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dbt-expectations

dbt-expectations is an extension package for dbt, inspired by the Great Expectations package for Python. The intent is to allow dbt users to deploy GE-like tests in their data warehouse directly from dbt, vs having to add another integration with their data warehouse.

Featured Sponsors ❤️

Development of dbt-expectations (and dbt-date) is funded by our amazing sponsors, including our featured sponsors:

Install

dbt-expectations currently supports dbt 1.0.x.

Check dbt Hub for the latest installation instructions, or read the docs for more information on installing packages.

Include in packages.yml

packages:
  - package: calogica/dbt_expectations
    version: [">=0.5.0", "<0.6.0"]
    # <see https://github.com/calogica/dbt-expectations/releases/latest> for the latest version tag

For latest release, see https://github.com/calogica/dbt-expectations/releases

Dependencies

This package includes a reference to dbt-date which in turn references dbt-utils so there's no need to also import dbt-utils in your local project.

Note: we no longer include spark_utils in this package to avoid versioning conflicts. If you are running this package on non-core platforms (outside of Snowflake, BigQuery, Redshift, Postgres), you will need to use a package like spark_utils to shim macros.

For example, in packages.yml, you will need to include the relevant package:

  - package: dbt-labs/spark_utils
    version: <latest or range>

And reference in the dispatch list for dbt_utils in dbt_project.yml:

vars:
    dbt_utils_dispatch_list: [spark_utils]

Variables

The following variables need to be defined in your dbt_project.yml file:

vars:
  'dbt_date:time_zone': 'America/Los_Angeles'

You may specify any valid timezone string in place of America/Los_Angeles. For example, use America/New_York for East Coast Time.

Available Tests

Table shape

Missing values, unique values, and types

Sets and ranges

String matching

Aggregate functions

Multi-column

Distributional functions

Documentation

Expect the specified column to exist.

Applies to: Column

tests:
- dbt_expectations.expect_column_to_exist

Expect the model to have rows that are at least as recent as the defined interval prior to the current timestamp. Optionally gives the possibility to apply filters on the results.

Applies to: Column

tests:
  - dbt_expectations.expect_row_values_to_have_recent_data:
        datepart: day
        interval: 1
        row_condition: 'id is not null' #optional

Expect the model to have grouped rows that are at least as recent as the defined interval prior to the current timestamp. Use this to test whether there is recent data for each grouped row defined by group_by (which is a list of columns) and a timestamp_column. Optionally gives the possibility to apply filters on the results.

Applies to: Model, Seed, Source

models: # or seeds:
  - name : my_model
    tests :
        - dbt_expectations.expect_grouped_row_values_to_have_recent_data:
            group_by: [group_id]
            timestamp_column: date_day
            datepart: day
            interval: 1
            row_condition: "id is not null" #optional
        # or also:
        - dbt_expectations.expect_grouped_row_values_to_have_recent_data:
            group_by: [group_id, other_group_id]
            timestamp_column: date_day
            datepart: day
            interval: 1
            row_condition: "id is not null" #optional

Expect the number of columns in a model to be between two values.

Applies to: Model, Seed, Source

tests:
  - dbt_expectations.expect_table_column_count_to_be_between:
      min_value: 1 # (Optional)
      max_value: 4 # (Optional)

Expect the number of columns in a model to match another model.

Applies to: Model, Seed, Source

models: # or seeds:
  - name: my_model
    tests:
    - dbt_expectations.expect_table_column_count_to_equal_other_table:
        compare_model: ref("other_model")

Expect the columns in a model not to contain a given list.

Applies to: Model, Seed, Source

models: # or seeds:
  - name: my_model
    tests:
    - dbt_expectations.expect_table_columns_to_not_contain_set:
        column_list: ["col_a", "col_b"]
        transform: uppper # (Optional)

Expect the columns in a model to contain a given list.

Applies to: Model, Seed, Source

models: # or seeds:
  - name: my_model
    tests:
    - dbt_expectations.expect_table_columns_to_contain_set:
        column_list: ["col_a", "col_b"]
        transform: uppper # (Optional)

Expect the number of columns in a model to be equal to expected_number_of_columns.

