Update configurations for ruff (mckinsey#304)

pyproject.toml

@@ -1,6 +1,15 @@
 # THIS IS NOT DESCRIBING A PACKAGE, but the DEV environment of this mono-repo
 # In order to install the packages of this mono-repo from source, refer to the pyproject.toml in the relevant folder
 
+[lint.isort]
+known-first-party = ["vizro"]
+
+[lint.pydocstyle]
+convention = "google"
+
+[lint.pylint]
+max-args = 6
+
 [project]
 authors = [
   {name = "Vizro Team"}
@@ -48,12 +57,18 @@ warn_required_dynamic_aliases = true
 warn_untyped_fields = true
 
 [tool.ruff]
+line-length = 120
+target-version = "py38"
+
+[tool.ruff.lint]
 # see: https://beta.ruff.rs/docs/rules/
 ignore = [
-  "D104"  # undocumented-public-package
+  "D104",  # undocumented-public-package
+  "D401",  # first-line should be in imperative mood
+  # D407 needs to be ignored as it otherwise messes up the formatting in our API docs
+  "D407"  # missing dashed underline after section
 ]
 ignore-init-module-imports = true
-line-length = 120
 select = [
   "E",  # pycodestyle errors
   "W",  # pycodestyle warnings
@@ -65,12 +80,8 @@ select = [
   "RUF",  # Ruff-specific rules
   "PL"  # pylint
 ]
-target-version = "py38"
-
-[tool.ruff.isort]
-known-first-party = ["vizro"]
 
-[tool.ruff.per-file-ignores]
+[tool.ruff.lint.per-file-ignores]
 # Ignore current false positives for pydantic models subclassing across files
 # See: https://github.com/astral-sh/ruff/issues/5243#issuecomment-1860776975
 "**/models/**" = ["RUF012"]
@@ -79,9 +90,3 @@ known-first-party = ["vizro"]
 "**/tests/**" = ["PLR2004", "S101", "TID252", "D100", "D101", "D102", "D103", "PLC1901", "RUF012"]
 # Ignore import violations in all __init__.py files
 "__init__.py" = ["E402", "F401"]
-
-[tool.ruff.pydocstyle]
-convention = "google"
-
-[tool.ruff.pylint]
-max-args = 6

tools/check_for_datafiles.py

@@ -24,8 +24,9 @@
 def check_for_data_files():
     """Recursively finds all data files in non-whitelisted folders.
 
-    Raises:
+    Raises
         AssertionError if data files are present in non-whitelisted folders.
+
     """
     project_dir = str(Path(__file__).parent.parent)
     whitelist_dir = {f"{project_dir}{dir}" for dir in whitelist_folders}

vizro-ai/changelog.d/20240208_161900_huong_li_nguyen_tidy_ruff.md

@@ -0,0 +1,48 @@
+<!--
+A new scriv changelog fragment.
+
+Uncomment the section that is right (remove the HTML comment wrapper).
+-->
+
+<!--
+### Highlights ✨
+
+- A bullet item for the Highlights ✨ category with a link to the relevant PR at the end of your entry, e.g. Enable feature XXX ([#1](https://github.com/mckinsey/vizro/pull/1))
+
+-->
+<!--
+### Removed
+
+- A bullet item for the Removed category with a link to the relevant PR at the end of your entry, e.g. Enable feature XXX ([#1](https://github.com/mckinsey/vizro/pull/1))
+
+-->
+<!--
+### Added
+
+- A bullet item for the Added category with a link to the relevant PR at the end of your entry, e.g. Enable feature XXX ([#1](https://github.com/mckinsey/vizro/pull/1))
+
+-->
+<!--
+### Changed
+
+- A bullet item for the Changed category with a link to the relevant PR at the end of your entry, e.g. Enable feature XXX ([#1](https://github.com/mckinsey/vizro/pull/1))
+
+-->
+<!--
+### Deprecated
+
+- A bullet item for the Deprecated category with a link to the relevant PR at the end of your entry, e.g. Enable feature XXX ([#1](https://github.com/mckinsey/vizro/pull/1))
+
+-->
+<!--
+### Fixed
+
+- A bullet item for the Fixed category with a link to the relevant PR at the end of your entry, e.g. Enable feature XXX ([#1](https://github.com/mckinsey/vizro/pull/1))
+
+-->
+<!--
+### Security
+
+- A bullet item for the Security category with a link to the relevant PR at the end of your entry, e.g. Enable feature XXX ([#1](https://github.com/mckinsey/vizro/pull/1))
+
+-->

