BigQuery

Seed BigQuery tables and check the rows your services write.

The steps use the scenario’s project (the {word} gcp project with the following properties:, from gcp-core). Tables are named dataset.table (in the project) or project.dataset.table.

A seed is a YAML or JSON file that maps tables to the rows to insert (a streaming insert, tabledata.insertAll):

billing.carrier_rates:
  - carrier: KESTREL
    service: express
    price_per_kg: 1.35

Checks wait (10 seconds unless within {duration} says otherwise) until the table has a row, or a number of rows, meeting every condition: column | value rows, with a dotted path into RECORD columns (address.city), compared as text: numbers as written, NUMERIC as its decimal, TIMESTAMP in RFC 3339 (2026-09-24T09:30:00Z), DATE as 2026-09-24; null for NULL. A check reads the columns its conditions name, of up to 5,000 rows of the table: check the tables your scenarios write, not warehouse-size ones.

Add it to a project with axx pack add gcp-bigquery; it builds on gcp-core, which comes with it.

Steps

gcp-bigquery.seed

Given a {filepath} bigquery seed

Insert the rows of a seed file into their tables: YAML or JSON that maps tables (dataset.table or project.dataset.table) to lists of rows. The rows are streamed in (tabledata.insertAll).

Parameter	Takes	For example
{filepath}	a file of the project: a path relative to the feature file’s directory, the resources directories or axx.yaml’s directory (looked for in that order), or an absolute path, quoted when it has a space	seeds/parcels.yaml, kafka/scan-delivered.json

Example:

Given a seeds/carrier-rates.yaml bigquery seed

Since 0.1.0.

gcp-bigquery.row

Then [[within {duration} ]]the {word} bigquery table has a row where:
  | column | value |

The table may start with the row naming its columns, as above, or go straight to its rows.

Check that the table has a row with those values in those columns.

• The check waits for it: 10 seconds, or within {duration}.
• Name the table dataset.table, or project.dataset.table for another project’s.
• Values compare as text: numbers as written, NUMERIC as its decimal, TIMESTAMP in RFC 3339 (2026-09-24T09:30:00Z), DATE as 2026-09-24, DATETIME as 2026-09-24T09:30:00, BYTES in base64; null for NULL.
• The check reads only the columns the step names, of up to 5,000 rows.

Parameter	Takes	For example
{duration}	a duration in seconds (s) or minutes (m)	5s, 2m
{word}	one word, with no spaces	parcels, PX-4101

Each row names a column, or a dotted path into a RECORD column (address.city), and the value in it.

Variants, the parts in [[...]] said or left out:

• the {word} bigquery table has a row where:
• within {duration} the {word} bigquery table has a row where:

Example:

Then within 30s the billing.invoice_lines bigquery table has a row where:
  | invoice  | INV-2026-09-KES2 |
  | parcel   | PX-5103          |
  | status   | OVERCHARGED      |
  | billed   | 2.5              |
  | expected | 1.35             |

Since 0.1.0.

gcp-bigquery.rows

Then [[within {duration} ]]the {word} bigquery table has {int} row(s) where:
  | column | value |

The table may start with the row naming its columns, as above, or go straight to its rows.

Check that exactly that many rows of the table have those values in those columns.

• The check waits for it: 10 seconds, or within {duration}.
• Name the table dataset.table, or project.dataset.table for another project’s.
• Values compare as text: numbers as written, NUMERIC as its decimal, TIMESTAMP in RFC 3339 (2026-09-24T09:30:00Z), DATE as 2026-09-24, DATETIME as 2026-09-24T09:30:00, BYTES in base64; null for NULL.
• The check reads only the columns the step names, of up to 5,000 rows.

Parameter	Takes	For example
{duration}	a duration in seconds (s) or minutes (m)	5s, 2m
{word}	one word, with no spaces	parcels, PX-4101
{int}	a whole number	200, 3

Each row names a column, or a dotted path into a RECORD column (address.city), and the value in it.

Variants, the parts in [[...]] said or left out:

• the {word} bigquery table has {int} row(s) where:
• within {duration} the {word} bigquery table has {int} row(s) where:

Example:

Then the billing.invoice_lines bigquery table has 2 rows where:
  | invoice | INV-2026-09-KES1 |
  | status  | MATCHED          |

Since 0.1.0.