dbt-utils package tests - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to use the dbt-utils test to check for duplicates in a column.

dbt

tests:
  - dbt_utils.unique_combination_of_columns:
      combination_of_columns: [[1]]

Drag options to blanks, or click blank then click option'

Acount

Bdate

Cid

Dvalue

Attempts:

3 left

💡 Hint

Common Mistakes

Using a column that is not unique like 'count' or 'value'.

Forgetting to put the column name inside the list brackets.

The unique_combination_of_columns test checks that the specified column(s) have unique values. Here, id is the column to check for duplicates.

2fill in blank

medium

Complete the code to use the dbt-utils test to check if a column has any null values.

dbt

tests:
  - dbt_utils.not_null:
      column_name: [1]

Drag options to blanks, or click blank then click option'

Astatus

Btotal

Cdate

Duser_id

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing a column that can have nulls like 'status'.

Not specifying the column name correctly.

The not_null test checks that the specified column does not contain any null values. Here, user_id is the column to check.

3fill in blank

hard

Fix the error in the dbt-utils test to check if two columns together are unique.

dbt

tests:
  - dbt_utils.unique_combination_of_columns:
      combination_of_columns: [[1]]

Drag options to blanks, or click blank then click option'

Auser_id, order_id

B['user_id', 'order_id']

Cuser_id

D'user_id', 'order_id'

Attempts:

3 left

💡 Hint

Common Mistakes

Not quoting the column names.

Not using a list format with brackets.

Using Python list syntax inside YAML incorrectly.

The combination_of_columns expects a list of column names as strings inside brackets. The correct syntax is a list with quoted column names separated by commas.

4fill in blank

hard

Fill both blanks to write a dbt-utils test that checks if values in a column exist in another table's column.

dbt

tests:
  - dbt_utils.relationships:
      to: [1]
      field: [2]

Drag options to blanks, or click blank then click option'

Aref('customers')

Bcustomer_id

Corder_id

Dref('orders')

Attempts:

3 left

💡 Hint

Common Mistakes

Using table names as strings instead of using ref().

Mixing up the 'to' and 'field' values.

The relationships test checks if values in the current model's field exist in the to model's primary key. Here, ref('customers') is the referenced table and customer_id is the column to check.

5fill in blank

hard

Fill all three blanks to write a dbt-utils test that checks if a column's values are within a list of allowed values.

dbt

tests:
  - dbt_utils.accepted_values:
      column: [1]
      values: [[2]]
      quote_values: [3]

Drag options to blanks, or click blank then click option'

Astatus

B'active', 'inactive', 'pending'

Ctrue

Dfalse

Attempts:

3 left

💡 Hint

Common Mistakes

Not quoting the string values in the list.

Setting quote_values to false when values are strings.

The accepted_values test checks if the column's values are only from the allowed list. The column is 'status', values is a list of allowed strings, and quote_values is true to treat values as strings.

Practice

1. What is the main purpose of using dbt-utils package tests in your data models?

easy

A. To write complex SQL queries faster

B. To speed up data loading processes

C. To check data quality by validating conditions like uniqueness and nulls

D. To create visual dashboards automatically

Solution

1. Step 1: Understand the role of dbt-utils tests

   dbt-utils tests are designed to check data quality by validating conditions such as uniqueness, null values, and accepted values.

2. Step 2: Compare options with the purpose

   Only To check data quality by validating conditions like uniqueness and nulls describes checking data quality, which matches the purpose of dbt-utils tests.

3. Final Answer:

   To check data quality by validating conditions like uniqueness and nulls -> Option C

4. Quick Check:

   dbt-utils tests = data quality checks [OK]

Hint: Tests in dbt-utils check data quality, not speed or visuals [OK]

Common Mistakes:

• Thinking dbt-utils speeds up data loading
• Confusing tests with dashboard creation
• Assuming tests write SQL queries automatically

2. Which of the following is the correct syntax to add a uniqueness test using dbt-utils in a model YAML file?

easy

A. tests:
- dbt_utils.unique:
column_name: column_name

B. tests: - dbt_utils.unique: ['column_name']

C. tests: - dbt_utils.unique - column_name

D. tests: - dbt_utils.unique: {column_name}

Solution

1. Step 1: Recall dbt-utils test syntax in YAML

   The correct syntax uses column_name parameter under the test, like dbt_utils.unique: column_name: column_name.

