diff --git a/graphblas_algorithms/algorithms/core.py b/graphblas_algorithms/algorithms/core.py
index 9212242..85ab592 100644
--- a/graphblas_algorithms/algorithms/core.py
+++ b/graphblas_algorithms/algorithms/core.py
@@ -34,4 +34,4 @@ def k_truss(G: Graph, k) -> Graph:
     # Convert back to networkx graph with correct node ids
     keys = G.list_to_keys(indices)
     key_to_id = dict(zip(keys, range(len(indices))))
-    return Graph.from_graphblas(Ktruss, key_to_id=key_to_id)
+    return Graph(Ktruss, key_to_id=key_to_id)
diff --git a/graphblas_algorithms/algorithms/tests/test_cluster.py b/graphblas_algorithms/algorithms/tests/test_cluster.py
index 82e9efc..50a3196 100644
--- a/graphblas_algorithms/algorithms/tests/test_cluster.py
+++ b/graphblas_algorithms/algorithms/tests/test_cluster.py
@@ -9,8 +9,8 @@ def test_triangles_full():
     G = gb.Matrix(bool, 5, 5)
     G[:, :] = True
     G2 = gb.select.offdiag(G).new()
-    G = Graph.from_graphblas(G)
-    G2 = Graph.from_graphblas(G2)
+    G = Graph(G)
+    G2 = Graph(G2)
     result = cluster.triangles(G)
     expected = gb.Vector(int, 5)
     expected[:] = 6
diff --git a/graphblas_algorithms/classes/_utils.py b/graphblas_algorithms/classes/_utils.py
index c8f4eba..237dcf3 100644
--- a/graphblas_algorithms/classes/_utils.py
+++ b/graphblas_algorithms/classes/_utils.py
@@ -2,7 +2,6 @@
 import numpy as np
 from graphblas import Matrix, Vector, binary
 from graphblas.core.matrix import TransposedMatrix
-from graphblas.core.utils import ensure_type
 
 ################
 # Classmethods #
@@ -19,21 +18,6 @@ def from_networkx(cls, G, weight=None, dtype=None):
     return rv
 
 
-def from_graphblas(cls, A, *, key_to_id=None):
-    # Does not copy if A is a Matrix!
-    A = ensure_type(A, Matrix)
-    if A.nrows != A.ncols:
-        raise ValueError(f"Adjacency matrix must be square; got {A.nrows} x {A.ncols}")
-    rv = cls()
-    # If there is no mapping, it may be nice to keep this as None
-    if key_to_id is None:
-        rv._key_to_id = {i: i for i in range(A.nrows)}
-    else:
-        rv._key_to_id = key_to_id
-    rv._A = A
-    return rv
-
-
 ##############
 # Properties #
 ##############
@@ -144,23 +128,17 @@ def vector_to_nodemap(self, v, *, mask=None, fillvalue=None):
     elif fillvalue is not None and v.nvals < v.size:
         v(mask=~v.S) << fillvalue
 
-    rv = object.__new__(NodeMap)
-    rv.vector = v
-    rv._key_to_id = self._key_to_id
+    rv = NodeMap(v, key_to_id=self._key_to_id)
     rv._id_to_key = self._id_to_key
     return rv
-    # return NodeMap.from_graphblas(v, key_to_id=self._key_to_id)
 
 
 def vector_to_nodeset(self, v):
     from .nodeset import NodeSet
 
-    rv = object.__new__(NodeSet)
-    rv.vector = v
-    rv._key_to_id = self._key_to_id
+    rv = NodeSet(v, key_to_id=self._key_to_id)
     rv._id_to_key = self._id_to_key
     return rv
-    # return NodeSet.from_graphblas(v, key_to_id=self._key_to_id)
 
 
 def vector_to_set(self, v):
diff --git a/graphblas_algorithms/classes/digraph.py b/graphblas_algorithms/classes/digraph.py
index 7b6890d..167bd29 100644
--- a/graphblas_algorithms/classes/digraph.py
+++ b/graphblas_algorithms/classes/digraph.py
@@ -1,5 +1,6 @@
 from collections import defaultdict
 
+import graphblas as gb
 from graphblas import Matrix, Vector, binary, replace, select, unary
 
 import graphblas_algorithms as ga
@@ -415,7 +416,7 @@ def to_directed_graph(G, weight=None, dtype=None):
     if isinstance(G, DiGraph):
         return G
     try:
-        return DiGraph.from_graphblas(G)
+        return DiGraph(G)
     except TypeError:
         pass
 
@@ -435,7 +436,7 @@ def to_graph(G, weight=None, dtype=None):
         return G
     try:
         # Should we check if it can be undirected?
-        return DiGraph.from_graphblas(G)
+        return DiGraph(G)
     except TypeError:
         pass
 
@@ -538,22 +539,28 @@ class DiGraph(Graph):
     }
     graph_attr_dict_factory = dict
 
-    def __init__(self, incoming_graph_data=None, **attr):
+    def __init__(self, incoming_graph_data=None, *, key_to_id=None, **attr):
         if incoming_graph_data is not None:
-            raise NotImplementedError("incoming_graph_data is not None")
+            # Does not copy if A is a Matrix!
+            A = gb.core.utils.ensure_type(incoming_graph_data, Matrix)
+            if A.nrows != A.ncols:
+                raise ValueError(f"Adjacency matrix must be square; got {A.nrows} x {A.ncols}")
+        else:
+            A = Matrix()
         self.graph_attr_dict_factory = self.graph_attr_dict_factory
         self.graph = self.graph_attr_dict_factory()  # dictionary for graph attributes
         self.graph.update(attr)
 
         # Graphblas-specific properties
-        self._A = Matrix()
-        self._key_to_id = {}
+        self._A = A
+        if key_to_id is None:
+            key_to_id = {i: i for i in range(A.nrows)}
+        self._key_to_id = key_to_id
         self._id_to_key = None
         self._cache = {}
 
     # Graphblas-specific methods
     from_networkx = classmethod(_utils.from_networkx)
-    from_graphblas = classmethod(_utils.from_graphblas)
     id_to_key = property(_utils.id_to_key)
     get_property = _utils.get_property
     get_properties = _utils.get_properties
@@ -586,6 +593,10 @@ def name(self, s):
         self._A.name = s
         self.graph["name"] = s
 
+    @property
+    def matrix(self):
+        return self._A
+
     def __iter__(self):
         return iter(self._key_to_id)
 
diff --git a/graphblas_algorithms/classes/graph.py b/graphblas_algorithms/classes/graph.py
index bc4ba24..a8f14f3 100644
--- a/graphblas_algorithms/classes/graph.py
+++ b/graphblas_algorithms/classes/graph.py
@@ -1,5 +1,6 @@
 from collections import defaultdict
 
+import graphblas as gb
 from graphblas import Matrix, Vector, select
 
 import graphblas_algorithms as ga
@@ -153,7 +154,7 @@ def to_undirected_graph(G, weight=None, dtype=None):
     if isinstance(G, Graph):
         return G
     try:
-        return Graph.from_graphblas(G)
+        return Graph(G)
     except TypeError:
         pass
 
@@ -243,22 +244,28 @@ class Graph:
     }
     graph_attr_dict_factory = dict
 
-    def __init__(self, incoming_graph_data=None, **attr):
+    def __init__(self, incoming_graph_data=None, *, key_to_id=None, **attr):
         if incoming_graph_data is not None:
-            raise NotImplementedError("incoming_graph_data is not None")
+            # Does not copy if A is a Matrix!
+            A = gb.core.utils.ensure_type(incoming_graph_data, Matrix)
+            if A.nrows != A.ncols:
+                raise ValueError(f"Adjacency matrix must be square; got {A.nrows} x {A.ncols}")
+        else:
+            A = Matrix()
         self.graph_attr_dict_factory = self.graph_attr_dict_factory
         self.graph = self.graph_attr_dict_factory()  # dictionary for graph attributes
         self.graph.update(attr)
 
         # Graphblas-specific properties
-        self._A = Matrix()
-        self._key_to_id = {}
+        self._A = A
+        if key_to_id is None:
+            key_to_id = {i: i for i in range(A.nrows)}
+        self._key_to_id = key_to_id
         self._id_to_key = None
         self._cache = {}
 
     # Graphblas-specific methods
     from_networkx = classmethod(_utils.from_networkx)
-    from_graphblas = classmethod(_utils.from_graphblas)
     id_to_key = property(_utils.id_to_key)
     get_property = _utils.get_property
     get_properties = _utils.get_properties
@@ -292,6 +299,10 @@ def name(self, s):
         self._A.name = s
         self.graph["name"] = s
 
+    @property
+    def matrix(self):
+        return self._A
+
     def __iter__(self):
         return iter(self._key_to_id)
 
diff --git a/graphblas_algorithms/classes/nodemap.py b/graphblas_algorithms/classes/nodemap.py
index bedba8a..7878772 100644
--- a/graphblas_algorithms/classes/nodemap.py
+++ b/graphblas_algorithms/classes/nodemap.py
@@ -6,20 +6,13 @@
 
 
 class NodeMap(MutableMapping):
-    def __init__(self):
-        raise NotImplementedError()
-        # .vector, ._key_to_id, ._id_to_key
-
-    @classmethod
-    def from_graphblas(cls, v, *, key_to_id=None):
-        rv = object.__new__(cls)
-        rv.vector = v
+    def __init__(self, v, *, key_to_id=None):
+        self.vector = v
         if key_to_id is None:
-            rv._key_to_id = {i: i for i in range(v.size)}
+            self._key_to_id = {i: i for i in range(v.size)}
         else:
-            rv._key_to_id = key_to_id
-        rv._id_to_key = None
-        return rv
+            self._key_to_id = key_to_id
+        self._id_to_key = None
 
     id_to_key = property(_utils.id_to_key)
     # get_property = _utils.get_property
@@ -104,15 +97,8 @@ def setdefault(self, key, default=None):
 
 
 class VectorMap(MutableMapping):
-    def __init__(self):
-        raise NotImplementedError()
-        # .vector
-
-    @classmethod
-    def from_graphblas(cls, v):
-        rv = object.__new__(cls)
-        rv.vector = v
-        return rv
+    def __init__(self, v):
+        self.vector = v
 
     # Requirements for MutableMapping
     def __delitem__(self, key):
@@ -176,21 +162,14 @@ def setdefault(self, key, default=None):
 
 
 class VectorNodeMap(MutableMapping):
-    def __init__(self):
-        raise NotImplementedError()
-        # .matrix, ._key_to_id, ._id_to_key, ._rows
-
-    @classmethod
-    def from_graphblas(cls, A, *, key_to_id=None):
-        rv = object.__new__(cls)
-        rv.matrix = A
+    def __init__(self, A, *, key_to_id=None):
+        self.matrix = A
         if key_to_id is None:
-            rv._key_to_id = {i: i for i in range(A.size)}
+            self._key_to_id = {i: i for i in range(A.size)}
         else:
-            rv._key_to_id = key_to_id
-        rv._id_to_key = None
-        rv._rows = None
-        return rv
+            self._key_to_id = key_to_id
+        self._id_to_key = None
+        self._rows = None
 
     def _get_rows(self):
         if self._rows is None:
@@ -226,7 +205,7 @@ def __getitem__(self, key):
         idx = self._key_to_id[key]
         if self._get_rows().get(idx) is None:
             raise KeyError(key)
-        return VectorMap.from_graphblas(self.matrix[idx, :].new())
+        return VectorMap(self.matrix[idx, :].new())
 
     def __iter__(self):
         # Slow if we iterate over one; fast if we iterate over all
@@ -273,7 +252,7 @@ def get(self, key, default=None):
         idx = self._key_to_id[key]
         if self._get_rows().get(idx) is None:
             return default
-        return VectorMap.from_graphblas(self.matrix[idx, :].new())
+        return VectorMap(self.matrix[idx, :].new())
 
     # items
     # keys
@@ -285,7 +264,7 @@ def popitem(self):
             idx = next(rows.ss.iterkeys())
         except StopIteration:
             raise KeyError from None
-        value = VectorMap.from_graphblas(self.matrix[idx, :].new())
+        value = VectorMap(self.matrix[idx, :].new())
         del self.matrix[idx, :]
         del rows[idx]
         return self.id_to_key[idx], value
diff --git a/graphblas_algorithms/classes/nodeset.py b/graphblas_algorithms/classes/nodeset.py
index 81f4839..1713a7d 100644
--- a/graphblas_algorithms/classes/nodeset.py
+++ b/graphblas_algorithms/classes/nodeset.py
@@ -6,20 +6,13 @@
 
 
 class NodeSet(MutableSet):
-    def __init__(self):
-        raise NotImplementedError()
-        # .vector, ._key_to_id, ._id_to_key
-
-    @classmethod
-    def from_graphblas(cls, v, *, key_to_id=None):
-        rv = object.__new__(cls)
-        rv.vector = v
+    def __init__(self, v, *, key_to_id=None):
+        self.vector = v
         if key_to_id is None:
-            rv._key_to_id = {i: i for i in range(v.size)}
+            self._key_to_id = {i: i for i in range(v.size)}
         else:
-            rv._key_to_id = key_to_id
-        rv._id_to_key = None
-        return rv
+            self._key_to_id = key_to_id
+        self._id_to_key = None
 
     id_to_key = property(_utils.id_to_key)
     # get_property = _utils.get_property
diff --git a/graphblas_algorithms/nxapi/cluster.py b/graphblas_algorithms/nxapi/cluster.py
index 6644189..7ac5618 100644
--- a/graphblas_algorithms/nxapi/cluster.py
+++ b/graphblas_algorithms/nxapi/cluster.py
@@ -139,6 +139,6 @@ def generalized_degree(G, nodes=None):
         return G.vector_to_nodemap(result)
     mask = G.list_to_mask(nodes)
     result = algorithms.generalized_degree(G, mask=mask)
-    rv = VectorNodeMap.from_graphblas(result, key_to_id=G._key_to_id)
+    rv = VectorNodeMap(result, key_to_id=G._key_to_id)
     rv._id_to_key = G._id_to_key
     return rv