🚀 feat(*/*) Extend python versions to 3.9 and 3.10 (#76)

* feat(*/*) extend support for python 3.9 and 3.10

---------

Co-authored-by: Fabien Casenave <fabien.casenave@safrangroup.com>

Author: casenave

.github/workflows/testing.yml

@@ -16,7 +16,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: [3.11, 3.12]
+        python-version: ["3.9", "3.10", "3.11", "3.12"]
 
     steps:
       - name: Checkout code
@@ -33,16 +33,14 @@ jobs:
       - name: Modify environment.yml with matrix Python version (Linux/macOS)
         if: runner.os != 'Windows'
         run: |
-          python_version=${{ matrix.python-version }}
-          sed -i.bak "s/^  - python=.*/  - python=${python_version}/" environment.yml
+          sed -i.bak "s/^  - python=.*/  - python=${{ matrix.python-version }}/" environment.yml
 
       - name: Modify environment.yml with matrix Python version (Windows)
         if: runner.os == 'Windows'
         shell: powershell
         run: |
-          $python_version = '${{ matrix.python-version }}'
           $file = 'environment.yml'
-          (Get-Content $file) -replace '^\s+- python=.*', "  - python=$python_version" | Set-Content $file
+          (Get-Content $file) -replace '^\s+- python=.*', "  - python=${{ matrix.python-version }}" | Set-Content $file
 
       - name: Create environment
         run: |

environment.yml

@@ -3,7 +3,7 @@ channels:
   - conda-forge
   - nodefaults
 dependencies:
-  - python=3.12
+  - python=3.11
 ##### RUN #####
 #---# base
   - tqdm

pyproject.toml

@@ -8,7 +8,7 @@ build-backend = "setuptools.build_meta"
 name = "pyplaid"
 authors = [{name = "Safran", email = "fabien.casenave@safrangroup.com"}]
 description = "A package that implements a data model tailored for AI and ML in the context of physics problems"
-requires-python = ">=3.11, <3.13"
+requires-python = ">=3.9, <3.13"
 keywords=[
     "machine learning",
     "physics",
@@ -21,6 +21,8 @@ classifiers = [
     "Operating System :: MacOS",
     "Operating System :: POSIX",
     "Operating System :: Microsoft :: Windows",
+    "Programming Language :: Python :: 3.9",
+    "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
     "Topic :: Scientific/Engineering",

src/plaid/bridges/huggingface_bridge.py

@@ -1,7 +1,15 @@
 """Huggingface bridge for PLAID datasets."""
 
 import pickle
-from typing import Callable, Self
+import sys
+from typing import Callable
+
+if sys.version_info >= (3, 11):
+    from typing import Self
+else:  # pragma: no cover
+    from typing import TypeVar
+
+    Self = TypeVar("Self")
 
 import datasets
 

src/plaid/containers/dataset.py

@@ -8,11 +8,14 @@
 #
 
 # %% Imports
+import sys
 
-try:  # pragma: no cover
+if sys.version_info >= (3, 11):
     from typing import Self
-except ImportError:  # pragma: no cover
-    from typing import Any as Self
+else:  # pragma: no cover
+    from typing import TypeVar
+
+    Self = TypeVar("Self")
 
 import logging
 import os

src/plaid/containers/sample.py

@@ -8,11 +8,14 @@
 #
 
 # %% Imports
+import sys
 
-try:  # pragma: no cover
+if sys.version_info >= (3, 11):
     from typing import Self
-except ImportError:  # pragma: no cover
-    from typing import Any as Self
+else:  # pragma: no cover
+    from typing import TypeVar
+
+    Self = TypeVar("Self")
 
 import copy
 import glob

src/plaid/post/bisect.py

@@ -1,6 +1,7 @@
 """Utiliy function to plot bisect graphs comparing predictions vs. targets dataset."""
 
 import subprocess
+from typing import Union
 
 import matplotlib as mpl
 import matplotlib.pyplot as plt
@@ -77,10 +78,10 @@ def is_dvipng_available(verbose: bool) -> bool:
 
 
 def plot_bisect(
-    ref_dataset: Dataset | str,
-    pred_dataset: Dataset | str,
-    problem_def: ProblemDefinition | str,
-    scalar: str | int,
+    ref_dataset: Union[Dataset, str],
+    pred_dataset: Union[Dataset, str],
+    problem_def: Union[ProblemDefinition, str],
+    scalar: Union[str, int],
     save_file_name: str = "bissec_plots",
     verbose: bool = False,
 ) -> None:

src/plaid/post/metrics.py

@@ -1,5 +1,7 @@
 """Utility functions for computing and printing metrics for regression problems in PLAID."""
 
+from typing import Union
+
 import numpy as np
 import yaml
 from sklearn.metrics import r2_score
@@ -125,9 +127,9 @@ def pretty_metrics(metrics: dict) -> None:
 
 
 def compute_metrics(
-    ref_dataset: Dataset | str,
-    pred_dataset: Dataset | str,
-    problem: ProblemDefinition | str,
+    ref_dataset: Union[Dataset, str],
+    pred_dataset: Union[Dataset, str],
+    problem: Union[ProblemDefinition, str],
     save_file_name: str = "test_metrics",
     verbose: bool = False,
 ) -> None:

src/plaid/problem_definition.py

@@ -9,10 +9,14 @@
 
 # %% Imports
 
-try:  # pragma: no cover
+import sys
+
+if sys.version_info >= (3, 11):
     from typing import Self
-except ImportError:  # pragma: no cover
-    from typing import Any as Self
+else:  # pragma: no cover
+    from typing import TypeVar
+
+    Self = TypeVar("Self")
 
 import csv
 import logging

src/plaid/utils/interpolation.py

@@ -63,7 +63,7 @@ def binary_search_vectorized(
 def piece_wise_linear_interpolation(
     item: float,
     item_indices: np.ndarray,
-    vectors: np.ndarray | dict,
+    vectors: Union[np.ndarray, dict],
     tolerance: float = 1e-4,
 ) -> np.ndarray:
     """Computes a item interpolation for temporal vectors defined either by item_indices  and vectors at these indices.
@@ -101,7 +101,7 @@ def piece_wise_linear_interpolation(
 def piece_wise_linear_interpolation_with_map(
     item: float,
     item_indices: np.ndarray,
-    vectors: np.ndarray | dict,
+    vectors: Union[np.ndarray, dict],
     vectors_map: list = None,
     tolerance: float = 1e-4,
 ) -> float:
@@ -143,7 +143,7 @@ def piece_wise_linear_interpolation_with_map(
 
 
 def piece_wise_linear_interpolation_vectorized(
-    items: list[float], item_indices: np.ndarray, vectors: np.ndarray | dict
+    items: list[float], item_indices: np.ndarray, vectors: Union[np.ndarray, str]
 ) -> list[np.ndarray]:
     """piece_wise_linear_interpolation for more than one call (items is now a list or one-dimensional np.ndarray).
 
@@ -165,7 +165,7 @@ def piece_wise_linear_interpolation_vectorized(
 def piece_wise_linear_interpolation_vectorized_with_map(
     items: list[float],
     item_indices: np.ndarray,
-    vectors: np.ndarray | dict,
+    vectors: Union[np.ndarray, dict],
     vectors_map: list = None,
 ) -> list[np.ndarray]:
     """piece_wise_linear_interpolation_with_map for more than one call (items is now a list or one-dimensional np.ndarray).