BigQuery ADBC driver for Python

bigquery-adbc gives Python columnar access to Google BigQuery, through a DB-API 2.0 interface or the low-level ADBC API. Results arrive as Arrow, and bulk ingestion streams Arrow to the BigQuery Storage Write API. The wheels bundle the native Rust driver; a Rust toolchain is needed only when building from source. Requires Python 3.11 or newer.

This project is experimental and AI-generated, and has not seen real-world use. See the known limitations.

Install

python3 -m pip install "bigquery-adbc[dbapi]"

The dbapi extra installs PyArrow; the pandas extra also adds pandas for cursor.fetch_df(). The low-level bigquery_adbc.connect() API needs neither.

To build from source, install Rust, then run this from the repository root. The build uses the repository's pinned Rust toolchain:

python3 -m pip install "./python[dbapi]"

To install a built wheel, replace ./python with its path.

Usage

The driver uses Application Default Credentials (ADC) by default. For local development, set them up with:

gcloud auth application-default login

Replace my-gcp-project with a project where those credentials can run BigQuery jobs:

from bigquery_adbc import dbapi

with dbapi.connect("bigquery:///my-gcp-project", autocommit=True) as connection:
    with connection.cursor() as cursor:
        cursor.execute("SELECT 1")
        print(cursor.fetchone())

cursor.fetch_arrow_table() reads a result as Arrow and cursor.fetch_df() as pandas. See more examples of bulk ingestion and query parameters.

The low-level ADBC API can take its whole configuration as options:

import bigquery_adbc as bigquery

with bigquery.connect(
    db_kwargs={
        bigquery.DatabaseOptions.PROJECT_ID: "my-gcp-project",
    }
) as database:
    print(database.get_option(bigquery.DatabaseOptions.PROJECT_ID))

bigquery.connect() returns an adbc_driver_manager.AdbcDatabase; dbapi.connect() returns a DB-API connection. Both accept a URI, db_kwargs, or both, and explicit options override URI parameters. See connection URIs for dataset, location, quota-project and impersonation settings.

Transactions, batching, and errors

Use autocommit=True for independent queries. With the PEP 249 default, autocommit=False, the first query that needs a transaction opens a BigQuery session. BigQuery rejects permanent-table DDL such as CREATE TABLE inside a transaction, and the driver rejects adbc_ingest. Leaving the with block rolls back uncommitted work; call connection.commit() first to keep it.

executemany executes the query once per parameter row. For bulk inserts, use cursor.adbc_ingest, which streams rows through the Storage Write API. On a reused cursor, an adbc_ingest call that omits catalog_name or db_schema_name keeps the previous call's value; pass "" for the connection's default (UP-95).

Invalid credentials raise ProgrammingError; transient token-exchange failures raise OperationalError. Catch dbapi.DatabaseError to handle both. See error statuses.

Set ADBC_DRIVER_BIGQUERY_LOG_LEVEL=warn before the first connect() to log Storage Read fallbacks and failed cancellations to standard error; debug also logs retries. Jupyter shows these in the kernel console. See diagnostics.

Options

Configure database and connection options when connecting, and statement options on a cursor:

Pass autocommit as a keyword to dbapi.connect(), not in conn_kwargs. New statements inherit their connection's read controls and bulk-ingest method.

Option enums are StrEnums and work directly as keys and values: str(DatabaseOptions.PROJECT_ID) is "bigquery.project_id". The manager's typed getters need .value, for example statement.get_option_float(StatementOptions.PROGRESS.value).

BulkIngestMethod.STORAGE_WRITE is the only supported bulk-ingest method; the raw value "load" returns NOT_IMPLEMENTED. StatementOptions.QUERY_MAXIMUM_BILLING_TIER also returns NOT_IMPLEMENTED; use QUERY_MAXIMUM_BYTES_BILLED to cap query cost.

See the option reference for defaults, constraints, and write-only credential options. Reading uri returns the configured URI with credentials redacted; read individual options to see the effective configuration.

Development

Package builds, local tests and loading a development driver are covered in the Python development guide.