Update Pydantic to version 2

- Upgrading Pydantic from version 1 to 2. This is not backwardly compatible.
- Modify all `model` definitions to comply with Pydantic updates.
- Upgrading Modine and Ray.
- Fix tests effected by updates.
- Minor updates to documentation.
- No functional or API changes.

Author: turukawa

.gitignore

@@ -8,6 +8,7 @@ Thumbs.db
 # Folder config file
 Desktop.ini
 .vscode/
+*.code-workspace
 
 #############
 ## Python
@@ -32,6 +33,7 @@ develop-eggs
 
 # Installer logs
 pip-log.txt
+log.txt
 
 # Unit test / coverage reports
 .coverage

CHANGELOG

@@ -1,3 +1,4 @@
+- 1.2.0: Upgrading Pydantic from version 1.8 to version 2.10
 - 1.1.3: Improving exception error messages to be more helpful.
 - 1.1.2: Fixes for `CATEGORY` parser for ambiguous term names.
 - 1.1.1: Fixes for action parser where field names contain ambiguous characters.

docs-requirements.txt

@@ -0,0 +1,8 @@
+markdown==3.5.2
+mkdocs==1.5.3
+pymdown-extensions==10.7.1
+paginate==0.5.6
+mkdocs-exclude==1.0.2
+mkdocstrings-python==1.8.0
+mkdocs-redirects==1.2.1
+mkdocs-material==9.5.13

docs/strategies/datasource.md

@@ -77,7 +77,7 @@ datasource.validate()
 source data, including a [citation](#citation). If your data are accessable via a persistent url, then distributing
 this file ensures that all metadata definitions associated with your source data are maintained.
 
-`.validate` will repeat the derivation and test that the [checksum](#derive-a-schema-from-source-data) derived for the 
+`.validate` will repeat the derivation and test that the [checksum](#hashing-for-data-probity) derived for the 
 model is repeatable.
 
 **whyqd** can import this file and produce schemas, crosswalks and data transformations.
@@ -91,7 +91,7 @@ model is repeatable.
 You can read it:
 
 ```python
-datasource.get.dict(by_alias=True, exclude_defaults=True, exclude_none=True)
+datasource.get.model_dump(by_alias=True, exclude_defaults=True, exclude_none=True)
 
 {'uuid': UUID('827941cb-fc89-4849-beea-5779fefb9f87'),
  'path': DATASOURCE_PATH,
@@ -236,7 +236,7 @@ Categorical terms are not validated on assignment, so if you choose to set arbit
 ```python
 name = "column_1"
 st.set_field_categories(name=name, terms=["fish", "frog", "fennel"])
-st.schema.fields.get(name=name).dict(by_alias=True, exclude_defaults=True, exclude_none=True)
+st.schema.fields.get(name=name).model_dump(by_alias=True, exclude_defaults=True, exclude_none=True)
 
 	{'uuid': UUID('a43b7a94-ca6f-438d-83b9-4c84d9d7a0b7'),
 	 'name': 'column_1',

docs/strategies/schema.md

@@ -374,7 +374,7 @@ constraints = {
     ]
   }
 schema_destination.fields.set_constraints(name="occupation_state_reliefs", constraints=constraints)
-schema_destination.fields.get(name="occupation_state_reliefs").dict(by_alias=True, exclude_defaults=True, exclude_none=True)
+schema_destination.fields.get(name="occupation_state_reliefs").model_dump(by_alias=True, exclude_defaults=True, exclude_none=True)
 
   {'uuid': UUID('cf4d066e-22a8-4b76-8956-f6120eec4c52'),
   'name': 'occupation_state_reliefs',
@@ -398,7 +398,7 @@ schema_destination.fields.get(name="occupation_state_reliefs").dict(by_alias=Tru
   {'uuid': UUID('8a3af6f4-f48c-4614-83f2-ba472b2129e9'), 'name': 'other'}]}}
 ```
 
-The term `.dict(by_alias=True, exclude_defaults=True, exclude_none=True)` is used to extract a dictionary format from 
+The term `.model_dump(by_alias=True, exclude_defaults=True, exclude_none=True)` is used to extract a dictionary format from 
 the underlying [Pydantic](https://pydantic-docs.helpmanual.io/) model used by `whyqd`.
 
 !!! info
@@ -409,7 +409,7 @@ the underlying [Pydantic](https://pydantic-docs.helpmanual.io/) model used by `w
 Review your schema, then `save` and we're ready to begin schema-to-schema conversion:
 
 ```python
-schema_destination.get.dict(by_alias=True, exclude_defaults=True, exclude_none=True)
+schema_destination.get.model_dump(by_alias=True, exclude_defaults=True, exclude_none=True)
 
 	{'uuid': UUID('19692345-2caf-46b1-9a8f-276491520c6b'),
 	'name': 'test_schema',

docs/tutorials/tutorial1.md

@@ -183,12 +183,12 @@ constraints = {
 schema_destination.fields.set_constraints(name="occupation_state_reliefs", constraints=constraints)
 ```
 
-Use `.dict(by_alias=True, exclude_defaults=True, exclude_none=True)` to extract a dictionary format from the underlying
+Use `.model_dump(by_alias=True, exclude_defaults=True, exclude_none=True)` to extract a dictionary format from the underlying
 [Pydantic](https://pydantic-docs.helpmanual.io/) model.
 
 ```python
 schema_destination.fields.get(name="occupation_state_reliefs"
-                              ).dict(
+                              ).model_dump(
                                 by_alias=True, 
                                 exclude_defaults=True, 
                                 exclude_none=True)
@@ -315,7 +315,7 @@ for ds in datasource.get:
 Leaving us with a list of source schema, along with their appropriate categories:
 
 ```python
-SCHEMA_SOURCE["Report1"].get.dict(by_alias=True, exclude_defaults=True, exclude_none=True)
+SCHEMA_SOURCE["Report1"].get.model_dump(by_alias=True, exclude_defaults=True, exclude_none=True)
 
 {'uuid': UUID('a25091ef-2bad-4207-8e04-dc50760de5f9'),
  'name': 'portsmouth-report1',

mkdocs.yml

@@ -81,8 +81,8 @@ markdown_extensions:
 - pymdownx.highlight
 - pymdownx.extra
 - pymdownx.emoji:
-    emoji_index: !!python/name:materialx.emoji.twemoji
-    emoji_generator: !!python/name:materialx.emoji.to_svg
+    emoji_index: !!python/name:material.extensions.emoji.twemoji
+    emoji_generator: !!python/name:material.extensions.emoji.to_svg
 - pymdownx.tabbed:
     alternate_style: true
 
@@ -92,6 +92,8 @@ watch:
 plugins:
 - search
 - mkdocstrings:
+    default_handler: python
     handlers:
       python:
-        path: .
+        options:
+          show_source: false