Update various blocks for pydantic v2

Author: BenjaminCharmes

pydatalab/src/pydatalab/apps/chat/blocks.py

@@ -205,8 +205,8 @@ def _prepare_item_json_for_chat(self, item_id: str, item_data: dict | None = Non
             item_model.blocks_obj = {
                 k: block for k, block in item_model.blocks_obj.items() if block.blocktype != "chat"
             }
-        item_data = item_model.dict(exclude_none=True, exclude_unset=True)
-        item_data["type"] = item_model.type
+        item_info = item_model.model_dump(exclude_none=True, exclude_unset=True)
+        item_info["type"] = item_model.type
 
         # strip irrelevant or large fields
         item_filenames = {

pydatalab/src/pydatalab/apps/xrd/blocks.py

@@ -263,7 +263,7 @@ def generate_xrd_plot(self, filenames: list[str | Path] | None = None) -> None:
                 except Exception as exc:
                     warnings.warn(f"Could not parse file {f['location']} as XRD data. Error: {exc}")
                     continue
-                peak_information[str(f["immutable_id"])] = PeakInformation(**peak_data).dict()
+                peak_information[str(f["immutable_id"])] = PeakInformation(**peak_data).model_dump()
                 pattern_df["normalized intensity (staggered)"] += ind
                 pattern_dfs.append(pattern_df)
 
@@ -292,7 +292,9 @@ def generate_xrd_plot(self, filenames: list[str | Path] | None = None) -> None:
             peak_model = PeakInformation(**peak_data)
             if "computed" not in self.data:
                 self.data["computed"] = {"peak_data": {}}
-            self.data["computed"]["peak_data"][str(file_info["immutable_id"])] = peak_model.dict()
+            self.data["computed"]["peak_data"][str(file_info["immutable_id"])] = (
+                peak_model.model_dump()
+            )
             pattern_dfs = [pattern_df]
 
         else:
@@ -311,7 +313,7 @@ def generate_xrd_plot(self, filenames: list[str | Path] | None = None) -> None:
                 peak_model = PeakInformation(**peak_data)
                 if "computed" not in self.data:
                     self.data["computed"] = {"peak_data": {}}
-                self.data["computed"]["peak_data"][f] = peak_model.dict()
+                self.data["computed"]["peak_data"][f] = peak_model.model_dump()
                 pattern_dfs = [pattern_df]
 
         if pattern_dfs:

pydatalab/src/pydatalab/blocks/base.py

@@ -201,7 +201,7 @@ def to_db(self) -> dict:
         block, ready to be input into mongodb"""
 
         LOGGER.debug("Casting block %s to database object.", self.__class__.__name__)
-        return self.block_db_model(**self.data).dict(
+        return self.block_db_model(**self.data).model_dump(
             exclude={"bokeh_plot_data", "b64_encoded_image"}, exclude_unset=True
         )
 
@@ -245,7 +245,7 @@ def to_web(self) -> dict[str, Any]:
         else:
             self.data.pop("warnings", None)
 
-        return self.block_db_model(**self.data).dict(exclude_unset=True, exclude_none=True)
+        return self.block_db_model(**self.data).model_dump(exclude_unset=True, exclude_none=True)
 
     def process_events(self, events: list[dict] | dict):
         """Handle any supported events passed to the block."""
@@ -333,7 +333,7 @@ def update_from_web(self, data: dict):
             self.__class__.__name__,
         )
         self.data.update(
-            self.block_db_model(**data).dict(
+            self.block_db_model(**data).model_dump(
                 exclude={"computed", "metadata", "bokeh_plot_data", "b64_encoded_image"},
                 exclude_unset=True,
             )