dbt-expectations

About

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:

datacoves.com

Install

dbt-expectations currently supports dbt 1.2.x or higher.

Check dbt package 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: [">=0.9.0", "<0.10.0"]
    # <see https://github.com/calogica/dbt-expectations/releases/latest> for the latest version tag

This package supports:

Postgres
Snowflake
BigQuery
DuckDB

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

Dependencies

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

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

Documentation

expect_column_to_exist

Expect the specified column to exist.

Applies to: Column

tests:
  - dbt_expectations.expect_column_to_exist

expect_row_values_to_have_recent_data

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_grouped_row_values_to_have_recent_data

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_table_aggregation_to_equal_other_table

Except an (optionally grouped) expression to match the same (or optionally other) expression in a different table.

Applies to: Model, Seed, Source

Simple:

tests:
  - dbt_expectations.expect_table_aggregation_to_equal_other_table:
      expression: sum(col_numeric_a)
      compare_model: ref("other_model")
      group_by: [idx]

More complex:

tests:
  - dbt_expectations.expect_table_aggregation_to_equal_other_table:
      expression: count(*)
      compare_model: ref("other_model")
      compare_expression: count(distinct id)
      group_by: [date_column]
      compare_group_by: [some_other_date_column]

or:

tests:
  - dbt_expectations.expect_table_aggregation_to_equal_other_table:
      expression: max(column_a)
      compare_model: ref("other_model")
      compare_expression: max(column_b)
      group_by: [date_column]
      compare_group_by: [some_other_date_column]
      row_condition: some_flag=true
      compare_row_condition: some_flag=false

Note: You can also express a tolerance factor, either as an absolute tolerable difference, tolerance, or as a tolerable % difference tolerance_percent expressed as a decimal (i.e 0.05 for 5%).

expect_table_column_count_to_be_between

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_table_column_count_to_equal_other_table

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_table_columns_to_not_contain_set

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: upper # (Optional)

expect_table_columns_to_contain_set

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: upper # (Optional)

expect_table_column_count_to_equal

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_table_columns_to_match_ordered_list

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: upper # (Optional)

expect_table_columns_to_match_set

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: upper # (Optional)

expect_table_row_count_to_be_between

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_table_row_count_to_equal_other_table

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")
          group_by: [col1, col2] # (Optional)
          compare_group_by: [col1, col2] # (Optional)
          factor: 1 # (Optional)
          row_condition: "id is not null" # (Optional)
          compare_row_condition: "id is not null" # (Optional)

expect_table_row_count_to_equal_other_table_times_factor

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
          group_by: [col1, col2] # (Optional)
          compare_group_by: [col1, col2] # (Optional)
          row_condition: "id is not null" # (Optional)
          compare_row_condition: "id is not null" # (Optional)

expect_table_row_count_to_equal

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_column_values_to_be_unique

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

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

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_column_values_to_be_of_type

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_column_values_to_be_in_type_list

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_column_values_to_have_consistent_casing

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_column_values_to_be_in_set

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. Default is 'true'.)
      row_condition: "id is not null" # (Optional)

expect_column_values_to_be_between

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_column_values_to_not_be_in_set

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. Default is 'true'.)
      row_condition: "id is not null" # (Optional)

expect_column_values_to_be_increasing

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

Expect column values to be decreasing.

If strictly=True, then this expectation is only satisfied if each consecutive value is strictly decreasing – 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_value_lengths_to_be_between

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_value_lengths_to_equal

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_values_to_match_regex

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".

Optional (keyword) arguments:

is_raw indicates the regex pattern is a "raw" string and should be escaped. The default is False.
flags is a string of one or more characters that are passed to the regex engine as flags (or parameters). Allowed flags are adapter-specific. A common flag is i, for case-insensitive matching. The default is no flags.

Applies to: Column

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

expect_column_values_to_not_match_regex

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”.

