Partial support library for structured testing
Project description
speclike
A helper library for pytest designed to make test code clearer and more structured.
The following is reproduced from __init__.py.
speclike
speclike is a pytest helper library designed to define tests in a more structured and expressive way.
It provides a declarative approach for building tests from two complementary perspectives:
- Individual test bodies, written as ordinary methods.
- Externally defined dispatchers and actors, representing scenario-driven or behavior-based tests.
The framework automatically generates executable pytest test functions (test_...) from decorated functions and classes.
🧩 Core Concepts
1. Spec and ExSpec Classes
Spec— the main base class for declarative test specifications.
It manages auto-generated tests and delegates execution throughdispatch()ordispatch_async().ExSpec— groups externally defined dispatchers (functions that control test flow outside of the class).
Both are implemented using metaclasses (_SpecMeta, _ExSpecMeta) that synthesize pytest-compatible test functions during class creation.
2. Case and Ex Decorators
Case— marks individual test bodies or actor functions (def _(...):) within aSpecclass.
It can attach pytest marks, parametrize data, or skip tests dynamically.Ex— marks dispatcher functions used inExSpecor top-level definitions.
Dispatchers define parameter structure usingPRM, and connect to actors via@case.ex(dispatcher).
3. PRM (Parameter Prefix Rules)
Defines how test parameters behave and interact between dispatcher and actor.
| Prefix | Kind | Behavior |
|---|---|---|
_ |
AO (Actor-Only) | Created by dispatcher, passed to actor (not parametrized) |
| (none) | AP (Actor-Parametrized) | Parametrized and passed to actor |
__ |
PO (Param-Only) | Parametrized but not passed to actor (used for assertions) |
Parameter ordering must follow AO → AP → PO.
PRM validates actor signatures, generates pytest parametrization, and bridges runtime values through _ParamsBridge.
4. Dispatcher and Actor
- Dispatcher: a function decorated with
@exthat defines test input combinations usingPRM. - Actor: a function named
_decorated with@case.ex(dispatcher)that performs the actual behavior under test. - The library automatically links each actor to its dispatcher and generates a
test_<dispatcher>method that executes the pair.
5. Test Generation Workflow
- The metaclass scans for decorated functions (
TargetKind). - Each test body or dispatcher/actor pair is converted into a pytest-visible
test_...function. - Signatures, parametrization, and pytest marks are copied to preserve readability and IDE support.
- For external specs (
ExSpec), tests are created dynamically based on defined dispatchers.
6. Highlights
- Strong signature validation for actors against their
PRMdefinitions. - Automatic propagation of
pytest.mark.parametrizeand other pytest marks. - Source location (
co_firstlineno) is preserved for accurate traceback references. - Supports both sync and async test execution paths.
Example
from speclike import Spec, PRM
# Example domain object
class Context:
def compute(self, x: int) -> int:
return x * 10
# Get decorators
case, ex = Spec.get_decorators()
# Dispatcher (external). Parameters are NOT taken as direct function args.
# Access AP/PO values via the bridge `p`, and call the actor via `p.act(...)`.
@ex.follows(
[(1, 10), (2, 20), (3, 30)], # (value, __expected)
ids=["x1", "x2", "x3"]
)
def check(p = PRM(_ctx=Context, value=int, __expected=int)):
ctx = Context() # AO: create here
result = p.act(_ctx=ctx, value=p.value) # call actor with AO/AP
assert result == p.__expected # PO: only used in dispatcher
# Spec class with actor method named "_"
class TestCompute(Spec):
@case.ex(check)
def _(self, _ctx: Context, value: int) -> int:
# Actor receives AO/AP only, in the declared order.
return _ctx.compute(value)
At runtime, this generates:
test_check— a parametrized pytest function executing the dispatcher.act_for_check— an internal bound actor function used by the dispatcher.
Installation
pip
pip install speclike
github
pip install git+https://github.com/minoru-jp/speclike.git
Status
This project is in very early development (alpha stage).
APIs and behavior may change without notice.
License
MIT License © 2025 minoru_jp
Project details
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