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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 1.7.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: [">=0.10.0", "<0.11.0"]
# <see https://github.com/calogica/dbt-expectations/releases/latest> for the latest version tag
This package supports:
- Postgres
- Snowflake
- BigQuery
- DuckDB
- Spark (experimental)
- Trino
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
Table shape
- expect_column_to_exist
- expect_row_values_to_have_recent_data
- expect_grouped_row_values_to_have_recent_data
- expect_table_aggregation_to_equal_other_table
- expect_table_column_count_to_be_between
- expect_table_column_count_to_equal_other_table
- expect_table_column_count_to_equal
- expect_table_columns_to_not_contain_set
- expect_table_columns_to_contain_set
- expect_table_columns_to_match_ordered_list
- expect_table_columns_to_match_set
- expect_table_row_count_to_be_between
- expect_table_row_count_to_equal_other_table
- expect_table_row_count_to_equal_other_table_times_factor
- expect_table_row_count_to_equal
Missing values, unique values, and types
- expect_column_values_to_be_null
- expect_column_values_to_not_be_null
- expect_column_values_to_be_unique
- expect_column_values_to_be_of_type
- expect_column_values_to_be_in_type_list
- expect_column_values_to_have_consistent_casing
Sets and ranges
- expect_column_values_to_be_in_set
- expect_column_values_to_not_be_in_set
- expect_column_values_to_be_between
- expect_column_values_to_be_decreasing
- expect_column_values_to_be_increasing
String matching
- expect_column_value_lengths_to_be_between
- expect_column_value_lengths_to_equal
- expect_column_values_to_match_like_pattern
- expect_column_values_to_match_like_pattern_list
- expect_column_values_to_match_regex
- expect_column_values_to_match_regex_list
- expect_column_values_to_not_match_like_pattern
- expect_column_values_to_not_match_like_pattern_list
- expect_column_values_to_not_match_regex
- expect_column_values_to_not_match_regex_list
Aggregate functions
- expect_column_distinct_count_to_be_greater_than
- expect_column_distinct_count_to_be_less_than
- expect_column_distinct_count_to_equal_other_table
- expect_column_distinct_count_to_equal
- expect_column_distinct_values_to_be_in_set
- expect_column_distinct_values_to_contain_set
- expect_column_distinct_values_to_equal_set
- expect_column_max_to_be_between
- expect_column_mean_to_be_between
- expect_column_median_to_be_between
- expect_column_min_to_be_between
- expect_column_most_common_value_to_be_in_set
- expect_column_proportion_of_unique_values_to_be_between
- expect_column_quantile_values_to_be_between
- expect_column_stdev_to_be_between
- expect_column_sum_to_be_between
- expect_column_unique_value_count_to_be_between
Multi-column
- expect_column_pair_values_A_to_be_greater_than_B
- expect_column_pair_values_to_be_equal
- expect_column_pair_values_to_be_in_set
- expect_compound_columns_to_be_unique
- expect_multicolumn_sum_to_equal
- expect_select_column_values_to_be_unique_within_record
Distributional functions
- expect_column_values_to_be_within_n_moving_stdevs
- expect_column_values_to_be_within_n_stdevs
- expect_row_values_to_have_data_for_every_n_datepart
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
Expect 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)
step: 1 # (Optional. If set, it requires the difference between values to be exactly this step. Requires numeric columns.)
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)
step: 1 # (Optional. If set, it requires the difference between values to be exactly this step. Requires numeric columns.)
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 theregex
pattern is a "raw" string and should be escaped. The default isFalse
.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 isi
, 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 theregex
pattern is a "raw" string and should be escaped. The default isFalse
.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 isi
, 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 theregex
pattern is a "raw" string and should be escaped. The default isFalse
.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 isi
, 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 theregex
pattern is a "raw" string and should be escaped. The default isFalse
.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 isi
, 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 arenull
any_value_is_missing
means that rows are excluded where either of the test columns arenull
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 arenull
any_value_is_missing
means that rows are excluded where either of the test columns arenull
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 specifieddate_col
(default). - A specified
test_start_date
and/ortest_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 withtest_end_date
value of'2020-01-05'
will pass if your model has data through'2021-01-04'
. -
If
test_start_date
ortest_end_date
are not specified, the test automatically determines themin
/max
of the specifieddate_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-inmodules.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, rundbt build
to run the test models inintegration_tests/models/schema_tests/
and run the tests specified inintegration_tests/models/schema_tests/schema.yml