def test_file_regression_workflow(testdir, monkeypatch):
"""
:type testdir: _pytest.pytester.TmpTestdir
:type monkeypatch: _pytest.monkeypatch.monkeypatch
"""
import sys
monkeypatch.setattr(sys, "get_data", lambda: "foo", raising=False)
source = """
import sys
def test_1(file_regression):
contents = sys.get_data()
file_regression.check(contents, extension='.test')
"""
def get_file_contents():
fn = Path(str(testdir.tmpdir)) / "test_file" / "test_1.test"
assert fn.is_file()
return fn.read_text()
check_regression_fixture_workflow(
testdir,
source,
data_getter=get_file_contents,
data_modifier=lambda: monkeypatch.setattr(
sys, "get_data", lambda: "foobar", raising=False),
expected_data_1="foo",
expected_data_2="foobar",
)
def test_usage_workflow(testdir, monkeypatch):
"""
:type testdir: _pytest.pytester.TmpTestdir
:type monkeypatch: _pytest.monkeypatch.monkeypatch
"""
import sys
import yaml
monkeypatch.setattr(sys,
"testing_get_data",
lambda: {
"contents": "Foo",
"value": 10
},
raising=False)
source = """
import sys
def test_1(data_regression):
contents = sys.testing_get_data()
data_regression.check(contents)
"""
def get_yaml_contents():
yaml_filename = testdir.tmpdir / "test_file" / "test_1.yml"
assert yaml_filename.check(file=1)
with yaml_filename.open() as f:
return yaml.safe_load(f)
check_regression_fixture_workflow(
testdir,
source=source,
data_getter=get_yaml_contents,
data_modifier=lambda: monkeypatch.setattr(
sys,
"testing_get_data",
lambda: {
"contents": "Bar",
"value": 20
},
raising=False,
),
expected_data_1={
"contents": "Foo",
"value": 10
},
expected_data_2={
"contents": "Bar",
"value": 20
},
)
def test_usage_workflow(testdir, monkeypatch):
"""
:type testdir: _pytest.pytester.TmpTestdir
:type monkeypatch: _pytest.monkeypatch.monkeypatch
"""
# stdlib
import sys
monkeypatch.setattr(sys,
"testing_get_data",
lambda: {"data": 1.1 * np.ones(50)},
raising=False)
source = """
import sys
def test_1(num_regression):
contents = sys.testing_get_data()
num_regression.check(contents)
"""
def get_csv_contents():
filename = testdir.tmpdir / "test_file" / "test_1.csv"
frame = pd.read_csv(str(filename))
return {"data": frame["data"].values}
def compare_arrays(obtained, expected):
assert (obtained["data"] == expected["data"]).all()
check_regression_fixture_workflow(
testdir,
source=source,
data_getter=get_csv_contents,
data_modifier=lambda: monkeypatch.setattr(sys,
"testing_get_data",
lambda:
{"data": 1.2 * np.ones(50)},
raising=False),
expected_data_1={"data": 1.1 * np.ones(50)},
expected_data_2={"data": 1.2 * np.ones(50)},
compare_fn=compare_arrays,
)
def test_image_regression_workflow(testdir, monkeypatch, datadir):
"""
:type testdir: _pytest.pytester.TmpTestdir
:type monkeypatch: _pytest.monkeypatch.monkeypatch
"""
# stdlib
import sys
# 3rd party
from PIL import Image # type: ignore
def get_image(color):
f = io.BytesIO()
img = Image.new("RGB", (100, 100), color)
img.save(f, "PNG")
return f.getvalue()
monkeypatch.setattr(sys, "get_image", partial(get_image, "white"), raising=False)
source = """
import sys
def test_1(image_regression):
contents = sys.get_image()
image_regression.check(contents)
"""
def get_file_contents():
fn = Path(str(testdir.tmpdir)) / "test_file" / "test_1.png"
assert fn.is_file()
return fn.read_bytes()
check_regression_fixture_workflow(
testdir,
source,
data_getter=get_file_contents,
data_modifier=lambda: monkeypatch.
setattr(sys, "get_image", partial(get_image, "black"), raising=False),
expected_data_1=partial(get_image, "white"),
expected_data_2=partial(get_image, "black"),
)
