Adjust "auto" setting for io to process timestamps on default values (s…

…entinel-hub#730)

* add test

* implement

* fix docs

eolearn/core/core_tasks.py

@@ -118,8 +118,8 @@ def __init__(
         :param overwrite_permission: A level of permission for overwriting an existing EOPatch
         :param compress_level: A level of data compression and can be specified with an integer from 0 (no compression)
             to 9 (highest compression).
-        :save_timestamps: Whether to save the timestamps of the EOPatch. By default they are saved whenever temporal
-            features are being saved.
+        :save_timestamps: Whether to save the timestamps of the EOPatch. With the `"auto"` setting timestamps are saved
+            if `features=...` or if other temporal features are being saved.
         :param use_zarr: Saves numpy-array based features into Zarr files. Requires ZARR extra dependencies.
         :param temporal_selection: Writes all of the data to the chosen temporal indices of preexisting arrays. Can be
             used for saving data in multiple steps for memory optimization. When set to `"infer"` it will match the
@@ -185,8 +185,8 @@ def __init__(
             default configuration will be taken.
         :param features: A collection of features to be loaded. By default, all features will be loaded.
         :param lazy_loading: If `True` features will be lazy loaded.
-        :load_timestamps: Whether to load the timestamps of the EOPatch. By default they are loaded whenever temporal
-            features are being loaded.
+        :load_timestamps: Whether to load the timestamps of the EOPatch. With the `"auto"` setting timestamps are loaded
+            if `features=...` or if other temporal features are being loaded.
         :param temporal_selection: Only loads data corresponding to the chosen indices. Can also be a callable that,
             given a list of timestamps, returns a list of booleans declaring which temporal slices to load.
         """

eolearn/core/eodata.py

@@ -621,8 +621,8 @@ def save(
             to 9 (highest compression).
         :param filesystem: An existing filesystem object. If not given it will be initialized according to the `path`
             parameter.
-        :save_timestamps: Whether to save the timestamps of the EOPatch. By default they are saved whenever temporal
-            features are being saved.
+        :save_timestamps: Whether to save the timestamps of the EOPatch. With the `"auto"` setting timestamps are saved
+            if `features=...` or if other temporal features are being saved.
         :param use_zarr: Saves numpy-array based features into Zarr files. Requires ZARR extra dependencies.
         :param temporal_selection: Writes all of the data to the chosen temporal indices of preexisting arrays. Can be
             used for saving data in multiple steps for memory optimization. When set to `"infer"` it will match the
@@ -661,8 +661,8 @@ def load(
         :param lazy_loading: If `True` features will be lazy loaded.
         :param filesystem: An existing filesystem object. If not given it will be initialized according to the `path`
             parameter.
-        :load_timestamps: Whether to load the timestamps of the EOPatch. By default they are loaded whenever temporal
-            features are being loaded.
+        :load_timestamps: Whether to load the timestamps of the EOPatch. With the `"auto"` setting timestamps are loaded
+            if `features=...` or if other temporal features are being loaded.
         :param temporal_selection: Only loads data corresponding to the chosen indices. Can also be a callable that,
             given a list of timestamps, returns a list of booleans declaring which temporal slices to load.
         :return: Loaded EOPatch

eolearn/core/eodata_io.py

@@ -132,7 +132,9 @@ def save_eopatch(
     _check_collisions(overwrite_permission, eopatch_features, file_information)
 
     if save_timestamps == "auto":
-        save_timestamps = any(ftype.is_temporal() for ftype, _ in eopatch_features) and temporal_selection is None
+        save_timestamps = (
+            features is ... or any(ftype.is_temporal() for ftype, _ in eopatch_features)
+        ) and temporal_selection is None
 
     # Data must be collected before any tinkering with files due to lazy-loading
     data_for_saving = list(
@@ -306,7 +308,9 @@ def load_eopatch_content(
     if file_information.bbox is not None:
         bbox = FeatureIOBBox(file_information.bbox, filesystem).load()
 
-    auto_load = load_timestamps == "auto" and any(ftype.is_temporal() for ftype, _ in features_dict)
+    auto_load = load_timestamps == "auto" and (
+        features is ... or any(ftype.is_temporal() for ftype, _ in features_dict)
+    )
 
     timestamps = None
     if load_timestamps is True or auto_load:

tests/core/test_eodata_io.py

@@ -242,6 +242,15 @@ def test_save_timestamps(eopatch, fs_loader, save_timestamps, features, should_s
         assert temp_fs.exists("/timestamps.json.gz") == should_save
 
 
+def test_auto_save_load_timestamps(eopatch):
+    """Saving and loading with default values should process timestamps."""
+    test_patch = EOPatch(bbox=eopatch.bbox, timestamps=eopatch.timestamps)  # no temporal stuff
+    with TempFS() as temp_fs:
+        test_patch.save("/", filesystem=temp_fs)
+        assert temp_fs.exists("/timestamps.json.gz")
+        assert EOPatch.load("/", filesystem=temp_fs).timestamps is not None
+
+
 @mock_s3
 @pytest.mark.parametrize("fs_loader", FS_LOADERS)
 @pytest.mark.parametrize(