Expose rel label for Python and Node.js API

tools/nodejs_api/src_cpp/node_util.cpp

@@ -1,11 +1,11 @@
 #include "include/node_util.h"
 
 #include "common/exception/exception.h"
-#include "common/types/value/value.h"
 #include "common/types/value/nested.h"
 #include "common/types/value/node.h"
 #include "common/types/value/recursive_rel.h"
 #include "common/types/value/rel.h"
+#include "common/types/value/value.h"
 
 Napi::Value Util::ConvertToNapiObject(const Value& value, Napi::Env env) {
     if (value.isNull()) {
@@ -119,6 +119,7 @@ Napi::Value Util::ConvertToNapiObject(const Value& value, Napi::Env env) {
         }
         napiObj.Set("_src", ConvertNodeIdToNapiObject(RelVal::getSrcNodeID(&value), env));
         napiObj.Set("_dst", ConvertNodeIdToNapiObject(RelVal::getDstNodeID(&value), env));
+        napiObj.Set("_label", Napi::String::New(env, RelVal::getLabelName(&value)));
         return napiObj;
     }
     case LogicalTypeID::INTERNAL_ID: {

tools/nodejs_api/test/test_data_type.js

@@ -294,6 +294,7 @@ describe("REL", function () {
     assert.equal(rel.grading.length, 2);
     assert.equal(rel.grading[0], 2.1);
     assert.equal(rel.grading[1], 4.4);
+    assert.equal(rel._label, "workAt");
     assert.approximately(rel.rating, 7.6, EPSILON);
   });
 });
@@ -327,6 +328,7 @@ describe("RECURSIVE_REL", function () {
           usedAddress: null,
           address: null,
           note: null,
+          _label: "studyAt",
           _src: {
             offset: 0,
             table: 0,

tools/python_api/src_cpp/py_query_result.cpp

@@ -169,6 +169,7 @@ py::object PyQueryResult::convertValueToPyObject(const Value& value) {
         py::dict dict;
         dict["_src"] = convertNodeIdToPyDict(RelVal::getSrcNodeID(&value));
         dict["_dst"] = convertNodeIdToPyDict(RelVal::getDstNodeID(&value));
+        dict["_label"] = py::cast(RelVal::getLabelName(&value));
         auto numProperties = RelVal::getNumProperties(&value);
         for (auto i = 0u; i < numProperties; ++i) {
             auto key = py::str(RelVal::getPropertyName(&value, i));

tools/python_api/test/test_datatype.py

@@ -141,6 +141,7 @@ def test_rel(establish_connection):
     assert (r['year'] == 2010)
     assert (r['_src'] == p['_id'])
     assert (r['_dst'] == o['_id'])
+    assert (r['_label'] == 'workAt')
     assert not result.has_next()
     result.close()
 
@@ -179,6 +180,7 @@ def test_recursive_rel(establish_connection):
     rel = e["_rels"][0]
     excepted_rel = {'_src': {'offset': 0, 'table': 0},
                     '_dst': {'offset': 0, 'table': 1},
+                    '_label': 'studyAt', 
                     'date': None, 'meetTime': None, 'validInterval': None,
                     'comments': None, 'year': 2021,
                     'places': ['wwAewsdndweusd', 'wek'],

tools/python_api/test/test_torch_geometric.py

@@ -188,7 +188,7 @@ def test_to_torch_geometric_homogeneous_graph(establish_connection):
         assert src != dst
         assert pos_to_idx[dst] in ground_truth.TINY_SNB_KNOWS_GROUND_TRUTH[pos_to_idx[src]]
 
-    assert len(edge_properties) == 4
+    assert len(edge_properties) == 5
     assert 'date' in edge_properties
     assert 'meetTime' in edge_properties
     assert 'validInterval' in edge_properties
@@ -310,11 +310,12 @@ def test_to_torch_geometric_heterogeneous_graph(establish_connection):
         assert src != dst
         assert pos_to_idx['person'][dst] in ground_truth.TINY_SNB_KNOWS_GROUND_TRUTH[pos_to_idx['person'][src]]
 
-    assert len(edge_properties['person', 'person']) == 4
+    assert len(edge_properties['person', 'person']) == 5
     assert 'date' in edge_properties['person', 'person']
     assert 'meetTime' in edge_properties['person', 'person']
     assert 'validInterval' in edge_properties['person', 'person']
     assert 'comments' in edge_properties['person', 'person']
+    assert '_label' in edge_properties['person', 'person']
     for i in range(3):
         src, dst = torch_geometric_data['person', 'person'].edge_index[0][i].item(
         ), torch_geometric_data['person', 'person'].edge_index[1][i].item()
@@ -328,6 +329,7 @@ def test_to_torch_geometric_heterogeneous_graph(establish_connection):
             original_src, original_dst)]['validInterval'] == edge_properties['person', 'person']['validInterval'][i]
         assert ground_truth.TINY_SNB_KNOWS_PROPERTIES_GROUND_TRUTH[(
             original_src, original_dst)]['comments'] == edge_properties['person', 'person']['comments'][i]
+        assert edge_properties['person', 'person']['_label'][i] == 'knows'
 
     assert torch_geometric_data['organisation'].ID.shape == torch.Size([2])
     assert torch_geometric_data['organisation'].ID.dtype == torch.int64
@@ -386,14 +388,16 @@ def test_to_torch_geometric_heterogeneous_graph(establish_connection):
         assert dst in pos_to_idx['organisation']
         assert src != dst
         assert pos_to_idx['organisation'][dst] in ground_truth.TINY_SNB_WORKS_AT_GROUND_TRUTH[pos_to_idx['person'][src]]
-    assert len(edge_properties['person', 'organisation']) == 3
+    assert len(edge_properties['person', 'organisation']) == 4
     assert 'year' in edge_properties['person', 'organisation']
+    assert '_label' in edge_properties['person', 'organisation']
     for i in range(2):
         src, dst = torch_geometric_data['person', 'organisation'].edge_index[0][i].item(
         ), torch_geometric_data['person', 'organisation'].edge_index[1][i].item()
         original_src, original_dst = pos_to_idx['person'][src], pos_to_idx['organisation'][dst]
         assert ground_truth.TINY_SNB_WORKS_AT_PROPERTIES_GROUND_TRUTH[(
             original_src, original_dst)]['year'] == edge_properties['person', 'organisation']['year'][i]
+        assert edge_properties['person', 'organisation']['_label'][i] == 'workAt'
 
 
 def test_to_torch_geometric_multi_dimensional_lists(establish_connection):