Setup: Allow using pydantic 1

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 3.0.4
+current_version = 3.0.5
 commit = True
 tag = True
 

ceruleo/__init__.py

@@ -9,4 +9,4 @@
 CACHE_PATH.mkdir(parents=True, exist_ok=True)
 
 
-__version__ = "3.0.4"
+__version__ = "3.0.5"

ceruleo/dataset/analysis/correlation.py

@@ -6,6 +6,8 @@
 from ceruleo.dataset.utils import iterate_over_features
 from pydantic import BaseModel
 
+from ceruleo.utils import pydantic_to_dict
+
 
 class CorrelationAnalysisElement(BaseModel):
     mean_correlation: float
@@ -31,7 +33,7 @@ def get(self, feature_1: str, feature_2: str) -> CorrelationAnalysisElement:
     def to_pandas(self) -> pd.DataFrame:
         return (
             pd.DataFrame.from_dict(
-                {(k[0], k[1]): v.model_dump() for k, v in self.data.items()},
+                {(k[0], k[1]): pydantic_to_dict(v) for k, v in self.data.items()},
                 orient="index",
             )
             .reset_index()

ceruleo/dataset/analysis/sample_rate.py

@@ -6,6 +6,7 @@
 from pydantic import BaseModel
 
 from ceruleo.dataset.ts_dataset import AbstractPDMDataset
+from ceruleo.utils import pydantic_to_dict
 
 logger = logging.getLogger(__name__)
 
@@ -16,7 +17,7 @@ class SampleRateAnalysis(BaseModel):
     std: float
 
     def to_pandas(self) -> pd.Series:
-        return pd.Series(self.model_dump()).to_frame().T
+        return pd.Series(pydantic_to_dict(self)).to_frame().T
 
 
 def sample_rate(ds: AbstractPDMDataset, unit: str = "s") -> np.ndarray:

ceruleo/utils/__init__.py

@@ -0,0 +1,7 @@
+from pydantic import BaseModel, version
+
+def pydantic_to_dict(b:BaseModel):
+    if version.VERSION.startswith("1"):
+        return b.dict()
+    else:
+        return b.model_dump()

pyproject.toml

@@ -29,7 +29,7 @@ dependencies = [
         "antropy >= 0.1.5",
         "uncertainties >= 3.1",
         "PyWavelets >= 1.3",
-        "pydantic>=2.6.2",
+        "pydantic >= 1.0.0,<3.0.0"
 ]