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async def test_replace_option_prompt_with_invalid_index() -> None:
"""Attempting to replace the prompt of an option index that doesn't exist should raise an exception."""
async with OptionListApp().run_test() as pilot:
with pytest.raises(OptionDoesNotExist):
pilot.app.query_one(OptionList).replace_option_prompt_at_index(23, "new-prompt") | Attempting to replace the prompt of an option index that doesn't exist should raise an exception. | test_replace_option_prompt_with_invalid_index | python | Textualize/textual | tests/option_list/test_option_prompt_replacement.py | https://github.com/Textualize/textual/blob/master/tests/option_list/test_option_prompt_replacement.py | MIT |
async def test_replace_option_prompt_with_valid_id() -> None:
"""It should be possible to replace the prompt of an option ID that does exist."""
async with OptionListApp().run_test() as pilot:
option_list = pilot.app.query_one(OptionList)
option_list.replace_option_prompt("0", "new-prompt")
assert option_list.get_option("0").prompt == "new-prompt" | It should be possible to replace the prompt of an option ID that does exist. | test_replace_option_prompt_with_valid_id | python | Textualize/textual | tests/option_list/test_option_prompt_replacement.py | https://github.com/Textualize/textual/blob/master/tests/option_list/test_option_prompt_replacement.py | MIT |
async def test_replace_option_prompt_with_valid_index() -> None:
"""It should be possible to replace the prompt of an option index that does exist."""
async with OptionListApp().run_test() as pilot:
option_list = pilot.app.query_one(OptionList).replace_option_prompt_at_index(1, "new-prompt")
assert option_list.get_option_at_index(1).prompt == "new-prompt" | It should be possible to replace the prompt of an option index that does exist. | test_replace_option_prompt_with_valid_index | python | Textualize/textual | tests/option_list/test_option_prompt_replacement.py | https://github.com/Textualize/textual/blob/master/tests/option_list/test_option_prompt_replacement.py | MIT |
async def test_replace_single_line_option_prompt_with_multiple() -> None:
"""It should be possible to replace single line prompt with multiple lines """
new_prompt = "new-prompt\nsecond line"
async with OptionListApp().run_test() as pilot:
option_list = pilot.app.query_one(OptionList)
option_list.replace_option_prompt("0", new_prompt)
assert option_list.get_option("0").prompt == new_prompt | It should be possible to replace single line prompt with multiple lines | test_replace_single_line_option_prompt_with_multiple | python | Textualize/textual | tests/option_list/test_option_prompt_replacement.py | https://github.com/Textualize/textual/blob/master/tests/option_list/test_option_prompt_replacement.py | MIT |
async def test_replace_multiple_line_option_prompt_with_single() -> None:
"""It should be possible to replace multiple line prompt with a single line"""
new_prompt = "new-prompt"
async with OptionListApp().run_test() as pilot:
option_list = pilot.app.query_one(OptionList)
option_list.replace_option_prompt("0", new_prompt)
assert option_list.get_option("0").prompt == new_prompt | It should be possible to replace multiple line prompt with a single line | test_replace_multiple_line_option_prompt_with_single | python | Textualize/textual | tests/option_list/test_option_prompt_replacement.py | https://github.com/Textualize/textual/blob/master/tests/option_list/test_option_prompt_replacement.py | MIT |
async def test_replace_multiple_line_option_prompt_with_multiple() -> None:
"""It should be possible to replace multiple line prompt with multiple lines"""
new_prompt = "new-prompt\nsecond line"
async with OptionListApp().run_test() as pilot:
option_list = pilot.app.query_one(OptionList)
option_list.replace_option_prompt_at_index(1, new_prompt)
assert option_list.get_option_at_index(1).prompt == new_prompt | It should be possible to replace multiple line prompt with multiple lines | test_replace_multiple_line_option_prompt_with_multiple | python | Textualize/textual | tests/option_list/test_option_prompt_replacement.py | https://github.com/Textualize/textual/blob/master/tests/option_list/test_option_prompt_replacement.py | MIT |
async def test_checkbox_initial_state() -> None:
"""The initial states of the check boxes should be as we specified."""
async with CheckboxApp().run_test() as pilot:
assert [box.value for box in pilot.app.query(Checkbox)] == [False, False, True]
assert [box.has_class("-on") for box in pilot.app.query(Checkbox)] == [
False,
False,
True,
]
assert pilot.app.events_received == [] | The initial states of the check boxes should be as we specified. | test_checkbox_initial_state | python | Textualize/textual | tests/toggles/test_checkbox.py | https://github.com/Textualize/textual/blob/master/tests/toggles/test_checkbox.py | MIT |
async def test_checkbox_toggle() -> None:
"""Test the status of the check boxes after they've been toggled."""
async with CheckboxApp().run_test() as pilot:
for box in pilot.app.query(Checkbox):
box.toggle()
assert [box.value for box in pilot.app.query(Checkbox)] == [True, True, False]
assert [box.has_class("-on") for box in pilot.app.query(Checkbox)] == [
True,
True,
False,
]
await pilot.pause()
assert pilot.app.events_received == [
("cb1", True, True),
("cb2", True, True),
("cb3", False, True),
] | Test the status of the check boxes after they've been toggled. | test_checkbox_toggle | python | Textualize/textual | tests/toggles/test_checkbox.py | https://github.com/Textualize/textual/blob/master/tests/toggles/test_checkbox.py | MIT |
async def test_change_labels() -> None:
"""It should be possible to change the labels of toggle buttons."""
async with LabelChangeApp().run_test() as pilot:
assert pilot.app.query_one(Checkbox).label == Text("Before")
assert pilot.app.query_one("Screen > RadioButton", RadioButton).label == Text(
"Before"
)
assert pilot.app.query_one("RadioSet > RadioButton", RadioButton).label == Text(
"Before"
)
pilot.app.query_one(Checkbox).label = "After"
pilot.app.query_one("Screen > RadioButton", RadioButton).label = "After"
pilot.app.query_one("RadioSet > RadioButton", RadioButton).label = "After"
await pilot.pause()
assert pilot.app.query_one(Checkbox).label == Text("After")
assert pilot.app.query_one("Screen > RadioButton", RadioButton).label == Text(
"After"
)
assert pilot.app.query_one("RadioSet > RadioButton", RadioButton).label == Text(
"After"
) | It should be possible to change the labels of toggle buttons. | test_change_labels | python | Textualize/textual | tests/toggles/test_labels.py | https://github.com/Textualize/textual/blob/master/tests/toggles/test_labels.py | MIT |
async def test_radio_sets_initial_state():
"""The initial states of the radio sets should be as we specified."""
async with RadioSetApp().run_test() as pilot:
assert pilot.app.query_one("#from_buttons", RadioSet).pressed_index == 2
assert pilot.app.query_one("#from_buttons", RadioSet).pressed_button is not None
assert pilot.app.query_one("#from_strings", RadioSet).pressed_index == -1
assert pilot.app.query_one("#from_strings", RadioSet).pressed_button is None
assert pilot.app.events_received == [] | The initial states of the radio sets should be as we specified. | test_radio_sets_initial_state | python | Textualize/textual | tests/toggles/test_radioset.py | https://github.com/Textualize/textual/blob/master/tests/toggles/test_radioset.py | MIT |
async def test_click_sets_focus():
"""Clicking within a radio set should set focus."""
async with RadioSetApp().run_test() as pilot:
pilot.app.set_focus(None)
assert pilot.app.screen.focused is None
await pilot.click("#clickme")
assert pilot.app.screen.focused == pilot.app.query_one("#from_buttons") | Clicking within a radio set should set focus. | test_click_sets_focus | python | Textualize/textual | tests/toggles/test_radioset.py | https://github.com/Textualize/textual/blob/master/tests/toggles/test_radioset.py | MIT |
async def test_radio_sets_toggle():
"""Test the status of the radio sets after they've been toggled."""
async with RadioSetApp().run_test() as pilot:
pilot.app.query_one("#from_buttons", RadioSet)._nodes[0].toggle()
pilot.app.query_one("#from_strings", RadioSet)._nodes[2].toggle()
await pilot.pause()
assert pilot.app.query_one("#from_buttons", RadioSet).pressed_index == 0
assert pilot.app.query_one("#from_buttons", RadioSet).pressed_button is not None
assert pilot.app.query_one("#from_strings", RadioSet).pressed_index == 2
assert pilot.app.query_one("#from_strings", RadioSet).pressed_button is not None
assert pilot.app.events_received == [
("from_buttons", 0, [True, False, False]),
("from_strings", 2, [False, False, True]),
] | Test the status of the radio sets after they've been toggled. | test_radio_sets_toggle | python | Textualize/textual | tests/toggles/test_radioset.py | https://github.com/Textualize/textual/blob/master/tests/toggles/test_radioset.py | MIT |
async def test_radioset_same_button_mash():
"""Mashing the same button should have no effect."""
async with RadioSetApp().run_test() as pilot:
assert pilot.app.query_one("#from_buttons", RadioSet).pressed_index == 2
pilot.app.query_one("#from_buttons", RadioSet)._nodes[2].toggle()
assert pilot.app.query_one("#from_buttons", RadioSet).pressed_index == 2
assert pilot.app.events_received == [] | Mashing the same button should have no effect. | test_radioset_same_button_mash | python | Textualize/textual | tests/toggles/test_radioset.py | https://github.com/Textualize/textual/blob/master/tests/toggles/test_radioset.py | MIT |
async def test_radioset_inner_navigation():
"""Using the cursor keys should navigate between buttons in a set."""
async with RadioSetApp().run_test() as pilot:
for key, landing in (
("down", 1),
("up", 0),
("right", 1),
("left", 0),
("up", 2),
("down", 0),
):
await pilot.press(key, "enter")
assert (
pilot.app.query_one("#from_buttons", RadioSet).pressed_button
== pilot.app.query_one("#from_buttons").children[landing]
)
async with RadioSetApp().run_test() as pilot:
assert pilot.app.screen.focused is pilot.app.screen.query_one("#from_buttons")
await pilot.press("tab")
assert pilot.app.screen.focused is pilot.app.screen.query_one("#from_strings")
assert pilot.app.query_one("#from_strings", RadioSet)._selected == 0
await pilot.press("down")
assert pilot.app.query_one("#from_strings", RadioSet)._selected == 1 | Using the cursor keys should navigate between buttons in a set. | test_radioset_inner_navigation | python | Textualize/textual | tests/toggles/test_radioset.py | https://github.com/Textualize/textual/blob/master/tests/toggles/test_radioset.py | MIT |
async def test_radioset_breakout_navigation():
"""Shift/Tabbing while in a radioset should move to the previous/next focsuable after the set itself."""
async with RadioSetApp().run_test() as pilot:
assert pilot.app.screen.focused is pilot.app.query_one("#from_buttons")
await pilot.press("tab")
assert pilot.app.screen.focused is pilot.app.query_one("#from_strings")
await pilot.press("shift+tab")
assert pilot.app.screen.focused is pilot.app.query_one("#from_buttons") | Shift/Tabbing while in a radioset should move to the previous/next focsuable after the set itself. | test_radioset_breakout_navigation | python | Textualize/textual | tests/toggles/test_radioset.py | https://github.com/Textualize/textual/blob/master/tests/toggles/test_radioset.py | MIT |
async def test_there_can_only_be_one():
"""Adding multiple 'on' buttons should result in only one on."""
async with BadRadioSetApp().run_test() as pilot:
assert len(pilot.app.query("RadioButton.-on")) == 1
assert pilot.app.query_one(RadioSet).pressed_index == 0 | Adding multiple 'on' buttons should result in only one on. | test_there_can_only_be_one | python | Textualize/textual | tests/toggles/test_radioset.py | https://github.com/Textualize/textual/blob/master/tests/toggles/test_radioset.py | MIT |
async def test_keyboard_navigation_with_disabled_buttons():
"""Regression test for https://github.com/Textualize/textual/issues/3839."""