vizro-ai/src/vizro_ai/_vizro_ai.py

@@ -25,6 +25,7 @@ def __init__(self, model_name: str = "gpt-3.5-turbo-0613", temperature: int = 0)
         Args:
             model_name: Model name in string format.
             temperature: Temperature parameter for LLM.
+
         """
         self.model_name = model_name
         self.temperature = temperature
@@ -97,6 +98,7 @@ def _get_chart_code(self, df: pd.DataFrame, user_input: str) -> str:
         Args:
             df: The dataframe to be analyzed
             user_input: User questions or descriptions of the desired visual
+
         """
         # TODO refine and update error handling
         return self._run_plot_tasks(df, user_input, explain=False).get("code_string")
@@ -111,6 +113,7 @@ def plot(
             user_input: User questions or descriptions of the desired visual.
             explain: Flag to include explanation in response.
             max_debug_retry: Maximum number of retries to debug errors. Defaults to `3`.
+
         """
         output_dict = self._run_plot_tasks(df, user_input, explain=explain, max_debug_retry=max_debug_retry)
         code_string = output_dict.get("code_string")

vizro-ai/src/vizro_ai/chains/_llm_chain.py

@@ -36,7 +36,7 @@ def execute_chain(self, input_str: str):
 class FunctionCallChain(VizroBaseChain, ABC):
     """LLM Chain with Function Calling."""
 
-    def __init__(
+    def __init__(  # noqa: PLR0913
         self,
         llm: LLM_MODELS,
         raw_prompt: str,
@@ -107,6 +107,7 @@ def execute_chain(self, input_str: str) -> Dict[str, Any]:
 
         Returns:
             args as a dictionary
+
         """
         raw_ans = self.chain.generate([{"input": input_str}])
         args = self._custom_parse(raw_ans.generations[0])

vizro-ai/src/vizro_ai/chains/_llm_models.py

@@ -38,10 +38,11 @@
 class LLM(BaseModel):
     """Represents a Language Learning Model (LLM).
 
-    Attributes:
+    Attributes
         name (str): The name of the LLM.
         max_tokens (int): The maximum number of tokens that the LLM can handle.
         wrapper (callable): The langchain function used to instantiate the model.
+
     """
 
     name: str
@@ -73,6 +74,7 @@ def get_llm_model(self, model_name: str, temperature: float = 0) -> LLM_MODELS:
 
         Raises:
             ValueError: If the model name is not found.
+
         """
         model = self.models.get(model_name.lower())
         if model:

vizro-ai/src/vizro_ai/components/_base.py

@@ -8,7 +8,7 @@
 class VizroAiComponentBase(ABC):
     """Abstract Base Class that represents a blueprint for Vizro-AI components.
 
-    Attributes:
+    Attributes
         prompt (str): Prompt for specific components.
 
     Public Methods:
@@ -17,6 +17,7 @@ class VizroAiComponentBase(ABC):
     Private Methods:
         _pre_process: A helper method for LLMChain input vars preprocess.
         _post_process: Another helper method for LLMChain output postprocess.
+
     """
 
     prompt: str = "default prompt place holder"
@@ -26,6 +27,7 @@ def __init__(self, llm: LLM_MODELS):
 
         Args:
             llm: LLM model wrapped with Langchain wrapper.
+
         """
         self.llm = llm
 

vizro-ai/src/vizro_ai/components/chart_selection.py

@@ -41,8 +41,9 @@ class ChartSelection(BaseModel):
 class GetChartSelection(VizroAiComponentBase):
     """Get Chart Types.
 
-    Attributes:
+    Attributes
         prompt (str): Prompt chart selection chains.
+
     """
 
     prompt: str = chart_type_prompt

vizro-ai/src/vizro_ai/components/code_validation.py

@@ -37,8 +37,9 @@ class CodeDebug(BaseModel):
 class GetDebugger(VizroAiComponentBase):
     """Get Visual code.
 
-    Attributes:
+    Attributes
         prompt (str): Prompt visual code.
+
     """
 
     prompt: str = debugging_prompt

vizro-ai/src/vizro_ai/components/custom_chart_wrap.py

@@ -41,8 +41,9 @@ class GetCustomChart(VizroAiComponentBase):
     # TODO Explore if it is possible to create CustomChart without LLM
     """Get custom chart code.
 
-    Attributes:
+    Attributes
         prompt (str): Prompt custom chart code.
+
     """
 
     prompt: str = custom_chart_prompt

vizro-ai/src/vizro_ai/components/dataframe_craft.py

@@ -44,8 +44,9 @@ class DataFrameCraft(BaseModel):
 class GetDataFrameCraft(VizroAiComponentBase):
     """Get dataframe code.
 
