Update documentation for parse_env_var

docs/examples/settings_with_custom_parsing.py

@@ -1,16 +1,22 @@
 # output-json
-import os
-from typing import List
+from typing import Any, List
 
-from pydantic import BaseSettings, Field
+from pydantic import BaseSettings
 
 
 def parse_list(s: str) -> List[int]:
     return [int(x.strip()) for x in s.split(',')]
 
 
 class Settings(BaseSettings):
-    numbers: List[int] = Field(env_parse=parse_list)
+    numbers: List[int]
+
+    class Config:
+        @classmethod
+        def parse_env_var(cls, field_name: str, raw_val: str) -> Any:
+            if field_name == "numbers":
+                return parse_list(raw_val)
+            return cls.json_loads(raw_val)
 
 
 os.environ['numbers'] = '1,2,3'

docs/usage/settings.md

@@ -100,20 +100,12 @@ Nested environment variables take precedence over the top-level environment vari
 (e.g. in the example above, `SUB_MODEL__V2` trumps `SUB_MODEL`).
 
 You may also populate a complex type by providing your own parsing function to
-`env_parse` in the field extras.
+the `parse_env_var` classmethod in the Config object.
 
 ```py
 {!.tmp_examples/settings_with_custom_parsing.py!}
 ```
 
-You might choose to pass the environment string value through to pydantic and
-transform in a validator instead.
-
-```py
-{!.tmp_examples/settings_with_custom_parsing_validator.py!}
-```
-
-
 ## Dotenv (.env) support
 
 !!! note