Applies to: Model, Seed, Source

models: # or seeds:
  - name: my_model
    tests:
    - dbt_expectations.expect_table_column_count_to_equal:
        value: 7

Expect the columns to exactly match a specified list.

Applies to: Model, Seed, Source

models: # or seeds:
  - name: my_model
    tests:
    - dbt_expectations.expect_table_columns_to_match_ordered_list:
        column_list: ["col_a", "col_b"]
        transform: uppper # (Optional)

Expect the columns in a model to match a given list.

Applies to: Model, Seed, Source

models: # or seeds:
  - name: my_model
    tests:
    - dbt_expectations.expect_table_columns_to_match_set:
        column_list: ["col_a", "col_b"]
        transform: uppper # (Optional)

Expect the number of rows in a model to be between two values. Applies to: Model, Seed, Source

models: # or seeds:
  - name: my_model
    tests:
    - dbt_expectations.expect_table_row_count_to_be_between:
        min_value: 1 # (Optional)
        max_value: 4 # (Optional)
        group_by: [group_id, other_group_id, ...] # (Optional)
        row_condition: "id is not null" # (Optional)
        strictly: false # (Optional. Adds an 'or equal to' to the comparison operator for min/max)

Expect the number of rows in a model match another model.

Applies to: Model, Seed, Source

models: # or seeds:
  - name: my_model
    tests:
    - dbt_expectations.expect_table_row_count_to_equal_other_table:
        compare_model: ref("other_model")
        factor: 1 # (Optional)
        row_condition: "id is not null" # (Optional)
        compare_row_condition: "id is not null" # (Optional)

Expect the number of rows in a model to match another model times a preconfigured factor.

Applies to: Model, Seed, Source

models: # or seeds:
  - name: my_model
    tests:
    - dbt_expectations.expect_table_row_count_to_equal_other_table_times_factor:
        compare_model: ref("other_model")
        factor: 13
        row_condition: "id is not null" # (Optional)
        compare_row_condition: "id is not null" # (Optional)

Expect the number of rows in a model to be equal to expected_number_of_rows.

Applies to: Model, Seed, Source

models: # or seeds:
  - name: my_model
    tests:
    - dbt_expectations.expect_table_row_count_to_equal:
        value: 4
        group_by: [group_id, other_group_id, ...] # (Optional)
        row_condition: "id is not null" # (Optional)

Expect each column value to be unique.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_be_unique:
      row_condition: "id is not null" # (Optional)

Expect column values to not be null.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_not_be_null:
      row_condition: "id is not null" # (Optional)

Expect column values to be null.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_be_null:
      row_condition: "id is not null" # (Optional)

Expect a column to be of a specified data type.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_be_of_type:
      column_type: date

Expect a column to be one of a specified type list.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_be_in_type_list:
      column_type_list: [date, datetime]

Expect a column to have consistent casing. By setting display_inconsistent_columns to true, the number of inconsistent values in the column will be displayed in the terminal whereas the inconsistent values themselves will be returned if the SQL compiled test is run.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_have_consistent_casing:
      display_inconsistent_columns: false # (Optional)

Expect each column value to be in a given set.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_be_in_set:
      value_set: ['a','b','c']
      quote_values: true # (Optional)
      row_condition: "id is not null" # (Optional)

Expect each column value to be between two values.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_be_between:
      min_value: 0  # (Optional)
      max_value: 10 # (Optional)
      row_condition: "id is not null" # (Optional)
      strictly: false # (Optional. Default is 'false'. Adds an 'or equal to' to the comparison operator for min/max)

Expect each column value not to be in a given set.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_not_be_in_set:
      value_set: ['e','f','g']
      quote_values: true # (Optional)
      row_condition: "id is not null" # (Optional)

Expect column values to be increasing.

If strictly: True, then this expectation is only satisfied if each consecutive value is strictly increasing–equal values are treated as failures.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_be_increasing:
      sort_column: date_day
      row_condition: "id is not null" # (Optional)
      strictly: true # (Optional for comparison operator. Default is 'true', and it uses '>'. If set to 'false' it uses '>='.)
      group_by: [group_id, other_group_id, ...] # (Optional)

Expect column values to be decreasing.

