Support Python 3.15 and the GDS client 2.3

.github/workflows/unit-tests.yml

@@ -26,7 +26,7 @@ jobs:
       fail-fast: false
       matrix:
         os: [ubuntu-latest]
-        python-version: ["3.11", "3.12", "3.13", "3.14"]
+        python-version: ["3.11", "3.12", "3.13", "3.14", "3.15"]
 
     defaults:
       run:

changelog.md

@@ -6,8 +6,15 @@
 
 ## Bug fixes
 
+* Avoid pandas 3.1 deprecation warnings when building a graph from GDS
+
 ## Improvements
 
+* Support Python 3.15
+* Support the GDS client 2.3
+
 ## Other changes
 
 * Drop support for Python 3.10
+* On Python 3.15, the `pandas` extra installs pandas 3 (pandas 2 has no 3.15 wheels)
+* The `snowflake` extra is not available on Python 3.15 until `snowflake-connector-python` ships 3.15 wheels

python-wrapper/pyproject.toml

@@ -22,6 +22,7 @@ classifiers = [
     "Programming Language :: Python :: 3.12",
     "Programming Language :: Python :: 3.13",
     "Programming Language :: Python :: 3.14",
+    "Programming Language :: Python :: 3.15",
     "Topic :: Database :: Front-Ends",
     "Topic :: Scientific/Engineering",
     "Topic :: Scientific/Engineering :: Visualization",
@@ -41,10 +42,17 @@ requires-python = ">=3.11"
 
 
 [project.optional-dependencies]
-pandas = ["pandas>=2, <3", "pandas-stubs>=2, <3"]
+# pandas 2 has no Python 3.15 wheels, so 3.15+ uses pandas 3 (which needs >=3.11).
+pandas = [
+    "pandas>=2, <3; python_version < '3.15'",
+    "pandas>=3, <4; python_version >= '3.15'",
+    "pandas-stubs>=2, <3; python_version < '3.15'",
+    "pandas-stubs>=3, <4; python_version >= '3.15'",
+]
 gds = ["graphdatascience>=1.22, <3"]
 neo4j = ["neo4j"]
-snowflake = ["snowflake-snowpark-python<2,>=1"]
+# snowflake-connector-python has no 3.15 wheels yet, so the extra is unavailable there.
+snowflake = ["snowflake-snowpark-python<2,>=1; python_version < '3.15'"]
 # The Streamlit integration (neo4j_viz.streamlit) uses the Components v2 API,
 # available from streamlit 1.58.
 streamlit = ["streamlit<2,>=1.58"]
@@ -61,7 +69,7 @@ dev = [
     "pytest-mock==3.17.0",
     "playwright==1.64.1",
     "nbconvert==7.17.2",
-    "streamlit==1.65.0",
+    "streamlit==1.66.1",
     "matplotlib>=3.9.4",
     "jupyterlab>=4.5.7",
     "marimo",
@@ -83,7 +91,7 @@ notebook = [
     "ipywidgets>=8.0.0",
     "palettable>=3.3.3",
     "matplotlib>=3.9.4",
-    "snowflake-snowpark-python==1.55.3",
+    "snowflake-snowpark-python==1.55.3; python_version < '3.15'",
     "requests",
     "python-dotenv"
 ]

python-wrapper/src/neo4j_viz/gds.py

@@ -153,8 +153,7 @@ def from_gds(
             gds, G_fetched, node_properties_by_label, node_properties_by_label.keys(), db_node_properties
         )
         if property_name is not None:
-            for df in node_dfs.values():
-                df.drop(columns=[property_name], inplace=True)
+            node_dfs = {lbl: df.drop(columns=[property_name]) for lbl, df in node_dfs.items()}
 
         rel_dfs = _fetch_rel_dfs(gds, G_fetched)
     finally:
@@ -163,16 +162,19 @@ def from_gds(
         elif property_name is not None:
             _catalog(gds).node_properties.drop(G_fetched, node_properties=[property_name])
 
-    for df in node_dfs.values():
-        if property_name is not None and property_name in df.columns:
-            df.drop(columns=[property_name], inplace=True)
+    if property_name is not None:
+        node_dfs = {
+            lbl: df.drop(columns=[property_name]) if property_name in df.columns else df for lbl, df in node_dfs.items()
+        }
 
     node_props_df = pd.concat(node_dfs.values(), ignore_index=True, axis=0).drop_duplicates(subset=["nodeId"])
 
-    for lbl, df in node_dfs.items():
+    for lbl in node_dfs:
+        df = node_dfs[lbl]
         if "labels" in all_gds_properties:
-            df.rename(columns={"labels": "__labels"}, inplace=True)
+            df = df.rename(columns={"labels": "__labels"})
         df["labels"] = lbl
+        node_dfs[lbl] = df
 
     node_labels_df = pd.concat([df[["nodeId", "labels"]] for df in node_dfs.values()], ignore_index=True, axis=0)
     node_labels_df = node_labels_df.groupby("nodeId").agg({"labels": list})

python-wrapper/src/neo4j_viz/pandas.py

@@ -70,7 +70,7 @@ def _parse_nodes(node_dfs: DFS_TYPE, dropna: bool = False) -> list[Node]:
     for node_df in node_dfs_iter:
         for _, row in node_df.iterrows():
             if dropna:
-                row = row.dropna(inplace=False)
+                row = row.dropna()
             mandatory_fields = {}
             properties = {}
             for key, value in row.to_dict().items():
@@ -102,7 +102,7 @@ def _parse_relationships(rel_dfs: DFS_TYPE, dropna: bool = False) -> list[Relati
     for rel_df in rel_dfs_iter:
         for _, row in rel_df.iterrows():
             if dropna:
-                row = row.dropna(inplace=False)
+                row = row.dropna()
             mandatory_fields = {}
             properties = {}
             for key, value in row.to_dict().items():