Remove deprecated code for unsupported types

guardrails/applications/text2sql.rail

@@ -1,6 +1,6 @@
 <rail version="0.1">
 <output>
-    <sql
+    <string
         name="generated_sql"
         description="Generate SQL for the given natural language instruction."
         format="bug-free-sql: ${conn_str} ${schema_file}"

guardrails/datatypes.py

@@ -1,5 +1,4 @@
 import datetime
-import warnings
 from dataclasses import dataclass
 from types import SimpleNamespace
 from typing import Any, Dict, Iterable
@@ -15,15 +14,6 @@
 from guardrails.validator_base import Validator, ValidatorSpec
 from guardrails.validatorsattr import ValidatorsAttr
 
-# TODO - deprecate these altogether
-deprecated_string_types = {"sql", "email", "url", "pythoncode"}
-
-
-def update_deprecated_type_to_string(type):
-    if type in deprecated_string_types:
-        return "string"
-    return type
-
 
 @dataclass
 class FieldValidation:
@@ -165,16 +155,6 @@ def decorator(cls: T) -> T:
     return decorator
 
 
-# Decorator for deprecation
-def deprecate_type(cls: type):
-    warnings.warn(
-        f"""The '{cls.__name__}' type  is deprecated and will be removed in \
-versions 0.3.0 and beyond. Use the pydantic 'str' primitive instead.""",
-        DeprecationWarning,
-    )
-    return cls
-
-
 class ScalarType(DataType):
     def set_children_from_xml(self, element: ET._Element):
         for _ in element:
@@ -350,66 +330,6 @@ def from_xml(cls, element: ET._Element, strict: bool = False) -> "Time":
         return datatype
 
 
-@deprecate_type
-@register_type("email")
-class Email(ScalarType):
-    """Element tag: `<email>`"""
-
-    tag = "email"
-
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        deprecate_type(type(self))
-
-    def get_example(self):
-        return "hello@example.com"
-
-
-@deprecate_type
-@register_type("url")
-class URL(ScalarType):
-    """Element tag: `<url>`"""
-
-    tag = "url"
-
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        deprecate_type(type(self))
-
-    def get_example(self):
-        return "https://example.com"
-
-
-@deprecate_type
-@register_type("pythoncode")
-class PythonCode(ScalarType):
-    """Element tag: `<pythoncode>`"""
-
-    tag = "pythoncode"
-
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        deprecate_type(type(self))
-
-    def get_example(self):
-        return "print('hello world')"
-
-
-@deprecate_type
-@register_type("sql")
-class SQLCode(ScalarType):
-    """Element tag: `<sql>`"""
-
-    tag = "sql"
-
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        deprecate_type(type(self))
-
-    def get_example(self):
-        return "SELECT * FROM table"
-
-
 @register_type("percentage")
 class Percentage(ScalarType):
     """Element tag: `<percentage>`"""
@@ -507,7 +427,7 @@ def set_children_from_xml(self, element: ET._Element):
                 # The child must be the datatype that all items in the list
                 # must conform to.
                 raise ValueError("List data type must have exactly one child.")
-            child_data_type_tag = update_deprecated_type_to_string(child.tag)
+            child_data_type_tag = child.tag
             child_data_type = registry[child_data_type_tag]
             self._children["item"] = child_data_type.from_xml(child)
 

guardrails/utils/json_utils.py

@@ -1,30 +1,21 @@
 import json
-import warnings
 from dataclasses import dataclass
 from typing import Any, Dict, Optional, Tuple, Type, Union
 
 import regex
 
 from guardrails.datatypes import (
-    URL,
     Boolean,
     Case,
     Choice,
     DataType,
     Date,
-    Email,
     Enum,
     Float,
     Integer,
 )
 from guardrails.datatypes import List as ListDataType
-from guardrails.datatypes import (
-    Object,
-    PythonCode,
-    String,
-    Time,
-    deprecated_string_types,
-)
+from guardrails.datatypes import Object, String, Time
 from guardrails.utils.parsing_utils import get_code_block, has_code_block
 
 
@@ -56,21 +47,13 @@ def verify(
     Enum: str,
 }
 
-ignore_types = [
-    Email,  # email and url should become string validators
-    URL,
-    PythonCode,
-]
-
 
