Unique check

python/pydantic_core/core_schema.py

@@ -1240,6 +1240,7 @@ class ListSchema(TypedDict, total=False):
     items_schema: CoreSchema
     min_length: int
     max_length: int
+    unique: bool
     strict: bool
     ref: str
     metadata: Any
@@ -1251,6 +1252,7 @@ def list_schema(
     *,
     min_length: int | None = None,
     max_length: int | None = None,
+    unique: bool | None = None,
     strict: bool | None = None,
     ref: str | None = None,
     metadata: Any = None,
@@ -1271,6 +1273,7 @@ def list_schema(
         items_schema: The value must be a list of items that match this schema
         min_length: The value must be a list with at least this many items
         max_length: The value must be a list with at most this many items
+        unique: The value must be a list without any repeated items
         strict: The value must be a list with exactly this many items
         ref: optional unique identifier of the schema, used to reference the schema in other places
         metadata: Any other information you want to include with the schema, not used by pydantic-core
@@ -1281,6 +1284,7 @@ def list_schema(
         items_schema=items_schema,
         min_length=min_length,
         max_length=max_length,
+        unique=unique,
         strict=strict,
         ref=ref,
         metadata=metadata,
@@ -1292,6 +1296,7 @@ class TuplePositionalSchema(TypedDict, total=False):
     type: Required[Literal['tuple-positional']]
     items_schema: Required[List[CoreSchema]]
     extra_schema: CoreSchema
+    unique: bool
     strict: bool
     ref: str
     metadata: Any
@@ -1301,6 +1306,7 @@ class TuplePositionalSchema(TypedDict, total=False):
 def tuple_positional_schema(
     items_schema: list[CoreSchema],
     *,
+    unique: bool | None = None,
     extra_schema: CoreSchema | None = None,
     strict: bool | None = None,
     ref: str | None = None,
@@ -1322,6 +1328,7 @@ def tuple_positional_schema(
 
     Args:
         items_schema: The value must be a tuple with items that match these schemas
+        unique: The value must be a tuple without any repeated items
         extra_schema: The value must be a tuple with items that match this schema
             This was inspired by JSON schema's `prefixItems` and `items` fields.
             In python's `typing.Tuple`, you can't specify a type for "extra" items -- they must all be the same type
@@ -1334,6 +1341,7 @@ def tuple_positional_schema(
     return _dict_not_none(
         type='tuple-positional',
         items_schema=items_schema,
+        unique=unique,
         extra_schema=extra_schema,
         strict=strict,
         ref=ref,
@@ -1347,6 +1355,7 @@ class TupleVariableSchema(TypedDict, total=False):
     items_schema: CoreSchema
     min_length: int
     max_length: int
+    unique: bool
     strict: bool
     ref: str
     metadata: Any
@@ -1358,6 +1367,7 @@ def tuple_variable_schema(
     *,
     min_length: int | None = None,
     max_length: int | None = None,
+    unique: bool | None = None,
     strict: bool | None = None,
     ref: str | None = None,
     metadata: Any = None,
@@ -1380,6 +1390,7 @@ def tuple_variable_schema(
         items_schema: The value must be a tuple with items that match this schema
         min_length: The value must be a tuple with at least this many items
         max_length: The value must be a tuple with at most this many items
+        unique: The value must be a tuple without any repeated items
         strict: The value must be a tuple with exactly this many items
         ref: optional unique identifier of the schema, used to reference the schema in other places
         metadata: Any other information you want to include with the schema, not used by pydantic-core
@@ -1390,6 +1401,7 @@ def tuple_variable_schema(
         items_schema=items_schema,
         min_length=min_length,
         max_length=max_length,
+        unique=unique,
         strict=strict,
         ref=ref,
         metadata=metadata,
@@ -1402,6 +1414,7 @@ class SetSchema(TypedDict, total=False):
     items_schema: CoreSchema
     min_length: int
     max_length: int
+    unique: bool
     strict: bool
     ref: str
     metadata: Any
@@ -1413,6 +1426,7 @@ def set_schema(
     *,
     min_length: int | None = None,
     max_length: int | None = None,
+    unique: bool | None = None,
     strict: bool | None = None,
     ref: str | None = None,
     metadata: Any = None,
@@ -1435,6 +1449,7 @@ def set_schema(
         items_schema: The value must be a set with items that match this schema
         min_length: The value must be a set with at least this many items
         max_length: The value must be a set with at most this many items
+        unique: The value must be a set without any repeated items
         strict: The value must be a set with exactly this many items
         ref: optional unique identifier of the schema, used to reference the schema in other places
         metadata: Any other information you want to include with the schema, not used by pydantic-core
@@ -1445,6 +1460,7 @@ def set_schema(
         items_schema=items_schema,
         min_length=min_length,
         max_length=max_length,
+        unique=unique,
         strict=strict,
         ref=ref,
         metadata=metadata,
@@ -1457,6 +1473,7 @@ class FrozenSetSchema(TypedDict, total=False):
     items_schema: CoreSchema
     min_length: int
     max_length: int
+    unique: bool
     strict: bool
     ref: str
     metadata: Any
@@ -1468,6 +1485,7 @@ def frozenset_schema(
     *,
     min_length: int | None = None,
     max_length: int | None = None,
+    unique: bool | None = None,
     strict: bool | None = None,
     ref: str | None = None,
     metadata: Any = None,
@@ -1490,6 +1508,7 @@ def frozenset_schema(
         items_schema: The value must be a frozenset with items that match this schema
         min_length: The value must be a frozenset with at least this many items
         max_length: The value must be a frozenset with at most this many items
+        unique: The value must be a frozenset with no repeated items
         strict: The value must be a frozenset with exactly this many items
         ref: optional unique identifier of the schema, used to reference the schema in other places
         metadata: Any other information you want to include with the schema, not used by pydantic-core
@@ -1500,6 +1519,7 @@ def frozenset_schema(
         items_schema=items_schema,
         min_length=min_length,
         max_length=max_length,
+        unique=unique,
         strict=strict,
         ref=ref,
         metadata=metadata,
@@ -3840,6 +3860,7 @@ def definition_reference_schema(
     'finite_number',
     'too_short',
     'too_long',
+    'non_unique',
     'iterable_type',
     'iteration_error',
     'string_type',

