Add more checks to sequence metadata obtained via URL

These additional checks do some basic asserts to ensure
the schema of the metadata columns used by Cladetime
and to ensure completeness/uniqueness of the strain
column (which acts, essentially, as a primary key)

tests/unit/test_sequence.py

@@ -69,9 +69,13 @@ def test_get_metadata_url(s3_setup, test_file_path):
     # ensure lazyframe can be collected and check its shape and columns
     metadata_df = metadata.collect()
     assert metadata_df.shape == (99373, 58)
-    assert all(
-        col in metadata_df.columns for col in ["strain", "date", "country", "division", "location", "clade_nextstrain"]
-    )
+    # focus on a handful of columns that an integral to cladetime
+    metadata_df = metadata.collect().select("strain", "date", "country", "division", "location", "clade_nextstrain")
+    # strain column is required and should be unique
+    assert metadata_df.select("strain").n_unique() == len(metadata_df)
+    # all columns should have a string data type
+    for data_type in metadata_df.schema.to_python().values():
+        assert data_type is str
 
     # Get metadata file from S3 using XZ compression. Here we can use a presigned S3 URL
     # because for .xz files, get_metadata uses requests to download the file in chunks
@@ -85,9 +89,13 @@ def test_get_metadata_url(s3_setup, test_file_path):
     # ensure lazyframe can be collected and check its shape and columns
     metadata_df = metadata.collect()
     assert metadata_df.shape == (99373, 58)
-    assert all(
-        col in metadata_df.columns for col in ["strain", "date", "country", "division", "location", "clade_nextstrain"]
-    )
+    # focus on a handful of columns that an integral to cladetime
+    metadata_df = metadata.collect().select("strain", "date", "country", "division", "location", "clade_nextstrain")
+    # strain column is required and should be unique
+    assert metadata_df.select("strain").n_unique() == len(metadata_df)
+    # all columns should have a string data type
+    for data_type in metadata_df.schema.to_python().values():
+        assert data_type is str
 
 
 def test_filter_metadata():