 @dataclass
 class ValuePlaceholder(Placeholder):
     datatype_type: Type[DataType]
 
     @property
     def type_object(self):
-        if self.datatype_type in ignore_types:
-            return Any
         return type_map[self.datatype_type]
 
     class VerificationFailed:
@@ -327,14 +310,6 @@ def _recurse_schema(schema: DataType):
             )
         else:
             datatype_type = type(schema)
-            if schema.tag in deprecated_string_types:
-                datatype_type = String
-                warnings.warn(
-                    f"""The '{schema.tag}' type is deprecated. Use the \
-string type instead. Support for this type will \
-be dropped in version 0.3.0 and beyond.""",
-                    DeprecationWarning,
-                )
 
             return ValuePlaceholder(
                 datatype_type=datatype_type,

guardrails/utils/pydantic_utils/v2.py

@@ -5,10 +5,9 @@
 from enum import Enum
 from typing import Any, Callable, Dict, List, Optional, Type, TypeVar, Union, get_args
 
-from pydantic import BaseModel, ConfigDict, HttpUrl, field_validator
+from pydantic import BaseModel, ConfigDict, field_validator
 from pydantic.fields import FieldInfo
 
-from guardrails.datatypes import URL as URLDataType
 from guardrails.datatypes import Boolean as BooleanDataType
 from guardrails.datatypes import Case as CaseDataType
 from guardrails.datatypes import Choice
@@ -20,7 +19,6 @@
 from guardrails.datatypes import Integer as IntegerDataType
 from guardrails.datatypes import List as ListDataType
 from guardrails.datatypes import Object as ObjectDataType
-from guardrails.datatypes import PythonCode as PythonCodeDataType
 from guardrails.datatypes import String as StringDataType
 from guardrails.datatypes import Time as TimeDataType
 from guardrails.validator_base import Validator
@@ -284,9 +282,6 @@ def field_to_datatype(field: Union[FieldInfo, Type]) -> Type[DataType]:
     # Get the type annotation from the type_annotation
     type_annotation = prepare_type_annotation(field)
 
-    # Use inline import to avoid circular dependency
-    from guardrails.datatypes import PythonCode
-
     # Map the type annotation to the corresponding field type
     if is_list(type_annotation):
         return ListDataType
@@ -306,12 +301,8 @@ def field_to_datatype(field: Union[FieldInfo, Type]) -> Type[DataType]:
         return StringDataType
     elif type_annotation == time:
         return TimeDataType
-    elif type_annotation == HttpUrl:
-        return URLDataType
     elif typing.get_origin(type_annotation) == Union:
         return ChoiceDataType
-    elif type_annotation == PythonCode:
-        return PythonCodeDataType
     else:
         raise ValueError(f"Unsupported type: {type_annotation}")
 

tests/integration_tests/test_assets/fixtures/__init__.py

@@ -11,8 +11,6 @@ def fixture_rail_spec():
     <integer name="dummy_integer" description="Any dummy integer" />
     <float name="dummy_float" description="Any dummy float" />
     <bool name="dummy_boolean" description="Any dummy boolean" />
-    <email name="dummy_email" description="Any dummy email" />
-    <url name="dummy_url" description="Any dummy url" />
     <date name="dummy_date" description="Any dummy date" />
     <time name="dummy_time" description="Any dummy time" />
     <list name="dummy_list" description="Any dummy list" />
@@ -40,8 +38,6 @@ def fixture_llm_output():
     "dummy_integer": 42,
     "dummy_float": 3.14,
     "dummy_boolean": true,
-    "dummy_email": "example@example.com",
-    "dummy_url": "https://www.example.com",
     "dummy_date": "2020-01-01",
     "dummy_time": "12:00:00",
     "dummy_list": ["item1", "item2", "item3"],
@@ -60,8 +56,6 @@ def fixture_validated_output():
         "dummy_integer": 42,
         "dummy_float": 3.14,
         "dummy_boolean": True,
-        "dummy_email": "example@example.com",
-        "dummy_url": "https://www.example.com",
         "dummy_date": "2020-01-01",
         "dummy_time": "12:00:00",
         "dummy_list": ["item1", "item2", "item3"],