IO import issues

CHANGELOG.md

@@ -41,14 +41,14 @@ Example on 2 processes:
 - [#768](https://github.com/helmholtz-analytics/heat/pull/768) Fixed an issue where `deg2rad` and `rad2deg`are not working with the 'out' parameter.
 - [#785](https://github.com/helmholtz-analytics/heat/pull/785) Removed `storage_offset` when finding the mpi buffer (`communication. MPICommunication.as_mpi_memory()`).
 - [#785](https://github.com/helmholtz-analytics/heat/pull/785) added allowance for 1 dimensional non-contiguous local tensors in `communication. MPICommunication.mpi_type_and_elements_of()`
+- [#787](https://github.com/helmholtz-analytics/heat/pull/787) Fixed an issue where Heat cannot be imported when some optional dependencies are not available.
 - [#790](https://github.com/helmholtz-analytics/heat/pull/790) catch incorrect device after `bcast` in `DNDarray.__getitem__`
 ### Linear Algebra
 - [#718](https://github.com/helmholtz-analytics/heat/pull/718) New feature: `trace()`
 - [#768](https://github.com/helmholtz-analytics/heat/pull/768) New feature: unary positive and negative operations
 ### Misc.
 - [#761](https://github.com/helmholtz-analytics/heat/pull/761) New feature: `result_type`
 
-
 # v1.0.0
 
 ## New features / Highlights

heat/classification/tests/test_knn.py

@@ -1,10 +1,12 @@
+import unittest
 import heat as ht
 
 from heat.classification.kneighborsclassifier import KNeighborsClassifier
 from heat.core.tests.test_suites.basic_test import TestCase
 
 
 class TestKNN(TestCase):
+    @unittest.skipUnless(ht.supports_hdf5(), "Requires HDF5")
     def test_split_none(self):
         x = ht.load_hdf5("heat/datasets/iris.h5", dataset="data")
 
@@ -27,6 +29,7 @@ def test_split_none(self):
         self.assertIsInstance(result, ht.DNDarray)
         self.assertEqual(result.shape, y.shape)
 
+    @unittest.skipUnless(ht.supports_hdf5(), "Requires HDF5")
     def test_split_zero(self):
         x = ht.load_hdf5("heat/datasets/iris.h5", dataset="data", split=0)
 
@@ -73,6 +76,7 @@ def test_utility(self,):
         one_hot = KNeighborsClassifier.one_hot_encoding(a)
         self.assertTrue((one_hot == b).all())
 
+    @unittest.skipUnless(ht.supports_hdf5(), "Requires HDF5")
     def test_fit_one_hot(self,):
         x = ht.load_hdf5("heat/datasets/iris.h5", dataset="data")
 

heat/core/io.py

@@ -23,7 +23,7 @@
 __NETCDF_EXTENSIONS = frozenset([".nc", ".nc4", "netcdf"])
 __NETCDF_DIM_TEMPLATE = "{}_dim_{}"
 
-__all__ = ["load", "load_csv", "save", "supports_hdf5", "supports_netcdf", "save_hdf5"]
+__all__ = ["load", "load_csv", "save", "supports_hdf5", "supports_netcdf"]
 
 try:
     import h5py
@@ -677,6 +677,8 @@ def load(
     -------
     ValueError
         If the file extension is not understood or known.
+    RuntimeError
+        If the optional dependency for a file extension is not available.
 
     Examples
     --------
@@ -691,10 +693,16 @@ def load(
 
     if extension in __CSV_EXTENSION:
         return load_csv(path, *args, **kwargs)
-    elif supports_hdf5() and extension in __HDF5_EXTENSIONS:
-        return load_hdf5(path, *args, **kwargs)
-    elif supports_netcdf() and extension in __NETCDF_EXTENSIONS:
-        return load_netcdf(path, *args, **kwargs)
+    elif extension in __HDF5_EXTENSIONS:
+        if supports_hdf5():
+            return load_hdf5(path, *args, **kwargs)
+        else:
+            raise RuntimeError("hdf5 is required for file extension {}".format(extension))
+    elif extension in __NETCDF_EXTENSIONS:
+        if supports_netcdf():
+            return load_netcdf(path, *args, **kwargs)
+        else:
+            raise RuntimeError("netcdf is required for file extension {}".format(extension))
     else:
         raise ValueError("Unsupported file extension {}".format(extension))
 
@@ -934,6 +942,8 @@ def save(
     -------
     ValueError
         If the file extension is not understood or known.
+    RuntimeError
+        If the optional dependency for a file extension is not available.
 
