Drop Python 3.8 support (microsoft#1246)

.github/workflows/style.yaml

@@ -123,7 +123,7 @@ jobs:
         pip install -r requirements/style.txt
         pip list
     - name: Run pyupgrade checks
-      run: pyupgrade --py38-plus $(find . -path ./docs/src -prune -o -name "*.py" -print)
+      run: pyupgrade --py39-plus $(find . -path ./docs/src -prune -o -name "*.py" -print)
 concurrency:
   group: ${{ github.workflow }}-${{ github.ref }}
   cancel-in-progress: true

.github/workflows/tests.yaml

@@ -40,7 +40,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: ['3.8', '3.9', '3.10']
+        python-version: ['3.9', '3.10']
     steps:
     - name: Clone repo
       uses: actions/[email protected]
@@ -99,7 +99,7 @@ jobs:
     - name: Set up python
       uses: actions/[email protected]
       with:
-        python-version: '3.8'
+        python-version: '3.9'
     - name: Cache dependencies
       uses: actions/[email protected]
       id: cache

.pre-commit-config.yaml

@@ -3,7 +3,7 @@ repos:
         rev: v3.3.1
         hooks:
         -   id: pyupgrade
-            args: [--py38-plus]
+            args: [--py39-plus]
 
     -   repo: https://github.com/pycqa/isort
         rev: 5.12.0

.readthedocs.yaml

@@ -6,9 +6,9 @@ version: 2
 
 # Set the version of Python
 build:
-  os: ubuntu-20.04
+  os: ubuntu-22.04
   tools:
-    python: "3.9"
+    python: "3.10"
 
 # Configuration of the Python environment to be used
 python:

docs/user/contributing.rst

@@ -58,14 +58,14 @@ For example, if you add a new dataset in ``torchgeo/datasets/foo.py``, you'll ne
 
    $ pytest --cov=torchgeo/datasets --cov-report=term-missing tests/datasets/test_foo.py
    ========================= test session starts =========================
-   platform darwin -- Python 3.8.11, pytest-6.2.4, py-1.9.0, pluggy-0.13.0
+   platform darwin -- Python 3.10.11, pytest-6.2.4, py-1.9.0, pluggy-0.13.0
    rootdir: ~/torchgeo, configfile: pyproject.toml
    plugins: mock-1.11.1, anyio-3.2.1, cov-2.8.1, nbmake-0.5
    collected 7 items
 
    tests/datasets/test_foo.py .......                              [100%]
 
-   ---------- coverage: platform darwin, python 3.8.11-final-0 -----------
+   ---------- coverage: platform darwin, python 3.10.11-final-0 -----------
    Name                                      Stmts   Miss  Cover   Missing
    -----------------------------------------------------------------------
    torchgeo/datasets/__init__.py                26      0   100%
@@ -103,7 +103,7 @@ All of these tools should be used from the root of the project to ensure that ou
 
    $ black .
    $ isort .
-   $ pyupgrade --py38-plus $(find . -name "*.py")
+   $ pyupgrade --py39-plus $(find . -name "*.py")
 
 
 Flake8, pydocstyle, and mypy won't format your code for you, but they will warn you about potential issues with your code or docstrings:

environment.yml

@@ -4,19 +4,19 @@ channels:
   - conda-forge
 dependencies:
   - einops>=0.3
-  - fiona>=1.8.12
-  - h5py>=2.9
-  - matplotlib>=3.3
-  - numpy>=1.17.3
+  - fiona>=1.8.19
+  - h5py>=3
+  - matplotlib>=3.3.3
+  - numpy>=1.19.3
   - pip
   - pycocotools>=2.0.1
-  - pyproj>=2.4.1
-  - python>=3.8
+  - pyproj>=3
+  - python>=3.9
   - pytorch>=1.12
   - pyvista>=0.25.2
   - rarfile>=4
-  - rasterio>=1.1.1
-  - shapely>=1.7
+  - rasterio>=1.2
+  - shapely>=1.7.1
   - torchvision>=0.13
   - pip:
     - black[jupyter]>=21.8
@@ -30,18 +30,18 @@ dependencies:
     - nbmake>=1.3.3
     - nbsphinx>=0.8.5
     - omegaconf>=2.1
-    - opencv-python>=4.1.2
-    - pandas>=0.25.2
-    - pillow>=6.2.1
+    - opencv-python>=4.4.0.46
+    - pandas>=1.1.3
+    - pillow>=8
     - pydocstyle[toml]>=6.1
     - pytest>=6.1.2
     - pytest-cov>=2.4
     - git+https://github.com/pytorch/pytorch_sphinx_theme
-    - pyupgrade>=2.4
+    - pyupgrade>=2.8
     - radiant-mlhub>=0.3
     - rtree>=1
     - scikit-image>=0.18
-    - scikit-learn>=0.22
+    - scikit-learn>=0.24
     - scipy>=1.6.2
     - segmentation-models-pytorch>=0.2
     - setuptools>=42

