Adds properties on edges (#306)

Define relationship properties in many_to_many via name_mappings and properties field

docs/how-to-guides/loaders/import-table-data-to-graph-database.md

@@ -27,14 +27,21 @@ data is located, here are two guides on how to import it to Memgraph:
 
 ## Loading a CSV file from the local file system
 
-Let's say you have a simple table data in a CSV file stored at
-`/home/user/table_data`:
+Let's say you have a simple dataset stored in CSV files:
 
+`/home/user/table_data/individual.csv`:
 ```csv
-name,surname,grade
-Ivan,Horvat,4
-Marko,Andric,5
-Luka,Lukic,3
+ind_id, name, surname, add_id
+1, Ivan,  Horvat, 2
+2, Marko, Andric, 2
+3, Luka,  Lukic,  1
+```
+
+`/home/user/table_data/address.csv`:
+```csv
+add_id, street, num, city
+1, Ilica,    2,  Zagreb
+2, Broadway, 12, New York
 ```
 
 To create a translation from table to graph data, you need to define a **data
@@ -78,24 +85,37 @@ many_to_many_relations:       # intended to be used in case of associative table
       column_name:
       reference_table:
       reference_key:
-    label:
+    label:                   # relationship's label
+    properties:              # list of properties to add to the relationship
 
 ```
 
+### One to many
+
 For this example, you don't need all of those fields. You only need to define
 `indices` and `one_to_many_relations`. Hence, you have the following YAML file:
 
 ```yaml
 indices:
-  example:
-    - name
+  address:
+    - add_id
+  individual:
+    - ind_id
 
 name_mappings:
-  example:
-    label: PERSON
+  individual:
+    label: INDIVIDUAL
+  address:
+    label: ADDRESS
 
 one_to_many_relations:
-  example: []
+  address: []
+  individual:
+    - foreign_key:
+        column_name: add_id
+        reference_table: address
+        reference_key: add_id
+      label: LIVES_IN
 ```
 
 In order to read the data configuration from the YAML file, run:
@@ -114,12 +134,65 @@ make an instance of an `Importer` and call `translate()`.
 ```python
 importer = CSVLocalFileSystemImporter(
     data_configuration=parsed_yaml,
-    path="/home/user/table_data",
+    path="/home/user/table_data/",
 )
 
