Remove pydantic-yaml as dependency

pyproject.toml

@@ -29,7 +29,7 @@ dependencies = [
   "numpy",
   "isoduration",
   "pydantic",
-  "pydantic-yaml",
+  "ruamel.yaml",
   "aiida-core>=2.5",
   "aiida-workgraph==0.4.10",
   "termcolor",

src/sirocco/parsing/_yaml_data_models.py

@@ -6,6 +6,7 @@
 import typing
 from dataclasses import dataclass, field
 from datetime import datetime
+from io import StringIO
 from pathlib import Path
 from typing import Annotated, Any, ClassVar, Literal
 
@@ -18,9 +19,11 @@
     Discriminator,
     Field,
     Tag,
+    TypeAdapter,
     field_validator,
     model_validator,
 )
+from ruamel.yaml import YAML
 
 from sirocco.parsing._utils import TimeUtils
 
@@ -41,16 +44,16 @@ class _NamedBaseModel(BaseModel):
         >>> _NamedBaseModel(foo={})
         _NamedBaseModel(name='foo')
 
-        >>> import pydantic_yaml, textwrap
-        >>> pydantic_yaml.parse_yaml_raw_as(
+        >>> import textwrap
+        >>> validate_yaml_content(
         ...     _NamedBaseModel,
         ...     textwrap.dedent('''
         ...     foo:
         ... '''),
         ... )
         _NamedBaseModel(name='foo')
 
-        >>> pydantic_yaml.parse_yaml_raw_as(
+        >>> validate_yaml_content(
         ...     _NamedBaseModel,
         ...     textwrap.dedent('''
         ...     name: foo
@@ -479,15 +482,14 @@ class ConfigBaseData(_NamedBaseModel, ConfigBaseDataSpecs):
         yaml snippet:
 
             >>> import textwrap
-            >>> import pydantic_yaml
             >>> snippet = textwrap.dedent(
             ...     '''
             ...       foo:
             ...         type: "file"
             ...         src: "foo.txt"
             ...     '''
             ... )
-            >>> pydantic_yaml.parse_yaml_raw_as(ConfigBaseData, snippet)
+            >>> validate_yaml_content(ConfigBaseData, snippet)
             ConfigBaseData(type=<DataType.FILE: 'file'>, src='foo.txt', format=None, computer=None, name='foo', parameters=[])
 
 
@@ -533,7 +535,6 @@ class ConfigData(BaseModel):
         yaml snippet:
 
             >>> import textwrap
-            >>> import pydantic_yaml
             >>> snippet = textwrap.dedent(
             ...     '''
             ...     available:
@@ -546,7 +547,7 @@ class ConfigData(BaseModel):
             ...           src: "bar.txt"
             ...     '''
             ... )
-            >>> data = pydantic_yaml.parse_yaml_raw_as(ConfigData, snippet)
+            >>> data = validate_yaml_content(ConfigData, snippet)
             >>> assert data.available[0].name == "foo"
             >>> assert data.generated[0].name == "bar"
 
@@ -592,7 +593,6 @@ class ConfigWorkflow(BaseModel):
         minimal yaml to generate:
 
             >>> import textwrap
-            >>> import pydantic_yaml
             >>> config = textwrap.dedent(
             ...     '''
             ...     cycles:
@@ -613,7 +613,7 @@ class ConfigWorkflow(BaseModel):
             ...             src: some_task_output
             ...     '''
             ... )
-            >>> wf = pydantic_yaml.parse_yaml_raw_as(ConfigWorkflow, config)
+            >>> wf = validate_yaml_content(ConfigWorkflow, config)
 
         minimum programmatically created instance
 
@@ -698,13 +698,11 @@ def load_workflow_config(workflow_config: str) -> CanonicalWorkflow:
 
     :param workflow_config: the string to the config yaml file containing the workflow definition
     """
-    from pydantic_yaml import parse_yaml_raw_as
-
     config_path = Path(workflow_config)
 
     content = config_path.read_text()
 
-    parsed_workflow = parse_yaml_raw_as(ConfigWorkflow, content)
+    parsed_workflow = validate_yaml_content(ConfigWorkflow, content)
 
     # If name was not specified, then we use filename without file extension
     if parsed_workflow.name is None:
@@ -713,3 +711,26 @@ def load_workflow_config(workflow_config: str) -> CanonicalWorkflow:
     rootdir = config_path.resolve().parent
 
     return canonicalize_workflow(config_workflow=parsed_workflow, rootdir=rootdir)
+
+
+OBJECT_T = typing.TypeVar("OBJECT_T")
+
+
+def validate_yaml_content(cls: type[OBJECT_T], content: str) -> OBJECT_T:
+    """Parses the YAML content into a python object using generic types and subsequently validates it with pydantic.
+
+    Args:
+        cls (type[OBJECT_T]): The class type to which the parsed yaml content should
+            be validated. It must be compatible with pydantic validation.
+        content (str): The yaml content as a string.
+
+    Returns:
+        OBJECT_T: An instance of the specified class type with data parsed and
+        validated from the YAML content.
+
+    Raises:
+        pydantic.ValidationError: If the YAML content cannot be validated
+        against the specified class type.
+        ruamel.yaml.YAMLError: If there is an error in parsing the YAML content.
+    """
+    return TypeAdapter(cls).validate_python(YAML(typ="safe", pure=True).load(StringIO(content)))