pytest-dataset 0.3.2

Plugin for loading different datasets for pytest by prefix from json or yaml files

The dataset plugin for pytest provides the dataset, dataset_case_data and dataset_copy fixtures which allow test functions to easily access resources in data directories. It was inspired by the pytest-datadir-ng plugin . The dataset return data from files in json or yaml formats. The main function is usage parameter --dataset-prefix in options or dataset_prefix in ini file.

The files are searched in directories in order:

• {dataset_prefix}_{name}.yaml

• {dataset_prefix}_{name}.json

• {name}.yaml

• {name}.json

This plugin provides three fixtures:

• The dataset fixture allows test functions and methods to access resources in so-called “data directories”.

• The dataset_copy fixture is similar to the dataset fixture, but it copies the requested resources to a temporary directory first so that test functions or methods can modify their resources on-disk without affecting other test functions and methods.

• The dataset_case_data fixture return dataset named by the test function name.

Installation

Just do:

pip install pytest-dataset

The dataset fixture

The “dataset” fixture allows test functions and methods to access resources in so-called “data directories”.

The fixture behaves like a dictionary. Currently, only retrieving items using the d[key] syntax is supported. Things like iterators, len(d) etc. are not. The pytest is called with option --dataset-prefix testing

def test_func(dataset):
    data_path = dataset["test_data"]

    # ...

The file test_two.py contains the following class:

class TestClass(object):
    def test_method(self, dataset):
        strings_path = dataset["test_data_two"]

        # ...

When the test_func() function asks for the test_data resource, the following directories are searched for a file in this order.

Files:

• testing_test_data.yaml

• testing_test_data.json

• test_data.yaml

• test_data.json

Directories:

• tests/test_one/test_func/

• tests/test_one/

• tests/data/test_one/test_func/

• tests/data/test_one/

• tests/data/

The path to the first existing file is returned as data. In this case, the returned data would be from file tests/test_one/test_func/testing_test_data.yaml.

When the test_method() method asks for the test_data_two resource, the following directories are searched for a file with the name in this order:

Files:

• testing_test_data_two.yaml

• testing_test_data_two.json

• test_data_two.yaml

• test_data_two.json

Directories:

• tests/test_two/TestClass/test_method/

• tests/test_two/TestClass/

• tests/test_two/

• tests/data/test_two/TestClass/test_method/

• tests/data/test_two/TestClass/

• tests/data/test_two/

• tests/data/

Here, this would return the data from tests/test_two/TestClass/test_method/testing_test_data_two.yaml.

As you can see, the searched directory hierarchy is slighly different if a method instead of a function asks for a resource. This allows you to load different resources based on the name of the test class, if you wish.

Finally, if a test function or test method would ask for a resource named global, then the resulting file would be tests/data/{filename} since no other directory in the searched directory hierarchy contains the file. In other words, the tests/data/ directory is the place for global (or fallback) resources.

If a resource cannot be found in any of the searched directories, a KeyError is raised.

The dataset_session fixture

Similar to “dataset” only used for scope “session”. The path, where are searched the dataset files are reduced to only {rootdir}/data/ .

The dataset_package fixture

Similar to “dataset” only used for scope “package”. The path, where are searched the dataset files are reduced to only {rootdir}/data/ .

The dataset_module fixture

Similar to “dataset” only used for scope “module”. The path, where are searched the dataset files are reduced to only possible for “module” scope.

The dataset_class fixture

Similar to “dataset” only used for scope “class”. The path, where are searched the dataset files are reduced to only possible for “class” scope.

The dataset_copy fixture

The “dataset_copy” fixture is similar to the dataset fixture, but copies the requested resources to a temporary directory first so that test functions or methods can modify their resources on-disk without affecting other test functions and methods.

Each test function or method gets its own temporary directory and thus its own fresh copies of the resources it requests.

The dataset_case_data fixture

The “dataset_case_data” fixture allows test functions and methods to access resources used the function name as seareched dataset name.

class TestClass(object):
    def test_method(self, dataset_case_data):

        # ...

When the test_method() method is called than dataset_case_data directly contain the data searched in order:

Files:

• testing_test_method.yaml

• testing_test_method.json

• test_method.yaml

• test_method.json

Directories:

• tests/test_two/TestClass/test_method/

• tests/test_two/TestClass/

• tests/test_two/

• tests/data/test_two/TestClass/test_method/

• tests/data/test_two/TestClass/

• tests/data/test_two/

• tests/data/

Here, this would return the data from tests/test_two/TestClass/test_method/testing_test_method.yaml.