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Expyct

Partial matching of any Python object.
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Table of Contents

  1. Expyct
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact
  8. Acknowledgements

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.

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Bump the version in expyct/__version__.py following SemVer
  5. Push the Branch (git push origin feature/AmazingFeature)
  6. 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

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