Increase test coverage

src/rechunk_data/_rechunk.py

@@ -44,9 +44,7 @@ def _save_dataset(
     logger.debug("Saving file ot %s", str(file_name))
     try:
         dset.to_netcdf(
-            file_name,
-            engine=engine,
-            encoding=encoding,
+            file_name, engine=engine, encoding=encoding,
         )
     except Exception as error:
         logger.error("Saving to file failed: %s", str(error))
@@ -55,7 +53,6 @@ def _save_dataset(
 def _rechunk_dataset(dset: xr.Dataset) -> Tuple[xr.Dataset, Dict[str, Any]]:
     encoding: Dict[str, Dict[str, Any]] = {}
     for var in map(str, dset.data_vars):
-        skip_var: bool = False
         if not isinstance(dset[var].data, Array):
             logger.debug("Skipping rechunking variable %s", var)
             continue
@@ -66,27 +63,18 @@ def _rechunk_dataset(dset: xr.Dataset) -> Tuple[xr.Dataset, Dict[str, Any]]:
                 chunks[i] = None
             else:
                 chunks[i] = "auto"
-        try:
-            old_chunks = dset[var].encoding.get("chunksizes")
-            new_chunks = dset[var].data.rechunk(chunks).chunksize
-            if new_chunks == old_chunks:
-                logger.debug("%s: chunk sizes already optimized, skipping", var)
-                skip_var = True
-                continue
-            dset[var] = dset[var].chunk(dict(zip(dset[var].dims, new_chunks)))
-            logger.debug(
-                "%s: old chunk size: %s, new chunk size: %s",
-                var,
-                old_chunks,
-                new_chunks,
-            )
-        except Exception as error:
-            logger.warning("Could not set chunk size for %s: %s", var, str(error))
+        old_chunks = dset[var].encoding.get("chunksizes")
+        new_chunks = dset[var].data.rechunk(chunks).chunksize
+        if new_chunks == old_chunks:
+            logger.debug("%s: chunk sizes already optimized, skipping", var)
             continue
-        if not skip_var:
-            logger.debug("Settings encoding of variable %s", var)
-            encoding[var] = {str(k): v for k, v in dset[var].encoding.items()}
-            encoding[var]["chunksizes"] = new_chunks
+        dset[var] = dset[var].chunk(dict(zip(dset[var].dims, new_chunks)))
+        logger.debug(
+            "%s: old chunk size: %s, new chunk size: %s", var, old_chunks, new_chunks,
+        )
+        logger.debug("Settings encoding of variable %s", var)
+        encoding[var] = {str(k): v for k, v in dset[var].encoding.items()}
+        encoding[var]["chunksizes"] = new_chunks
     return dset, encoding
 
 
@@ -102,7 +90,7 @@ def rechunk_dataset(dset: xr.Dataset) -> xr.Dataset:
     -------
     xarray.Dataset: rechunked dataset
     """
-    data, _ = _rechunk_dataset(dset)
+    data, _ = _rechunk_dataset(dset.chunk())
     return data
 
 

src/rechunk_data/tests/conftest.py

@@ -31,6 +31,15 @@ def small_chunk() -> Generator[Tuple[int, int, int, int], None, None]:
     yield (1, 1, 24, 24)
 
 
+@pytest.fixture(scope="session")
+def empty_data() -> Generator[xr.Dataset, None, None]:
+    """Create an empty datasset."""
+
+    yield xr.Dataset(
+        {"tas_bnds": xr.DataArray(["hallo"], name="tas_bnds", dims=("lon",))}
+    )
+
+
 @pytest.fixture(scope="session")
 def large_chunk() -> Generator[Tuple[int, int, int, int], None, None]:
     """Define tuple for smaller chunks sizes."""

src/rechunk_data/tests/test_rechunking.py

 """Unit tests for rechunking the data."""
-
+import dask
 import xarray as xr
 
 from rechunk_data._rechunk import _rechunk_dataset
@@ -16,6 +16,13 @@ def test_rechunking_small_data(
     assert encoding == {}
 
 
+def test_empty_dataset(empty_data):
+    """Test handling of empyt data."""
+    with dask.config.set({"array.chunk-size": "0.01b"}):
+        dset, encoding = _rechunk_dataset(empty_data)
+    assert encoding == {}
+
+
 def test_rechunking_large_data(
     large_chunk_data: xr.Dataset, variable_name: str
 ) -> None: