Partial matching of any object
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Expyct
Partial matching of any Python object.
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Expyct
Partial matching of any Python object.
import expyct as exp
def test_my_function():
result = my_function()
assert result == exp.Float(optional=True, close_to=0.076, error=0.01)
Using Expyct is a good idea when you need to assert something in a test case but there is some non-determinism.
For example, rounding errors prevent you from comparing a float
exactly. Or a timestamp is created on-the-fly, and therefore changes every test run.
In these cases, you need to be able to set specific constraints on the expected value. That is what Expyct is for!
The constraints can be provided as constructor arguments. For example n == Number(min=3, max=5)
is only true when n
is between 3 and 5.
Some other examples of classes are Float
, String
, Any
and DateTime
. As you can see, they closely match the built-in Python types.
The library also comes with many commonly used data validators like ANY_UUID
which matches any UUID string. And TODAY
which matches any datetime occurring on the current day.
Checking nested data structures is easy as well.
See Usage examples
Getting Started
Prerequisites
Supported and tested for:
- Python 3.6
- Python 3.7
- Python 3.8
- Python 3.9
Installation
pip install expyct
Or install using any Python package manager like conda, pipenv or poetry.
Usage
See below examples of how to use Expyct with pytest.
Simple example:
import expyct as exp
from myclass import MyClass
def test_my_function():
result = my_function()
assert result == exp.AnyValue(instance_of=MyClass, vars={"property": "value"})
More complicated nested example:
import expyct as exp
from datetime import datetime
def test_my_function():
result = my_function()
assert result == {
"first_name": exp.String(regex="(mary)|(peter)", ignore_case=True),
"last_name": "Johnson",
"signup_date": exp.DateTime(after=datetime(2020, 1, 2), before=datetime(2020, 3, 5)),
"details": {
"number": exp.Int(min=2),
"amount": exp.Float(close_to=2.3, error=0.001),
"purchases": exp.List(exp.Dict(keys={"id", "product", "category"}), non_empty=True),
},
"time_of_purchase": exp.OneOf([exp.TODAY, exp.THIS_HOUR]),
"type": exp.AnyType(subclass_of=str),
"item_ids": exp.Set(subset_of=[1, 2, 3]),
"metadata": exp.Dict(keys_any=exp.Collection(superset_of=["a", "b"])),
"context": exp.ANY,
}
Roadmap
See the open issues for a list of proposed features (and known issues).
Contributing
Any contributions you make are greatly appreciated.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature
) - Commit your Changes (
git commit -m 'Add some AmazingFeature'
) - Bump the version in
expyct/__version__.py
following SemVer - Push the Branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
Before starting to contribute to Expyct, please install pre-commit to make sure your changes get checked for style and standards before committing them to repository:
$ pre-commit install
License
Distributed under the MIT License. See LICENSE
for more information.
Contact
Please file an issue on Github.
Acknowledgements
Project details
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