fix for hsload with --link and s3paths (#131)

* fix for append with chunks

* fix for append mode with s3 links

h5pyd/_apps/utillib.py

@@ -787,6 +787,15 @@ def create_dataset(dobj, ctx):
             # just use the dims field of dobj.chunks as chunk shape
             chunks = get_chunk_dims(dobj)
         if chunks is not None:
+            if dset_preappend is not None:
+                # check to see if an extra dimension is needed for the chunk shape
+                if isinstance(chunks, dict):
+                    # chunktable is already adjusted
+                    pass
+                else:
+                    new_chunks = [1,]
+                    new_chunks.extend(chunks)
+                    chunks = tuple(new_chunks)
             kwargs["chunks"] = chunks
         if (
             dobj.shape is None

h5pyd/_hl/dataset.py

@@ -127,8 +127,8 @@ def make_new_dset(
         chunk > dim for dim, chunk in zip(tmp_shape, chunks) if dim is not None
     ):
         errmsg = (
-            "Chunk shape must not be greater than data shape in any dimension. "
-            "{} is not compatible with {}".format(chunks, shape)
+            f"Chunk shape must not be greater than data shape in any dimension. "
+            "{chunks} is not compatible with {shape}"
         )
         raise ValueError(errmsg)
 

h5pyd/_hl/filters.py

@@ -92,9 +92,9 @@ def rq_tuple(tpl, name):
         try:
             tpl = tuple(tpl)
         except TypeError:
-            raise TypeError('"%s" argument must be None or a sequence object' % name)
+            raise TypeError(f'"{name}" argument must be None or a sequence object')
         if len(tpl) != len(shape):
-            raise ValueError('"%s" must have same rank as dataset shape' % name)
+            raise ValueError(f'"{name}" must have same rank as dataset shape')
 
     rq_tuple(chunks, "chunks")
     rq_tuple(maxshape, "maxshape")