-    Attributes:
+    Attributes
         prompt (str): Prompt dataframe wrangling chain.
+
     """
 
     prompt: str = dataframe_prompt

vizro-ai/src/vizro_ai/components/explanation.py

@@ -37,8 +37,9 @@ class CodeExplanation(BaseModel):
 class GetCodeExplanation(VizroAiComponentBase):
     """Get Explanation of a code snippet.
 
-    Attributes:
+    Attributes
         prompt (str): Prompt code explanation.
+
     """
 
     prompt: str = code_explanation_prompt

vizro-ai/src/vizro_ai/components/visual_code.py

@@ -36,8 +36,9 @@ class VizroCode(BaseModel):
 class GetVisualCode(VizroAiComponentBase):
     """Get Visual code.
 
-    Attributes:
+    Attributes
         prompt (str): Prompt visual code.
+
     """
 
     prompt: str = visual_code_prompt

vizro-ai/src/vizro_ai/schema_manager/schema_manager.py

@@ -21,6 +21,7 @@ def register(self, obj: Union[Callable, BaseModel]):
 
         Args:
             obj (Union[Callable, BaseModel]): function or pydantic model to register
+
         """
         if inspect.isfunction(obj):
             annotations = obj.__annotations__

vizro-ai/src/vizro_ai/task_pipeline/_pipeline.py

@@ -13,6 +13,7 @@ def __init__(self, llm: LLM_MODELS):
 
         Args:
             llm: The LLM instance to be used by components in the pipeline.
+
         """
         self.llm = llm
         self.components = []
@@ -27,6 +28,7 @@ def add(self, component_class, input_keys: Optional[List[str]] = None, output_ke
                     These should match the output keys of previous components in the pipeline, if applicable.
             output_key: The key or identifier for the output that this component will produce.
                     This can be used as an input key for subsequent components.
+
         """
         self.components.append((component_class, input_keys, output_key))
 

vizro-ai/src/vizro_ai/task_pipeline/_pipeline_manager.py

@@ -13,6 +13,7 @@ def __init__(self, llm: LLM_MODELS = None):
 
         Args:
             llm: Large language Model.
+
         """
         self.llm = llm
 

vizro-ai/tests/unit/vizro-ai/components/test_code_validation.py

@@ -5,7 +5,7 @@
 
 @pytest.fixture
 def fake_llm():
-    """This is to simulate the response of LLM."""
+    """Simulate the response of LLM."""
     response = ['{{"fixed_code": "{}"}}'.format("print(df[['country', 'continent']])")]
     return FakeListLLM(responses=response)
 

vizro-ai/tests/unit/vizro-ai/components/test_custom_chart_wrap.py

@@ -83,7 +83,7 @@ def some_chart_name(data_frame):
 
 @pytest.fixture
 def fake_llm(output_custom_chart_LLM_1):
-    """This is to simulate the response of LLM."""
+    """Simulate the response of LLM."""
     response = ['{{"custom_chart_code": "{}"}}'.format(output_custom_chart_LLM_1)]
     return FakeListLLM(responses=response)
 

vizro-ai/tests/unit/vizro-ai/components/test_visual_code.py

@@ -72,7 +72,7 @@ def expected_final_output_2():
 
 @pytest.fixture
 def fake_llm(output_visual_code_LLM_1):
-    """This is to simulate the response of LLM."""
+    """Simulate the response of LLM."""
     response = ['{{"visual_code": "{}"}}'.format(output_visual_code_LLM_1)]
     return FakeListLLM(responses=response)
 
@@ -106,7 +106,14 @@ def test_post_process(self, input, output, df_code, request):
 
 
 class TestGetVisualCodeRun:
-    def test_fake_run(self, fake_llm, output_visual_code_LLM_1, expected_final_output_1, df_code_1, chart_types):
+    def test_fake_run(  # noqa: PLR0913
+        self,
+        fake_llm,
+        output_visual_code_LLM_1,
+        expected_final_output_1,
+        df_code_1,
+        chart_types,
+    ):
         get_visual_code = GetVisualCode(fake_llm)
         processed_code = get_visual_code.run(
             chain_input=output_visual_code_LLM_1, df_code=df_code_1, chart_types=chart_types

vizro-ai/tests/unit/vizro-ai/conftest.py

@@ -1,7 +1,6 @@
 """Fixtures to be shared across several tests."""
 
 import pytest
-
 import vizro.plotly.express as px