Schema validation basics in Postman - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to validate the response status code is 200.

Postman

pm.test('Status code is 200', function () { pm.response.to.have.status([1]); });

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

A404

B200

C500

D201

Attempts:

3 left

💡 Hint

Common Mistakes

Using 201 which means created, not OK.

Using 404 which means not found.

Using 500 which means server error.

The status code 200 means the request was successful. We check this with pm.response.to.have.status(200).

2fill in blank

medium

Complete the code to check if the JSON response has a property named 'userId'.

Postman

pm.test('Response has userId', function () { pm.expect(pm.response.json()).to.have.property([1]); });

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

A'name'

B'id'

C'userId'

D'email'

Attempts:

3 left

💡 Hint

Common Mistakes

Using property names that do not exist in the response.

Forgetting to put quotes around the property name.

We check if the JSON response has the property userId by passing its name as a string to have.property.

3fill in blank

hard

Fix the error in the code to correctly validate the response JSON schema.

Postman

const schema = [1];
pm.test('Schema is valid', function () { pm.response.to.have.jsonSchema(schema); });

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

Anull

B'{ type: object, properties: { id: { type: number } }, required: [id] }'

C42

D{ type: 'object', properties: { id: { type: 'number' } }, required: ['id'] }

Attempts:

3 left

💡 Hint

Common Mistakes

Using a string instead of an object for the schema.

Using null or numbers instead of a schema object.

The schema must be a valid JavaScript object describing the JSON structure. Option D is correct syntax.

4fill in blank

hard

Fill both blanks to check that the response JSON has a 'name' property of type string.

Postman

const schema = { type: 'object', properties: { name: { type: [1] } }, required: [[2]] };
pm.test('Name property is string', function () { pm.response.to.have.jsonSchema(schema); });

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

A'string'

B'name'

C'number'

D'id'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'number' instead of 'string' for the type.

Forgetting to put quotes around the required property name.

The property 'name' should be of type 'string' and must be required, so the required array includes 'name'.

5fill in blank

hard

Fill all three blanks to validate a response JSON with 'id' as number, 'email' as string, and both required.

Postman

const schema = {
  type: 'object',
  properties: {
    id: { type: [1] },
    email: { type: [2] }
  },
  required: [[3]]
};
pm.test('Validate id and email', function () {
  pm.response.to.have.jsonSchema(schema);
});

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

A'number'

B'string'

C'id', 'email'

D'email'

Attempts:

3 left

💡 Hint

Common Mistakes

Putting the required properties without quotes or as separate strings.

Mixing up the types for id and email.

The 'id' property type is 'number', 'email' is 'string', and both are required, so the required array includes both 'id' and 'email' as strings.

Practice

1. What is the main purpose of schema validation in Postman?

easy

A. To check if the server is online

B. To measure the response time of an API

C. To verify the API endpoint URL is correct

D. To check if the response data matches the expected structure and data types

Solution

1. Step 1: Understand schema validation concept

   Schema validation ensures the response data structure and types match what is expected.

2. Step 2: Compare options with schema validation purpose

   Only To check if the response data matches the expected structure and data types describes checking data structure and types, which is the core of schema validation.

3. Final Answer:

   To check if the response data matches the expected structure and data types -> Option D

4. Quick Check:

   Schema validation = check structure and types [OK]

Hint: Schema validation checks data shape and types [OK]

Common Mistakes:

• Confusing schema validation with performance testing
• Thinking schema validation checks URL correctness
• Assuming schema validation checks server status

2. Which Postman assertion syntax correctly validates a JSON response against a schema stored in schema variable?

easy

A. pm.response.to.have.jsonSchema(schema);

B. pm.response.to.have.schemaJson(schema);

C. pm.response.has.jsonSchema(schema);

D. pm.response.to.have.jsonSchemaCheck(schema);

Solution

1. Step 1: Recall correct Postman syntax for schema validation

   The correct method is pm.response.to.have.jsonSchema(schema); to validate JSON schema.

2. Step 2: Check each option for syntax correctness

   Only pm.response.to.have.jsonSchema(schema); matches the exact Postman syntax; others are invalid method names.

