Prepare for release, adjust extras

CHANGELOG.md

@@ -1,3 +1,31 @@
+## [Version 1.5.0] - 2023-09-06
+
+The release focuses on making `eo-learn` much simpler to install, reducing the number of dependencies, and improving validation of soundness of `EOPatch` data.
+
+- `eo-learn` is now distributed as a single package. Installation of `eo-learn-mask` and similar is no longer necessary and users are warned when such installations are detected.
+- Changes to `timestamps` and `bbox` attributes of `EOPatch` objects:
+    - `FeatureType.TIMESTAMPS` and `FeatureType.BBOX` have been deprecated, data should be accessed via attributes. Feature parsers no longer return these values (for instance when calling `EOPatch.get_features`).
+    - EOPatches without temporal information now have a timestamp value of `None`, whereas a timestamp value `[]` signifies that the EOPatch has a temporal dimension of 0.
+    - Introduced a `get_timestamps` method that will fail if `timestamps` are `None`. This can be used in cases where timestamps are assumed to be present (to avoid issues with type-checking and ill formed inputs).
+    - Loading, saving, and copying of EOPatches will take `timestamps` into account either when processing the full eopatch (i.e. `features=...`) or if the selection contains a temporal feature. The behavior can be controlled via the `load_timestamps`/`save_timestamps`/`copy_timestamps` parameter.
+- Saving and loading of `FeatureType.META_INFO` now processes each feature as a separate file, allowing better filtering and preventing accidental overwriting.
+- The default backend for `SpatialResizeTask` has been switched to `cv2` to reduce the number of dependencies.
+- `eolearn.geometry.morphology` tasks now use `cv2` instead of `scikit-image` to reduce the number of dependencies. The task interfaces have been slightly adjusted.
+- Improved reports:
+  - Exception grouping is now done by exception origin instead of exception message, resulting in shorter reports.
+  - Added execution time statistics per node
+- `CloudMaskTask` has been restricted to mono-temporal predictions using the `s2cloudless` package. For the multi-temporal one check [here](https://github.com/sentinel-hub/eo-learn-examples/blob/main/extra-tasks/cloud_mask/cloud_mask.py).
+- Certain tasks (for instance `SaveTask` and `LoadTask`) no longer pass arguments to the super-class via **kwargs in order to improve documentation and type-checking.
+- `SaveTask` and `LoadTask` now raise `OSError` exceptions instead of `IOError`.
+- Project-specific and outdated EOTasks were moved to extras or to the example repository [eo-learn-examples/extra-tasks](https://github.com/sentinel-hub/eo-learn-examples/tree/main/extra-tasks).
+- The submodule `eolearn.features.bands_extraction` has been renamed to `eolearn.features.ndi`.
+- The submodule `eolearn.ml_tools.extra.plotting` has been moved to `eolearn.visualization.utils`.
+- Compression of EOPatch files has been hardcoded. The parameter `compression_level` has been deprecated and has no effect.
+- Introduced experimental `zarr` support for loading/saving temporal slices of temporal features. The API might be changed in future releases.
+- Limited `rasterio` to 1.3.7 due to an issue with importing rasters from AWS S3
+- Updated examples, simplified tests, various improvements.
+
+
 ## [Version 1.4.2] - 2023-03-14
 
 - Introduced support for Python 3.11.

core/requirements.txt

@@ -1 +1 @@
-eo-learn[ALL]
+eo-learn

coregistration/requirements.txt

@@ -1 +1 @@
-eo-learn[ALL]
+eo-learn

eolearn/__init__.py

@@ -1,5 +1,5 @@
 """Main module of the `eolearn` package."""
-__version__ = "1.4.2"
+__version__ = "1.5.0"
 
 import importlib.util
 import warnings

eolearn/core/eodata.py

@@ -782,7 +782,7 @@ def plot(
             from eolearn.visualization.eopatch import plot_eopatch
         except ImportError:
             raise RuntimeError(
-                "Subpackage eo-learn-visualization has to be installed in order to use EOPatch visualization method"
+                "Dependencies `eo-learn[VISUALIZATION]` have to be installed in order to use EOPatch plotting."
             )
 