app = RadioSetDisabledButtonsApp()
async with app.run_test() as pilot:
await pilot.press("enter")
for _ in range(5):
await pilot.press("down")
await pilot.press("enter")
for _ in range(5):
await pilot.press("up")
await pilot.press("enter")
assert app.selected == [
"1",
"4",
"5",
"7",
"1",
"4",
"1",
"7",
"5",
"4",
"1",
] | Regression test for https://github.com/Textualize/textual/issues/3839. | test_keyboard_navigation_with_disabled_buttons | python | Textualize/textual | tests/toggles/test_radioset.py | https://github.com/Textualize/textual/blob/master/tests/toggles/test_radioset.py | MIT |
async def test_radio_button_initial_state() -> None:
"""The initial states of the radio buttons should be as we specified."""
async with RadioButtonApp().run_test() as pilot:
assert [button.value for button in pilot.app.query(RadioButton)] == [
False,
False,
True,
]
assert [button.has_class("-on") for button in pilot.app.query(RadioButton)] == [
False,
False,
True,
]
assert pilot.app.events_received == [] | The initial states of the radio buttons should be as we specified. | test_radio_button_initial_state | python | Textualize/textual | tests/toggles/test_radiobutton.py | https://github.com/Textualize/textual/blob/master/tests/toggles/test_radiobutton.py | MIT |
async def test_radio_button_toggle() -> None:
"""Test the status of the radio buttons after they've been toggled."""
async with RadioButtonApp().run_test() as pilot:
for box in pilot.app.query(RadioButton):
box.toggle()
assert [button.value for button in pilot.app.query(RadioButton)] == [
True,
True,
False,
]
assert [button.has_class("-on") for button in pilot.app.query(RadioButton)] == [
True,
True,
False,
]
await pilot.pause()
assert pilot.app.events_received == [
("rb1", True, True),
("rb2", True, True),
("rb3", False, True),
] | Test the status of the radio buttons after they've been toggled. | test_radio_button_toggle | python | Textualize/textual | tests/toggles/test_radiobutton.py | https://github.com/Textualize/textual/blob/master/tests/toggles/test_radiobutton.py | MIT |
def replace_link_ids(render: str) -> str:
"""Link IDs have a random ID and system path which is a problem for
reproducible tests.
"""
return re_link_ids.sub("id=0;foo\x1b", render) | Link IDs have a random ID and system path which is a problem for
reproducible tests. | replace_link_ids | python | Textualize/textual | tests/utilities/render.py | https://github.com/Textualize/textual/blob/master/tests/utilities/render.py | MIT |
def test_insert_range_text_no_newlines():
"""Ensuring we can do a simple replacement of text."""
document = Document(TEXT)
document.replace_range((0, 2), (0, 6), "MUST")
assert document.lines == [
"I MUST not fear.",
"Fear is the mind-killer.",
] | Ensuring we can do a simple replacement of text. | test_insert_range_text_no_newlines | python | Textualize/textual | tests/document/test_document_insert.py | https://github.com/Textualize/textual/blob/master/tests/document/test_document_insert.py | MIT |
def test_delete_single_newline(document):
"""Testing deleting newline from right to left"""
replace_result = document.replace_range((1, 0), (0, 16), "")
assert replace_result == EditResult(end_location=(0, 16), replaced_text="\n")
assert document.lines == [
"I must not fear.Fear is the mind-killer.",
"I forgot the rest of the quote.",
"Sorry Will.",
] | Testing deleting newline from right to left | test_delete_single_newline | python | Textualize/textual | tests/document/test_document_delete.py | https://github.com/Textualize/textual/blob/master/tests/document/test_document_delete.py | MIT |
def test_delete_near_end_of_document(document):
"""Test deleting a range near the end of a document."""
replace_result = document.replace_range((1, 0), (3, 11), "")
assert replace_result == EditResult(
end_location=(1, 0),
replaced_text="Fear is the mind-killer.\n"
"I forgot the rest of the quote.\n"
"Sorry Will.",
)
assert document.lines == [
"I must not fear.",
"",
] | Test deleting a range near the end of a document. | test_delete_near_end_of_document | python | Textualize/textual | tests/document/test_document_delete.py | https://github.com/Textualize/textual/blob/master/tests/document/test_document_delete.py | MIT |
def test_delete_multiple_lines_partially_spanned(document):
"""Deleting a selection that partially spans the first and final lines of the selection."""
replace_result = document.replace_range((0, 2), (2, 2), "")
assert replace_result == EditResult(
end_location=(0, 2),
replaced_text="must not fear.\nFear is the mind-killer.\nI ",
)
assert document.lines == [
"I forgot the rest of the quote.",
"Sorry Will.",
] | Deleting a selection that partially spans the first and final lines of the selection. | test_delete_multiple_lines_partially_spanned | python | Textualize/textual | tests/document/test_document_delete.py | https://github.com/Textualize/textual/blob/master/tests/document/test_document_delete.py | MIT |
def test_delete_end_of_line(document):
"""Testing deleting newline from left to right"""
replace_result = document.replace_range((0, 16), (1, 0), "")
assert replace_result == EditResult(
end_location=(0, 16),
replaced_text="\n",
)
assert document.lines == [
"I must not fear.Fear is the mind-killer.",
"I forgot the rest of the quote.",
"Sorry Will.",
] | Testing deleting newline from left to right | test_delete_end_of_line | python | Textualize/textual | tests/document/test_document_delete.py | https://github.com/Textualize/textual/blob/master/tests/document/test_document_delete.py | MIT |
def test_delete_single_line_excluding_newline(document):
"""Delete from the start to the end of the line."""
replace_result = document.replace_range((2, 0), (2, 31), "")
assert replace_result == EditResult(
end_location=(2, 0),
replaced_text="I forgot the rest of the quote.",
)
assert document.lines == [
"I must not fear.",
"Fear is the mind-killer.",
"",
"Sorry Will.",
] | Delete from the start to the end of the line. | test_delete_single_line_excluding_newline | python | Textualize/textual | tests/document/test_document_delete.py | https://github.com/Textualize/textual/blob/master/tests/document/test_document_delete.py | MIT |
def test_delete_single_line_including_newline(document):
"""Delete from the start of a line to the start of the line below."""
replace_result = document.replace_range((2, 0), (3, 0), "")
assert replace_result == EditResult(
end_location=(2, 0),
replaced_text="I forgot the rest of the quote.\n",
)
assert document.lines == [
"I must not fear.",
"Fear is the mind-killer.",
"Sorry Will.",
] | Delete from the start of a line to the start of the line below. | test_delete_single_line_including_newline | python | Textualize/textual | tests/document/test_document_delete.py | https://github.com/Textualize/textual/blob/master/tests/document/test_document_delete.py | MIT |
def test_text(text):
"""The text we put in is the text we get out."""
document = Document(text)
assert document.text == text | The text we put in is the text we get out. | test_text | python | Textualize/textual | tests/document/test_document.py | https://github.com/Textualize/textual/blob/master/tests/document/test_document.py | MIT |
def test_no_pipeline_requirements_txt(
self, fake_project_cli, fake_metadata, fake_repo_path
):
"""No pipeline requirements.txt and no project requirements.txt does not
create project requirements.txt."""
# Remove project requirements.txt
project_requirements_txt = fake_repo_path / "requirements.txt"
project_requirements_txt.unlink()
self.call_pipeline_create(fake_project_cli, fake_metadata)
self.call_micropkg_package(fake_project_cli, fake_metadata)
self.call_pipeline_delete(fake_project_cli, fake_metadata)
self.call_micropkg_pull(fake_project_cli, fake_metadata, fake_repo_path)
assert not project_requirements_txt.exists() | No pipeline requirements.txt and no project requirements.txt does not
create project requirements.txt. | test_no_pipeline_requirements_txt | python | kedro-org/kedro | tests/framework/cli/micropkg/test_micropkg_requirements.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/cli/micropkg/test_micropkg_requirements.py | Apache-2.0 |
def test_empty_pipeline_requirements_txt(
self, fake_project_cli, fake_metadata, fake_package_path, fake_repo_path
):
"""Empty pipeline requirements.txt and no project requirements.txt does not
create project requirements.txt."""
# Remove project requirements.txt
project_requirements_txt = fake_repo_path / "requirements.txt"
project_requirements_txt.unlink()
self.call_pipeline_create(fake_project_cli, fake_metadata)
pipeline_requirements_txt = (
fake_package_path / "pipelines" / PIPELINE_NAME / "requirements.txt"
)
pipeline_requirements_txt.touch()
self.call_micropkg_package(fake_project_cli, fake_metadata)
self.call_pipeline_delete(fake_project_cli, fake_metadata)
self.call_micropkg_pull(fake_project_cli, fake_metadata, fake_repo_path)
assert not project_requirements_txt.exists() | Empty pipeline requirements.txt and no project requirements.txt does not
create project requirements.txt. | test_empty_pipeline_requirements_txt | python | kedro-org/kedro | tests/framework/cli/micropkg/test_micropkg_requirements.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/cli/micropkg/test_micropkg_requirements.py | Apache-2.0 |
def test_complex_requirements(
self, requirement, fake_project_cli, fake_metadata, fake_package_path
):
"""Options that are valid in requirements.txt but cannot be packaged in
pyproject.toml."""
self.call_pipeline_create(fake_project_cli, fake_metadata)
pipeline_requirements_txt = (
fake_package_path / "pipelines" / PIPELINE_NAME / "requirements.txt"
)
pipeline_requirements_txt.write_text(requirement)
result = CliRunner().invoke(
fake_project_cli,
["micropkg", "package", f"pipelines.{PIPELINE_NAME}"],
obj=fake_metadata,
)
assert result.exit_code == 1
assert (
"InvalidRequirement: Expected package name at the start of dependency specifier"
in result.output
or "InvalidRequirement: Expected end or semicolon" in result.output
or "InvalidRequirement: Parse error" in result.output
) | Options that are valid in requirements.txt but cannot be packaged in
pyproject.toml. | test_complex_requirements | python | kedro-org/kedro | tests/framework/cli/micropkg/test_micropkg_requirements.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/cli/micropkg/test_micropkg_requirements.py | Apache-2.0 |
def test_micropkg_package_same_name_as_package_name(
self, fake_metadata, fake_project_cli, fake_repo_path
):
"""Create modular pipeline with the same name as the
package name, then package as is. The command should run
and the resulting sdist should have all expected contents.
"""
pipeline_name = fake_metadata.package_name
result = CliRunner().invoke(
fake_project_cli, ["pipeline", "create", pipeline_name], obj=fake_metadata
)
assert result.exit_code == 0
result = CliRunner().invoke(
fake_project_cli,
["micropkg", "package", f"pipelines.{pipeline_name}"],
obj=fake_metadata,
)
sdist_location = fake_repo_path / "dist"
assert result.exit_code == 0
assert f"Location: {sdist_location}" in result.output
self.assert_sdist_contents_correct(
sdist_location=sdist_location, package_name=pipeline_name
) | Create modular pipeline with the same name as the
package name, then package as is. The command should run
and the resulting sdist should have all expected contents. | test_micropkg_package_same_name_as_package_name | python | kedro-org/kedro | tests/framework/cli/micropkg/test_micropkg_package.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/cli/micropkg/test_micropkg_package.py | Apache-2.0 |
def test_micropkg_package_same_name_as_package_name_alias(
self, fake_metadata, fake_project_cli, fake_repo_path
):
"""Create modular pipeline, then package under alias
the same name as the package name. The command should run
and the resulting sdist should have all expected contents.
"""
alias = fake_metadata.package_name
result = CliRunner().invoke(
fake_project_cli, ["pipeline", "create", PIPELINE_NAME], obj=fake_metadata
)
assert result.exit_code == 0
result = CliRunner().invoke(
fake_project_cli,
["micropkg", "package", f"pipelines.{PIPELINE_NAME}", "--alias", alias],
obj=fake_metadata,
)
sdist_location = fake_repo_path / "dist"
assert result.exit_code == 0
assert f"Location: {sdist_location}" in result.output
self.assert_sdist_contents_correct(
sdist_location=sdist_location, package_name=alias
) | Create modular pipeline, then package under alias
the same name as the package name. The command should run
and the resulting sdist should have all expected contents. | test_micropkg_package_same_name_as_package_name_alias | python | kedro-org/kedro | tests/framework/cli/micropkg/test_micropkg_package.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/cli/micropkg/test_micropkg_package.py | Apache-2.0 |
def test_package_modular_pipeline_with_nested_parameters(
self, fake_repo_path, fake_project_cli, fake_metadata
):
"""
The setup for the test is as follows:
Create two modular pipelines, to verify that only the parameter file with matching pipeline
name will be packaged.
