Connections

Attention

Hashquery is currently in public preview. Here are some caveats to keep in mind for early adopters:

  • Backwards compatibility may not be preserved between version upgrades, and you may need to update your package regularly.

  • There may be differences in the SQL logic generated by hashquery compared to the Hashboard app.

  • You may encounter dialect-specific SQL syntax errors or other unexpected errors. If you come across one, let us know by reporting an issue.

class Connection
classmethod duckdb(**contents: LocalDataFrameRef) → DuckDBConnection

Initialize a new DuckDB connection with the provided contents. Takes in a mapping of names to content data frames, which will each be loaded into a DuckDB instance as table with that name.

Content can be specified as a path to a .csv, .json, or .parquet file, a pandas DataFrame, or a list of Python records.

classmethod bigquery(
*,
credentials_path: str | None = None,
credentials_info: dict | None = None,
) → BigQueryConnection

Initialize a new BigQuery connection.

By default, the connection will be authenticated using the environment variable GOOGLE_APPLICATION_CREDENTIALS, according to the same logic as the BigQuery client library. https://cloud.google.com/docs/authentication/application-default-credentials

Alternatively, you can specify an explicit path to a service account JSON file using credentials_path, or use a python dictionary using credentials_info. https://github.com/googleapis/python-bigquery-sqlalchemy?tab=readme-ov-file#authentication

classmethod postgres(
*,
host: str,
port: str = '5432',
user: str,
password: str,
database: str,
default_schema: str | None = None,
) → PostgresConnection

Initialize a new Postgres connection.

The default port is 5432.

classmethod snowflake(
*,
account: str,
user: str,
database: str,
default_schema: str | None = None,
warehouse: str,
role: str,
password: str | None = None,
private_key: str | None = None,
encryption_passphrase: str | None = None,
) → SnowflakeConnection

Initialize a new Snowflake connection.

Credentials may be specified via password or key-pair authentication. If key-pair authentication is used, private_key must be specified and encryption_passphrase may optionally be provided. https://docs.snowflake.com/en/user-guide/key-pair-auth

run_reflection(
*,
include_views: bool = True,
include_columns: bool = True,
include_column_descriptions: bool = False,
) → List[ReflectionGroup]

Run reflection on this connection, gathering up information about all the available tables and views.

This can be a slow operation, particularly for databases with lots of wide tables. You can omit columns from the reflection with include_columns=False. You can omit views from the reflection with include_views=False. You can omit column descriptions from the reflection with include_column_descriptions=False.

To run a reflection on a single table or view, use run_table_reflection.

run_table_reflection(
table_name: str,
*,
schema: str | None = None,
) → List[ReflectionColumn]

Run reflection on the provided table or view, gathering up information about its columns.

Connections store secrets in a special wrapped Secret value and are never serialized or sent across network boundaries.