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Python OpenSearch Mock for test purposes

Project description

Openmock

Mock/fake of opensearch library, allows you to mock opensearch-py

Fork of Python Elasticsearch(TM) Mock. Sometimes the developers who work with elasticsearch (TM), don't really have any input in choice of host and need to get work done.

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Installation

pip install openmock

Usage

To use Openmock, decorate your test method with @openmock decorator:

from unittest import TestCase

from openmock import openmock


class TestClass(TestCase):

    @openmock
    def test_should_return_something_from_opensearch(self):
        self.assertIsNotNone(some_function_that_uses_opensearch())

Custom Behaviours

You can also force the behaviour of the OpenSearch instance by importing the openmock.behaviour module:

from unittest import TestCase

from openmock import behaviour


class TestClass(TestCase):

    ...

    def test_should_return_internal_server_error_when_simulate_server_error_is_true(self):
        behaviour.server_failure.enable()
        ...
        behaviour.server_failure.disable()

You can also disable all behaviours by calling behaviour.disable_all() (Consider put this in your def tearDown(self) method)

Available Behaviours

  • server_failure: Will make all calls to OpenSearch returns the following error message:
    {
        'status_code': 500,
        'error': 'Internal Server Error'
    }
    

Code example

Let's say you have a prod code snippet like this one:

import opensearchpy

class FooService:

    def __init__(self):
        self.es = opensearchpy.OpenSearch(hosts=[{'host': 'localhost', 'port': 9200}])

    def create(self, index, body):
        es_object = self.es.index(index, body)
        return es_object.get('_id')

    def read(self, index, id):
        es_object = self.es.get(index, id)
        return es_object.get('_source')

Then you should be able to test this class by mocking OpenSearch using the following test class:

from unittest import TestCase
from openmock import openmock
from foo.bar import FooService

class FooServiceTest(TestCase):

    @openmock
    def should_create_and_read_object(self):
        # Variables used to test
        index = 'test-index'
        expected_document = {
            'foo': 'bar'
        }

        # Instantiate service
        service = FooService()

        # Index document on OpenSearch
        id = service.create(index, expected_document)
        self.assertIsNotNone(id)

        # Retrieve document from OpenSearch
        document = service.read(index, id)
        self.assertEquals(expected_document, document)

Admin tools

Openmock ships three interactive admin tools for exploring fake state outside of tests.

Streamlit web UI (requires pip install openmock[web]):

openmock

Tkinter desktop GUI (no extra dependencies — uses Python's built-in tkinter):

openmock gui

FastAPI REST Bridge (requires pip install openmock[rest]):

openmock serve

These tools open a six-tab interface or an HTTP facade covering indices, search sandbox, cluster stats, CAT output, fake security (users/roles), and ingest pipelines. State in these tools is separate from your test processes.

Notes:

  • The mocked search method evaluates the query against indexed documents and returns matching results, not all documents. Use match_all if you want everything.
  • The mocked suggest method returns the exactly suggestions dictionary passed as body serialized in OpenSearch.suggest response. Attention: If the term is an int, the suggestion will be python term + 1. If not, the suggestion will be formatted as python {0}_suggestion.format(term) . Example:
    • Suggestion Body:
    suggestion_body = {
        'suggestion-string': {
            'text': 'test_text',
            'term': {
                'field': 'string'
            }
        },
        'suggestion-id': {
            'text': 1234567,
            'term': {
                'field': 'id'
            }
        }
    }
    
    • Suggestion Response:
    {
        'suggestion-string': [
            {
                'text': 'test_text',
                'length': 1,
                'options': [
                    {
                        'text': 'test_text_suggestion',
                        'freq': 1,
                        'score': 1.0
                    }
                ],
                'offset': 0
            }
        ],
        'suggestion-id': [
            {
                'text': 1234567,
                'length': 1,
                'options': [
                    {
                        'text': 1234568,
                        'freq': 1,
                        'score': 1.0
                    }
                ],
                'offset': 0
            }
        ],
    }
    

Testing

Preferred for testing one version of python.

pytest test

Run the same pytest suite against a disposable Docker OpenSearch instead of the in-memory fake:

uv run python scripts/opensearch_docker.py test

If you want to manage the container yourself, the backend seam is driven by OPENMOCK_TEST_BACKEND=real and OPENMOCK_REAL_OPENSEARCH_URL=http://localhost:9200. The default remains the in-memory mock backend.

The collected tests are split into two marker groups:

  • parity for live-backend parity coverage,
  • mock_backend for tests that are specific to the in-memory fake.

Examples:

uv run python -m pytest tests -m parity
uv run python -m pytest tests -m mock_backend

Won't catch pytest tests.

python -m unittest

We are trying to support a full matrix of openmock versions and python versions 3.9+. This is slow.

tox

Changelog

See CHANGELOG.md

License

MIT with normalize_host.py being Apache 2 from Elasticsearch.

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