If strictly=True, then this expectation is only satisfied if each consecutive value is strictly increasing–equal values are treated as failures.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_be_decreasing:
      sort_column: col_numeric_a
      row_condition: "id is not null" # (Optional)
      strictly: true # (Optional for comparison operator. Default is 'true' and it uses '<'. If set to 'false', it uses '<='.)
      group_by: [group_id, other_group_id, ...] # (Optional)

Expect column entries to be strings with length between a min_value value and a max_value value (inclusive).

Applies to: Column

tests:
  - dbt_expectations.expect_column_value_lengths_to_be_between:
      min_value: 1 # (Optional)
      max_value: 4 # (Optional)
      row_condition: "id is not null" # (Optional)
      strictly: false # (Optional. Default is 'false'. Adds an 'or equal to' to the comparison operator for min/max)

Expect column entries to be strings with length equal to the provided value.

Applies to: Column

tests:
  - dbt_expectations.expect_column_value_lengths_to_equal:
      value: 10
      row_condition: "id is not null" # (Optional)

Expect column entries to be strings that match a given regular expression. Valid matches can be found anywhere in the string, for example "[at]+" will identify the following strings as expected: "cat", "hat", "aa", "a", and "t", and the following strings as unexpected: "fish", "dog".

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_match_regex:
      regex: "[at]+"
      row_condition: "id is not null" # (Optional)

Expect column entries to be strings that do NOT match a given regular expression. The regex must not match any portion of the provided string. For example, "[at]+" would identify the following strings as expected: "fish”, "dog”, and the following as unexpected: "cat”, "hat”.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_not_match_regex:
      regex: "[at]+"
      row_condition: "id is not null" # (Optional)

Expect the column entries to be strings that can be matched to either any of or all of a list of regular expressions. Matches can be anywhere in the string.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_match_regex_list:
      regex_list: ["@[^.]*", "&[^.]*"]
      match_on: any # (Optional. Default is 'any', which applies an 'OR' for each regex. If 'all', it applies an 'AND' for each regex.)
      row_condition: "id is not null" # (Optional)

Expect the column entries to be strings that do not match any of a list of regular expressions. Matches can be anywhere in the string.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_not_match_regex_list:
      regex_list: ["@[^.]*", "&[^.]*"]
      match_on: any # (Optional. Default is 'any', which applies an 'OR' for each regex. If 'all', it applies an 'AND' for each regex.)
      row_condition: "id is not null" # (Optional)

Expect column entries to be strings that match a given SQL like pattern.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_match_like_pattern:
      like_pattern: "%@%"
      row_condition: "id is not null" # (Optional)

Expect column entries to be strings that do not match a given SQL like pattern.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_not_match_like_pattern:
      like_pattern: "%&%"
      row_condition: "id is not null" # (Optional)

Expect the column entries to be strings that match any of a list of SQL like patterns.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_match_like_pattern_list:
      like_pattern_list: ["%@%", "%&%"]
      match_on: any # (Optional. Default is 'any', which applies an 'OR' for each pattern. If 'all', it applies an 'AND' for each regex.)
      row_condition: "id is not null" # (Optional)

Expect the column entries to be strings that do not match any of a list of SQL like patterns.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_not_match_like_pattern_list:
      like_pattern_list: ["%@%", "%&%"]
      match_on: any # (Optional. Default is 'any', which applies an 'OR' for each pattern. If 'all', it applies an 'AND' for each regex.)
      row_condition: "id is not null" # (Optional)

Expect the number of distinct column values to be equal to a given value.

Applies to: Column

tests:
  - dbt_expectations.expect_column_distinct_count_to_equal:
      value: 10
      quote_values: false # (Optional. Default is 'false'.)
      group_by: [group_id, other_group_id, ...] # (Optional)
      row_condition: "id is not null" # (Optional)

Expect the number of distinct column values to be greater than a given value.

Applies to: Column

tests:
  - dbt_expectations.expect_column_distinct_count_to_be_greater_than:
      value: 10
      quote_values: false # (Optional. Default is 'false'.)
      group_by: [group_id, other_group_id, ...] # (Optional)
      row_condition: "id is not null" # (Optional)

Expect the set of distinct column values to be contained by a given set.

Applies to: Column

tests:
  - dbt_expectations.expect_column_distinct_values_to_be_in_set:
      value_set: ['a','b','c','d']
      quote_values: false # (Optional. Default is 'false'.)
      row_condition: "id is not null" # (Optional)

Expect the set of distinct column values to contain a given set.