     Examples
     --------
@@ -944,10 +954,16 @@ def save(
         raise TypeError("Expected path to be str, but was {}".format(type(path)))
     extension = os.path.splitext(path)[-1].strip().lower()
 
-    if supports_hdf5() and extension in __HDF5_EXTENSIONS:
-        save_hdf5(data, path, *args, **kwargs)
-    elif supports_netcdf() and extension in __NETCDF_EXTENSIONS:
-        save_netcdf(data, path, *args, **kwargs)
+    if extension in __HDF5_EXTENSIONS:
+        if supports_hdf5():
+            save_hdf5(data, path, *args, **kwargs)
+        else:
+            raise RuntimeError("hdf5 is required for file extension {}".format(extension))
+    elif extension in __NETCDF_EXTENSIONS:
+        if supports_netcdf():
+            save_netcdf(data, path, *args, **kwargs)
+        else:
+            raise RuntimeError("netcdf is required for file extension {}".format(extension))
     else:
         raise ValueError("Unsupported file extension {}".format(extension))
 

heat/core/tests/test_io.py

@@ -64,7 +64,7 @@ def test_load(self):
             # content
             self.assertTrue((self.IRIS == iris.larray).all())
         else:
-            with self.assertRaises(ValueError):
+            with self.assertRaises(RuntimeError):
                 _ = ht.load(self.HDF5_PATH, dataset=self.HDF5_DATASET)
 
         # netCDF
@@ -80,7 +80,7 @@ def test_load(self):
             # content
             self.assertTrue((self.IRIS == iris.larray).all())
         else:
-            with self.assertRaises(ValueError):
+            with self.assertRaises(RuntimeError):
                 _ = ht.load(self.NETCDF_PATH, variable=self.NETCDF_VARIABLE)
 
     def test_load_csv(self):
@@ -147,14 +147,14 @@ def test_load_exception(self):
             with self.assertRaises(IOError):
                 ht.load("foo.h5", "data")
         else:
-            with self.assertRaises(ValueError):
+            with self.assertRaises(ImportError):
                 ht.load("foo.h5", "data")
 
         if ht.io.supports_netcdf():
             with self.assertRaises(IOError):
                 ht.load("foo.nc", "data")
         else:
-            with self.assertRaises(ValueError):
+            with self.assertRaises(ImportError):
                 ht.load("foo.nc", "data")
 
         # unknown file extension
@@ -378,7 +378,7 @@ def test_save_exception(self):
             with self.assertRaises(TypeError):
                 ht.save(data, self.HDF5_OUT_PATH, 1)
         else:
-            with self.assertRaises(ValueError):
+            with self.assertRaises(RuntimeError):
                 ht.save(data, self.HDF5_OUT_PATH, self.HDF5_DATASET)
 
         if ht.io.supports_netcdf():
@@ -409,13 +409,16 @@ def test_save_exception(self):
                     mode="a",
                 )
         else:
-            with self.assertRaises(ValueError):
+            with self.assertRaises(RuntimeError):
                 ht.save(data, self.NETCDF_OUT_PATH, self.NETCDF_VARIABLE)
 
+        with self.assertRaises(ValueError):
+            ht.save(1, "data.dat")
+
     def test_load_hdf5(self):
         # HDF5 support is optional
         if not ht.io.supports_hdf5():
-            return
+            self.skipTest("Requires HDF5")
 
         # default parameters
         iris = ht.load_hdf5(self.HDF5_PATH, self.HDF5_DATASET)
@@ -453,7 +456,7 @@ def test_load_hdf5(self):
     def test_load_hdf5_exception(self):
         # HDF5 support is optional
         if not ht.io.supports_hdf5():
-            return
+            self.skipTest("Requires HDF5")
 
         # improper argument types
         with self.assertRaises(TypeError):
@@ -501,7 +504,7 @@ def test_save_hdf5(self):
     def test_save_hdf5_exception(self):
         # HDF5 support is optional
         if not ht.io.supports_hdf5():
-            return
+            self.skipTest("Requires HDF5")
 
         # dummy data
         data = ht.arange(1)
@@ -516,7 +519,7 @@ def test_save_hdf5_exception(self):
     def test_load_netcdf(self):
         # netcdf support is optional
         if not ht.io.supports_netcdf():
-            return
+            self.skipTest("Requires NetCDF")
 
         # default parameters
         iris = ht.load_netcdf(self.NETCDF_PATH, self.NETCDF_VARIABLE)
@@ -554,7 +557,7 @@ def test_load_netcdf(self):
     def test_load_netcdf_exception(self):
         # netcdf support is optional
         if not ht.io.supports_netcdf():
-            return
+            self.skipTest("Requires NetCDF")
 
         # improper argument types
         with self.assertRaises(TypeError):
@@ -573,7 +576,7 @@ def test_load_netcdf_exception(self):
     def test_save_netcdf(self):
         # netcdf support is optional
         if not ht.io.supports_netcdf():
-            return
+            self.skipTest("Requires NetCDF")
 
         # local unsplit data
         local_data = ht.arange(100)
@@ -602,7 +605,7 @@ def test_save_netcdf(self):
     def test_save_netcdf_exception(self):
         # netcdf support is optional
         if not ht.io.supports_netcdf():
-            return
+            self.skipTest("Requires NetCDF")
 
         # dummy data
         data = ht.arange(1)

heat/utils/data/tests/test_partial_dataset.py

@@ -4,6 +4,7 @@
 
 
 class TestPartialDataset(unittest.TestCase):
+    @unittest.skipUnless(ht.supports_hdf5(), "Requires HDF5")
     def test_partial_h5_dataset(self):
         # load h5 data and get the total shape
         full_data = ht.load("heat/datasets/iris.h5", dataset="data", split=None)