evaluate.py

@@ -8,7 +8,7 @@
 import argparse
 import csv
 import os
-from typing import Any, Dict, Union, cast
+from typing import Any, Union, cast
 
 import lightning.pytorch as pl
 import torch
@@ -155,7 +155,7 @@ def main(args: argparse.Namespace) -> None:
     dm.setup("validate")
 
     # Record model hyperparameters
-    hparams = cast(Dict[str, Union[str, float]], model.hparams)
+    hparams = cast(dict[str, Union[str, float]], model.hparams)
     if issubclass(TASK, ClassificationTask):
         val_row = {
             "split": "val",

experiments/download_ssl4eo.py

@@ -32,7 +32,7 @@
 from collections import OrderedDict
 from datetime import date, datetime, timedelta
 from multiprocessing.dummy import Lock, Pool
-from typing import Any, Dict, List, Optional, Tuple
+from typing import Any, Optional
 
 import ee
 import numpy as np
@@ -79,7 +79,7 @@ def date2str(date: datetime) -> str:
     return date.strftime("%Y-%m-%d")
 
 
-def get_period(date: datetime, days: int = 5) -> Tuple[str, str]:
+def get_period(date: datetime, days: int = 5) -> tuple[str, str]:
     date1 = date - timedelta(days=days / 2)
     date2 = date + timedelta(days=days / 2)
     return date2str(date1), date2str(date2)
@@ -121,7 +121,7 @@ def get_collection_s1() -> ee.ImageCollection:
 
 
 def filter_collection(
-    collection: ee.ImageCollection, coords: List[float], period: Tuple[str, str]
+    collection: ee.ImageCollection, coords: list[float], period: tuple[str, str]
 ) -> ee.ImageCollection:
     filtered = collection
     if period is not None:
@@ -137,7 +137,7 @@ def filter_collection(
 
 
 def filter_collection_s1(
-    collection: ee.ImageCollection, coords: List[float], period: Tuple[str, str]
+    collection: ee.ImageCollection, coords: list[float], period: tuple[str, str]
 ) -> ee.ImageCollection:
     filtered = collection
     if period is not None:
@@ -161,7 +161,7 @@ def filter_collection_s1(
 
 
 def center_crop(
-    img: np.ndarray[Any, np.dtype[Any]], out_size: Tuple[int, int]
+    img: np.ndarray[Any, np.dtype[Any]], out_size: tuple[int, int]
 ) -> np.ndarray[Any, np.dtype[Any]]:
     image_height, image_width = img.shape[:2]
     crop_height, crop_width = out_size
@@ -171,8 +171,8 @@ def center_crop(
 
 
 def adjust_coords(
-    coords: List[List[float]], old_size: Tuple[int, int], new_size: Tuple[int, int]
-) -> List[List[float]]:
+    coords: list[list[float]], old_size: tuple[int, int], new_size: tuple[int, int]
+) -> list[list[float]]:
     xres = (coords[1][0] - coords[0][0]) / old_size[1]
     yres = (coords[0][1] - coords[1][1]) / old_size[0]
     xoff = int((old_size[1] - new_size[1] + 1) * 0.5)
@@ -192,11 +192,11 @@ def get_properties(image: ee.Image) -> Any:
 
 def get_patch_s1(
     collection: ee.ImageCollection,
-    center_coord: List[float],
+    center_coord: list[float],
     radius: float,
-    bands: List[str],
-    crop: Optional[Dict[str, Any]] = None,
-) -> Dict[str, Any]:
+    bands: list[str],
+    crop: Optional[dict[str, Any]] = None,
+) -> dict[str, Any]:
     image = collection.sort("system:time_start", False).first()  # get most recent
     region = (
         ee.Geometry.Point(center_coord).buffer(radius).bounds()
@@ -233,11 +233,11 @@ def get_patch_s1(
 
 def get_patch_s2(
     collection: ee.ImageCollection,
-    center_coord: List[float],
+    center_coord: list[float],
     radius: float,
-    bands: Optional[List[str]] = None,
-    crop: Optional[Dict[str, Any]] = None,
-) -> Dict[str, Any]:
+    bands: Optional[list[str]] = None,
+    crop: Optional[dict[str, Any]] = None,
+) -> dict[str, Any]:
     if bands is None:
         bands = RGB_BANDS
 