 importer.translate(drop_database_on_start=True)
 ```
 
+### Many to many
+
+Relationships can also be defined using a third, associative table.
+
+`/home/user/table_data/tenant.csv`:
+```csv
+ind_id, add_id, duration
+1, 2, 21
+2, 2, 3
+3, 1, 5
+```
+
+We need to extend our data configuration YAML file to include the `many_to_many_relations`, like so:
+
+```
+indices:
+  address:
+    - add_id
+  individual:
+    - ind_id
+
+name_mappings:
+  individual:
+    label: INDIVIDUAL
+  address:
+    label: ADDRESS
+  tenant:
+    column_names_mapping:
+      duration: years
+
+one_to_many_relations:
+  address: []
+  individual: []
+
+many_to_many_relations:
+  tenant:
+    foreign_key_from:
+      column_name: ind_id
+      reference_table: individual
+      reference_key: ind_id
+    foreign_key_to:
+      column_name: add_id
+      reference_table: address
+      reference_key: add_id
+    label: LIVES_IN
+    properties:
+      - duration
+```
+
+From here the procedure is the same as before.
+In addition to having imported nodes and connected individuals and their addresses, we have also added an edge property.
+This property is read from the associative table and is named in accordance with the `name_mappings`.
+
 ## Using a cloud storage solution
 
 To connect to Azure Blob, simply change the Importer object you are using. Like

docs/reference/gqlalchemy/transformations/importing/loaders.md

@@ -27,7 +27,6 @@ Class that holds the full description of a single one to many mapping in a table
 - `foreign_key` - Foreign key used for mapping.
 - `label` - Label which will be applied to the relationship created from this object.
 - `from_entity` - Direction of the relationship created from the mapping object.
-- `parameters` - Parameters that will be added to the relationship created from this object (Optional).
 
 ## ManyToManyMapping Objects
 
@@ -44,7 +43,7 @@ Many to many mapping is intended to be used in case of associative tables.
 - `foreign_key_from` - Describes the source of the relationship.
 - `foreign_key_to` - Describes the destination of the relationship.
 - `label` - Label to be applied to the newly created relationship.
-- `parameters` - Parameters that will be added to the relationship created from this object (Optional).
+- `properties` - List of properties that will be added to the relationship created from this object (Optional).
 
 ## TableMapping Objects
 

gqlalchemy/transformations/importing/loaders.py

@@ -97,13 +97,11 @@ class OneToManyMapping:
         foreign_key: Foreign key used for mapping.
         label: Label which will be applied to the relationship created from this object.
         from_entity: Direction of the relationship created from the mapping object.
-        parameters: Parameters that will be added to the relationship created from this object (Optional).
     """
 
     foreign_key: ForeignKeyMapping
     label: str
     from_entity: bool = False
-    parameters: Optional[Dict[str, str]] = None
 
 
 @dataclass(frozen=True)
@@ -115,13 +113,13 @@ class ManyToManyMapping:
         foreign_key_from: Describes the source of the relationship.
         foreign_key_to: Describes the destination of the relationship.
         label: Label to be applied to the newly created relationship.
-        parameters: Parameters that will be added to the relationship created from this object (Optional).
+        properties: Properties that will be added to the relationship created from this object (Optional).
     """
 
     foreign_key_from: ForeignKeyMapping
     foreign_key_to: ForeignKeyMapping
     label: str
-    parameters: Optional[Dict[str, str]] = None
+    properties: Optional[List[str]] = None
 
 
 Mapping = Union[List[OneToManyMapping], ManyToManyMapping]
@@ -494,6 +492,8 @@ def _load_cross_relationships(self) -> None:
                     property_from=mapping_from.reference_key,
                     property_to=mapping_to.reference_key,
                     relation_label=many_to_many_mapping.mapping.label,
+                    table_name=many_to_many_mapping.table_name,
+                    properties=many_to_many_mapping.mapping.properties,
                     row=row,
                 )
 
@@ -606,6 +606,8 @@ def _save_row_as_relationship(
         property_from: str,
         property_to: str,
         relation_label: str,
+        table_name: str,
+        properties: List[str],
         row: Dict[str, Any],
     ) -> None:
         """Translates a row to a relationship and writes it to Memgraph.
@@ -616,6 +618,8 @@ def _save_row_as_relationship(
             property_from: Property of the source node.
             property_to: Property of the destination node.
             relation_label: Label for the relationship.
+            table_name: Name of the table used to read properties
+            properties: Relationship properties to be added
             row: The row to be translated.
         """
         (
@@ -642,7 +646,13 @@ def _save_row_as_relationship(
             )
             .create()
             .node(variable=NODE_A)
-            .to(relation_label)
+            .to(
+                relationship_type=relation_label,
+                **{
+                    self._name_mapper.get_property_name(collection_name=table_name, column_name=prop): row[prop]
+                    for prop in properties
+                },
+            )
             .node(variable=NODE_B)
             .execute()
         )

tests/transformations/loaders/data/address.csv

@@ -0,0 +1,5 @@
+add_id,street,street_num,city
+1,Ilica,2,Zagreb
+2,Death Valley,0,Knowhere
+3,Horvacanska,3,Horvati
+4,Broadway,12,New York

tests/transformations/loaders/data/i2a.csv

@@ -0,0 +1,3 @@
+add_id,ind_id,duration
+1,2,12
+2,1,5

tests/transformations/loaders/data/individual.csv

@@ -0,0 +1,6 @@
+ind_id,name,surname,add_id
+1,Tomislav,Petrov,1
+2,Ivan,Horvat,3
+3,Marko,Horvat,3
+4,John,Doe,2
+5,John,Though,4

tests/transformations/loaders/test_loaders.py

@@ -106,6 +106,48 @@ def test_local_table_to_graph_importer_csv(memgraph):
     importer = CSVLocalFileSystemImporter(path=path, data_configuration=my_configuration, memgraph=memgraph)
     importer.translate(drop_database_on_start=True)
 
+    conf_with_edge_params = {
+        "indices": {"address": ["add_id"], "individual": ["ind_id"]},
+        "name_mappings": {"individual": {"label": "INDIVIDUAL"}, "address": {"label": "ADDRESS"}},
+        "one_to_many_relations": {
+            "address": [],
+            "individual": [
+                {
+                    "foreign_key": {"column_name": "add_id", "reference_table": "address", "reference_key": "add_id"},
+                    "label": "LIVES_IN",
+                }
+            ],
+        },
+    }
+    importer = CSVLocalFileSystemImporter(path=path, data_configuration=conf_with_edge_params, memgraph=memgraph)
+    importer.translate(drop_database_on_start=True)
+
+    conf_with_many_to_many = {
+        "indices": {"address": ["add_id"], "individual": ["ind_id"]},
+        "name_mappings": {
+            "individual": {"label": "INDIVIDUAL"},
+            "address": {"label": "ADDRESS"},
+            "i2a": {
+                "column_names_mapping": {"duration": "years"},
+            },
+        },
+        "one_to_many_relations": {"address": [], "individual": []},
+        "many_to_many_relations": {
+            "i2a": {
+                "foreign_key_from": {
+                    "column_name": "ind_id",
+                    "reference_table": "individual",
+                    "reference_key": "ind_id",
+                },
+                "foreign_key_to": {"column_name": "add_id", "reference_table": "address", "reference_key": "add_id"},
+                "label": "LIVES_IN",
+                "properties": ["duration"],
+            }
+        },
+    }
+    importer = CSVLocalFileSystemImporter(path=path, data_configuration=conf_with_many_to_many, memgraph=memgraph)
+    importer.translate(drop_database_on_start=True)
+
 
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