3. Final Answer:

   pm.response.to.have.jsonSchema(schema); -> Option A

4. Quick Check:

   Correct method = jsonSchema() [OK]

Hint: Use pm.response.to.have.jsonSchema(schema) exactly [OK]

Common Mistakes:

• Using incorrect method names like jsonSchemaCheck
• Mixing up method chaining order
• Omitting 'to.have' in the assertion

3. Given this schema snippet in Postman test script:

{
  "type": "object",
  "properties": {
    "id": {"type": "integer"},
    "name": {"type": "string"}
  },
  "required": ["id", "name"]
}

What will happen if the API response is {"id": 10, "name": "Alice"}?

medium

A. The schema validation will fail because 'id' is not a string

B. The schema validation will pass successfully

C. The schema validation will fail because 'name' is missing

D. The schema validation will fail due to missing required fields

Solution

1. Step 1: Analyze the schema requirements

   The schema expects an object with 'id' as integer and 'name' as string, both required.

2. Step 2: Compare the response with schema

   The response has 'id' as 10 (integer) and 'name' as "Alice" (string), satisfying all requirements.

3. Final Answer:

   The schema validation will pass successfully -> Option B

4. Quick Check:

   Response matches schema types and required fields [OK]

Hint: Match response types exactly to schema required fields [OK]

Common Mistakes:

• Confusing integer with string type
• Assuming missing fields when all are present
• Ignoring required fields in schema

4. You wrote this Postman test to validate a response schema:

const schema = {
  type: "object",
  properties: {
    age: { type: "integer" }
  },
  required: ["age"]
};
pm.test("Schema is valid");
pm.response.to.have.jsonSchema(schema);

But the test always fails even when the response has an integer age. What is the likely error?

medium

A. The assertion should be inside pm.test callback, but the code uses pm.test incorrectly

B. The test function is named pm.test but should be pm.response.test

C. Using pm.test instead of pm.response.to.have.jsonSchema

D. The assertion is inside pm.test but the function name is misspelled as pm.test

Solution

1. Step 1: Check the test function usage

   The correct syntax is pm.test("name", () => { assertion }); but the code calls pm.test("Schema is valid"); without the required callback function.

2. Step 2: Check assertion placement

   The assertion pm.response.to.have.jsonSchema(schema); is outside the pm.test callback and will not be properly associated with the test.

3. Final Answer:

   The assertion should be inside pm.test callback, but the code uses pm.test incorrectly -> Option A

4. Quick Check:

   pm.test requires callback containing assertion [OK]

Hint: Always wrap assertions in pm.test("name", () => { ... }) [OK]

Common Mistakes:

• Calling assertions directly without pm.test wrapper
• Misspelling pm.test or using wrong test function
• Not wrapping assertion inside pm.test callback

5. You want to validate an API response that returns a list of user objects, each with id (integer) and optional email (string). Which JSON schema correctly validates this response array?

hard

A. {
"type": "array",
"properties": {
"id": {"type": "integer"},
"email": {"type": "string"}
},
"required": ["id"]
}

B. {
"type": "object",
"properties": {
"id": {"type": "integer"},
"email": {"type": "string"}
},
"required": ["id"]
}

C. {
"type": "array",
"items": {
"type": "object",
"properties": {
"id": {"type": "integer"},
"email": {"type": "string"}
},
"required": ["id"]
}
}

D. {
"type": "array",
"items": {
"type": "object",
"properties": {
"id": {"type": "string"},
"email": {"type": "string"}
},
"required": ["id", "email"]
}
}

Solution

1. Step 1: Identify the response type

   The response is an array of user objects, so schema type must be "array" with "items" describing each object.

2. Step 2: Check object properties and requirements

   Each object must have "id" as integer (required) and "email" as optional string (not required).

3. Step 3: Validate options against requirements

   { "type": "array", "items": { "type": "object", "properties": { "id": {"type": "integer"}, "email": {"type": "string"} }, "required": ["id"] } } correctly defines an array with items as objects, "id" integer required, "email" string optional. Others either define object instead of array, wrong types, or require "email".

4. Final Answer:

   { "type": "array", "items": { "type": "object", "properties": { "id": {"type": "integer"}, "email": {"type": "string"} }, "required": ["id"] } } -> Option C

5. Quick Check:

   Array of objects with required id integer and optional email string [OK]

Hint: Use "type": "array" with "items" for object schema [OK]

Common Mistakes:

• Defining response as object instead of array
• Marking optional fields as required
• Using wrong data types for properties