How deeply does Build Python Web Apps with Streamlit cover BigQuery?

Explains project, dataset, table, authentication, API clients, SQL querying, and deployment, without detailing infrastructure internals.

BigQuery

As explained in Build Python Web Apps with Streamlit

BigQuery is a fully managed Google Cloud service for storing and analyzing large datasets with SQL.

BigQuery is a fully managed Google Cloud data warehouse for storing and analyzing massive datasets with SQL. It removes the need to manage infrastructure or plan for scaling, making it a practical replacement for a static CSV when an app needs a larger or more queryable data source. section 7.7.1 section 7.7.3

Use the BigQuery interface to prepare data in a project:

Create or select a Google Cloud project, then open BigQuery. section 7.7.1
Create a dataset, which organizes tables within the project. section 7.7.1
Create a table by uploading a CSV file and selecting CSV as its format. section 7.7.1

A Python application connects through Google Cloud APIs and a service account. Enable the BigQuery and BigQuery Storage APIs, create a service account with Viewer access, generate a JSON key, and store its credentials in Streamlit secrets rather than embedding them in application code. section 7.7.2

Loading a BigQuery table into Pandas

Install google-cloud-bigquery, google-cloud-bigquery-storage, and db-dtypes. Create a BigQuery client from st.secrets, reuse its credentials for the Storage client, reference the table as project.dataset.table, run SELECT * FROM that table, and convert the result to a Pandas dataframe. Keeping this work inside load_data lets the rest of the dashboard remain unchanged. section 7.7.3

For Streamlit Community Cloud deployment, omit the CSV from the repository when BigQuery supplies the data, configure the GCP credentials in the deployment settings, and list required package versions in requirements.txt. section 7.7.4

How Build Python Web Apps with Streamlit covers it

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Related concepts

BigQuery APIused by · The BigQuery API is Google's programmatic interface for accessing and managing BigQuery resources.
PostgreSQLcontrasts with · PostgreSQL is an open-source object-relational database management system that implements SQL and supports transactional data storage and extensibility.
data warehousekind of · A data warehouse is a centralized repository of integrated data organized and optimized for analytical querying, reporting, and analysis.
Google Cloudpart of · Google Cloud is Google's public cloud computing platform, providing infrastructure, platform, and managed services for building and operating applications.
structured extractionused by · Structured extraction is the process of identifying specified information in source content and representing it as organized data in a defined structure.

This explainer was generated by Manning's knowledge graph from the text of Build Python Web Apps with Streamlit. The section links point to the parts of the book it draws on.