Monkey patching changes what an object, class, module, or name does while a Python program is running, without changing its original source definition. It is a broad technique—not a Python keyword or a single library—and its safest everyday use is a temporary, tightly scoped replacement in a test. The key is to patch the name the code actually looks up, then restore it as soon as the test no longer needs the change.
What is monkey patching in Python?
A monkey patch adds, replaces, or removes behavior at runtime. For example, code can assign a new function to a class attribute or replace a module-level name with a test double. The original source file remains unchanged, but code that uses the patched object may behave differently for as long as the replacement is in effect.
The term describes a technique, not one particular tool. Pytest’s monkeypatch fixture and the standard-library unittest.mock.patch utility can both make temporary changes for tests. Monkey patching can also refer more broadly to runtime changes outside tests; those changes may persist for the life of a process or application if nothing restores the original behavior.
When should you use monkey patching?
Use a temporary patch when a test needs to control a dependency or environment that would otherwise be unpredictable, slow, unavailable, or costly. For example, you can replace an API call so a unit test does not contact a real service, provide a known environment variable, change a mapping, or control the current working directory.
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A mock is especially useful when the test must also check how the code interacted with a replacement—for example, whether it was called with particular arguments. If you control the code, passing dependencies in explicitly is usually a clearer long-term design than relying on global patches.
Patch the name the code looks up
Python names are bindings: several names can refer to the same original object. If a module imports a function directly, its local name is separate from the function’s name in the original module. Replacing the original module attribute later may not change what the importing module calls. Patch the lookup site used by the code under test.
Example: patch a directly imported function
Suppose report.py contains from os import getcwd and later calls getcwd(). The code looks up report.getcwd, so patch that name—not os.getcwd.
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# report.py
from os import getcwd
def current_directory():
return getcwd()
# test_report.py
import report
def test_current_directory(monkeypatch):
monkeypatch.setattr(report, "getcwd", lambda: "/tmp/test")
assert report.current_directory() == "/tmp/test"
Pytest restores the attribute when the test finishes. This example assumes the test file can import report and that pytest is installed and configured for the project.
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Use pytest’s fixture when the function reads the environment at call time. This example gives the test a known value and lets pytest restore the prior environment afterward.
# settings.py
import os
def api_host():
return os.environ.get("API_HOST", "https://api.example.test")
# test_settings.py
import settings
def test_api_host_from_environment(monkeypatch):
monkeypatch.setenv("API_HOST", "https://test.example.test")
assert settings.api_host() == "https://test.example.test"
Choose pytest monkeypatch or unittest.mock.patch
Both approaches can temporarily change what code sees and restore it after a bounded scope. Choose based on the operation and whether you need interaction assertions.
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| Need | Useful choice | Why |
|---|---|---|
| Change an attribute, mapping, environment variable, import path, or current directory in a pytest test | monkeypatch fixture |
Provides methods for common changes and undoes them at test teardown. |
| Replace a target with a mock and assert calls or arguments | unittest.mock.patch |
It can create a mock replacement that records how it was used. |
| Contain an unusual or risky change in a small block | monkeypatch.context() or patch() as a context manager |
Both limit the change to a narrower scope and restore it when that scope ends. |
For example, a unittest.mock.patch context manager can replace the lookup site and let the test inspect the mock afterward:
from unittest.mock import patch
import report
def test_current_directory_with_mock():
with patch("report.getcwd", return_value="/tmp/test") as mock_getcwd:
assert report.current_directory() == "/tmp/test"
mock_getcwd.assert_called_once_with()
For either tool, patch where the system under test looks up the name. When a mock’s default flexibility could hide a changed interface, use spec or autospec where suitable, and keep integration tests for the connections between components.
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- Keep the scope small. Prefer a test fixture or context manager over a patch that remains active for an entire process. Pytest’s
monkeypatch.context()can further narrow a change within a test. - Let the tool clean up. Pytest undoes fixture changes at teardown;
unittest.mock.patchrestores the target when its decorator or context ends. Avoid manual restoration paths that can be skipped after an error. - Avoid broad patches to builtins. Replacing names such as
openorcompilecan interfere with pytest or libraries the test runner uses. If a patch is unavoidable, constrain it to the smallest block possible. - Prefer explicit dependencies in code you own. Passing a client, function, or other dependency into the code makes the dependency visible and easier to substitute deliberately.
- Do not mistake a passing unit test for compatibility. A permissive mock can continue to accept calls after the real interface changes. Use a suitable specification and integration coverage for the real boundary.
Common problems and fixes
The real function still runs
Cause: The patch changed a different name from the one the tested code uses, often because the code imported a function directly. Fix: Identify the module and attribute used at the call site, then patch that binding.
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A patch leaks into another test
Cause: A manual assignment or patch was not restored, or its scope is broader than intended. Fix: Use the pytest fixture, monkeypatch.context(), or a patch() context manager so cleanup happens at scope exit.
The test runner breaks after replacing a builtin
Cause: Pytest or a dependency uses the same builtin. Fix: Avoid the builtin patch if possible; otherwise use a narrowly scoped context and restore it immediately.
The test passes despite an interface change
Cause: The replacement accepts calls the real dependency would reject. Fix: Use spec or autospec where appropriate, and test integration with the actual component separately.
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Frequently Asked Questions
Is monkey patching a Python keyword?
No. It is a general term for changing behavior at runtime, not a Python keyword.
Can monkey patching be used outside tests?
Yes. The term also covers runtime changes in application code, though persistent patches can make behavior harder to trace and maintain.
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Does monkeypatching always mean using pytest?
No. Pytest’s fixture is one tool for temporary changes; monkey patching is the broader technique.
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