In contrast to expect_column_values_to_be_in_set this ensures not that all column values are members of the given set but that values from the set must be present in the column.

Applies to: Column

tests:
  - dbt_expectations.expect_column_distinct_values_to_contain_set:
      value_set: ['a','b']
      quote_values: false # (Optional. Default is 'false'.)
      row_condition: "id is not null" # (Optional)

Expect the set of distinct column values to equal a given set.

In contrast to expect_column_distinct_values_to_contain_set this ensures not only that a certain set of values are present in the column but that these and only these values are present.

Applies to: Column

tests:
  - dbt_expectations.expect_column_distinct_values_to_equal_set:
      value_set: ['a','b','c']
      quote_values: true # (Optional. Default is 'true'.)
      row_condition: "id is not null" # (Optional)

Expect the number of distinct column values to be equal to number of distinct values in another model.

Applies to: Model, Column, Seed, Source

This can be applied to a model:

models: # or seeds:
  - name: my_model_1
    tests:
      - dbt_expectations.expect_column_distinct_count_to_equal_other_table:
          column_name: col_1
          compare_model: ref("my_model_2")
          compare_column_name: col_2
          row_condition: "id is not null" # (Optional)
          compare_row_condition: "id is not null" # (Optional)

or at the column level:

models: # or seeds:
  - name: my_model_1
    columns:
      - name: col_1
        tests:
          - dbt_expectations.expect_column_distinct_count_to_equal_other_table:
              compare_model: ref("my_model_2")
              compare_column_name: col_2
              row_condition: "id is not null" # (Optional)
              compare_row_condition: "id is not null" # (Optional)

If compare_model or compare_column_name are no specified, model and column_name are substituted. So, one could compare distinct counts of two different columns in the same model, or identically named columns in separate models etc.

Expect the column mean to be between a min_value value and a max_value value (inclusive).

Applies to: Column

tests:
  - dbt_expectations.expect_column_mean_to_be_between:
      min_value: 0 # (Optional)
      max_value: 2 # (Optional)
      group_by: [group_id, other_group_id, ...] # (Optional)
      row_condition: "id is not null" # (Optional)
      strictly: false # (Optional. Default is 'false'. Adds an 'or equal to' to the comparison operator for min/max)

Expect the column median to be between a min_value value and a max_value value (inclusive).

Applies to: Column

tests:
  - dbt_expectations.expect_column_median_to_be_between:
      min_value: 0
      max_value: 2
      group_by: [group_id, other_group_id, ...] # (Optional)
      row_condition: "id is not null" # (Optional)
      strictly: false # (Optional. Default is 'false'. Adds an 'or equal to' to the comparison operator for min/max)

Expect specific provided column quantiles to be between provided min_value and max_value values.

Applies to: Column

tests:
  - dbt_expectations.expect_column_quantile_values_to_be_between:
      quantile: .95
      min_value: 0 # (Optional)
      max_value: 2 # (Optional)
      group_by: [group_id, other_group_id, ...] # (Optional)
      row_condition: "id is not null" # (Optional)
      strictly: false # (Optional. Default is 'false'. Adds an 'or equal to' to the comparison operator for min/max)

Expect the column standard deviation to be between a min_value value and a max_value value. Uses sample standard deviation (normalized by N-1).

Applies to: Column

tests:
  - dbt_expectations.expect_column_stdev_to_be_between:
      min_value: 0 # (Optional)
      max_value: 2 # (Optional)
      group_by: [group_id, other_group_id, ...] # (Optional)
      row_condition: "id is not null" # (Optional)
      strictly: false # (Optional. Default is 'false'. Adds an 'or equal to' to the comparison operator for min/max)

Expect the number of unique values to be between a min_value value and a max_value value.

Applies to: Column

tests:
  - dbt_expectations.expect_column_unique_value_count_to_be_between:
      min_value: 3 # (Optional)
      max_value: 3 # (Optional)
      group_by: [group_id, other_group_id, ...] # (Optional)
      row_condition: "id is not null" # (Optional)
      strictly: false # (Optional. Default is 'false'. Adds an 'or equal to' to the comparison operator for min/max)

Expect the proportion of unique values to be between a min_value value and a max_value value.

