e.g.:

```py
from decimal import Decimal
from pydantic_core import SchemaValidator, core_schema

schema = core_schema.decimal_schema(le=0.8, ge=0.2)
v = SchemaValidator(schema)
assert v.validate_python('0.5') == Decimal('0.5')
```

Args:
    allow_inf_nan: Whether to allow inf and nan values
    multiple_of: The value must be a multiple of this number
    le: The value must be less than or equal to this number
    ge: The value must be greater than or equal to this number
    lt: The value must be strictly less than this number
    gt: The value must be strictly greater than this number
    max_digits: The maximum number of decimal digits allowed
    decimal_places: The maximum number of decimal places allowed
    strict: Whether the value should be a float or a value that can be converted to a float
    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
    serialization: Custom serialization schema
Ú