chore: bump pydantic to 2.3.0

CHANGELOG.md

@@ -7,6 +7,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## \[Unreleased\]
 
+### Changed
+
+- Update to pydantic 2.3.0 ([#159](https://github.com/Substra/substrafl/pull/159))
+
 ## [0.40.0](https://github.com/Substra/substrafl/releases/tag/0.40.0) - 2023-09-07
 
 ### Added
@@ -22,7 +26,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
     )
   ```
 
-- Dependency objects are now computed at initialization in a cache directory, accessible through the `cache_directory` attribute. The cache directory is deleted at the Dependency object deletion. ([https://github.com/Substra/substrafl/pull/155])(https://github.com/Substra/substrafl/pull/155))
+- Dependency objects are now computed at initialization in a cache directory, accessible through the `cache_directory` attribute. The cache directory is deleted at the Dependency object deletion. ([https://github.com/Substra/substrafl/pull/155])(<https://github.com/Substra/substrafl/pull/155>))
 - Check created wheels name. ([#160](https://github.com/Substra/substrafl/pull/160))
 
 ### Changed

docs/conf.py

@@ -180,6 +180,7 @@
 # The following elements are the link that auto doc were not able to do
 nitpick_ignore = [
     ("py:class", "pydantic.main.BaseModel"),
+    ("py:class", "BaseModel"),
     ("py:class", "torch.nn.modules.module.Module"),
     ("py:class", "torch.nn.modules.loss._Loss"),
     ("py:class", "torch.optim.optimizer.Optimizer"),

setup.py

@@ -42,9 +42,9 @@
     install_requires=[
         "numpy>=1.20.3, <1.24",
         "cloudpickle>=1.6.0",
-        "substra~=0.47.0",
+        "substra~=0.48.0",
         "substratools~=0.20.0",
-        "pydantic>=1.9.0, <2.0",
+        "pydantic>=2.3.0,<3.0",
         "pip>=21.2",
         "wheel",
         "six",
@@ -59,7 +59,7 @@
             "pre-commit>=2.13.0",
             "types-PyYAML>=6.0.0",
             "torch>=1.9.1,!=1.12.0",  # bug in 1.12.0 (https://github.com/pytorch/pytorch/pull/80345)
-            "nbmake>=1.1",
+            "nbmake>=1.4.3",
             "docker",
         ],
     },

substrafl/dependency/schemas.py

@@ -70,7 +70,6 @@ class Dependency(BaseModel):
 
     class Config:
         arbitrary_types_allowed = True
-        underscore_attrs_are_private = True
 
     def __init__(self, *args, **kwargs):
         """Dependencies are computed at object initialization.

substrafl/nodes/aggregation_node.py

@@ -77,7 +77,7 @@ def update_states(
             else None
         )
 
-        task_metadata = {"round_idx": round_idx} if round_idx is not None else {}
+        task_metadata = {"round_idx": str(round_idx)} if round_idx is not None else {}
         aggregate_task = substra.schemas.ComputePlanTaskSpec(
             function_key=str(uuid.uuid4()),  # bogus function key
             task_id=op_id,

substrafl/nodes/test_data_node.py

@@ -114,7 +114,7 @@ def update_states(
                 parent_task_output_identifier=OutputIdentifiers.predictions,
             )
         ]
-        task_metadata = {"round_idx": round_idx} if round_idx is not None else {}
+        task_metadata = {"round_idx": str(round_idx)} if round_idx is not None else {}
 
         predicttask = substra.schemas.ComputePlanTaskSpec(
             function_key=str(uuid.uuid4()),  # bogus function key

substrafl/nodes/train_data_node.py

@@ -66,7 +66,7 @@ def init_states(
                 ),
             },
             metadata={
-                "round_idx": round_idx,
+                "round_idx": str(round_idx),
             },
             tag=TaskType.INITIALIZATION,
             worker=self.organization_id,
@@ -160,7 +160,7 @@ def update_states(
         else:
             shared_inputs = []
 
-        task_metadata = {"round_idx": round_idx} if round_idx is not None else {}
+        task_metadata = {"round_idx": str(round_idx)} if round_idx is not None else {}
         train_task = substra.schemas.ComputePlanTaskSpec(
             function_key=str(uuid.uuid4()),  # bogus function key
             task_id=op_id,