For example, in a column containing [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], there are 4 unique values and 10 total values for a proportion of 0.4.

Applies to: Column

tests:
  - dbt_expectations.expect_column_proportion_of_unique_values_to_be_between:
      min_value: 0  # (Optional)
      max_value: .4 # (Optional)
      group_by: [group_id, other_group_id, ...] # (Optional)
      row_condition: "id is not null" # (Optional)
      strictly: false # (Optional. Default is 'false'. Adds an 'or equal to' to the comparison operator for min/max)

Expect the most common value to be within the designated value set

Applies to: Column

tests:
  - dbt_expectations.expect_column_most_common_value_to_be_in_set:
      value_set: [0.5]
      top_n: 1
      quote_values: false # (Optional)
      data_type: "decimal" # (Optional. Default is 'decimal')
      strictly: false # (Optional. Default is 'false'. Adds an 'or equal to' to the comparison operator for min/max)

Expect the column max to be between a min and max value

Applies to: Column

tests:
  - dbt_expectations.expect_column_max_to_be_between:
      min_value: 1 # (Optional)
      max_value: 1 # (Optional)
      group_by: [group_id, other_group_id, ...] # (Optional)
      row_condition: "id is not null" # (Optional)
      strictly: false # (Optional. Default is 'false'. Adds an 'or equal to' to the comparison operator for min/max)

Expect the column min to be between a min and max value

Applies to: Column

tests:
  - dbt_expectations.expect_column_min_to_be_between:
      min_value: 0 # (Optional)
      max_value: 1 # (Optional)
      group_by: [group_id, other_group_id, ...] # (Optional)
      row_condition: "id is not null" # (Optional)
      strictly: false # (Optional. Default is 'false'. Adds an 'or equal to' to the comparison operator for min/max)

Expect the column to sum to be between a min and max value

Applies to: Column

tests:
  - dbt_expectations.expect_column_sum_to_be_between:
      min_value: 1 # (Optional)
      max_value: 2 # (Optional)
      group_by: [group_id, other_group_id, ...] # (Optional)
      row_condition: "id is not null" # (Optional)
      strictly: false # (Optional. Default is 'false'. Adds an 'or equal to' to the comparison operator for min/max)

Expect values in column A to be greater than column B.

Applies to: Model, Seed, Source

tests:
  - dbt_expectations.expect_column_pair_values_A_to_be_greater_than_B:
      column_A: col_numeric_a
      column_B: col_numeric_a
      or_equal: True
      row_condition: "id is not null" # (Optional)

Expect the values in column A to be the same as column B.

Applies to: Model, Seed, Source

tests:
  - dbt_expectations.expect_column_pair_values_to_be_equal:
      column_A: col_numeric_a
      column_B: col_numeric_a
      row_condition: "id is not null" # (Optional)

Expect paired values from columns A and B to belong to a set of valid pairs.

Note: value pairs are expressed as lists within lists

Applies to: Model, Seed, Source

tests:
  - dbt_expectations.expect_column_pair_values_to_be_in_set:
      column_A: col_numeric_a
      column_B: col_numeric_b
      value_pairs_set: [[0, 1], [1, 0], [0.5, 0.5], [0.5, 0.5]]
      row_condition: "id is not null" # (Optional)

Expect the values for each record to be unique across the columns listed. Note that records can be duplicated.

Applies to: Model, Seed, Source

tests:
  - dbt_expectations.expect_select_column_values_to_be_unique_within_record:
      column_list: ["col_string_a", "col_string_b"]
      ignore_row_if: "any_value_is_missing" # (Optional. Default is 'all_values_are_missing')
      quote_columns: false # (Optional)
      row_condition: "id is not null" # (Optional)

Expects that sum of all rows for a set of columns is equal to a specific value

Applies to: Model, Seed, Source

tests:
  - dbt_expectations.expect_multicolumn_sum_to_equal:
      column_list: ["col_numeric_a", "col_numeric_b"]
      sum_total: 4
      group_by: [group_id, other_group_id, ...] # (Optional)
      row_condition: "id is not null" # (Optional)

Expect that the columns are unique together, e.g. a multi-column primary key.

