From 818a108793804ab15d0569c4642c631d279a69f6 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=C3=89ric=20Dupuis?= <eric.dupuis.1@umontreal.ca>
Date: Fri, 25 Oct 2024 11:08:46 -0400
Subject: [PATCH] remove Union

---
 src/xscen/aggregate.py   | 2 +-
 src/xscen/catalog.py     | 4 ++--
 src/xscen/diagnostics.py | 8 +++-----
 src/xscen/indicators.py  | 4 ++--
 4 files changed, 8 insertions(+), 10 deletions(-)

diff --git a/src/xscen/aggregate.py b/src/xscen/aggregate.py
index 756e8bb5..32a9e187 100644
--- a/src/xscen/aggregate.py
+++ b/src/xscen/aggregate.py
@@ -952,7 +952,7 @@ def produce_horizon(  # noqa: C901
     ----------
     ds : xr.Dataset
         Input dataset with a time dimension.
-    indicators :  Union[str, os.PathLike, Sequence[Indicator], Sequence[Tuple[str, Indicator]], ModuleType]
+    indicators :  str | os.PathLike | Sequence[Indicator] | Sequence[Tuple[str, Indicator]] | ModuleType
         Indicators to compute. It will be passed to the `indicators` argument of `xs.compute_indicators`.
     periods : list of str or list of lists of str, optional
         Either [start, end] or list of [start_year, end_year] for the period(s) to be evaluated.
diff --git a/src/xscen/catalog.py b/src/xscen/catalog.py
index 08690228..a8445912 100644
--- a/src/xscen/catalog.py
+++ b/src/xscen/catalog.py
@@ -778,7 +778,7 @@ def update(
 
         Parameters
         ----------
-        df : Union[DataCatalog, intake_esm.esm_datastore, pd.DataFrame, pd.Series, Sequence[pd.Series]], optional
+        df : DataCatalog | intake_esm.esm_datastore | pd.DataFrame | pd.Series  | Sequence[pd.Series], optional
             Data to be added to the catalog. If None, nothing is added, but the catalog is still updated.
         """
         # Append the new DataFrame or Series
@@ -999,7 +999,7 @@ def unstack_id(df: pd.DataFrame | ProjectCatalog | DataCatalog) -> dict:
 
     Parameters
     ----------
-    df : Union[pd.DataFrame, ProjectCatalog, DataCatalog]
+    df : pd.DataFrame | ProjectCatalog | DataCatalog
         Either a Project/DataCatalog or a pandas DataFrame.
 
     Returns
diff --git a/src/xscen/diagnostics.py b/src/xscen/diagnostics.py
index 89af5733..dbd4b563 100644
--- a/src/xscen/diagnostics.py
+++ b/src/xscen/diagnostics.py
@@ -7,8 +7,6 @@
 from copy import deepcopy
 from pathlib import Path
 from types import ModuleType
-from typing import Union
-
 
 import numpy as np
 import xarray as xr
@@ -332,7 +330,7 @@ def properties_and_measures(  # noqa: C901
     ----------
     ds : xr.Dataset
         Input dataset.
-    properties : Union[str, os.PathLike, Sequence[Indicator], Sequence[tuple[str, Indicator]], ModuleType]
+    properties : str | os.PathLike | Sequence[Indicator] | Sequence[tuple[str, Indicator]] | ModuleType
         Path to a YAML file that instructs on how to calculate properties.
         Can be the indicator module directly, or a sequence of indicators or a sequence of
         tuples (indicator name, indicator) as returned by `iter_indicators()`.
@@ -535,7 +533,7 @@ def measures_heatmap(
 
 
 def measures_improvement(
-    meas_datasets: Union[list[xr.Dataset], dict],
+    meas_datasets: list[xr.Dataset] | dict,
     dim: str | Sequence[str] | None = None,
     to_level: str = "diag-improved",
 ) -> xr.Dataset:
@@ -544,7 +542,7 @@ def measures_improvement(
 
     Parameters
     ----------
-    meas_datasets: list of xr.Dataset or dict
+    meas_datasets: list[xr.Dataset] | dict
         List of 2 datasets: Initial dataset of measures and final (improved) dataset of measures.
         Both datasets must have the same variables.
         It is also possible to pass a dictionary where the values are the datasets and the key are not used.
diff --git a/src/xscen/indicators.py b/src/xscen/indicators.py
index 35bbe40d..68f096ab 100644
--- a/src/xscen/indicators.py
+++ b/src/xscen/indicators.py
@@ -123,7 +123,7 @@ def compute_indicators(  # noqa: C901
     ----------
     ds : xr.Dataset
         Dataset to use for the indicators.
-    indicators : Union[str, os.PathLike, Sequence[Indicator], Sequence[tuple[str, Indicator]], ModuleType]
+    indicators : str | os.PathLike | Sequence[Indicator] | Sequence[tuple[str, Indicator]] | ModuleType
         Path to a YAML file that instructs on how to calculate missing variables.
         Can also be only the "stem", if translations and custom indices are implemented.
         Can be the indicator module directly, or a sequence of indicators or a sequence of
@@ -349,7 +349,7 @@ def select_inds_for_avail_vars(
     ----------
     ds : xr.Dataset
         Dataset to use for the indicators.
-    indicators : Union[str, os.PathLike, Sequence[Indicator], Sequence[Tuple[str, Indicator]]]
+    indicators : str | os.PathLike | Sequence[Indicator] | Sequence[Tuple[str, Indicator]]
         Path to a YAML file that instructs on how to calculate indicators.
         Can also be only the "stem", if translations and custom indices are implemented.
         Can be the indicator module directly, or a sequence of indicators or a sequence of