2. Step 2: Check each option format

   tests: - dbt_utils.unique: column_name: column_name correctly uses the column_name key-value pair, matching dbt-utils documentation.

3. Final Answer:

   tests: - dbt_utils.unique: column_name: column_name -> Option A

4. Quick Check:

   Unique test syntax = column_name key [OK]

Hint: Use column_name: column_name for dbt_utils.unique [OK]

Common Mistakes:

• Broken YAML with multiple dashes
• Using list ['column_name'] instead of column_name key
• Using curly braces for parameters

3. Given this YAML snippet in a dbt model file:

tests:
  - dbt_utils.not_null:
      column_name: user_id
  - dbt_utils.unique:
      column_name: user_id

What will happen when you run dbt test?

medium

A. dbt will throw a syntax error due to wrong YAML format

B. dbt will check that user_id has no nulls and is unique

C. dbt will only check for nulls in user_id

D. dbt will ignore these tests and run default tests

Solution

1. Step 1: Analyze YAML test syntax

   The syntax uses column_name: user_id under dbt_utils tests, which is the correct format for not_null and unique tests.

2. Step 2: Identify dbt behavior

   This correct format will cause dbt to run both tests: no nulls and uniqueness on user_id.

3. Final Answer:

   dbt will check that user_id has no nulls and is unique -> Option B

4. Quick Check:

   Correct YAML format = runs both tests [OK]

Hint: dbt-utils tests use column_name: col correctly [OK]

Common Mistakes:

• Using lists [- user_id] instead of column_name key
• Wrong YAML indentation
• Missing quotes around column_name value

4. You wrote this test in your model YAML:

tests:
  - dbt_utils.accepted_values:
      column_name: ['status']
      values: ['active', 'inactive']

But when running dbt test, it fails with an error. What is the likely problem?

medium

A. The column_name should be a string, not a list

B. The values parameter should be a list under accepted_values, not a key-value pair

C. The accepted_values test requires a where clause

D. The values list must be a string, not a list

Solution

1. Step 1: Review dbt-utils accepted_values test syntax

   The accepted_values test expects column_name as a string identifier, not a list.

2. Step 2: Identify the YAML structure issue

   column_name: ['status'] passes a list instead of string 'status', causing an error.

3. Final Answer:

   The column_name should be a string, not a list -> Option A

4. Quick Check:

   accepted_values column_name = string [OK]

Hint: column_name must be string for accepted_values test [OK]

Common Mistakes:

• Passing column_name as list instead of string
• Using string instead of list for values
• Adding unnecessary where clause

5. You want to ensure a column email in your users model has no nulls and all values are unique using dbt-utils tests. Which YAML snippet correctly applies both tests?

hard

A. tests:
- dbt_utils.not_null:
email
- dbt_utils.unique:
email

B. tests:
- dbt_utils.not_null:
columns: ['email']
- dbt_utils.unique:
columns: ['email']

C. tests:
- dbt_utils.not_null:
- email
- dbt_utils.unique:
- email

D. tests:
- dbt_utils.not_null:
column_name: email
- dbt_utils.unique:
column_name: email

Solution

1. Step 1: Recall correct dbt-utils test syntax for columns

   dbt-utils not_null and unique tests expect column_name: email under the test name.

2. Step 2: Evaluate each YAML snippet

   Snippet with column_name: email for both tests correctly uses the required key-value format. The snippet missing colons after tests is invalid YAML. Using a list - email passes incorrect config type. Using columns is invalid key.

3. Final Answer:

   tests: - dbt_utils.not_null: column_name: email - dbt_utils.unique: column_name: email -> Option D

4. Quick Check:

   column_name: [col] under test name [OK]

Hint: Use column_name: email for not_null and unique tests [OK]

Common Mistakes:

• Omitting colon and using scalar email
• Using list - email for single-column tests
• Using wrong key columns instead of column_name