fix(pydantic) : migrate field_validator to model_validator

disdrodb/l0/check_configs.py

@@ -4,7 +4,7 @@
 from typing import List, Optional, Union
 
 import numpy as np
-from pydantic import BaseModel, ValidationError, field_validator
+from pydantic import BaseModel, ValidationError, field_validator, model_validator
 
 from disdrodb.l0.standards import (
     available_sensor_name,
@@ -128,25 +128,31 @@ class NetcdfEncodingSchema(BaseModel):
     chunksizes: Optional[Union[int, List[int]]]
 
     # if contiguous=False, chunksizes specified, otherwise should be not !
-    @field_validator("chunksizes")
-    def check_chunksizes(cls, v, values):
-        if not values.get("contiguous") and not v:
+    @model_validator(mode="before")
+    def check_chunksizes_and_zlib(cls, values):
+        contiguous = values.get("contiguous")
+        chunksizes = values.get("chunksizes")
+        if not contiguous and not chunksizes:
             raise ValueError("'chunksizes' must be defined if 'contiguous' is False")
-        return v
+        return values
 
     # if contiguous = True, then zlib must be set to False
-    @field_validator("zlib")
-    def check_zlib(cls, v, values):
-        if values.get("contiguous") and v:
+    @model_validator(mode="before")
+    def check_contiguous_and_zlib(cls, values):
+        contiguous = values.get("contiguous")
+        zlib = values.get("zlib")
+        if contiguous and zlib:
             raise ValueError("'zlib' must be set to False if 'contiguous' is True")
-        return v
+        return values
 
     # if contiguous = True, then fletcher32 must be set to False
-    @field_validator("fletcher32")
-    def check_fletcher32(cls, v, values):
-        if values.get("contiguous") and v:
+    @model_validator(mode="before")
+    def check_contiguous_and_fletcher32(cls, values):
+        contiguous = values.get("contiguous")
+        fletcher32 = values.get("fletcher32")
+        if contiguous and fletcher32:
             raise ValueError("'fletcher32' must be set to False if 'contiguous' is True")
-        return v
+        return values
 
 
 def check_l0b_encoding(sensor_name: str) -> None:
@@ -199,12 +205,12 @@ class RawDataFormatSchema(BaseModel):
     n_decimals: Optional[int]
     n_naturals: Optional[int]
     data_range: Optional[List[float]]
-    nan_flags: Optional[str]
-    valid_values: Optional[List[float]]
-    dimension_order: Optional[List[str]]
-    n_values: Optional[int]
+    nan_flags: Optional[Union[int, str]] = None
+    valid_values: Optional[List[float]] = None
+    dimension_order: Optional[List[str]] = None
+    n_values: Optional[int] = None
 
-    @field_validator("data_range", pre=True)
+    @field_validator("data_range")
     def check_list_length(cls, value):
         if value:
             if len(value) != 2:
@@ -224,7 +230,6 @@ def check_raw_data_format(sensor_name: str) -> None:
 
     # check that the second level of the dictionary match the schema
     for key, value in data.items():
-        print(key, value)
         schema_error(
             object_to_validate=value,
             schema=RawDataFormatSchema,

disdrodb/l0/issue.py

@@ -250,8 +250,7 @@ def check_issue_file(fpath: str) -> None:
 
 def _write_issue_docs(f):
     """Provide template for issue.yml"""
-    f.write(
-        """# This file is used to store timesteps/time periods with wrong/corrupted observation.
+    f.write("""# This file is used to store timesteps/time periods with wrong/corrupted observation.
 # The specified timesteps are dropped during the L0 processing.
 # The time format used is the isoformat : YYYY-mm-dd HH:MM:SS.
 # The 'timesteps' key enable to specify the list of timesteps to be discarded.
@@ -267,8 +266,7 @@ def _write_issue_docs(f):
 # - ['2018-08-01 12:00:00', '2018-08-01 14:00:00']
 # - ['2018-08-01 15:44:30', '2018-08-01 15:59:31']
 # - ['2018-08-02 12:44:30', '2018-08-02 12:59:31'] \n
-"""
-    )
+""")
     return None
 
 

disdrodb/tests/test_config_files.py

@@ -3,7 +3,7 @@
 
 import pytest
 import yaml
-from pydantic import BaseModel, validator
+from pydantic import BaseModel, field_validator
 
 
 # Define the pydantic models for *.bins.yaml config files
@@ -13,7 +13,7 @@ class raw_data_format_2n_level(BaseModel):
     n_decimals: Optional[int]
     data_range: Optional[list]
 
-    @validator("data_range", pre=True)
+    @field_validator("data_range")
     def check_list_length(cls, value):
         if value:
             if len(value) != 2: