Apply PEP 604 union type syntax codemod (facebook#2808)

Summary:
This codemods all `Optional[X]` type definitions to use the PEP 604 syntax `X | None` instead.

Pull Request resolved: facebook#2808

Reviewed By: mpolson64

Differential Revision: D63764095

Pulled By: Balandat

fbshipit-source-id: 79ccaf16011b4ba06d29230586f2ef3a7ba889d8

ax/analysis/analysis.py

@@ -5,9 +5,10 @@
 
 # pyre-strict
 
+from collections.abc import Iterable
 from enum import Enum
 from logging import Logger
-from typing import Iterable, Optional, Protocol
+from typing import Protocol
 
 import pandas as pd
 from ax.core.experiment import Experiment
@@ -105,8 +106,8 @@ class Analysis(Protocol):
 
     def compute(
         self,
-        experiment: Optional[Experiment] = None,
-        generation_strategy: Optional[GenerationStrategyInterface] = None,
+        experiment: Experiment | None = None,
+        generation_strategy: GenerationStrategyInterface | None = None,
     ) -> AnalysisCard:
         # Note: when implementing compute always prefer experiment.lookup_data() to
         # experiment.fetch_data() to avoid unintential data fetching within the report
@@ -115,8 +116,8 @@ def compute(
 
     def compute_result(
         self,
-        experiment: Optional[Experiment] = None,
-        generation_strategy: Optional[GenerationStrategyInterface] = None,
+        experiment: Experiment | None = None,
+        generation_strategy: GenerationStrategyInterface | None = None,
     ) -> Result[AnalysisCard, ExceptionE]:
         """
         Utility method to compute an AnalysisCard as a Result. This can be useful for

ax/analysis/healthcheck/healthcheck_analysis.py

@@ -6,7 +6,6 @@
 # pyre-strict
 import json
 from enum import IntEnum
-from typing import Optional
 
 from ax.analysis.analysis import AnalysisCard
 from ax.core.experiment import Experiment
@@ -33,6 +32,6 @@ class HealthcheckAnalysis:
 
     def compute(
         self,
-        experiment: Optional[Experiment] = None,
-        generation_strategy: Optional[GenerationStrategy] = None,
+        experiment: Experiment | None = None,
+        generation_strategy: GenerationStrategy | None = None,
     ) -> HealthcheckAnalysisCard: ...

ax/analysis/markdown/markdown_analysis.py

@@ -5,7 +5,6 @@
 
 # pyre-strict
 
-from typing import Optional
 
 from ax.analysis.analysis import Analysis, AnalysisCard
 from ax.core.experiment import Experiment
@@ -34,6 +33,6 @@ class MarkdownAnalysis(Analysis):
 
     def compute(
         self,
-        experiment: Optional[Experiment] = None,
-        generation_strategy: Optional[GenerationStrategyInterface] = None,
+        experiment: Experiment | None = None,
+        generation_strategy: GenerationStrategyInterface | None = None,
     ) -> MarkdownAnalysisCard: ...

ax/analysis/old/analysis_report.py

@@ -5,7 +5,6 @@
 
 # pyre-strict
 
-from typing import Optional
 
 import pandas as pd
 import plotly.graph_objects as go
@@ -27,15 +26,15 @@ class AnalysisReport:
     analyses: list[BaseAnalysis] = []
     experiment: Experiment
 
-    time_started: Optional[int] = None
-    time_completed: Optional[int] = None
+    time_started: int | None = None
+    time_completed: int | None = None
 
     def __init__(
         self,
         experiment: Experiment,
         analyses: list[BaseAnalysis],
-        time_started: Optional[int] = None,
-        time_completed: Optional[int] = None,
+        time_started: int | None = None,
+        time_completed: int | None = None,
     ) -> None:
         """
         This class is a collection of AnalysisReport.
@@ -65,7 +64,7 @@ def run_analysis_report(
         tuple[
             BaseAnalysis,
             pd.DataFrame,
-            Optional[go.Figure],
+            go.Figure | None,
         ]
     ]:
         """

ax/analysis/old/base_analysis.py

@@ -5,7 +5,6 @@
 
 # pyre-strict
 
-from typing import Optional
 
 import pandas as pd
 from ax.core.experiment import Experiment
@@ -21,7 +20,7 @@ class BaseAnalysis:
     def __init__(
         self,
         experiment: Experiment,
-        df_input: Optional[pd.DataFrame] = None,
+        df_input: pd.DataFrame | None = None,
         # TODO: add support for passing in experiment name, and markdown message
     ) -> None:
         """
@@ -30,7 +29,7 @@ def __init__(
         we can pass the dataframe as an input.
         """
         self._experiment = experiment
-        self._df: Optional[pd.DataFrame] = df_input
+        self._df: pd.DataFrame | None = df_input
 
     @property
     def experiment(self) -> Experiment:

ax/analysis/old/base_plotly_visualization.py

@@ -5,7 +5,6 @@
 
 # pyre-strict
 
-from typing import Optional
 
 import pandas as pd
 
@@ -25,8 +24,8 @@ class BasePlotlyVisualization(BaseAnalysis):
     def __init__(
         self,
         experiment: Experiment,
-        df_input: Optional[pd.DataFrame] = None,
-        fig_input: Optional[go.Figure] = None,
+        df_input: pd.DataFrame | None = None,
+        fig_input: go.Figure | None = None,
     ) -> None:
         """
         Initialize the analysis with the experiment object.

ax/analysis/old/cross_validation_plot.py

@@ -6,7 +6,7 @@
 # pyre-strict
 
 from copy import deepcopy
-from typing import Any, Optional
+from typing import Any
 
 import pandas as pd
 
@@ -43,7 +43,7 @@ def __init__(
         self,
         experiment: Experiment,
         model: ModelBridge,
-        label_dict: Optional[dict[str, str]] = None,
+        label_dict: dict[str, str] | None = None,
         caption: str = CROSS_VALIDATION_CAPTION,
     ) -> None:
         """
@@ -56,7 +56,7 @@ def __init__(
         self.model = model
         self.cv: list[CVResult] = cross_validate(model=model)
 
-        self.label_dict: Optional[dict[str, str]] = label_dict
+        self.label_dict: dict[str, str] | None = label_dict
         if self.label_dict:
             self.cv = self.remap_label(cv_results=self.cv, label_dict=self.label_dict)
 

ax/analysis/old/helpers/cross_validation_helpers.py

@@ -6,7 +6,7 @@
 
 # pyre-strict
 
-from typing import Any, Optional
+from typing import Any
 
 import numpy as np
 import pandas as pd
@@ -186,7 +186,7 @@ def diagonal_trace(min_: float, max_: float, visible: bool = True) -> dict[str,
     )
 
 
-def default_value_se_raw(se_raw: Optional[list[float]], out_length: int) -> list[float]:
+def default_value_se_raw(se_raw: list[float] | None, out_length: int) -> list[float]:
     """
     Takes a list of standard errors and maps edge cases to default list
     of floats.

ax/analysis/old/helpers/plot_helpers.py

@@ -43,7 +43,7 @@ def _format_dict(param_dict: TParameterization, name: str = "Parameterization")
         )
     else:
         blob = "<br><em>{}:</em><br>{}".format(
-            name, "<br>".join("{}: {}".format(n, v) for n, v in param_dict.items())
+            name, "<br>".join(f"{n}: {v}" for n, v in param_dict.items())
         )
     return blob
 

ax/analysis/old/helpers/scatter_helpers.py

@@ -8,7 +8,7 @@
 
 import numbers
 
-from typing import Any, Optional
+from typing import Any
 
 import numpy as np
 import pandas as pd
@@ -119,7 +119,7 @@ def extract_mean_and_error_from_df(
 
 def make_label(
     arm_name: str,
-    x_axis_values: Optional[tuple[str, float, float]],
+    x_axis_values: tuple[str, float, float] | None,
     y_axis_values: tuple[str, float, float],
     param_blob: TParameterization,
     rel: bool,
@@ -240,8 +240,8 @@ def error_scatter_trace_from_df(
     df: pd.DataFrame,
     show_CI: bool = True,
     visible: bool = True,
-    y_axis_label: Optional[str] = None,
-    x_axis_label: Optional[str] = None,
+    y_axis_label: str | None = None,
+    x_axis_label: str | None = None,
 ) -> dict[str, Any]:
     """Plot scatterplot with error bars.
 

ax/analysis/old/predicted_outcomes_dot_plot.py

@@ -101,12 +101,12 @@ def get_fig(
                 reverse=True,
             )
 
-            name_order_axes["xaxis{}".format(i + 1)] = {
+            name_order_axes[f"xaxis{i + 1}"] = {
                 "categoryorder": "array",
                 "categoryarray": names_by_arm,
                 "type": "category",
             }
-            name_order_axes["yaxis{}".format(i + 1)] = {
+            name_order_axes[f"yaxis{i + 1}"] = {
                 "ticksuffix": "%",
                 "zerolinecolor": "red",
             }

ax/analysis/plotly/parallel_coordinates.py

@@ -5,7 +5,7 @@
 
 # pyre-strict
 
-from typing import Any, Optional
+from typing import Any
 
 import numpy as np
 import pandas as pd
@@ -32,7 +32,7 @@ class ParallelCoordinatesPlot(PlotlyAnalysis):
         - **PARAMETER_NAME: The value of said parameter for the arm, for each parameter
     """
 