Optional (keyword) arguments:

is_raw indicates the regex pattern is a "raw" string and should be escaped. The default is False.
flags is a string of one or more characters that are passed to the regex engine as flags (or parameters). Allowed flags are adapter-specific. A common flag is i, for case-insensitive matching. The default is no flags.

Applies to: Column

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

expect_column_values_to_match_regex_list

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.

Optional (keyword) arguments:

is_raw indicates the regex pattern is a "raw" string and should be escaped. The default is False.
flags is a string of one or more characters that are passed to the regex engine as flags (or parameters). Allowed flags are adapter-specific. A common flag is i, for case-insensitive matching. The default is no flags.

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)
      is_raw: True # (Optional)
      flags: i # (Optional)

expect_column_values_to_not_match_regex_list

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.

Optional (keyword) arguments:

is_raw indicates the regex pattern is a "raw" string and should be escaped. The default is False.
flags is a string of one or more characters that are passed to the regex engine as flags (or parameters). Allowed flags are adapter-specific. A common flag is i, for case-insensitive matching. The default is no flags.

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)
      is_raw: True # (Optional)
      flags: i # (Optional)

expect_column_values_to_match_like_pattern

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_values_to_not_match_like_pattern

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_column_values_to_match_like_pattern_list

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_column_values_to_not_match_like_pattern_list

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_column_distinct_count_to_equal

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: true # (Optional. Default is 'true'.)
      group_by: [group_id, other_group_id, ...] # (Optional)
      row_condition: "id is not null" # (Optional)

expect_column_distinct_count_to_be_greater_than

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: true # (Optional. Default is 'true'.)
      group_by: [group_id, other_group_id, ...] # (Optional)
      row_condition: "id is not null" # (Optional)

expect_column_distinct_count_to_be_less_than

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

Applies to: Column

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

expect_column_distinct_values_to_be_in_set

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: true # (Optional. Default is 'true'.)
      row_condition: "id is not null" # (Optional)

expect_column_distinct_values_to_contain_set

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: true # (Optional. Default is 'true'.)
      row_condition: "id is not null" # (Optional)

expect_column_distinct_values_to_equal_set

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_column_distinct_count_to_equal_other_table

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_column_mean_to_be_between

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_column_median_to_be_between

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_column_quantile_values_to_be_between

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_column_stdev_to_be_between

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_column_unique_value_count_to_be_between

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_column_proportion_of_unique_values_to_be_between

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_column_most_common_value_to_be_in_set

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: true # (Optional. Default is 'true'.)
      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_column_max_to_be_between

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_column_min_to_be_between

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_column_sum_to_be_between

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_column_pair_values_A_to_be_greater_than_B

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_column_pair_values_to_be_equal

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_column_pair_values_to_be_in_set

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_select_column_values_to_be_unique_within_record

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)

Note:

all_values_are_missing (default) means that rows are excluded where all of the test columns are null
any_value_is_missing means that rows are excluded where either of the test columns are null

expect_multicolumn_sum_to_equal

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_compound_columns_to_be_unique

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)

Note:

all_values_are_missing (default) means that rows are excluded where all of the test columns are null
any_value_is_missing means that rows are excluded where either of the test columns are null

expect_column_values_to_be_within_n_moving_stdevs

A simple anomaly test based on the assumption that differences between periods in a given time series follow a log-normal distribution. Thus, we would expect the logged differences (vs N periods ago) in metric values to be within Z sigma away from a moving average. By applying a list of columns in the group_by parameter, you can also test for deviations within a group.

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. Default is 'true')
      group_by: [group_id] # (Optional. Default is 'None')

expect_column_values_to_be_within_n_stdevs

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: group_id # (Optional. Default is 'None')
      sigma_threshold: 3 # (Optional. Default is 3)

expect_row_values_to_have_data_for_every_n_datepart

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 date_spine macro 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:

You will need a profile called integration_tests in ~/.dbt/profiles.yml pointing to a writable database. We only support postgres, BigQuery and Snowflake.
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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