Bruin CLI

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Available Checks ​

Bruin provides the following checks to validate assets, ensuring that asset data meets specified quality standards.

You can find a detailed description of each check below.

Accepted values ​

This check will verify that the value of the column will be one of the accepted values

yaml
columns:
  - name: one
    type: integer
    description: "Just a number"
    checks:
      - name: accepted_values
        value: [1, 3, 5, 7, 9]

Negative ​

This check will verify that the values of the column are all negative

yaml
columns:
  - name: one
    type: integer
    description: "Just a number"
    checks:
      - name: negative

Non-Negative ​

This check will verify that the values of the column are all non negative (positive or zero)

yaml
columns:
  - name: one
    type: integer
    description: "Just a number"
    checks:
      - name: non_negative

Not-Null ​

This check will verify that none of the values of the checked column are null.

yaml
columns:
  - name: one
    type: integer
    description: "Just a number"
    checks:
      - name: not_null

Pattern ​

The pattern quality check ensures that the values of the column match a specified regular expression.

WARNING

For most platforms, POSIX regular expressions are the ones meant to be used with this check, but some platforms that don't support it (Synapse, MsSQL) might have other pattern languages (see Pattern matching in SQL Server)

yaml
columns:
  - name: name
    type: string
    description: "Just a name"
    checks:
        - name: pattern
          value: "^[A-Z][a-z]*$"

Positive ​

This check will verify that the values of the column are all positive, i.e. greater than zero.

yaml
columns:
  - name: one
    type: integer
    description: "Just a number"
    checks:
      - name: positive

Relationships ​

This check verifies referential integrity: every non-null value in the checked column must exist in the column identified by its foreign_key metadata. Null values are ignored; add a separate not_null check when nulls should fail.

yaml
columns:
  - name: customer_id
    type: integer
    foreign_key:
      table: analytics.customers
      column: id
    checks:
      - name: relationships

The referenced table must be another asset in the pipeline. The check runs on the child asset's connection and returns the number of child rows whose keys are missing from the parent. It does not verify that the referenced parent column is unique; add a unique check to that column separately when required.

Neither foreign_key metadata nor a relationships check creates a scheduler dependency. Add the referenced asset to the child asset's depends list when it must be refreshed before the relationship check runs.

Unique ​

This check will verify that no value in the specified column appears more than once

yaml
columns:
  - name: one
    type: integer
    description: "Just a number"
    checks:
      - name: unique

Min ​

This check ensures that all values in the column are greater than or equal to the specified minimum threshold.

yaml
columns:
  - name: amount
    type: float
    checks:
      - name: min
        value: 0.0

You can also use integers or strings where appropriate (e.g., dates):

yaml
checks:
  - name: min
    value: 10
  - name: min
    value: "2024-01-01"

Max ​

This check ensures that all values in the column are less than or equal to the specified maximum threshold.

yaml
columns:
  - name: amount
    type: float
    checks:
      - name: max
        value: 100.0

You can also use integers or strings where appropriate (e.g., dates):

yaml
checks:
  - name: max
    value: 100
  - name: max
    value: "2024-12-31"