-    def __init__(self, metric_name: Optional[str] = None) -> None:
+    def __init__(self, metric_name: str | None = None) -> None:
         """
         Args:
             metric_name: The name of the metric to plot. If not specified the objective
@@ -44,8 +44,8 @@ def __init__(self, metric_name: Optional[str] = None) -> None:
 
     def compute(
         self,
-        experiment: Optional[Experiment] = None,
-        generation_strategy: Optional[GenerationStrategyInterface] = None,
+        experiment: Experiment | None = None,
+        generation_strategy: GenerationStrategyInterface | None = None,
     ) -> PlotlyAnalysisCard:
         if experiment is None:
             raise UserInputError("ParallelCoordinatesPlot requires an Experiment")

ax/analysis/plotly/plotly_analysis.py

@@ -5,7 +5,6 @@
 
 # pyre-strict
 
-from typing import Optional
 
 from ax.analysis.analysis import Analysis, AnalysisCard
 from ax.core.experiment import Experiment
@@ -35,6 +34,6 @@ class PlotlyAnalysis(Analysis):
 
     def compute(
         self,
-        experiment: Optional[Experiment] = None,
-        generation_strategy: Optional[GenerationStrategyInterface] = None,
+        experiment: Experiment | None = None,
+        generation_strategy: GenerationStrategyInterface | None = None,
     ) -> PlotlyAnalysisCard: ...

ax/analysis/plotly/predicted_effects.py

@@ -4,7 +4,7 @@
 # LICENSE file in the root directory of this source tree.
 
 from itertools import chain
-from typing import Any, Optional
+from typing import Any
 
 import pandas as pd
 from ax.analysis.analysis import AnalysisCardLevel
@@ -43,8 +43,8 @@ def __init__(self, metric_name: str) -> None:
 
     def compute(
         self,
-        experiment: Optional[Experiment] = None,
-        generation_strategy: Optional[GenerationStrategyInterface] = None,
+        experiment: Experiment | None = None,
+        generation_strategy: GenerationStrategyInterface | None = None,
     ) -> PlotlyAnalysisCard:
         if experiment is None:
             raise UserInputError("PredictedEffectsPlot requires an Experiment.")
@@ -116,8 +116,8 @@ def _get_predictions(
     model: ModelBridge,
     metric_name: str,
     outcome_constraints: list[OutcomeConstraint],
-    gr: Optional[GeneratorRun] = None,
-    trial_index: Optional[int] = None,
+    gr: GeneratorRun | None = None,
+    trial_index: int | None = None,
 ) -> list[dict[str, Any]]:
     if gr is None:
         observations = model.get_training_data()
@@ -187,7 +187,7 @@ def _get_predictions(
     ]
 
 
-def _get_max_observed_trial_index(model: ModelBridge) -> Optional[int]:
+def _get_max_observed_trial_index(model: ModelBridge) -> int | None:
     """Returns the max observed trial index to appease multitask models for prediction
     by giving fixed features. This is not necessarily accurate and should eventually
     come from the generation strategy.

ax/benchmark/benchmark_metric.py

@@ -5,7 +5,7 @@
 
 # pyre-strict
 
-from typing import Any, Optional
+from typing import Any
 
 import pandas as pd
 from ax.core.base_trial import BaseTrial
@@ -26,7 +26,7 @@ def __init__(
         name: str,
         lower_is_better: bool,  # TODO: Do we need to define this here?
         observe_noise_sd: bool = True,
-        outcome_index: Optional[int] = None,
+        outcome_index: int | None = None,
     ) -> None:
         """
         Args:

ax/benchmark/benchmark_problem.py

@@ -7,7 +7,7 @@
 
 from collections.abc import Mapping
 from dataclasses import dataclass, field
-from typing import Any, Optional, Union
+from typing import Any
 
 import pandas as pd
 
@@ -38,7 +38,7 @@
 def _get_name(
     test_problem: BaseTestProblem,
     observe_noise_sd: bool,
-    dim: Optional[int] = None,
+    dim: int | None = None,
 ) -> str:
     """
     Get a string name describing the problem, in a format such as
@@ -86,7 +86,7 @@ class BenchmarkProblem(Base):
     name: str
     optimization_config: OptimizationConfig
     num_trials: int
-    observe_noise_stds: Union[bool, dict[str, bool]] = False
+    observe_noise_stds: bool | dict[str, bool] = False
     optimal_value: float
 
     search_space: SearchSpace = field(repr=False)

ax/benchmark/benchmark_result.py

@@ -12,7 +12,6 @@
 
 from collections.abc import Iterable
 from dataclasses import dataclass
-from typing import Optional
 
 import numpy as np
 from ax.core.experiment import Experiment
@@ -87,8 +86,8 @@ class BenchmarkResult(Base):
     fit_time: float
     gen_time: float
 
-    experiment: Optional[Experiment] = None
-    experiment_storage_id: Optional[str] = None
+    experiment: Experiment | None = None
+    experiment_storage_id: str | None = None
 
     def __post_init__(self) -> None:
         if self.experiment is not None and self.experiment_storage_id is not None: