Fix for issue #22: ensuring order of imports and using local imports

README.md

@@ -32,11 +32,14 @@ pip install fastgraphml
 #### Example Homogneous Graphs
 
 ```python
-from fastgraphml.graph_embeddings import SAGE, GAT
+from fastgraphml.graph_embeddings import get_sage_model, get_gat_model
 from fastgraphml.graph_embeddings import downstream_tasks
 from fastgraphml import Datasets 
 from arango import ArangoClient
 
+SAGE = get_sage_model()
+GAT  = get_gat_model() 
+
 # Initialize the ArangoDB client.
 client = ArangoClient("http://127.0.0.1:8529")
 db = client.db('_system', username='root', password='')
@@ -66,12 +69,15 @@ embeddings = model.get_embeddings() # get embeddings
 #### Example Heterogeneous Graphs
 
 ```python
-from fastgraphml.graph_embeddings import METAPATH2VEC, DMGI
+from fastgraphml.graph_embeddings import get_metapath2vec_model, get_dmgi_model
 from fastgraphml.graph_embeddings import downstream_tasks 
 from fastgraphml import Datasets 
 
 from arango import ArangoClient
 
+METAPATH2VEC = get_metapath2vec_model()
+DMGI         = get_dmgi_model()
+
 # Initialize the ArangoDB client.
 client = ArangoClient("http://127.0.0.1:8529")
 db = client.db('_system', username='root')
@@ -107,10 +113,13 @@ embeddings = model.get_embeddings() # get embeddings
 ### Use Case 2: Generates Graph Embeddings using PyG graphs:
 
 ```python
-from fastgraphml.graph_embeddings import SAGE, GAT
+from fastgraphml.graph_embeddings import get_sage_model, get_gat_model
 from fastgraphml.graph_embeddings import downstream_tasks 
 from torch_geometric.datasets import Planetoid
 
+SAGE = get_sage_model()
+GAT  = get_gat_model()
+
 # load pyg dataset
 dataset = Planetoid(root='/tmp/Cora', name='Cora')
 data = dataset[0]

fastgraphml/__init__.py

@@ -1,8 +1,18 @@
-from arango_datasets.datasets import Datasets
+def get_dmgi_model():
+    from .graph_embeddings.models.dmgi import DMGI
+    return DMGI
 
-from fastgraphml.graph_embeddings.models.dmgi import DMGI
-from fastgraphml.graph_embeddings.models.gat import GAT
-from fastgraphml.graph_embeddings.models.graph_sage import SAGE
-from fastgraphml.graph_embeddings.models.metapath2vec import METAPATH2VEC
+def get_gat_model():
+    from .graph_embeddings.models.gat import GAT
+    return GAT
+
+def get_sage_model():
+    from .graph_embeddings.models.graph_sage import SAGE
+    return SAGE
+
+def get_metapath2vec_model():
+    from .graph_embeddings.models.metapath2vec import METAPATH2VEC
+    return METAPATH2VEC
+
+__all__ = ["get_dmgi_model", "get_gat_model", "get_sage_model", "get_metapath2vec_model"]
 
-__all__ = ["DMGI", "GAT", "SAGE", "METAPATH2VEC", "Datasets"]

fastgraphml/graph_embeddings/__init__.py

@@ -1,6 +1,18 @@
-from fastgraphml.graph_embeddings.models.dmgi import DMGI
-from fastgraphml.graph_embeddings.models.gat import GAT
-from fastgraphml.graph_embeddings.models.graph_sage import SAGE
-from fastgraphml.graph_embeddings.models.metapath2vec import METAPATH2VEC
+def get_dmgi_model():
+    from .models.dmgi import DMGI
+    return DMGI
+
+def get_gat_model():
+    from .models.gat import GAT
+    return GAT
+
+def get_sage_model():
+    from .models.graph_sage import SAGE
+    return SAGE
+
+def get_metapath2vec_model():
+    from .models.metapath2vec import METAPATH2VEC
+    return METAPATH2VEC
+
+__all__ = ["get_dmgi_model", "get_gat_model", "get_sage_model", "get_metapath2vec_model"]
 
-__all__ = ["DMGI", "GAT", "SAGE", "METAPATH2VEC"]