diff --git a/virtualizarr/readers/zarr.py b/virtualizarr/readers/zarr.py
index 03035f3b..1fabf1bb 100644
--- a/virtualizarr/readers/zarr.py
+++ b/virtualizarr/readers/zarr.py
@@ -62,7 +62,7 @@ async def _parse_zarr_v3_metadata(zarr_array: zarr.Array) -> ZArray:
     )
 
 
-async def build_chunk_manifest(
+async def build_chunk_manifest_from_dict_mapping(
     store_path: str, chunk_mapping_dict: dict, array_name: str, zarr_format: int
 ) -> ChunkManifest:
     chunk_manifest_dict = {}
@@ -88,12 +88,59 @@ async def build_chunk_manifest(
     return ChunkManifest(chunk_manifest_dict)
 
 
+async def build_chunk_manifest(
+    zarr_array: zarr.AsyncArray, prefix: str, filepath: str
+) -> ChunkManifest:
+    """Build a ChunkManifest from arrays
+    keys will be chunks
+    add in filepath to chunks to make '_paths'
+    offsets are array of 0 of length (len(keys)) or len(paths)) np.ndarray[Any, np.dtype[np.uint64]]
+    sizes are '_lengths'
+
+    """
+    import numpy as np
+
+    keys = [x async for x in zarr_array.store.list_prefix(prefix)]
+    filepath_list = [filepath] * len(keys)
+
+    # can this be lambda'ed?
+    # stolen from manifest.py
+    def combine_path_chunk(filepath: str, chunk_key: str):
+        return filepath + chunk_key
+
+    vectorized_chunk_path_combine_func = np.vectorize(
+        combine_path_chunk, otypes=[np.dtypes.StringDType()]
+    )
+
+    # _paths: np.ndarray[Any, np.dtypes.StringDType]
+    _paths = vectorized_chunk_path_combine_func(filepath_list, keys)
+
+    # _offsets: np.ndarray[Any, np.dtype[np.uint64]]
+    # this seems like a very overly complicated way to make a list of len n of 0s with a
+    # certain dtype... I might have gotten carried away on the np.vectorize hypetrain
+    _offsets = np.vectorize(lambda x: [x] * len(_paths), otypes=[np.uint64])(0)
+
+    # _lengths: np.ndarray[Any, np.dtype[np.uint64]]
+    # maybe concurrent_map isn't the way to go, I think it expects tuples...
+    _lengths = await concurrent_map((keys), zarr_array.store.getsize)
+
+    import ipdb
+
+    ipdb.set_trace()
+    return ChunkManifest.from_arrays(
+        paths=_paths,  # type: ignore
+        offsets=_offsets,
+        lengths=_lengths,
+    )
+
+
 async def get_chunk_mapping_prefix(zarr_array: zarr.AsyncArray, prefix: str) -> dict:
     """Create a chunk map"""
 
     keys = [(x,) async for x in zarr_array.store.list_prefix(prefix)]
 
     sizes = await concurrent_map(keys, zarr_array.store.getsize)
+
     return {key[0]: size for key, size in zip(keys, sizes)}
 
 
@@ -122,11 +169,17 @@ async def virtual_variable_from_zarr_array(zarr_array: zarr.AsyncArray, filepath
     array_name = zarr_array.basename
     zarray_array = await build_zarray_metadata(zarr_array=zarr_array)
 
+    ## TEST - build chunk manifest from arrays
+    chunk_manifest = await build_chunk_manifest(
+        zarr_array, prefix=f"{array_name}/c", filepath=filepath
+    )
+
     # build mapping between chunks and # of bytes (size)
+    # FIXME!!!!: This is hardcoded for v3!
     chunk_map = await get_chunk_mapping_prefix(zarr_array, prefix=f"{array_name}/c")
 
     # transform chunk_map into ChunkManifest that fits into ManifestArray
-    chunk_manifest = await build_chunk_manifest(
+    chunk_manifest = await build_chunk_manifest_from_dict_mapping(
         store_path=filepath,
         chunk_mapping_dict=chunk_map,
         array_name=array_name,