Add a directory with a parameter file to verify that if a project has parameters structured
like below, that the ones inside a directory with the pipeline name are packaged as well
when calling `kedro micropkg package` for a specific pipeline.
parameters
└── retail
└── params1.ym
"""
CliRunner().invoke(
fake_project_cli, ["pipeline", "create", "retail"], obj=fake_metadata
)
CliRunner().invoke(
fake_project_cli,
["pipeline", "create", "retail_banking"],
obj=fake_metadata,
)
nested_param_path = Path(
fake_repo_path / "conf" / "base" / "parameters" / "retail"
)
nested_param_path.mkdir(parents=True, exist_ok=True)
(nested_param_path / "params1.yml").touch()
result = CliRunner().invoke(
fake_project_cli,
["micropkg", "package", "pipelines.retail"],
obj=fake_metadata,
)
assert result.exit_code == 0
assert "'dummy_package.pipelines.retail' packaged!" in result.output
sdist_location = fake_repo_path / "dist"
assert f"Location: {sdist_location}" in result.output
sdist_name = _get_sdist_name(name="retail", version="0.1")
sdist_file = sdist_location / sdist_name
assert sdist_file.is_file()
assert len(list(sdist_location.iterdir())) == 1
with tarfile.open(sdist_file, "r") as tar:
sdist_contents = set(tar.getnames())
assert (
"retail-0.1/retail/config/parameters/retail/params1.yml" in sdist_contents
)
assert "retail-0.1/retail/config/parameters_retail.yml" in sdist_contents
assert (
"retail-0.1/retail/config/parameters_retail_banking.yml"
not in sdist_contents
) | The setup for the test is as follows:
Create two modular pipelines, to verify that only the parameter file with matching pipeline
name will be packaged.
Add a directory with a parameter file to verify that if a project has parameters structured
like below, that the ones inside a directory with the pipeline name are packaged as well
when calling `kedro micropkg package` for a specific pipeline.
parameters
└── retail
└── params1.ym | test_package_modular_pipeline_with_nested_parameters | python | kedro-org/kedro | tests/framework/cli/micropkg/test_micropkg_package.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/cli/micropkg/test_micropkg_package.py | Apache-2.0 |
def _assert_hook_call_record_has_expected_parameters(
call_record: logging.LogRecord, expected_parameters: list[str]
):
"""Assert the given call record has all expected parameters."""
for param in expected_parameters:
assert hasattr(call_record, param) | Assert the given call record has all expected parameters. | _assert_hook_call_record_has_expected_parameters | python | kedro-org/kedro | tests/framework/session/conftest.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/session/conftest.py | Apache-2.0 |
def logs_listener():
"""Fixture to start the logs listener before a test and clean up after the test finishes"""
listener = LogsListener()
listener.start()
yield listener
logger.removeHandler(listener.log_handler)
listener.stop() | Fixture to start the logs listener before a test and clean up after the test finishes | logs_listener | python | kedro-org/kedro | tests/framework/session/conftest.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/session/conftest.py | Apache-2.0 |
def project_hooks():
"""A set of project hook implementations that log to stdout whenever it is invoked."""
return LoggingHooks() | A set of project hook implementations that log to stdout whenever it is invoked. | project_hooks | python | kedro-org/kedro | tests/framework/session/conftest.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/session/conftest.py | Apache-2.0 |
def mock_session_with_before_node_run_hooks(
mocker, project_hooks, mock_package_name, tmp_path
):
class BeforeNodeRunHook:
"""Should overwrite the `cars` dataset"""
@hook_impl
def before_node_run(self, node: Node):
return {"cars": MockDatasetReplacement()} if node.name == "node1" else None
class MockSettings(_ProjectSettings):
_HOOKS = Validator("HOOKS", default=(project_hooks, BeforeNodeRunHook()))
_mock_imported_settings_paths(mocker, MockSettings())
return KedroSession.create(tmp_path) | Should overwrite the `cars` dataset | mock_session_with_before_node_run_hooks | python | kedro-org/kedro | tests/framework/session/test_session_extension_hooks.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/session/test_session_extension_hooks.py | Apache-2.0 |
def mock_session_with_broken_before_node_run_hooks(
mocker, project_hooks, mock_package_name, tmp_path
):
class BeforeNodeRunHook:
"""Should overwrite the `cars` dataset"""
@hook_impl
def before_node_run(self):
return MockDatasetReplacement()
class MockSettings(_ProjectSettings):
_HOOKS = Validator("HOOKS", default=(project_hooks, BeforeNodeRunHook()))
_mock_imported_settings_paths(mocker, MockSettings())
return KedroSession.create(tmp_path) | Should overwrite the `cars` dataset | mock_session_with_broken_before_node_run_hooks | python | kedro-org/kedro | tests/framework/session/test_session_extension_hooks.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/session/test_session_extension_hooks.py | Apache-2.0 |
def create_attrs_autospec(spec: type, spec_set: bool = True) -> Any:
"""Creates a mock of an attr class (creates mocks recursively on all attributes).
https://github.com/python-attrs/attrs/issues/462#issuecomment-1134656377
:param spec: the spec to mock
:param spec_set: if True, AttributeError will be raised if an attribute that is not in the spec is set.
"""
if not hasattr(spec, ATTRS_ATTRIBUTE):
raise TypeError(f"{spec!r} is not an attrs class")
mock = create_autospec(spec, spec_set=spec_set)
for attribute in getattr(spec, ATTRS_ATTRIBUTE):
attribute_type = attribute.type
if NEW_TYPING:
# A[T] does not get a copy of __dict__ from A(Generic[T]) anymore, use __origin__ to get it
while hasattr(attribute_type, "__origin__"):
attribute_type = attribute_type.__origin__
if hasattr(attribute_type, ATTRS_ATTRIBUTE):
mock_attribute = create_attrs_autospec(attribute_type, spec_set)
else:
mock_attribute = create_autospec(attribute_type, spec_set=spec_set)
object.__setattr__(mock, attribute.name, mock_attribute)
return mock | Creates a mock of an attr class (creates mocks recursively on all attributes).
https://github.com/python-attrs/attrs/issues/462#issuecomment-1134656377
:param spec: the spec to mock
:param spec_set: if True, AttributeError will be raised if an attribute that is not in the spec is set. | create_attrs_autospec | python | kedro-org/kedro | tests/framework/session/test_session.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/session/test_session.py | Apache-2.0 |
def test_git_describe(
self, fake_project, fake_commit_hash, fake_git_status, mocker
):
"""Test that git information is added to the session store"""
mocker.patch(
"subprocess.check_output",
side_effect=[fake_commit_hash.encode(), fake_git_status.encode()],
)
session = KedroSession.create(fake_project)
expected_git_info = {
"commit_sha": fake_commit_hash,
"dirty": bool(fake_git_status),
}
assert session.store["git"] == expected_git_info | Test that git information is added to the session store | test_git_describe | python | kedro-org/kedro | tests/framework/session/test_session.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/session/test_session.py | Apache-2.0 |
def test_git_describe_error(self, fake_project, exception, mocker, caplog):
"""Test that git information is not added to the session store
if call to git fails
"""
caplog.set_level(logging.DEBUG, logger="kedro")
mocker.patch("subprocess.check_output", side_effect=exception)
session = KedroSession.create(fake_project)
assert "git" not in session.store
expected_log_message = f"Unable to git describe {fake_project}"
actual_log_messages = [
rec.getMessage()
for rec in caplog.records
if rec.name == SESSION_LOGGER_NAME and rec.levelno == logging.DEBUG
]
assert expected_log_message in actual_log_messages | Test that git information is not added to the session store
if call to git fails | test_git_describe_error | python | kedro-org/kedro | tests/framework/session/test_session.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/session/test_session.py | Apache-2.0 |
def test_get_username_error(self, fake_project, mocker, caplog):
"""Test that username information is not added to the session store
if call to getuser() fails
"""
caplog.set_level(logging.DEBUG, logger="kedro")
mocker.patch("subprocess.check_output")
mocker.patch("getpass.getuser", side_effect=FakeException("getuser error"))
session = KedroSession.create(fake_project)
assert "username" not in session.store
expected_log_messages = [
"Unable to get username. Full exception: getuser error"
]
actual_log_messages = [
rec.getMessage()
for rec in caplog.records
if rec.name == SESSION_LOGGER_NAME and rec.levelno == logging.DEBUG
]
assert actual_log_messages == expected_log_messages | Test that username information is not added to the session store
if call to getuser() fails | test_get_username_error | python | kedro-org/kedro | tests/framework/session/test_session.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/session/test_session.py | Apache-2.0 |
def test_log_error(self, fake_project):
"""Test logging the error by the session"""
# test that the error is not swallowed by the session
with pytest.raises(FakeException), KedroSession.create(fake_project) as session:
raise FakeException
exception = session.store["exception"]
assert exception["type"] == "tests.framework.session.test_session.FakeException"
assert not exception["value"]
assert any(
"raise FakeException" in tb_line for tb_line in exception["traceback"]
) | Test logging the error by the session | test_log_error | python | kedro-org/kedro | tests/framework/session/test_session.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/session/test_session.py | Apache-2.0 |
def test_run(
self,
fake_project,
fake_session_id,
fake_pipeline_name,
mock_context_class,
mock_runner,
mocker,
):
"""Test running the project via the session"""
mock_hook = mocker.patch(
"kedro.framework.session.session._create_hook_manager"
).return_value.hook
mock_pipelines = mocker.patch(
"kedro.framework.session.session.pipelines",
return_value={
_FAKE_PIPELINE_NAME: mocker.Mock(),
"__default__": mocker.Mock(),
},
)
mock_context = mock_context_class.return_value
mock_catalog = mock_context._get_catalog.return_value
mock_runner.__name__ = "SequentialRunner"
mock_pipeline = mock_pipelines.__getitem__.return_value.filter.return_value
with KedroSession.create(fake_project) as session:
session.run(runner=mock_runner, pipeline_name=fake_pipeline_name)
record_data = {
"session_id": fake_session_id,
"project_path": fake_project.as_posix(),
"env": mock_context.env,
"kedro_version": kedro_version,
"tags": None,
"from_nodes": None,
"to_nodes": None,
"node_names": None,
"from_inputs": None,
"to_outputs": None,
"load_versions": None,
"extra_params": {},
"pipeline_name": fake_pipeline_name,
"namespace": None,
"runner": mock_runner.__name__,
}
mock_hook.before_pipeline_run.assert_called_once_with(
run_params=record_data, pipeline=mock_pipeline, catalog=mock_catalog
)
mock_runner.run.assert_called_once_with(
mock_pipeline, mock_catalog, session._hook_manager, fake_session_id
)
mock_hook.after_pipeline_run.assert_called_once_with(
run_params=record_data,
run_result=mock_runner.run.return_value,
pipeline=mock_pipeline,
catalog=mock_catalog,
) | Test running the project via the session | test_run | python | kedro-org/kedro | tests/framework/session/test_session.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/session/test_session.py | Apache-2.0 |
def test_run_thread_runner(
self,
fake_project,
fake_session_id,
fake_pipeline_name,
mock_context_class,
mock_thread_runner,
mocker,
match_pattern,
):
"""Test running the project via the session"""
mock_hook = mocker.patch(
"kedro.framework.session.session._create_hook_manager"
).return_value.hook
ds_mock = mocker.Mock(**{"datasets.return_value": ["ds_1", "ds_2"]})
filter_mock = mocker.Mock(**{"filter.return_value": ds_mock})
pipelines_ret = {
_FAKE_PIPELINE_NAME: filter_mock,
"__default__": filter_mock,
}
mocker.patch("kedro.framework.session.session.pipelines", pipelines_ret)
mocker.patch(
"kedro.io.data_catalog.CatalogConfigResolver.match_pattern",
return_value=match_pattern,
)
with KedroSession.create(fake_project) as session:
session.run(runner=mock_thread_runner, pipeline_name=fake_pipeline_name)
mock_context = mock_context_class.return_value
record_data = {
"session_id": fake_session_id,
"project_path": fake_project.as_posix(),
"env": mock_context.env,
"kedro_version": kedro_version,
"tags": None,
"from_nodes": None,
"to_nodes": None,
"node_names": None,
"from_inputs": None,
"to_outputs": None,
"load_versions": None,
"extra_params": {},
"pipeline_name": fake_pipeline_name,
"namespace": None,
"runner": mock_thread_runner.__name__,
}
mock_catalog = mock_context._get_catalog.return_value
mock_pipeline = filter_mock.filter()
mock_hook.before_pipeline_run.assert_called_once_with(
run_params=record_data, pipeline=mock_pipeline, catalog=mock_catalog
)
mock_thread_runner.run.assert_called_once_with(
mock_pipeline, mock_catalog, session._hook_manager, fake_session_id
)
mock_hook.after_pipeline_run.assert_called_once_with(
run_params=record_data,
run_result=mock_thread_runner.run.return_value,
pipeline=mock_pipeline,
catalog=mock_catalog,
) | Test running the project via the session | test_run_thread_runner | python | kedro-org/kedro | tests/framework/session/test_session.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/session/test_session.py | Apache-2.0 |
def test_run_multiple_times(
self,
fake_project,
fake_session_id,
fake_pipeline_name,
mock_context_class,
mock_runner,
mocker,
):
"""Test running the project more than once via the session"""
mock_hook = mocker.patch(
"kedro.framework.session.session._create_hook_manager"
).return_value.hook
mock_pipelines = mocker.patch(
"kedro.framework.session.session.pipelines",
return_value={
_FAKE_PIPELINE_NAME: mocker.Mock(),
"__default__": mocker.Mock(),
},
)
mock_context = mock_context_class.return_value
mock_catalog = mock_context._get_catalog.return_value
mock_pipeline = mock_pipelines.__getitem__.return_value.filter.return_value
message = (
"A run has already been completed as part of the active KedroSession. "
"KedroSession has a 1-1 mapping with runs, and thus only one run should be"
" executed per session."
)
with pytest.raises(Exception, match=message):
with KedroSession.create(fake_project) as session:
session.run(runner=mock_runner, pipeline_name=fake_pipeline_name)
session.run(runner=mock_runner, pipeline_name=fake_pipeline_name)
record_data = {
"session_id": fake_session_id,
"project_path": fake_project.as_posix(),
"env": mock_context.env,
"kedro_version": kedro_version,
"tags": None,
"from_nodes": None,
"to_nodes": None,
"node_names": None,
"from_inputs": None,
"to_outputs": None,
"load_versions": None,
"extra_params": {},
"pipeline_name": fake_pipeline_name,
"namespace": None,
"runner": mock_runner.__name__,
}
mock_hook.before_pipeline_run.assert_called_once_with(
run_params=record_data,
pipeline=mock_pipeline,
catalog=mock_catalog,
)
mock_runner.run.assert_called_once_with(
mock_pipeline, mock_catalog, session._hook_manager, fake_session_id
)
mock_hook.after_pipeline_run.assert_called_once_with(
run_params=record_data,
run_result=mock_runner.run.return_value,
pipeline=mock_pipeline,
catalog=mock_catalog,
) | Test running the project more than once via the session | test_run_multiple_times | python | kedro-org/kedro | tests/framework/session/test_session.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/session/test_session.py | Apache-2.0 |
def test_run_exception(
self,
fake_project,
fake_session_id,
fake_pipeline_name,
mock_context_class,
mock_runner,
mocker,
):
"""Test exception being raised during the run"""
mock_hook = mocker.patch(
"kedro.framework.session.session._create_hook_manager"
).return_value.hook
mock_pipelines = mocker.patch(
"kedro.framework.session.session.pipelines",
return_value={
_FAKE_PIPELINE_NAME: mocker.Mock(),
"__default__": mocker.Mock(),
},
)
mock_context = mock_context_class.return_value
mock_catalog = mock_context._get_catalog.return_value
error = FakeException("You shall not pass!")
mock_runner.run.side_effect = error # runner.run() raises an error
mock_pipeline = mock_pipelines.__getitem__.return_value.filter.return_value
with pytest.raises(FakeException), KedroSession.create(fake_project) as session:
session.run(runner=mock_runner, pipeline_name=fake_pipeline_name)
record_data = {
"session_id": fake_session_id,
"project_path": fake_project.as_posix(),
"env": mock_context.env,
"kedro_version": kedro_version,
"tags": None,
"from_nodes": None,
"to_nodes": None,
"node_names": None,
"from_inputs": None,
"to_outputs": None,
"load_versions": None,
"extra_params": {},
"pipeline_name": fake_pipeline_name,
"namespace": None,
"runner": mock_runner.__name__,
}
mock_hook.on_pipeline_error.assert_called_once_with(
error=error,
run_params=record_data,
pipeline=mock_pipeline,
catalog=mock_catalog,
)
mock_hook.after_pipeline_run.assert_not_called()
exception = session.store["exception"]
assert exception["type"] == "tests.framework.session.test_session.FakeException"
assert exception["value"] == "You shall not pass!"
assert exception["traceback"] | Test exception being raised during the run | test_run_exception | python | kedro-org/kedro | tests/framework/session/test_session.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/session/test_session.py | Apache-2.0 |
def test_run_broken_pipeline_multiple_times(
self,
fake_project,
fake_session_id,
fake_pipeline_name,
mock_context_class,
mock_runner,
mocker,
):
"""Test exception being raised during the first run and
a second run is allowed to be executed in the same session."""
mock_hook = mocker.patch(
"kedro.framework.session.session._create_hook_manager"
).return_value.hook
mock_pipelines = mocker.patch(
"kedro.framework.session.session.pipelines",
return_value={
_FAKE_PIPELINE_NAME: mocker.Mock(),
"__default__": mocker.Mock(),
},
)
mock_context = mock_context_class.return_value
mock_catalog = mock_context._get_catalog.return_value
session = KedroSession.create(fake_project)
broken_runner = mocker.patch(
"kedro.runner.SequentialRunner",
autospec=True,
)
broken_runner.__name__ = "BrokenRunner"
error = FakeException("You shall not pass!")
broken_runner.run.side_effect = error # runner.run() raises an error
mock_pipeline = mock_pipelines.__getitem__.return_value.filter.return_value
with pytest.raises(FakeException):
# Execute run with broken runner
session.run(runner=broken_runner, pipeline_name=fake_pipeline_name)
record_data = {
"session_id": fake_session_id,
"project_path": fake_project.as_posix(),
"env": mock_context.env,
"kedro_version": kedro_version,
"tags": None,
"from_nodes": None,
"to_nodes": None,
"node_names": None,
"from_inputs": None,
"to_outputs": None,
"load_versions": None,
"extra_params": {},
"pipeline_name": fake_pipeline_name,
"namespace": None,
"runner": broken_runner.__name__,
}
mock_hook.on_pipeline_error.assert_called_once_with(
error=error,
run_params=record_data,
pipeline=mock_pipeline,
catalog=mock_catalog,
)
mock_hook.after_pipeline_run.assert_not_called()
# Execute run another time with fixed runner
fixed_runner = mock_runner
session.run(runner=fixed_runner, pipeline_name=fake_pipeline_name)
fixed_runner.run.assert_called_once_with(
mock_pipeline, mock_catalog, session._hook_manager, fake_session_id
)
record_data["runner"] = "MockRunner"
mock_hook.after_pipeline_run.assert_called_once_with(
run_params=record_data,
run_result=fixed_runner.run.return_value,
pipeline=mock_pipeline,
catalog=mock_catalog,
) | Test exception being raised during the first run and
a second run is allowed to be executed in the same session. | test_run_broken_pipeline_multiple_times | python | kedro-org/kedro | tests/framework/session/test_session.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/session/test_session.py | Apache-2.0 |
def test_calling_register_hooks_twice(self, project_hooks, mock_session):
"""Calling hook registration multiple times should not raise"""
hook_manager = mock_session._hook_manager
assert hook_manager.is_registered(project_hooks)
_register_hooks(hook_manager, (project_hooks,))
_register_hooks(hook_manager, (project_hooks,))
assert hook_manager.is_registered(project_hooks) | Calling hook registration multiple times should not raise | test_calling_register_hooks_twice | python | kedro-org/kedro | tests/framework/session/test_session_hook_manager.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/session/test_session_hook_manager.py | Apache-2.0 |
def mock_package_name_with_pipelines_file(tmpdir):
pipelines_file_path = tmpdir.mkdir("test_package") / "pipeline_registry.py"
pipelines_file_path.write(
textwrap.dedent(
"""
from kedro.pipeline import Pipeline
def register_pipelines():
return {"new_pipeline": Pipeline([])}
"""
)
)
project_path, package_name, _ = str(pipelines_file_path).rpartition("test_package")
sys.path.insert(0, project_path)
yield package_name
sys.path.pop(0) | from kedro.pipeline import Pipeline
def register_pipelines():
return {"new_pipeline": Pipeline([])} | mock_package_name_with_pipelines_file | python | kedro-org/kedro | tests/framework/project/test_pipeline_registry.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/project/test_pipeline_registry.py | Apache-2.0 |
def mock_package_name_with_unimportable_pipelines_file(tmpdir):
pipelines_file_path = tmpdir.mkdir("test_broken_package") / "pipeline_registry.py"
pipelines_file_path.write(
textwrap.dedent(
"""
import this_is_not_a_real_thing
from kedro.pipeline import Pipeline
def register_pipelines():
return {"new_pipeline": Pipeline([])}
"""
)
)
project_path, package_name, _ = str(pipelines_file_path).rpartition(
"test_broken_package"
)
sys.path.insert(0, project_path)
yield package_name
sys.path.pop(0) | import this_is_not_a_real_thing
from kedro.pipeline import Pipeline
def register_pipelines():
return {"new_pipeline": Pipeline([])} | mock_package_name_with_unimportable_pipelines_file | python | kedro-org/kedro | tests/framework/project/test_pipeline_registry.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/project/test_pipeline_registry.py | Apache-2.0 |
def test_find_pipelines_skips_hidden_modules(
mock_package_name_with_pipelines, pipeline_names
):
pipelines_dir = Path(sys.path[0]) / mock_package_name_with_pipelines / "pipelines"
pipeline_dir = pipelines_dir / ".ipynb_checkpoints"
pipeline_dir.mkdir()
(pipeline_dir / "__init__.py").write_text(
textwrap.dedent(
"""
from __future__ import annotations
from kedro.pipeline import Pipeline, node, pipeline
def create_pipeline(**kwargs) -> Pipeline:
return pipeline([node(lambda: 1, None, "simple_pipeline")])
"""
)
)
configure_project(mock_package_name_with_pipelines)
pipelines = find_pipelines()
assert set(pipelines) == pipeline_names | {"__default__"}
assert sum(pipelines.values()).outputs() == pipeline_names | from __future__ import annotations
from kedro.pipeline import Pipeline, node, pipeline
def create_pipeline(**kwargs) -> Pipeline:
return pipeline([node(lambda: 1, None, "simple_pipeline")]) | test_find_pipelines_skips_hidden_modules | python | kedro-org/kedro | tests/framework/project/test_pipeline_discovery.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/project/test_pipeline_discovery.py | Apache-2.0 |
def test_find_pipelines_skips_modules_with_unexpected_return_value_type(
mock_package_name_with_pipelines, pipeline_names
):
# Define `create_pipelines` so that it does not return a `Pipeline`.
pipelines_dir = Path(sys.path[0]) / mock_package_name_with_pipelines / "pipelines"
pipeline_dir = pipelines_dir / "not_my_pipeline"
pipeline_dir.mkdir()
(pipeline_dir / "__init__.py").write_text(
textwrap.dedent(
"""
from __future__ import annotations
from kedro.pipeline import Pipeline, node, pipeline
def create_pipeline(**kwargs) -> dict[str, Pipeline]:
return {
"pipe1": pipeline([node(lambda: 1, None, "pipe1")]),
"pipe2": pipeline([node(lambda: 2, None, "pipe2")]),
}
"""
)
)
configure_project(mock_package_name_with_pipelines)
with pytest.warns(
UserWarning,
match=(
r"Expected the 'create_pipeline' function in the '\S+' "
r"module to return a 'Pipeline' object, got 'dict' instead."