src/errors/types.rs

@@ -139,6 +139,11 @@ pub enum ErrorType {
         actual_length: usize,
     },
     // ---------------------
+    // generic collection uniqueness error
+    NonUnique {
+        field_type: String,
+    },
+    // ---------------------
     // generic collection and iteration errors
     IterableType,
     IterationError {
@@ -425,6 +430,7 @@ impl ErrorType {
                 max_length: usize,
                 actual_length: usize
             ),
+            Self::NonUnique { .. } => extract_context!(NonUnique, ctx, field_type: String),
             Self::IterationError { .. } => extract_context!(IterationError, ctx, error: String),
             Self::StringTooShort { .. } => extract_context!(StringTooShort, ctx, min_length: usize),
             Self::StringTooLong { .. } => extract_context!(StringTooLong, ctx, max_length: usize),
@@ -502,6 +508,7 @@ impl ErrorType {
             Self::FiniteNumber => "Input should be a finite number",
             Self::TooShort {..} => "{field_type} should have at least {min_length} item{expected_plural} after validation, not {actual_length}",
             Self::TooLong {..} => "{field_type} should have at most {max_length} item{expected_plural} after validation, not {actual_length}",
+            Self::NonUnique {..} => "{field_type} should be unique, but an item appeared more than once",
             Self::IterableType => "Input should be iterable",
             Self::IterationError {..} => "Error iterating over object, error: {error}",
             Self::StringType => "Input should be a valid string",
@@ -647,6 +654,7 @@ impl ErrorType {
                 let expected_plural = plural_s(*max_length);
                 to_string_render!(tmpl, field_type, max_length, actual_length, expected_plural)
             }
+            Self::NonUnique { field_type } => render!(tmpl, field_type),
             Self::IterationError { error } => render!(tmpl, error),
             Self::StringTooShort { min_length } => to_string_render!(tmpl, min_length),
             Self::StringTooLong { max_length } => to_string_render!(tmpl, max_length),
@@ -719,6 +727,7 @@ impl ErrorType {
                 max_length,
                 actual_length,
             } => py_dict!(py, field_type, max_length, actual_length),
+            Self::NonUnique { field_type } => py_dict!(py, field_type),
             Self::IterationError { error } => py_dict!(py, error),
             Self::StringTooShort { min_length } => py_dict!(py, min_length),
             Self::StringTooLong { max_length } => py_dict!(py, max_length),

src/input/mod.rs

@@ -18,9 +18,9 @@ pub(crate) use datetime::{
 pub(crate) use input_abstract::{Input, InputType};
 pub(crate) use parse_json::{JsonInput, JsonObject};
 pub(crate) use return_enums::{
-    py_string_str, AttributesGenericIterator, DictGenericIterator, EitherBytes, EitherFloat, EitherInt, EitherString,
-    GenericArguments, GenericIterable, GenericIterator, GenericMapping, Int, JsonArgs, JsonObjectGenericIterator,
-    MappingGenericIterator, PyArgs,
+    py_string_str, unique_check, AttributesGenericIterator, DictGenericIterator, EitherBytes, EitherFloat, EitherInt,
+    EitherString, GenericArguments, GenericIterable, GenericIterator, GenericMapping, Int, JsonArgs,
+    JsonObjectGenericIterator, MappingGenericIterator, PyArgs,
 };
 
 // Defined here as it's not exported by pyo3