credential file (JSON file) and declare its path as an environment variable GOOGLE_APPLICATION_CREDENTIALS (by default defined in modules/data_query.py).
To create the credential file follow steps explained here: https://cloud.google.com/bigquery/docs/quickstarts/quickstart-client-libraries
Code
app.py: Streamlit script to define the UI.
Modules:
-
modules/data_query.py: Define Data fetcher from BigQuery (takes an SQL command and return results in Pandas DataFrame). -
modules/sql_queries.py: Pre-defined parametrized SQL commands. -
modules/utils.py: Contains a function to run queries concurrently (multi-threading) and a function to compute size of data anluzed by a given query. -
modules/plot.py: Plot functions.
By Imad https://imadelhanafi.com