Remove pydantic-yaml as dependency (#110)

The amount of functionality we use of this library is extremly minimal.
We replace it with the dependency `ruamel.yaml` that parses the yaml
file into a python object. Furthermore, the library still uses pydantic
API v1 for validating the pydantic model which is deprecated so we can
replace it with pydantic v2. In addition this change gives us more
flexibility as it separates the parsing of the yaml file and the
validation through pydantic.

To have a similar utility function that can be used in the docstring
tests we implement `validate_yaml_content`.

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)))