),
):
pipelines = find_pipelines()
assert set(pipelines) == pipeline_names | {"__default__"}
assert sum(pipelines.values()).outputs() == pipeline_names | from __future__ import annotations
from kedro.pipeline import Pipeline, node, pipeline
def create_pipeline(**kwargs) -> dict[str, Pipeline]:
return {
"pipe1": pipeline([node(lambda: 1, None, "pipe1")]),
"pipe2": pipeline([node(lambda: 2, None, "pipe2")]),
} | test_find_pipelines_skips_modules_with_unexpected_return_value_type | python | kedro-org/kedro | tests/framework/project/test_pipeline_discovery.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/project/test_pipeline_discovery.py | Apache-2.0 |
def test_find_pipelines_handles_simplified_project_structure(
mock_package_name_with_pipelines, pipeline_names
):
(Path(sys.path[0]) / mock_package_name_with_pipelines / "pipeline.py").write_text(
textwrap.dedent(
"""
from kedro.pipeline import Pipeline, node, pipeline
def create_pipeline(**kwargs) -> Pipeline:
return pipeline([node(lambda: 1, None, "simple_pipeline")])
"""
)
)
configure_project(mock_package_name_with_pipelines)
pipelines = find_pipelines()
assert set(pipelines) == pipeline_names | {"__default__"}
assert sum(pipelines.values()).outputs() == pipeline_names | {"simple_pipeline"} | from kedro.pipeline import Pipeline, node, pipeline
def create_pipeline(**kwargs) -> Pipeline:
return pipeline([node(lambda: 1, None, "simple_pipeline")]) | test_find_pipelines_handles_simplified_project_structure | python | kedro-org/kedro | tests/framework/project/test_pipeline_discovery.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/project/test_pipeline_discovery.py | Apache-2.0 |
def test_find_pipelines_handles_project_structure_without_pipelines_dir(
mock_package_name_with_pipelines, simplified
):
# Delete the `pipelines` directory to simulate a project without it.
pipelines_dir = Path(sys.path[0]) / mock_package_name_with_pipelines / "pipelines"
shutil.rmtree(pipelines_dir)
if simplified:
(
Path(sys.path[0]) / mock_package_name_with_pipelines / "pipeline.py"
).write_text(
textwrap.dedent(
"""
from kedro.pipeline import Pipeline, node, pipeline
def create_pipeline(**kwargs) -> Pipeline:
return pipeline([node(lambda: 1, None, "simple_pipeline")])
"""
)
)
configure_project(mock_package_name_with_pipelines)
pipelines = find_pipelines()
assert set(pipelines) == {"__default__"}
assert sum(pipelines.values()).outputs() == (
{"simple_pipeline"} if simplified else set()
) | from kedro.pipeline import Pipeline, node, pipeline
def create_pipeline(**kwargs) -> Pipeline:
return pipeline([node(lambda: 1, None, "simple_pipeline")]) | test_find_pipelines_handles_project_structure_without_pipelines_dir | python | kedro-org/kedro | tests/framework/project/test_pipeline_discovery.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/project/test_pipeline_discovery.py | Apache-2.0 |
def mock_package_name_with_settings_file(tmpdir):
"""This mock settings file tests everything that can be customised in settings.py.
Where there are suggestions in the project template settings.py (e.g. as for
CONFIG_LOADER_CLASS), those suggestions should be tested."""
old_settings = settings.as_dict()
settings_file_path = tmpdir.mkdir("test_package").join("settings.py")
project_path, package_name, _ = str(settings_file_path).rpartition("test_package")
settings_file_path.write(
textwrap.dedent(
f"""
from {__name__} import ProjectHooks
HOOKS = (ProjectHooks(),)
DISABLE_HOOKS_FOR_PLUGINS = ("kedro-viz",)
from kedro.framework.session.store import BaseSessionStore
SESSION_STORE_CLASS = BaseSessionStore
SESSION_STORE_ARGS = {{
"path": "./sessions"
}}
from {__name__} import MyContext
CONTEXT_CLASS = MyContext
CONF_SOURCE = "test_conf"
from kedro.config import OmegaConfigLoader
CONFIG_LOADER_CLASS = OmegaConfigLoader
CONFIG_LOADER_ARGS = {{
"globals_pattern": "*globals.yml",
}}
# Class that manages the Data Catalog.
from {__name__} import MyDataCatalog
DATA_CATALOG_CLASS = MyDataCatalog
"""
)
)
sys.path.insert(0, project_path)
yield package_name
sys.path.pop(0)
# reset side-effect of configure_project
for key, value in old_settings.items():
settings.set(key, value) | This mock settings file tests everything that can be customised in settings.py.
Where there are suggestions in the project template settings.py (e.g. as for
CONFIG_LOADER_CLASS), those suggestions should be tested. | mock_package_name_with_settings_file | python | kedro-org/kedro | tests/framework/project/test_settings.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/project/test_settings.py | Apache-2.0 |
def mock_package_name_without_settings_file(tmpdir):
"""This mocks a project that doesn't have a settings.py file.
When configured, the project should have sensible default settings."""
package_name = "test_package_without_settings"
project_path, _, _ = str(tmpdir.mkdir(package_name)).rpartition(package_name)
sys.path.insert(0, project_path)
yield package_name
sys.path.pop(0) | This mocks a project that doesn't have a settings.py file.
When configured, the project should have sensible default settings. | mock_package_name_without_settings_file | python | kedro-org/kedro | tests/framework/project/test_settings.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/project/test_settings.py | Apache-2.0 |
def test_rich_traceback_configuration_extend_suppress(mocker, default_logging_config):
"""Test the configuration is not overrided but extend for `suppress`"""
import click
rich_traceback_install = mocker.patch("rich.traceback.install")
rich_pretty_install = mocker.patch("rich.pretty.install")
sys_executable_path = str(Path(sys.executable).parent)
traceback_install_defaults = {"suppress": [click, sys_executable_path]}
fake_path = "dummy"
rich_handler = {
"class": "kedro.logging.RichHandler",
"rich_tracebacks": True,
"tracebacks_suppress": [fake_path],
}
test_logging_config = default_logging_config
test_logging_config["handlers"]["rich"] = rich_handler
LOGGING.configure(test_logging_config)
expected_install_defaults = traceback_install_defaults
expected_install_defaults["suppress"].extend([fake_path])
rich_traceback_install.assert_called_with(**expected_install_defaults)
rich_pretty_install.assert_called_once() | Test the configuration is not overrided but extend for `suppress` | test_rich_traceback_configuration_extend_suppress | python | kedro-org/kedro | tests/framework/project/test_logging.py | https://github.com/kedro-org/kedro/blob/master/tests/framework/project/test_logging.py | Apache-2.0 |
def branchless_no_input_pipeline():
"""The pipeline runs in the order A->B->C->D->E."""
return pipeline(
[
node(identity, "D", "E", name="node1"),
node(identity, "C", "D", name="node2"),
node(identity, "A", "B", name="node3"),
node(identity, "B", "C", name="node4"),
node(random, None, "A", name="node5"),
]
) | The pipeline runs in the order A->B->C->D->E. | branchless_no_input_pipeline | python | kedro-org/kedro | tests/runner/conftest.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/conftest.py | Apache-2.0 |
def two_branches_crossed_pipeline_variable_inputs(request):
"""A ``Pipeline`` with an X-shape (two branches with one common node).
Non-persistent datasets (other than parameters) are prefixed with an underscore.
"""
extra_inputs = list(request.param)
return pipeline(
[
node(first_arg, ["ds0_A", *extra_inputs], "_ds1_A", name="node1_A"),
node(first_arg, ["ds0_B", *extra_inputs], "_ds1_B", name="node1_B"),
node(
multi_input_list_output,
["_ds1_A", "_ds1_B", *extra_inputs],
["ds2_A", "ds2_B"],
name="node2",
),
node(first_arg, ["ds2_A", *extra_inputs], "_ds3_A", name="node3_A"),
node(first_arg, ["ds2_B", *extra_inputs], "_ds3_B", name="node3_B"),
node(first_arg, ["_ds3_A", *extra_inputs], "_ds4_A", name="node4_A"),
node(first_arg, ["_ds3_B", *extra_inputs], "_ds4_B", name="node4_B"),
]
) | A ``Pipeline`` with an X-shape (two branches with one common node).
Non-persistent datasets (other than parameters) are prefixed with an underscore. | two_branches_crossed_pipeline_variable_inputs | python | kedro-org/kedro | tests/runner/conftest.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/conftest.py | Apache-2.0 |
def test_result_saved_not_returned(self, is_async, saving_result_pipeline):
"""The pipeline runs ds->dsX but save does not save the output."""
def _load():
return 0
def _save(arg):
assert arg == 0
catalog = DataCatalog(
{
"ds": LambdaDataset(load=_load, save=_save),
"dsX": LambdaDataset(load=_load, save=_save),
}
)
output = SequentialRunner(is_async=is_async).run(
saving_result_pipeline, catalog
)
assert output == {} | The pipeline runs ds->dsX but save does not save the output. | test_result_saved_not_returned | python | kedro-org/kedro | tests/runner/test_sequential_runner.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_sequential_runner.py | Apache-2.0 |
def test_conflict_feed_catalog(
self,
is_async,
memory_catalog,
unfinished_outputs_pipeline,
conflicting_feed_dict,
):
"""ds1 and ds3 will be replaced with new inputs."""
memory_catalog.add_feed_dict(conflicting_feed_dict, replace=True)
outputs = SequentialRunner(is_async=is_async).run(
unfinished_outputs_pipeline, memory_catalog
)
assert isinstance(outputs["ds8"], dict)
assert outputs["ds8"]["data"] == 0
assert isinstance(outputs["ds6"], pd.DataFrame) | ds1 and ds3 will be replaced with new inputs. | test_conflict_feed_catalog | python | kedro-org/kedro | tests/runner/test_sequential_runner.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_sequential_runner.py | Apache-2.0 |
def test_unsatisfied_inputs(self, is_async, unfinished_outputs_pipeline, catalog):
"""ds1, ds2 and ds3 were not specified."""
with pytest.raises(
ValueError, match=rf"not found in the {catalog.__class__.__name__}"
):
SequentialRunner(is_async=is_async).run(
unfinished_outputs_pipeline, catalog
) | ds1, ds2 and ds3 were not specified. | test_unsatisfied_inputs | python | kedro-org/kedro | tests/runner/test_sequential_runner.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_sequential_runner.py | Apache-2.0 |
def test_stricter_suggest_resume_scenario(
self,
caplog,
two_branches_crossed_pipeline_variable_inputs,
persistent_dataset_catalog,
failing_node_names,
expected_pattern,
):
"""
Stricter version of previous test.
Covers pipelines where inputs are shared across nodes.
"""
test_pipeline = two_branches_crossed_pipeline_variable_inputs
nodes = {n.name: n for n in test_pipeline.nodes}
for name in failing_node_names:
test_pipeline -= modular_pipeline([nodes[name]])
test_pipeline += modular_pipeline([nodes[name]._copy(func=exception_fn)])
with pytest.raises(Exception, match="test exception"):
SequentialRunner().run(
test_pipeline,
persistent_dataset_catalog,
hook_manager=_create_hook_manager(),
)
assert re.search(expected_pattern, caplog.text) | Stricter version of previous test.
Covers pipelines where inputs are shared across nodes. | test_stricter_suggest_resume_scenario | python | kedro-org/kedro | tests/runner/test_sequential_runner.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_sequential_runner.py | Apache-2.0 |
def test_thread_run_with_patterns(self, catalog_type):
"""Test warm-up is done and patterns are resolved before running pipeline.
Without the warm-up "Dataset 'dummy_1' has already been registered" error
would be raised for this test. We check that the dataset was registered at the
warm-up, and we successfully passed to loading it.
"""
catalog_conf = {"{catch_all}": {"type": "MemoryDataset"}}
catalog = catalog_type.from_config(catalog_conf)
test_pipeline = pipeline(
[
node(identity, inputs="dummy_1", outputs="output_1", name="node_1"),
node(identity, inputs="dummy_2", outputs="output_2", name="node_2"),
node(identity, inputs="dummy_1", outputs="output_3", name="node_3"),
]
)
with pytest.raises(
Exception, match="Data for MemoryDataset has not been saved yet"
):
ThreadRunner().run(test_pipeline, catalog) | Test warm-up is done and patterns are resolved before running pipeline.
