BigQuery resource

BigQueryResource ¶

BigQueryResource(
    paths,
    dataframes=None,
    bq_client=None,
    capture_schema_only=False,
    columns_description=None,
)

Bases: Resource

BigQuery resource reference wrapper.

This resource wraps BigQuery paths that you have stored in BigQuery with optional metadata and versioning. You pass it as an argument of your Vectice Dataset wrapper before logging it to an iteration.

from vectice import BigQueryResource

bq_resource = BigQueryResource(
    paths="bigquery-public-data.stackoverflow.posts_questions",
)

Vectice does not store your actual dataset. Instead, it stores your dataset's metadata, which is information about your dataset. These details are captured by resources tailored to the specific environment in use, such as: local (FileResource), Bigquery, S3, GCS...

Parameters:

Name	Type	Description	Default
`paths`	`str \| list[str]`	The paths to retrieve the datasets or the tables.	required
`dataframes`	`Optional`	The dataframes allowing vectice to optionally compute more metadata about this resource such as columns stats. (Support Pandas, Spark)	`None`
`bq_client`	`Optional`	The `google.cloud.bigquery.Client` to optionally retrieve file size, creation date and updated date (used for auto-versioning).	`None`
`capture_schema_only`	`Optional`	A boolean parameter indicating whether to capture only the schema or both the schema and column statistics of the dataframes.	`False`
`columns_description`	`Optional`	A dictionary or path to a csv file to map the column's name to a specific description. Dictionary should follow the format { "column_name": "Description", ... }	`None`