@@ -277,18 +277,18 @@ def get_patch_s2(
 
 def get_random_patches_match(
     idx: int,
-    collections: Dict[str, Any],
-    bands: Dict[str, Any],
-    crops: Dict[str, Any],
-    dates: List[Any],
+    collections: dict[str, Any],
+    bands: dict[str, Any],
+    crops: dict[str, Any],
+    dates: list[Any],
     radius: int,
     debug: bool = False,
-    match_coords: Dict[str, Any] = {},
-) -> Tuple[
-    Optional[List[Dict[str, Any]]],
-    Optional[List[Dict[str, Any]]],
-    Optional[List[Dict[str, Any]]],
-    List[float],
+    match_coords: dict[str, Any] = {},
+) -> tuple[
+    Optional[list[dict[str, Any]]],
+    Optional[list[dict[str, Any]]],
+    Optional[list[dict[str, Any]]],
+    list[float],
 ]:
     # (lon,lat) of idx patch
     coords = match_coords[str(idx)]
@@ -343,7 +343,7 @@ def get_random_patches_match(
 
 
 def save_geotiff(
-    img: np.ndarray[Any, np.dtype[Any]], coords: List[List[float]], filename: str
+    img: np.ndarray[Any, np.dtype[Any]], coords: list[list[float]], filename: str
 ) -> None:
     height, width, channels = img.shape
     xres = (coords[1][0] - coords[0][0]) / width
@@ -366,9 +366,9 @@ def save_geotiff(
 
 
 def save_patch(
-    raster: Dict[str, Any],
-    coords: List[List[float]],
-    metadata: Dict[str, Any],
+    raster: dict[str, Any],
+    coords: list[list[float]],
+    metadata: dict[str, Any],
     path: str,
 ) -> None:
     patch_id = metadata["properties"]["system:index"]

experiments/run_benchmarks_experiments.py

@@ -8,7 +8,6 @@
 import os
 import subprocess
 import time
-from typing import List
 
 EPOCH_SIZE = 4096
 
@@ -34,7 +33,7 @@
     ):
         print(f"\n{i}/{total_num_experiments} -- {time.time() - tic}")
         tic = time.time()
-        command: List[str] = [
+        command: list[str] = [
             "python",
             "benchmark.py",
             "--landsat-root",

experiments/run_so2sat_byol_experiments.py

@@ -7,7 +7,6 @@
 import os
 import subprocess
 from multiprocessing import Process, Queue
-from typing import List
 
 # list of GPU IDs that we want to use, one job will be started for every ID in the list
 GPUS = [0, 1, 2, 3, 3]
@@ -18,7 +17,7 @@
 model_options = ["resnet50"]
 lr_options = [1e-4]
 loss_options = ["ce"]
-weight_options: List[str] = []  # set paths to checkpoint files
+weight_options: list[str] = []  # set paths to checkpoint files
 bands_options = ["s2"]
 
 

experiments/sample_ssl4eo.py

@@ -37,7 +37,6 @@
 import os
 import time
 import warnings
-from typing import Tuple
 
 import numpy as np
 import pandas as pd
@@ -69,7 +68,7 @@ def km2deg(kms: float, radius: float = 6371) -> float:
     return kms / (2.0 * radius * np.pi / 360.0)
 
 
-def sample_point(cities: pd.DataFrame, std: float) -> Tuple[float, float]:
+def sample_point(cities: pd.DataFrame, std: float) -> tuple[float, float]:
     city = cities.sample()
     point = (float(city["lng"]), float(city["lat"]))
     std = km2deg(std)
@@ -78,8 +77,8 @@ def sample_point(cities: pd.DataFrame, std: float) -> Tuple[float, float]:
 
 
 def create_bbox(
-    coords: Tuple[float, float], bbox_size_degree: float
-) -> Tuple[float, float, float, float]:
+    coords: tuple[float, float], bbox_size_degree: float
+) -> tuple[float, float, float, float]:
     lon, lat = coords
     bbox = (
         lon - bbox_size_degree,

pyproject.toml

@@ -6,7 +6,7 @@ requires = [
 build-backend = "setuptools.build_meta"
 
 [tool.black]
-target-version = ["py38", "py39", "py310"]
+target-version = ["py39", "py310"]
 color = true
 skip_magic_trailing_comma = true
 
@@ -25,7 +25,7 @@ skip_gitignore = true
 color_output = true
 
 [tool.mypy]
-python_version = "3.8"
+python_version = "3.9"
 ignore_missing_imports = true
 show_error_codes = true
 exclude = "(build|data|dist|docs/src|images|logo|logs|output)/"