Without the warm-up "Dataset 'dummy_1' has already been registered" error
would be raised for this test. We check that the dataset was registered at the
warm-up, and we successfully passed to loading it. | test_thread_run_with_patterns | python | kedro-org/kedro | tests/runner/test_thread_runner.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_thread_runner.py | Apache-2.0 |
def test_specified_max_workers(
self,
mocker,
fan_out_fan_in,
catalog,
user_specified_number,
expected_number,
):
"""
We initialize the runner with max_workers=4.
`fan_out_fan_in` pipeline needs 3 threads.
A pool with 3 workers should be used.
"""
executor_cls_mock = mocker.patch(
"kedro.runner.thread_runner.ThreadPoolExecutor",
wraps=ThreadPoolExecutor,
)
catalog.add_feed_dict({"A": 42})
result = ThreadRunner(max_workers=user_specified_number).run(
fan_out_fan_in, catalog
)
assert result == {"Z": (42, 42, 42)}
executor_cls_mock.assert_called_once_with(max_workers=expected_number) | We initialize the runner with max_workers=4.
`fan_out_fan_in` pipeline needs 3 threads.
A pool with 3 workers should be used. | test_specified_max_workers | python | kedro-org/kedro | tests/runner/test_thread_runner.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_thread_runner.py | Apache-2.0 |
def test_stricter_suggest_resume_scenario(
self,
caplog,
two_branches_crossed_pipeline_variable_inputs,
persistent_dataset_catalog,
failing_node_names,
expected_pattern,
):
"""
Stricter version of previous test.
Covers pipelines where inputs are shared across nodes.
"""
test_pipeline = two_branches_crossed_pipeline_variable_inputs
nodes = {n.name: n for n in test_pipeline.nodes}
for name in failing_node_names:
test_pipeline -= modular_pipeline([nodes[name]])
test_pipeline += modular_pipeline([nodes[name]._copy(func=exception_fn)])
with pytest.raises(Exception, match="test exception"):
ThreadRunner(max_workers=1).run(
test_pipeline,
persistent_dataset_catalog,
hook_manager=_create_hook_manager(),
)
assert re.search(expected_pattern, caplog.text) | Stricter version of previous test.
Covers pipelines where inputs are shared across nodes. | test_stricter_suggest_resume_scenario | python | kedro-org/kedro | tests/runner/test_thread_runner.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_thread_runner.py | Apache-2.0 |
def test_simple_pipeline(
self,
pipeline_name,
persistent_dataset_catalog,
remaining_node_names,
expected_result,
request,
):
"""
Test suggestion for simple pipelines with a mix of persistent
and memory datasets.
"""
test_pipeline = request.getfixturevalue(pipeline_name)
remaining_nodes = test_pipeline.only_nodes(*remaining_node_names).nodes
result_node_names = _find_nodes_to_resume_from(
test_pipeline, remaining_nodes, persistent_dataset_catalog
)
assert expected_result == result_node_names | Test suggestion for simple pipelines with a mix of persistent
and memory datasets. | test_simple_pipeline | python | kedro-org/kedro | tests/runner/test_resume_logic.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_resume_logic.py | Apache-2.0 |
def test_all_datasets_persistent(
self,
pipeline_name,
persistent_dataset_catalog,
remaining_node_names,
expected_result,
request,
):
"""
Test suggestion for pipelines where all datasets are persisted:
In that case, exactly the set of remaining nodes should be re-run.
"""
test_pipeline = request.getfixturevalue(pipeline_name)
catalog = DataCatalog(
dict.fromkeys(
test_pipeline.datasets(),
LambdaDataset(load=lambda: 42, save=lambda data: None),
)
)
remaining_nodes = set(test_pipeline.only_nodes(*remaining_node_names).nodes)
result_node_names = _find_nodes_to_resume_from(
test_pipeline,
remaining_nodes,
catalog,
)
final_pipeline_nodes = set(test_pipeline.from_nodes(*result_node_names).nodes)
assert final_pipeline_nodes == remaining_nodes | Test suggestion for pipelines where all datasets are persisted:
In that case, exactly the set of remaining nodes should be re-run. | test_all_datasets_persistent | python | kedro-org/kedro | tests/runner/test_resume_logic.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_resume_logic.py | Apache-2.0 |
def test_added_shared_input(
self,
pipeline_name,
persistent_dataset_catalog,
remaining_node_names,
expected_result,
extra_input,
request,
):
"""
Test suggestion for pipelines where a single persistent dataset or
parameter is shared across all nodes. These do not change and
therefore should not affect resume suggestion.
"""
test_pipeline = request.getfixturevalue(pipeline_name)
# Add parameter shared across all nodes
test_pipeline = modular_pipeline(
[n._copy(inputs=[*n.inputs, extra_input]) for n in test_pipeline.nodes]
)
remaining_nodes = test_pipeline.only_nodes(*remaining_node_names).nodes
result_node_names = _find_nodes_to_resume_from(
test_pipeline, remaining_nodes, persistent_dataset_catalog
)
assert expected_result == result_node_names | Test suggestion for pipelines where a single persistent dataset or
parameter is shared across all nodes. These do not change and
therefore should not affect resume suggestion. | test_added_shared_input | python | kedro-org/kedro | tests/runner/test_resume_logic.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_resume_logic.py | Apache-2.0 |
def test_suggestion_consistency(
self,
pipeline_name,
persistent_dataset_catalog,
remaining_node_names,
expected_result,
request,
):
"""
Test that suggestions are internally consistent; pipeline generated
from resume nodes should exactly contain set of all required nodes.
"""
test_pipeline = request.getfixturevalue(pipeline_name)
remaining_nodes = test_pipeline.only_nodes(*remaining_node_names).nodes
required_nodes = _find_all_nodes_for_resumed_pipeline(
test_pipeline, remaining_nodes, persistent_dataset_catalog
)
resume_node_names = _find_nodes_to_resume_from(
test_pipeline, remaining_nodes, persistent_dataset_catalog
)
assert {n.name for n in required_nodes} == {
n.name for n in test_pipeline.from_nodes(*resume_node_names).nodes
} | Test that suggestions are internally consistent; pipeline generated
from resume nodes should exactly contain set of all required nodes. | test_suggestion_consistency | python | kedro-org/kedro | tests/runner/test_resume_logic.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_resume_logic.py | Apache-2.0 |
def test_specified_max_workers_bellow_cpu_cores_count(
self,
is_async,
mocker,
fan_out_fan_in,
catalog,
cpu_cores,
user_specified_number,
expected_number,
):
"""
The system has 2 cores, but we initialize the runner with max_workers=4.
`fan_out_fan_in` pipeline needs 3 processes.
A pool with 3 workers should be used.
"""
mocker.patch("os.cpu_count", return_value=cpu_cores)
executor_cls_mock = mocker.patch(
"kedro.runner.parallel_runner.ProcessPoolExecutor",
wraps=ProcessPoolExecutor,
)
catalog.add_feed_dict({"A": 42})
result = ParallelRunner(
max_workers=user_specified_number, is_async=is_async
).run(fan_out_fan_in, catalog)
assert result == {"Z": (42, 42, 42)}
executor_cls_mock.assert_called_once_with(max_workers=expected_number) | The system has 2 cores, but we initialize the runner with max_workers=4.
`fan_out_fan_in` pipeline needs 3 processes.
A pool with 3 workers should be used. | test_specified_max_workers_bellow_cpu_cores_count | python | kedro-org/kedro | tests/runner/test_parallel_runner.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_parallel_runner.py | Apache-2.0 |
def test_max_worker_windows(self, mocker):
"""The ProcessPoolExecutor on Python 3.7+
has a quirk with the max worker number on Windows
and requires it to be <=61
"""
mocker.patch("os.cpu_count", return_value=100)
mocker.patch("sys.platform", "win32")
parallel_runner = ParallelRunner()
assert parallel_runner._max_workers == _MAX_WINDOWS_WORKERS | The ProcessPoolExecutor on Python 3.7+
has a quirk with the max worker number on Windows
and requires it to be <=61 | test_max_worker_windows | python | kedro-org/kedro | tests/runner/test_parallel_runner.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_parallel_runner.py | Apache-2.0 |
def test_task_node_validation(self, is_async, fan_out_fan_in, catalog):
"""ParallelRunner cannot serialise the lambda function."""
catalog.add_feed_dict({"A": 42})
pipeline = modular_pipeline([fan_out_fan_in, node(lambda x: x, "Z", "X")])
with pytest.raises(AttributeError):
ParallelRunner(is_async=is_async).run(pipeline, catalog) | ParallelRunner cannot serialise the lambda function. | test_task_node_validation | python | kedro-org/kedro | tests/runner/test_parallel_runner.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_parallel_runner.py | Apache-2.0 |
def test_task_dataset_validation(self, is_async, fan_out_fan_in, catalog):
"""ParallelRunner cannot serialise datasets marked with `_SINGLE_PROCESS`."""
catalog.add("A", SingleProcessDataset())
with pytest.raises(AttributeError):
ParallelRunner(is_async=is_async).run(fan_out_fan_in, catalog) | ParallelRunner cannot serialise datasets marked with `_SINGLE_PROCESS`. | test_task_dataset_validation | python | kedro-org/kedro | tests/runner/test_parallel_runner.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_parallel_runner.py | Apache-2.0 |
def test_memory_dataset_output(self, is_async, fan_out_fan_in):
"""ParallelRunner does not support output to externally
created MemoryDatasets.
"""
pipeline = modular_pipeline([fan_out_fan_in])
catalog = DataCatalog({"C": MemoryDataset()}, {"A": 42})
with pytest.raises(AttributeError, match="['C']"):
ParallelRunner(is_async=is_async).run(pipeline, catalog) | ParallelRunner does not support output to externally
created MemoryDatasets. | test_memory_dataset_output | python | kedro-org/kedro | tests/runner/test_parallel_runner.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_parallel_runner.py | Apache-2.0 |
def test_dataset_not_serialisable(self, is_async, fan_out_fan_in):
"""Data set A cannot be serialisable because _load and _save are not
defined in global scope.
"""
def _load():
return 0 # pragma: no cover
def _save(arg):
assert arg == 0 # pragma: no cover
# Data set A cannot be serialised
catalog = DataCatalog({"A": LambdaDataset(load=_load, save=_save)})
pipeline = modular_pipeline([fan_out_fan_in])
with pytest.raises(AttributeError, match="['A']"):
ParallelRunner(is_async=is_async).run(pipeline, catalog) | Data set A cannot be serialisable because _load and _save are not
defined in global scope. | test_dataset_not_serialisable | python | kedro-org/kedro | tests/runner/test_parallel_runner.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_parallel_runner.py | Apache-2.0 |
def test_memory_dataset_not_serialisable(self, is_async, catalog):
"""Memory dataset cannot be serialisable because of data it stores."""
data = return_not_serialisable(None)
pipeline = modular_pipeline([node(return_not_serialisable, "A", "B")])
catalog.add_feed_dict(feed_dict={"A": 42})
pattern = (
rf"{data.__class__!s} cannot be serialised. ParallelRunner implicit "
rf"memory datasets can only be used with serialisable data"
)
with pytest.raises(DatasetError, match=pattern):
ParallelRunner(is_async=is_async).run(pipeline, catalog) | Memory dataset cannot be serialisable because of data it stores. | test_memory_dataset_not_serialisable | python | kedro-org/kedro | tests/runner/test_parallel_runner.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_parallel_runner.py | Apache-2.0 |
def test_unable_to_schedule_all_nodes(
self, mocker, is_async, fan_out_fan_in, catalog
):
"""Test the error raised when `futures` variable is empty,
but `todo_nodes` is not (can barely happen in real life).
"""
catalog.add_feed_dict({"A": 42})
runner = ParallelRunner(is_async=is_async)
real_node_deps = fan_out_fan_in.node_dependencies
# construct deliberately unresolvable dependencies for all
# pipeline nodes, so that none can be run
fake_node_deps = {k: {"you_shall_not_pass"} for k in real_node_deps}
# property mock requires patching a class, not an instance
mocker.patch(
"kedro.pipeline.Pipeline.node_dependencies",
new_callable=mocker.PropertyMock,
return_value=fake_node_deps,
)
pattern = "Unable to schedule new tasks although some nodes have not been run"
with pytest.raises(RuntimeError, match=pattern):
runner.run(fan_out_fan_in, catalog) | Test the error raised when `futures` variable is empty,
but `todo_nodes` is not (can barely happen in real life). | test_unable_to_schedule_all_nodes | python | kedro-org/kedro | tests/runner/test_parallel_runner.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_parallel_runner.py | Apache-2.0 |
def test_stricter_suggest_resume_scenario(
self,
caplog,
two_branches_crossed_pipeline_variable_inputs,
logging_dataset_catalog,
failing_node_names,
expected_pattern,
):
"""
Stricter version of previous test.
Covers pipelines where inputs are shared across nodes.
"""
test_pipeline = two_branches_crossed_pipeline_variable_inputs
nodes = {n.name: n for n in test_pipeline.nodes}
for name in failing_node_names:
test_pipeline -= modular_pipeline([nodes[name]])
test_pipeline += modular_pipeline([nodes[name]._copy(func=exception_fn)])
with pytest.raises(Exception, match="test exception"):
ParallelRunner().run(
test_pipeline,
logging_dataset_catalog,
hook_manager=_create_hook_manager(),
)
assert re.search(expected_pattern, caplog.text) | Stricter version of previous test.
Covers pipelines where inputs are shared across nodes. | test_stricter_suggest_resume_scenario | python | kedro-org/kedro | tests/runner/test_parallel_runner.py | https://github.com/kedro-org/kedro/blob/master/tests/runner/test_parallel_runner.py | Apache-2.0 |
def load_obj(obj_path: str, default_obj_path: str = "") -> Any:
"""Extract an object from a given path.
Args:
obj_path: Path to an object to be extracted, including the object name.
default_obj_path: Default object path.
Returns:
Extracted object.
Raises:
AttributeError: When the object does not have the given named attribute.
"""
obj_path_list = obj_path.rsplit(".", 1)
obj_path = obj_path_list.pop(0) if len(obj_path_list) > 1 else default_obj_path
obj_name = obj_path_list[0]
module_obj = importlib.import_module(obj_path)
return getattr(module_obj, obj_name) | Extract an object from a given path.
Args:
obj_path: Path to an object to be extracted, including the object name.
default_obj_path: Default object path.
Returns:
Extracted object.
Raises:
AttributeError: When the object does not have the given named attribute. | load_obj | python | kedro-org/kedro | kedro/utils.py | https://github.com/kedro-org/kedro/blob/master/kedro/utils.py | Apache-2.0 |
def _is_databricks() -> bool:
"""Evaluate if the current run environment is Databricks or not.
Useful to tailor environment-dependent activities like Kedro magic commands
or logging features that Databricks doesn't support.
Returns:
True if run environment is Databricks, otherwise False.
"""
return "DATABRICKS_RUNTIME_VERSION" in os.environ | Evaluate if the current run environment is Databricks or not.
Useful to tailor environment-dependent activities like Kedro magic commands
or logging features that Databricks doesn't support.
Returns:
True if run environment is Databricks, otherwise False. | _is_databricks | python | kedro-org/kedro | kedro/utils.py | https://github.com/kedro-org/kedro/blob/master/kedro/utils.py | Apache-2.0 |
def _is_project(project_path: Union[str, Path]) -> bool:
"""Evaluate if a given path is a root directory of a Kedro project or not.
Args:
project_path: Path to be tested for being a root of a Kedro project.
Returns:
True if a given path is a root directory of a Kedro project, otherwise False.
"""
metadata_file = Path(project_path).expanduser().resolve() / _PYPROJECT
if not metadata_file.is_file():
return False
try:
return "[tool.kedro]" in metadata_file.read_text(encoding="utf-8")
except Exception:
return False | Evaluate if a given path is a root directory of a Kedro project or not.
Args:
project_path: Path to be tested for being a root of a Kedro project.
Returns:
True if a given path is a root directory of a Kedro project, otherwise False. | _is_project | python | kedro-org/kedro | kedro/utils.py | https://github.com/kedro-org/kedro/blob/master/kedro/utils.py | Apache-2.0 |
def _find_kedro_project(current_dir: Path) -> Any: # pragma: no cover
"""Given a path, find a Kedro project associated with it.
Can be:
- Itself, if a path is a root directory of a Kedro project.
- One of its parents, if self is not a Kedro project but one of the parent path is.
- None, if neither self nor any parent path is a Kedro project.
Returns:
Kedro project associated with a given path,
or None if no relevant Kedro project is found.
"""
paths_to_check = [current_dir, *list(current_dir.parents)]
for parent_dir in paths_to_check:
if _is_project(parent_dir):
return parent_dir
return None | Given a path, find a Kedro project associated with it.
Can be:
- Itself, if a path is a root directory of a Kedro project.
- One of its parents, if self is not a Kedro project but one of the parent path is.
- None, if neither self nor any parent path is a Kedro project.
Returns:
Kedro project associated with a given path,
or None if no relevant Kedro project is found. | _find_kedro_project | python | kedro-org/kedro | kedro/utils.py | https://github.com/kedro-org/kedro/blob/master/kedro/utils.py | Apache-2.0 |
def _has_rich_handler(logger: Optional[logging.Logger] = None) -> bool:
"""Returns true if the logger has a RichHandler attached."""
if not logger:
logger = logging.getLogger() # User root by default
try:
from rich.logging import RichHandler
except ImportError:
return False
return any(isinstance(handler, RichHandler) for handler in logger.handlers) | Returns true if the logger has a RichHandler attached. | _has_rich_handler | python | kedro-org/kedro | kedro/utils.py | https://github.com/kedro-org/kedro/blob/master/kedro/utils.py | Apache-2.0 |
def _format_rich(value: str, markup: str) -> str:
"""Format string with rich markup"""
return f"[{markup}]{value}[/{markup}]" | Format string with rich markup | _format_rich | python | kedro-org/kedro | kedro/utils.py | https://github.com/kedro-org/kedro/blob/master/kedro/utils.py | Apache-2.0 |
def __init__( # noqa: PLR0913
self,
conf_source: str,
env: str | None = None,
runtime_params: dict[str, Any] | None = None,
*,
config_patterns: dict[str, list[str]] | None = None,
base_env: str | None = None,
default_run_env: str | None = None,
custom_resolvers: dict[str, Callable] | None = None,
merge_strategy: dict[str, str] | None = None,
):
"""Instantiates a ``OmegaConfigLoader``.
Args:
conf_source: Path to use as root directory for loading configuration.
env: Environment that will take precedence over base.
runtime_params: Extra parameters passed to a Kedro run.
config_patterns: Regex patterns that specify the naming convention for configuration
files so they can be loaded. Can be customised by supplying config_patterns as
in `CONFIG_LOADER_ARGS` in `settings.py`.
base_env: Name of the base environment. When the ``OmegaConfigLoader`` is used directly
this defaults to `None`. Otherwise, the value will come from the `CONFIG_LOADER_ARGS` in the project
settings, where base_env defaults to `"base"`.
This is used in the `conf_paths` property method to construct
the configuration paths.
default_run_env: Name of the default run environment. When the ``OmegaConfigLoader`` is used directly
this defaults to `None`. Otherwise, the value will come from the `CONFIG_LOADER_ARGS` in the project
settings, where default_run_env defaults to `"local"`.
Can be overridden by supplying the `env` argument.
custom_resolvers: A dictionary of custom resolvers to be registered. For more information,
see here: https://omegaconf.readthedocs.io/en/2.3_branch/custom_resolvers.html#custom-resolvers
merge_strategy: A dictionary that specifies the merging strategy for each configuration type.
The accepted merging strategies are `soft` and `destructive`. Defaults to `destructive`.
"""
self.base_env = base_env or ""
self.default_run_env = default_run_env or ""
self.merge_strategy = merge_strategy or {}
self._globals_oc: DictConfig | None = None
self._runtime_params_oc: DictConfig | None = None
self.config_patterns = {
"catalog": ["catalog*", "catalog*/**", "**/catalog*"],
"parameters": ["parameters*", "parameters*/**", "**/parameters*"],
"credentials": ["credentials*", "credentials*/**", "**/credentials*"],
"globals": ["globals.yml"],
}
self.config_patterns.update(config_patterns or {})
# Deactivate oc.env built-in resolver for OmegaConf
OmegaConf.clear_resolver("oc.env")
# Register user provided custom resolvers
self._custom_resolvers = custom_resolvers
if custom_resolvers:
self._register_new_resolvers(custom_resolvers)
# Register globals resolver
self._register_globals_resolver()
# Setup file system and protocol
self._fs, self._protocol = self._initialise_filesystem_and_protocol(conf_source)
super().__init__(
conf_source=conf_source,
env=env,
runtime_params=runtime_params,
)
try:
self._globals = self["globals"]
except MissingConfigException:
self._globals = {} | Instantiates a ``OmegaConfigLoader``.
Args:
conf_source: Path to use as root directory for loading configuration.
env: Environment that will take precedence over base.
runtime_params: Extra parameters passed to a Kedro run.
config_patterns: Regex patterns that specify the naming convention for configuration
files so they can be loaded. Can be customised by supplying config_patterns as
in `CONFIG_LOADER_ARGS` in `settings.py`.
base_env: Name of the base environment. When the ``OmegaConfigLoader`` is used directly
this defaults to `None`. Otherwise, the value will come from the `CONFIG_LOADER_ARGS` in the project
settings, where base_env defaults to `"base"`.
This is used in the `conf_paths` property method to construct
the configuration paths.
default_run_env: Name of the default run environment. When the ``OmegaConfigLoader`` is used directly
this defaults to `None`. Otherwise, the value will come from the `CONFIG_LOADER_ARGS` in the project
settings, where default_run_env defaults to `"local"`.
Can be overridden by supplying the `env` argument.
custom_resolvers: A dictionary of custom resolvers to be registered. For more information,
see here: https://omegaconf.readthedocs.io/en/2.3_branch/custom_resolvers.html#custom-resolvers
merge_strategy: A dictionary that specifies the merging strategy for each configuration type.
The accepted merging strategies are `soft` and `destructive`. Defaults to `destructive`. | __init__ | python | kedro-org/kedro | kedro/config/omegaconf_config.py | https://github.com/kedro-org/kedro/blob/master/kedro/config/omegaconf_config.py | Apache-2.0 |
def __getitem__(self, key: str) -> dict[str, Any]: # noqa: PLR0912
"""Get configuration files by key, load and merge them, and
return them in the form of a config dictionary.
Args:
key: Key of the configuration type to fetch.
Raises:
KeyError: If key provided isn't present in the config_patterns of this
``OmegaConfigLoader`` instance.
MissingConfigException: If no configuration files exist matching the patterns
mapped to the provided key.
Returns:
Dict[str, Any]: A Python dictionary with the combined
configuration from all configuration files.
"""
# Allow bypassing of loading config from patterns if a key and value have been set
# explicitly on the ``OmegaConfigLoader`` instance.
# Re-register runtime params resolver incase it was previously deactivated
self._register_runtime_params_resolver()
if key in self:
return super().__getitem__(key) # type: ignore[no-any-return]
if key not in self.config_patterns:
raise KeyError(
f"No config patterns were found for '{key}' in your config loader"
)
patterns = [*self.config_patterns[key]]
if key == "globals":
# "runtime_params" resolver is not allowed in globals.
OmegaConf.clear_resolver("runtime_params")
read_environment_variables = key == "credentials"
processed_files: set[Path] = set()
# Load base env config
if self._protocol == "file":
base_path = str(Path(self.conf_source) / self.base_env)
else:
base_path = str(Path(self._fs.ls("", detail=False)[-1]) / self.base_env)
try:
base_config = self.load_and_merge_dir_config( # type: ignore[no-untyped-call]
base_path, patterns, key, processed_files, read_environment_variables
)
except UnsupportedInterpolationType as exc:
if "runtime_params" in str(exc):
raise UnsupportedInterpolationType(
"The `runtime_params:` resolver is not supported for globals."
)
else:
raise exc
config = base_config
# Load chosen env config
run_env = self.env or self.default_run_env
# Return if chosen env config is the same as base config to avoid loading the same config twice
if run_env == self.base_env:
return config # type: ignore[no-any-return]
if self._protocol == "file":
env_path = str(Path(self.conf_source) / run_env)
else:
env_path = str(Path(self._fs.ls("", detail=False)[-1]) / run_env)
try:
env_config = self.load_and_merge_dir_config( # type: ignore[no-untyped-call]
env_path, patterns, key, processed_files, read_environment_variables
)
except UnsupportedInterpolationType as exc:
if "runtime_params" in str(exc):
raise UnsupportedInterpolationType(
"The `runtime_params:` resolver is not supported for globals."
)
else:
raise exc
resulting_config = self._merge_configs(config, env_config, key, env_path)
if not processed_files and key != "globals":
raise MissingConfigException(
f"No files of YAML or JSON format found in {base_path} or {env_path} matching"
f" the glob pattern(s): {[*self.config_patterns[key]]}"
)
return resulting_config # type: ignore[no-any-return] | Get configuration files by key, load and merge them, and
return them in the form of a config dictionary.
Args:
key: Key of the configuration type to fetch.
Raises:
KeyError: If key provided isn't present in the config_patterns of this
``OmegaConfigLoader`` instance.
MissingConfigException: If no configuration files exist matching the patterns
mapped to the provided key.
Returns:
Dict[str, Any]: A Python dictionary with the combined
configuration from all configuration files. | __getitem__ | python | kedro-org/kedro | kedro/config/omegaconf_config.py | https://github.com/kedro-org/kedro/blob/master/kedro/config/omegaconf_config.py | Apache-2.0 |
def load_and_merge_dir_config(
self,
conf_path: str,
patterns: Iterable[str],
key: str,
processed_files: set,
read_environment_variables: bool | None = False,
) -> dict[str, Any]:
"""Recursively load and merge all configuration files in a directory using OmegaConf,
which satisfy a given list of glob patterns from a specific path.
Args:
conf_path: Path to configuration directory.
patterns: List of glob patterns to match the filenames against.
key: Key of the configuration type to fetch.
processed_files: Set of files read for a given configuration type.
read_environment_variables: Whether to resolve environment variables.
Raises:
MissingConfigException: If configuration path doesn't exist or isn't valid.
ValueError: If two or more configuration files contain the same key(s).
ParserError: If config file contains invalid YAML or JSON syntax.
Returns:
Resulting configuration dictionary.
"""
if not self._fs.isdir(Path(conf_path).as_posix()):
raise MissingConfigException(
f"Given configuration path either does not exist "
f"or is not a valid directory: {conf_path}"
)
paths = []
for pattern in patterns:
for each in self._fs.glob(Path(f"{conf_path!s}/{pattern}").as_posix()):
if not self._is_hidden(each):
paths.append(Path(each))
deduplicated_paths = set(paths)
config_files_filtered = [
path for path in deduplicated_paths if self._is_valid_config_path(path)
]
config_per_file = {}
for config_filepath in config_files_filtered:
try:
with self._fs.open(str(config_filepath.as_posix())) as open_config:
# As fsspec doesn't allow the file to be read as StringIO,
# this is a workaround to read it as a binary file and decode it back to utf8.
tmp_fo = io.StringIO(open_config.read().decode("utf8"))
config = OmegaConf.load(tmp_fo)
processed_files.add(config_filepath)
if read_environment_variables:
self._resolve_environment_variables(config)
config_per_file[config_filepath] = config
except (ParserError, ScannerError) as exc:
line = exc.problem_mark.line
cursor = exc.problem_mark.column
raise ParserError(
f"Invalid YAML or JSON file {Path(config_filepath).as_posix()},"
f" unable to read line {line}, position {cursor}."
) from exc
aggregate_config = config_per_file.values()
self._check_duplicates(key, config_per_file)
if not aggregate_config:
return {}
if key == "parameters":
# Merge with runtime parameters only for "parameters"
return OmegaConf.to_container(
OmegaConf.merge(*aggregate_config, self.runtime_params), resolve=True
)
merged_config_container = OmegaConf.to_container(
OmegaConf.merge(*aggregate_config), resolve=True
)
return {
k: v for k, v in merged_config_container.items() if not k.startswith("_")
} | Recursively load and merge all configuration files in a directory using OmegaConf,
which satisfy a given list of glob patterns from a specific path.
Args:
conf_path: Path to configuration directory.
patterns: List of glob patterns to match the filenames against.
key: Key of the configuration type to fetch.
processed_files: Set of files read for a given configuration type.
read_environment_variables: Whether to resolve environment variables.
Raises:
MissingConfigException: If configuration path doesn't exist or isn't valid.
ValueError: If two or more configuration files contain the same key(s).
ParserError: If config file contains invalid YAML or JSON syntax.
Returns:
Resulting configuration dictionary. | load_and_merge_dir_config | python | kedro-org/kedro | kedro/config/omegaconf_config.py | https://github.com/kedro-org/kedro/blob/master/kedro/config/omegaconf_config.py | Apache-2.0 |
def _initialise_filesystem_and_protocol(
conf_source: str,
) -> tuple[fsspec.AbstractFileSystem, str]:
"""Set up the file system based on the file type detected in conf_source."""
file_mimetype, _ = mimetypes.guess_type(conf_source)
if file_mimetype == "application/x-tar":
protocol = "tar"
elif file_mimetype in (
"application/zip",
"application/x-zip-compressed",
"application/zip-compressed",
):
protocol = "zip"
else:
protocol = "file"
fs = fsspec.filesystem(protocol=protocol, fo=conf_source)
return fs, protocol | Set up the file system based on the file type detected in conf_source. | _initialise_filesystem_and_protocol | python | kedro-org/kedro | kedro/config/omegaconf_config.py | https://github.com/kedro-org/kedro/blob/master/kedro/config/omegaconf_config.py | Apache-2.0 |
def _is_valid_config_path(self, path: Path) -> bool:
"""Check if given path is a file path and file type is yaml or json."""
posix_path = path.as_posix()
return self._fs.isfile(str(posix_path)) and path.suffix in [
".yml",
".yaml",
".json",
] | Check if given path is a file path and file type is yaml or json. | _is_valid_config_path | python | kedro-org/kedro | kedro/config/omegaconf_config.py | https://github.com/kedro-org/kedro/blob/master/kedro/config/omegaconf_config.py | Apache-2.0 |
def _register_globals_resolver(self) -> None:
"""Register the globals resolver"""
OmegaConf.register_new_resolver(
"globals",
self._get_globals_value,
replace=True,
) | Register the globals resolver | _register_globals_resolver | python | kedro-org/kedro | kedro/config/omegaconf_config.py | https://github.com/kedro-org/kedro/blob/master/kedro/config/omegaconf_config.py | Apache-2.0 |
def _get_globals_value(self, variable: str, default_value: Any = _NO_VALUE) -> Any:
"""Return the globals values to the resolver"""
if variable.startswith("_"):
raise InterpolationResolutionError(
"Keys starting with '_' are not supported for globals."
)
if not self._globals_oc:
self._globals_oc = OmegaConf.create(self._globals)
interpolated_value = OmegaConf.select(
self._globals_oc, variable, default=default_value
)
if interpolated_value != _NO_VALUE:
return interpolated_value
else:
raise InterpolationResolutionError(
f"Globals key '{variable}' not found and no default value provided."
) | Return the globals values to the resolver | _get_globals_value | python | kedro-org/kedro | kedro/config/omegaconf_config.py | https://github.com/kedro-org/kedro/blob/master/kedro/config/omegaconf_config.py | Apache-2.0 |
def _get_runtime_value(self, variable: str, default_value: Any = _NO_VALUE) -> Any:
"""Return the runtime params values to the resolver"""
if not self._runtime_params_oc:
self._runtime_params_oc = OmegaConf.create(self.runtime_params)
interpolated_value = OmegaConf.select(
self._runtime_params_oc, variable, default=default_value
)
if interpolated_value != _NO_VALUE:
return interpolated_value
else:
raise InterpolationResolutionError(
f"Runtime parameter '{variable}' not found and no default value provided."
) | Return the runtime params values to the resolver | _get_runtime_value | python | kedro-org/kedro | kedro/config/omegaconf_config.py | https://github.com/kedro-org/kedro/blob/master/kedro/config/omegaconf_config.py | Apache-2.0 |
def _register_new_resolvers(resolvers: dict[str, Callable]) -> None:
"""Register custom resolvers"""
for name, resolver in resolvers.items():
if not OmegaConf.has_resolver(name):
msg = f"Registering new custom resolver: {name}"
_config_logger.debug(msg)
OmegaConf.register_new_resolver(name=name, resolver=resolver) | Register custom resolvers | _register_new_resolvers | python | kedro-org/kedro | kedro/config/omegaconf_config.py | https://github.com/kedro-org/kedro/blob/master/kedro/config/omegaconf_config.py | Apache-2.0 |
def _resolve_environment_variables(config: DictConfig) -> None:
"""Use the ``oc.env`` resolver to read environment variables and replace
them in-place, clearing the resolver after the operation is complete if
it was not registered beforehand.
Arguments:
config {Dict[str, Any]} -- The configuration dictionary to resolve.
"""
if not OmegaConf.has_resolver("oc.env"):
OmegaConf.register_new_resolver("oc.env", oc.env)
OmegaConf.resolve(config)
OmegaConf.clear_resolver("oc.env")
else:
OmegaConf.resolve(config) | Use the ``oc.env`` resolver to read environment variables and replace
them in-place, clearing the resolver after the operation is complete if
it was not registered beforehand.
Arguments:
config {Dict[str, Any]} -- The configuration dictionary to resolve. | _resolve_environment_variables | python | kedro-org/kedro | kedro/config/omegaconf_config.py | https://github.com/kedro-org/kedro/blob/master/kedro/config/omegaconf_config.py | Apache-2.0 |
def _is_hidden(self, path_str: str) -> bool:
"""Check if path contains any hidden directory or is a hidden file"""
path = Path(path_str)
conf_path = Path(self.conf_source).resolve().as_posix()
if self._protocol == "file":
path = path.resolve()
posix_path = path.as_posix()
if posix_path.startswith(conf_path):
posix_path = posix_path.replace(conf_path, "")
parts = posix_path.split(self._fs.sep) # filesystem specific separator
HIDDEN = "."
# Check if any component (folder or file) starts with a dot (.)
return any(part.startswith(HIDDEN) for part in parts) | Check if path contains any hidden directory or is a hidden file | _is_hidden | python | kedro-org/kedro | kedro/config/omegaconf_config.py | https://github.com/kedro-org/kedro/blob/master/kedro/config/omegaconf_config.py | Apache-2.0 |
def _transcode_split(element: str) -> tuple[str, str]:
"""Split the name by the transcoding separator.
If the transcoding part is missing, empty string will be put in.
Returns:
Node input/output name before the transcoding separator, if present.
Raises:
ValueError: Raised if more than one transcoding separator
is present in the name.
"""
split_name = element.split(TRANSCODING_SEPARATOR)
if len(split_name) > 2: # noqa: PLR2004
raise ValueError(
f"Expected maximum 1 transcoding separator, found {len(split_name) - 1} "
f"instead: '{element}'."
)
if len(split_name) == 1:
split_name.append("")
return tuple(split_name) # type: ignore | Split the name by the transcoding separator.
If the transcoding part is missing, empty string will be put in.
Returns:
Node input/output name before the transcoding separator, if present.
Raises:
ValueError: Raised if more than one transcoding separator
is present in the name. | _transcode_split | python | kedro-org/kedro | kedro/pipeline/transcoding.py | https://github.com/kedro-org/kedro/blob/master/kedro/pipeline/transcoding.py | Apache-2.0 |
def _strip_transcoding(element: str) -> str:
"""Strip out the transcoding separator and anything that follows.
Returns:
Node input/output name before the transcoding separator, if present.
Raises:
ValueError: Raised if more than one transcoding separator
is present in the name.
"""
return _transcode_split(element)[0] | Strip out the transcoding separator and anything that follows.
Returns:
Node input/output name before the transcoding separator, if present.
Raises:
ValueError: Raised if more than one transcoding separator
is present in the name. | _strip_transcoding | python | kedro-org/kedro | kedro/pipeline/transcoding.py | https://github.com/kedro-org/kedro/blob/master/kedro/pipeline/transcoding.py | Apache-2.0 |
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