         return plot_eopatch(

eolearn/core/eoexecution.py

@@ -358,7 +358,7 @@ def make_report(self, include_logs: bool = True) -> None:
             from eolearn.visualization.eoexecutor import EOExecutorVisualization
         except ImportError:
             raise RuntimeError(
-                "Subpackage eo-learn-visualization has to be installed in order to create EOExecutor reports."
+                "Dependencies `eo-learn[VISUALIZATION]` have to be installed in order to create EOExecutor reports."
             )
 
         return EOExecutorVisualization(self).make_report(include_logs=include_logs)

eolearn/core/eoworkflow.py

@@ -347,7 +347,7 @@ def _get_visualization(self):  # type: ignore[no-untyped-def] # cannot type with
             from eolearn.visualization.eoworkflow import EOWorkflowVisualization
         except ImportError:
             raise RuntimeError(
-                "Subpackage eo-learn-visualization has to be installed in order to use EOWorkflow visualization methods"
+                "Dependencies `eo-learn[VISUALIZATION]` have to be installed in order to use EOWorkflow visualization."
             )
         return EOWorkflowVisualization(self._nodes)
 

examples/visualization/EOPatchVisualization.ipynb

@@ -97,7 +97,7 @@
    "source": [
     "## Basics\n",
     "\n",
-    "All visualizations can be done simply by calling `EOPatch.plot` method, however calling this method still requires that `eo-learn-visualization` subpackage is installed.\n",
+    "All visualizations can be done simply by calling `EOPatch.plot` method, however calling this method still requires that Dependencies `eo-learn[VISUALIZATION]` are installed.\n",
     "\n",
     "Plotting a simple timeless single-channel feature produces a single-image plot. Plotting method always returns a 2D grid of `AxesSubplot` objects which can be further customized before a plot is produced."
    ]
@@ -342,7 +342,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.4"
+   "version": "3.8.10"
   },
   "vscode": {
    "interpreter": {

features/requirements.txt

@@ -1 +1 @@
-eo-learn[ALL]
+eo-learn

geometry/requirements.txt

@@ -1 +1 @@
-eo-learn[ALL]
+eo-learn

install_all.py

@@ -16,5 +16,5 @@
     subprocess.check_call([sys.executable, "-m", "pip", "install", *sys.argv[1:], ".[ALL]"])
     warnings.warn(
         "Installing via `install_all.py` is no longer necessary and has been deprecated. Use `pip install"
-        " eo-learn[ALL]` instead."
+        " eo-learn` instead."
     )

io/requirements.txt

@@ -1 +1 @@
-eo-learn[ALL]
+eo-learn

mask/requirements.txt

@@ -1 +1 @@
-eo-learn[ALL]
+eo-learn

ml_tools/requirements.txt

@@ -1 +1 @@
-eo-learn[ALL]
+eo-learn

pyproject.toml

@@ -53,26 +53,23 @@ dependencies = [
     "sentinelhub>=3.9.0",
     "tqdm>=4.27",
     "typing-extensions",
+    "opencv-python-headless",
+    "affine",
+    "rasterio>=1.2.7, <1.3.8",
+    "shapely",
+    "fiona>=1.8.18",
 ]
 
 [project.optional-dependencies]
-all = [
-    "eo-learn[COREGISTRATION,FEATURES,GEOMETRY,IO,MASK,MLTOOLS,VISUALIZATION]",
-]
-full = ["eo-learn[ALL,RAY,ZARR,FEATURES_EXTRA,MASK_EXTRA]"]
+
+full = ["eo-learn[RAY,ZARR,FEATURES_EXTRA,MASK_EXTRA,VISUALIZATION]"]
 ray = ["ray[default]"]
 zarr = ["s3fs", "zarr"]
-coregistration = ["opencv-python-headless"]
-features = ["opencv-python-headless"]
 features_extra = ["numba>=0.53.0", "scikit-learn", "scipy"]
-geometry = ["affine", "opencv-python-headless", "rasterio>=1.2.7, <1.3.8", "shapely"]
-io = ["affine", "fiona>=1.8.18", "rasterio>=1.2.7, <1.3.8"]
-mask = ["opencv-python-headless"]
 mask_extra = ["s2cloudless"]
-mltools = ["shapely"]
 visualization = ["graphviz>=0.10.1", "jinja2", "matplotlib", "pygments"]
 docs = [
-    "eo-learn[ALL]",
+    "eo-learn[FULL]",
     "jupyter",
     "nbsphinx",
     "sphinx==7.1.2",

visualization/requirements.txt

@@ -1 +1 @@
-eo-learn[ALL]
+eo-learn