Applies to: Model, Seed, Source

tests:
  - dbt_expectations.expect_compound_columns_to_be_unique:
      column_list: ["date_col", "col_string_b"]
      ignore_row_if: "any_value_is_missing" # (Optional. Default is 'all_values_are_missing')
      quote_columns: false # (Optional)
      row_condition: "id is not null" # (Optional)

Expects changes in metric values to be within Z sigma away from a moving average, taking the (optionally logged) differences of an aggregated metric value and comparing it to its value N days ago.

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_be_within_n_moving_stdevs:
      date_column_name: date
      period: day # (Optional. Default is 'day')
      lookback_periods: 1 # (Optional. Default is 1)
      trend_periods: 7 # (Optional. Default is 7)
      test_periods: 14 # (Optional. Default is 14)
      sigma_threshold: 3 # (Optional. Default is 3)
      take_logs: true # (Optional. Default is 'true')
      sigma_threshold_upper: x # (Optional. Replace 'x' with a value. Default is 'None')
      sigma_threshold_lower: y # (Optional. Replace 'y' with a value. Default is 'None')
      take_diffs: true # (Optional)

Expects (optionally grouped & summed) metric values to be within Z sigma away from the column average

Applies to: Column

tests:
  - dbt_expectations.expect_column_values_to_be_within_n_stdevs:
      group_by: date_day # (Optional. Default is 'None')
      sigma_threshold: 3 # (Optional. Default is 3)

Expects model to have values for every grouped date_part.

For example, this tests whether a model has data for every day (grouped on date_col) between either:

  • The min/max value of the specified date_col (default).
  • A specified test_start_date and/or test_end_date.

Applies to: Model, Seed, Source

tests:
    - dbt_expectations.expect_row_values_to_have_data_for_every_n_datepart:
        date_col: date_day
        date_part: day # (Optional. Default is 'day')
        row_condition: "id is not null" # (Optional)
        test_start_date: 'yyyy-mm-dd' # (Optional. Replace 'yyyy-mm-dd' with a date. Default is 'None')
        test_end_date: 'yyyy-mm-dd' # (Optional. Replace 'yyyy-mm-dd' with a date. Default is 'None')
        exclusion_condition: statement # (Optional. See details below. Default is 'None')

Notes:

  • test_end_date is exclusive, e.g. a test with test_end_date value of '2020-01-05' will pass if your model has data through '2021-01-04'.

  • If test_start_date or test_end_date are not specified, the test automatically determines the min/max of the specified date_col from your data, respectively. On some platforms, and/or if your table is not partitione on that date column, this may lead to performance issues. In these cases, we recommend setting an explicit date literal. You may also set a "dynamic" date literal via the built-in modules.datetime functions:

    date_part: day
    test_start_date: '2021-05-01'
    test_end_date: '{{ modules.datetime.date.today() }}'

or, for example:

    date_part: day
    test_start_date: '2021-05-01'
    test_end_date: '{{ modules.datetime.date.today() - modules.datetime.timedelta(1)) }}'

Unfortunately, you currently cannot use a dynamic SQL date, such as current_date or macro from a dbt package such as dbt-date, as the underlying dbt_utils.date_spine expects a date literal.

The interval argument will optionally group date_part by a given integer to test data presence at a lower granularity, e.g. adding interval: 7 to the example above will test whether a model has data for each 7-day period instead of for each day.

Known or expected missing dates can be excluded from the test by setting the exclusion_criteria with a valid SQL statement; e.g., adding exclusion_condition: not(date_day = '2021-10-19') will ensure that test passes if and only if date_day = '2021-10-19' is the only date with missing data. Alternatively, exclusion_condition: not(date_part(month, date_day) = 12 and date_part(day, date_day) = 25) will permit data to be missing on the 25th of December (Christmas day) every year.

~ Developers Only ~

Integration Tests

This project contains integration tests for all test macros in a separate integration_tests dbt project contained in this repo.

To run the tests:

  1. You will need a profile called integration_tests in ~/.dbt/profiles.yml pointing to a writable database. We only support postgres, BigQuery and Snowflake.
  2. Then, from within the integration_tests folder, run dbt build to run the test models in integration_tests/models/schema_tests/ and run the tests specified in integration_tests/models/schema_tests/schema.yml

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