build: ⬆️ Updating to pydantic v2.0.0

.pre-commit-config.yaml

@@ -39,7 +39,7 @@ repos:
         exclude: ^spectrafit/test/, ^examples/
         entry: flake8  --max-doc-length 100 --max-line-length  88 --ignore E203,W503,W605
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.3.0
+    rev: v1.4.1
     hooks:
       - id: mypy
         additional_dependencies:
@@ -49,7 +49,7 @@ repos:
             types-tabulate==0.9.0.0,
             types-mock==5.0.0.2,
             numpy==1.23.4,
-            pydantic==1.10.1,
+            pydantic==2.0,
             pytest==7.1.3,
           ]
   - repo: https://github.com/pycqa/pydocstyle
@@ -61,7 +61,7 @@ repos:
     rev: "v3.0.0a6"
     hooks:
       - id: pylint
-        additional_dependencies: [toml==0.10.2, numpy==1.23.4, pydantic==1.10.1]
+        additional_dependencies: [toml==0.10.2, numpy==1.23.4, pydantic==2.0]
   - repo: https://github.com/pre-commit/mirrors-prettier
     rev: "v3.0.0-alpha.9-for-vscode"
     hooks:

Examples/example_7.json

@@ -12,7 +12,7 @@
     "shift": 0,
     "smooth": 0,
     "autopeak": {
-      "model_type": "gaussian",
+      "modeltype": "gaussian",
       "height": [0.0, 16],
       "threshold": [0.0, 16],
       "distance": 2,

Examples/example_7_summary.json

@@ -13,7 +13,7 @@
   "header": 0,
   "global_": 0,
   "autopeak": {
-    "model_type": "gaussian",
+    "modeltype": "gaussian",
     "height": [0.0, 16],
     "threshold": [0.0, 16],
     "distance": 2,

docs/examples/example7.md

@@ -22,7 +22,7 @@ In the following example the in example the section block looks like:
     "shift": 0,
     "smooth": 0,
     "autopeak": {
-      "model_type": "gaussian",
+      "modeltype": "gaussian",
       "height": [0.0, 16],
       "threshold": [0.0, 16],
       "distance": 2,

