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Description:

pytestschema 0.1.2

pytest-schema

👍 Validate return values against a schema-like object in testing
keleshev/schema is a library for validating Python data structures, such as
those obtained from config-files, forms, external services or
command-line parsing, converted from JSON/YAML (or something else) to Python data-types.
Install
pip install pytest-schema

Basic Example
Here is a quick example of using schema:
from pytest_schema import schema, exact_schema, like_schema

article_v1 = {
"id": int,
"title": str,
"completed": bool,
"engagement": {
"viewer": list,
"rating": float,
},
"metadata": dict
}

def test_article_v1_endpoint(test_client):
"""
Test calling v1 endpoint and validating the response
is in the correctly/expected format.
"""
response_v1 = test_client.get("/api/v1/article/1")
assert exact_schema(article_v1) == response_v1
# Same as:
# assert schema(article_v1) == response_v1

article_v2 = {
**article_v1,
"someNewField": int
}

def test_article_v2_endpoint(test_client):
"""
Test calling v2 endpoint is backwards compatible with v1
"""
response_v2 = test_client.get("/api/v2/article/1")

assert like_schema(article_v1) == response_v2

Full Example
Here is a more complex example of using schema:
import pytest
from pytest_schema import schema, And, Enum, Optional, Or, Regex, SchemaError

# single user schema
user = {
# id must be int
"id": int,
# name must be type str
"name": str,
# description must be type str or nullable
"description": Or(None, str),
# email valid str format
"email": Regex(r".*?@.*?\.[A-Za-z]{2,6}"),
# age converted to int then validated gt 18 lt 99 and must be type str
"age": And(int, lambda n: 18 <= n <= 99),
# gender key is optional but must be str
Optional("gender"): str,
# role of enum values
"role": Enum("user", "super-user", "admin"),
# list of ids ref friends
"friends": [ int ],
# nested dict to valid as address
"address": {
"street": str,
Optional("street2"): str,
"city": str,
"state": And(str, lambda s: len(s) == 2),
"zipcode": str,
}

}

# multiple users schema
users = [ user ]

def test_users_endpoint():
"""
Test calling a users endpoint and validating its
response of users info is correct format.
"""
response = [
# ✅ Valid
{
"id": 2,
"name": "Sue",
"description": "Sue, the admin",
"age": 28,
"email": "sue@gmail.com",
"gender": "female",
"role": "admin",
"friends": [5, 6],
"address": {
"street": "123 Washington Ave.",
"city": "New York",
"state": "NY",
"zipcode": "099012",
}
},
# ✅ Valid
{
"id": 5,
"name": "Sam",
"description": "Sam, the user",
"age": 42,
"email": "sam@aol.com",
"role": "user",
"friends": [2, 6, 7],
"address": {
"street": "5 Sunset St.",
"street2": "Apt # 55-b",
"city": "San Jose",
"state": "CA",
"zipcode": "054053",
}
},
]

assert schema(users) == response

def test_users_endpoint_INVALID():
"""
Test calling a users endpoint and validating its
response of users info is INVALID format.
"""
response = [
# ❌ Invalid
{
"id": "null",
"name": None,
"age": 0,
"email": "unknown@msn",
"role": "unknown",
"friends": None,
"address": "5 Sunset St., San Jose, CA, 054053",
},
]

# Option 1:
assert schema(users) != response

# Option 2:
with pytest.raises(SchemaError):
schema(users) == response

If data is valid, it will return the True.
If data is invalid, it will raise SchemaError exception.
Supported validations
See: keleshev/schema full documentation.