docs/interface/usage.md

@@ -378,7 +378,7 @@ follows:
 
 ```json
   "autopeak": {
-   "model_type": "gaussian",
+   "modeltype": "gaussian",
    "height": [0.0, 10],
    "threshold": [0.0, 10],
    "distance": 2,

pyproject.toml

@@ -57,7 +57,7 @@ exclude = ["docs/", "tools/"]
   art = ">=5.8,<7.0"
   tomli = "^2.0.1"
   tomli-w = "^1.0.0"
-  pydantic = "^1.10.1"
+  pydantic = ">=1.10,<3.0"
   jupyterlab = { version = ">=3.5.2,<5.0.0", optional = true }
   plotly = { version = "^5.14.0", optional = true }
   itables = { version = "^1.3.4", optional = true }
@@ -92,6 +92,7 @@ exclude = ["docs/", "tools/"]
   dash = { extras = ["testing"], version = "^2.7.1" }
   bandit = "^1.7.5"
   prospector = {extras = ["bandit", "black", "isort", "pylint"], version = "^1.10.2"}
+  bump-pydantic = "^0.1.0"
 
   [tool.poetry.group.docs.dependencies]
   mkdocstrings = { extras = ["python"], version = ">=0.19,<0.23" }

spectrafit/api/file_model.py

@@ -8,7 +8,7 @@
 
 from pydantic import BaseModel
 from pydantic import Field
-from pydantic import validator
+from pydantic.functional_validators import field_validator
 
 
 class DataFileAPI(BaseModel):
@@ -43,15 +43,15 @@ class DataFileAPI(BaseModel):
         description="File suffixes to use.",
     )
 
-    @validator("delimiter")
+    @field_validator("delimiter")
     @classmethod
     def check_delimiter(cls, v: str) -> Optional[str]:
         """Check if the delimiter is valid."""
         if v in {" ", "\t", ",", ";", "|", r"\s+"}:
             return v
         raise ValueError(f" {v} is not a valid delimiter.")
 
-    @validator("comment")
+    @field_validator("comment")
     @classmethod
     def check_comment(cls, v: str) -> Optional[str]:
         """Check if the comment marker is valid."""

spectrafit/api/notebook_model.py

@@ -12,7 +12,7 @@
 from _plotly_utils.colors.qualitative import Plotly as PlotlyColors
 from pydantic import BaseModel
 from pydantic import Field
-from pydantic import validator
+from pydantic.functional_validators import field_validator
 
 
 class XAxisAPI(BaseModel):
@@ -129,7 +129,7 @@ class ColorAPI(BaseModel):
     ticks: str = Field(default="black", description="Color of the ticks.")
     font: str = Field(default="black", description="Font color of the plot.")
 
-    @validator(
+    @field_validator(
         "paper",
         "layout",
         "grid",

spectrafit/api/report_model.py

@@ -14,6 +14,7 @@
 from pandas import __version__ as pandas_version
 from plotly import __version__ as plotly_version
 from pydantic import BaseModel
+from pydantic import ConfigDict
 from pydantic import Field
 from pydantic import __version__ as pydantic_version
 from scipy import __version__ as scipy_version
@@ -23,7 +24,7 @@
 from statsmodels import __version__ as statsmodels_version
 
 
-class CreditsAPI(BaseModel, allow_mutation=False):
+class CreditsAPI(BaseModel):
     """Credits API model."""
 
     dtale: str = f"dtale v{dtale_version}"
@@ -122,11 +123,7 @@ class OutputAPI(BaseModel):
         default={},
         description="DataFrame of the pre-processed data via 'records' orient",
     )
-
-    class Config:
-        """Config for the OutputAPI of arbitary types."""
-
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
 
 class ReportAPI(BaseModel):

spectrafit/api/rixs_model.py

@@ -1,13 +1,12 @@
 """Reference model for the API of the Jupyter Notebook interface."""
 
 
+from typing import Any
 from typing import Optional
 from typing import Tuple
 
-import numpy as np
-
-from numpy.typing import NDArray
 from pydantic import BaseModel
+from pydantic import ConfigDict
 from pydantic import Field
 
 
@@ -72,46 +71,40 @@ class SizeRatioAPI(BaseModel):
 class RIXSModelAPI(BaseModel):
     """Definition of the RIXS model."""
 
-    incident_energy: NDArray[np.float64] = Field(
+    incident_energy: Any = Field(
         ..., description="Incident energy values."
-    )
-    emission_energy: NDArray[np.float64] = Field(
+    )  # Should be NDArray[np.float64] but that's not supported for 3.8
+    emission_energy: Any = Field(
         ..., description="Emission energy values."
-    )
-    rixs_map: NDArray[np.float64] = Field(..., description="RIXS map values.")
-
-    class Config:
-        """Configurations for the RIXSModelAPI class."""
-
-        arbitrary_types_allowed = True
+    )  # Should be NDArray[np.float64] but that's not supported for 3.8
+    rixs_map: Any = Field(
+        ..., description="RIXS map values."
+    )  # Should be NDArray[np.float64] but that's not supported for 3.8
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
 
 class RIXSPlotAPI(BaseModel):
     """Definition of the plotly figure."""
 
-    incident_energy: NDArray[np.float64] = Field(
+    incident_energy: Any = Field(
         ..., description="Incident energy values."
-    )
-    emission_energy: NDArray[np.float64] = Field(
+    )  # Should be NDArray[np.float64] but that's not supported for 3.8
+    emission_energy: Any = Field(
         ..., description="Emission energy values."
-    )
-    emission_intensity: NDArray[np.float64] = Field(
+    )  # Should be NDArray[np.float64] but that's not supported for 3.8
+    emission_intensity: Any = Field(
         ..., description="Emission intensity values (RIXS), which has to be a 2D array."
-    )
-    energy_loss: Optional[NDArray[np.float64]] = Field(
+    )  # Should be NDArray[np.float64] but that's not supported for 3.8
+    energy_loss: Optional[Any] = Field(
         default=None, description="Energy loss values."
-    )
-    energy_loss_intensity: Optional[NDArray[np.float64]] = Field(
+    )  # Should be NDArray[np.float64] but that's not supported for 3.8
+    energy_loss_intensity: Optional[Any] = Field(
         default=None,
         description="Energy loss intensity values (XES), which has to be a 2D array.",
-    )
+    )  # Should be NDArray[np.float64] but that's not supported for 3.8
     x_axis: XAxisAPI = XAxisAPI()
     y_axis: YAxisAPI = YAxisAPI()
     z_axis: ZAxisAPI = ZAxisAPI()
     main_title: MainTitleAPI = MainTitleAPI()
     size_ratio: SizeRatioAPI = SizeRatioAPI()
-
-    class Config:
-        """Configurations for the RIXSPlotAPI class."""
-
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(arbitrary_types_allowed=True)

spectrafit/api/test/test_cmd_model.py

@@ -43,7 +43,7 @@ def test_overwrite_cmd() -> None:
         column=["col_1", "col_2"],
         separator="s+",
         autopeak={
-            "model_type": "ga",
+            "modeltype": "ga",
             "height": [1],
             "threshold": [0.1],
             "distance": 10,
@@ -63,7 +63,7 @@ def test_overwrite_cmd() -> None:
     assert result["column"] == ["col_1", "col_2"]
     assert result["separator"] == "s+"
     assert result["decimal"] == "."
-    assert result["autopeak"]["model_type"] == "ga"
+    assert result["autopeak"]["modeltype"] == "ga"
     assert result["autopeak"]["height"] == [1]
     assert result["autopeak"]["threshold"] == [0.1]
     assert result["autopeak"]["distance"] == 10

spectrafit/api/tools_model.py

@@ -8,7 +8,7 @@
 from typing import Union
 
 from pydantic import BaseModel
-from pydantic import Extra
+from pydantic import ConfigDict
 from pydantic import Field
 
 
@@ -23,7 +23,7 @@ class AutopeakAPI(BaseModel):
     )
     """
 
-    model_type: Optional[str] = None
+    modeltype: Optional[str] = None
     height: Optional[List[float]] = None
     threshold: Optional[List[float]] = None
     distance: Optional[int] = None
@@ -32,12 +32,7 @@ class AutopeakAPI(BaseModel):
     wlen: Optional[int] = None
     rel_height: Optional[float] = None
     plateau_size: Optional[float] = None
-
-    class Config:
-        """Activate the Validation Error Raise."""
-
-        extra = Extra.forbid
-        validate_assignment = True
+    model_config = ConfigDict(extra="forbid", validate_assignment=True)
 
 
 class DataPreProcessingAPI(BaseModel):
@@ -69,7 +64,7 @@ class DataPreProcessingAPI(BaseModel):
         description="Shift the energy axis; default to 0.",
     )
     column: List[Union[int, str]] = Field(
-        min_items=1,
+        min_length=1,
         default=[0, 1],
         dtypes=[int, str],
         description="Column of the data.",
@@ -109,7 +104,7 @@ class GeneralSolverModelsAPI(BaseModel):
     optimizer: Dict[str, Any] = SolverModelsAPI().optimizer
 
 
-class ColumnNamesAPI(BaseModel, allow_mutation=False):
+class ColumnNamesAPI(BaseModel):
     """Definition of the column names of the exported model."""
 
     energy: str = "energy"

spectrafit/models.py

@@ -1066,9 +1066,9 @@ def define_parameters_auto(self) -> None:
         positions, properties = self.__autodetect__()
         if (
             not isinstance(self.args["autopeak"], bool)
-            and "model_type" in self.args["autopeak"]
+            and "modeltype" in self.args["autopeak"]
         ):
-            _model = self.args["autopeak"]["model_type"].lower()
+            _model = self.args["autopeak"]["modeltype"].lower()
             ReferenceKeys().automodel_check(model=_model)
             models = _model
         else:

spectrafit/plugins/color_schemas.py

@@ -4,7 +4,7 @@
 from pydantic import BaseModel
 
 
-class DraculaColor(BaseModel, allow_mutation=False):
+class DraculaColor(BaseModel):
     """Dracula color schema for SpectraFit.
 
     !!! info "Dracula Color"
@@ -43,7 +43,7 @@ class DraculaColor(BaseModel, allow_mutation=False):
     font: str = "#f8f8f2"
 
 
-class DraculaFont(BaseModel, allow_mutation=False):
+class DraculaFont(BaseModel):
     """Dracula font schema for SpectraFit.
 
     !!! info "Dracula Font"

spectrafit/test/scripts/test_input_11.json

@@ -12,7 +12,7 @@
     "shift": 0,
     "smooth": 0,
     "autopeak": {
-      "model_type": "gaussian",
+      "modeltype": "gaussian",
       "height": [0.0, 10],
       "threshold": [0.0, 10],
       "distance": 2,

spectrafit/test/test_models.py

@@ -1070,7 +1070,7 @@ def test_autopeakdetection_userdef_voigt(self) -> None:
             "global_": 0,
             "column": ["Energy", "Noisy_Intensity"],
             "autopeak": {
-                "model_type": "voigt",
+                "modeltype": "voigt",
                 "height": (0.0, 10),
                 "threshold": (0.0, 10),
                 "distance": 2,
@@ -1093,7 +1093,7 @@ def test_autopeakdetection_userdef_pseudovoigt(self) -> None:
             "global_": 0,
             "column": ["Energy", "Noisy_Intensity"],
             "autopeak": {
-                "model_type": "pseudovoigt",
+                "modeltype": "pseudovoigt",
                 "height": (0.0, 10),
                 "threshold": (0.0, 10),
                 "distance": 2,
@@ -1116,7 +1116,7 @@ def test_autopeakdetection_userdef_lorentzian(self) -> None:
             "global_": 0,
             "column": ["Energy", "Noisy_Intensity"],
             "autopeak": {
-                "model_type": "lorentzian",
+                "modeltype": "lorentzian",
                 "height": (0.0, 10),
                 "threshold": (0.0, 10),
                 "distance": 2,
@@ -1161,7 +1161,7 @@ def test_autopeakdetection_userdef_failmodel(self) -> None:
             "global_": 0,
             "column": ["Energy", "Noisy_Intensity"],
             "autopeak": {
-                "model_type": "nomodel",
+                "modeltype": "nomodel",
                 "height": (0.0, 10),
                 "threshold": (0.0, 10),
                 "distance": 2,