qcodes.validators

Classes:

Anything()	Allow any value to pass.
Arrays([min_value, max_value, shape, ...])	Validator for numerical numpy arrays of numeric types (int, float, complex).
Bool()	Requires a boolean.
Callable()	Validator for callables such as functions.
ComplexNumbers()	A validator for complex numbers.
Dict([allowed_keys])	Validator for dictionaries.
Enum(*values)	Requires one of a provided set of values.
Ints([min_value, max_value])	Requires an integer.
Lists(elt_validator)	Validator for lists
Multiples([divisor])	A validator that checks if a value is an integer multiple of a fixed divisor.
MultiType(*validators[, combiner])	Allow the combination of several different validators.
MultiTypeAnd(*validators)	Allow the combination of several different validators.
MultiTypeOr(*validators)	Allow the combination of several different validators.
Nothing(reason)	Allow no value to pass.
Numbers([min_value, max_value])	Requires a number of type int, float, numpy.integer or numpy.floating.
OnOff()	Requires either the string 'on' or 'off'.
PermissiveInts([min_value, max_value])	Requires an integer or a float close to an integer optional parameters min_value and max_value enforce min_value <= value <= max_value.
PermissiveMultiples(divisor[, precision])	A validator that checks whether a value is an integer multiple of a fixed divisor (to within some precision).
Sequence(elt_validator, length, require_sorted)	Validator for Sequences.
Strings([min_length, max_length])	Requires a string optional parameters min_length and max_length limit the allowed length to min_length <= len(value) <= max_length
Validator()	Base class for all value validators each validator should implement:

Functions:

validate_all(*args[, context])

Takes a list of (validator, value) couplets and tests whether they are all valid, raising ValueError otherwise.

class qcodes.validators.Anything

Bases: Validator[Any]

Allow any value to pass.

Methods:

validate(value[, context])

Attributes:

is_numeric
valid_values

validate(value: Any, context: str = '') → None

is_numeric = True

property valid_values: Tuple[T, ...]

class qcodes.validators.Arrays(min_value: Optional[Union[float, int, floating, integer]] = None, max_value: Optional[Union[float, int, floating, integer]] = None, shape: Optional[Sequence[Union[int, Callable[[], int]]]] = None, valid_types: Optional[Sequence[type]] = None)

Bases: Validator[ndarray]

Validator for numerical numpy arrays of numeric types (int, float, complex). By default it validates int and float arrays.

Min and max validation is not supported for complex numbers.

Parameters

• min_value – Min value allowed, default None for which min value check is not performed

• max_value – Max value allowed, default None for which max value check is not performed

• shape – The shape of the array, tuple of either ints or Callables taking no arguments that return the size along that dim as an int.

• valid_types – Sequence of types that the validator should support. Should be a subset of the supported types, or None. If None, all real datatypes will validate.

Raises

TypeError – If value of arrays are not supported.

Attributes:

valid_values
shape_unevaluated
shape
is_numeric

Methods:

validate(value[, context])

property valid_values: Tuple[ndarray]

property shape_unevaluated: Optional[Tuple[Union[int, Callable[[], int]], ...]]

property shape: Optional[Tuple[int, ...]]

validate(value: ndarray, context: str = '') → None

is_numeric = True

class qcodes.validators.Bool

Bases: Validator[bool]

Requires a boolean.

Methods:

validate(value[, context])

Validates if bool else raises error.

Attributes:

is_numeric
valid_values

validate(value: bool, context: str = '') → None

Validates if bool else raises error.

Parameters

• value – Bool

• context – Context for validation.

Raises

TypeError – IF not a boolean.

is_numeric = False

property valid_values: Tuple[T, ...]

class qcodes.validators.Callable

Bases: Validator[Callable[[…], Any]]

Validator for callables such as functions.

Methods:

validate(value[, context])

Validates if callable else raise typeerror.

Attributes:

is_numeric
valid_values

validate(value: Callable[[...], Any], context: str = '') → None

Validates if callable else raise typeerror.

Parameters

• value – Value to validate.

• context – Context for validation.

Raises

TypeError – If not a callable.

is_numeric = False

property valid_values: Tuple[T, ...]

class qcodes.validators.ComplexNumbers

Bases: Validator[Union[complex, np.complexfloating[Any,Any]]]

A validator for complex numbers.

Attributes:

validtypes
is_numeric
valid_values

Methods:

validate(value[, context])

Validates if complex number else raises error.

validtypes = (<class 'complex'>, <class 'numpy.complex128'>, <class 'numpy.complex64'>)

validate(value: Union[complex, complexfloating[Any, Any]], context: str = '') → None

Validates if complex number else raises error.

Parameters

• value – A complex number.

• context – Context for validation.

Raises

TypeError – If not a complex number.

is_numeric = False

property valid_values: Tuple[T, ...]

class qcodes.validators.Dict(allowed_keys: Optional[Sequence[Hashable]] = None)

Bases: Validator[Dict[Hashable, Any]]

Validator for dictionaries.

Validator for dictionary keys

Parameters

allowed_keys – if set, all keys must be in allowed_keys

Attributes:

is_numeric
valid_values

Methods:

validate(value[, context])

Validates dictionary keys else raise typeerror.

is_numeric = False

property valid_values: Tuple[T, ...]

validate(value: Dict[Hashable, Any], context: str = '') → None

Validates dictionary keys else raise typeerror.

Parameters

• value – Dictionary.

• context – Context for validation.

Raises

• TypeError – If not a dictionary.

• SyntaxError – If keys are not in allowed keys.

class qcodes.validators.Enum(*values: Optional[Hashable])

Bases: Validator[Hashable]

Requires one of a provided set of values. eg. Enum(val1, val2, val3)

Raises

TypeError – If no value provided

Methods:

validate(value[, context])

Attributes:

is_numeric
valid_values

validate(value: Hashable, context: str = '') → None

is_numeric = False

property valid_values: Tuple[T, ...]

class qcodes.validators.Ints(min_value: Union[int, integer] = - 1000000000000000000, max_value: Union[int, integer] = 1000000000000000000)

Bases: Validator[Union[int, np.integer[Any]]]

Requires an integer. Optional parameters min_value and max_value, enforce min_value <= value <= max_value.

Parameters

• max_value – value must be <= max_value

• min_value – value must be >= min_value

Raises

TypeError – If min_value and max_value is not an integer. Or min_value is larger than the min_value.

Attributes:

validtypes
inttypes(*args, **kwargs)	alias of Union[int, integer]
is_numeric
valid_values

Methods:

validate(value[, context])

Validates if int else raises error.

validtypes = (<class 'int'>, <class 'numpy.integer'>)

inttypes(*args, **kwargs)

alias of Union[int, integer]

validate(value: Union[int, integer], context: str = '') → None

Validates if int else raises error.

Parameters

• value – An integer.

• context – Context for validation.

Raises

• TypeError – If not an integer.

• ValueError – If not between min_value and max_value.

is_numeric = True

property valid_values: Tuple[T, ...]

class qcodes.validators.Lists(elt_validator: ~qcodes.validators.validators.Validator[~typing.Any] = <Anything>)

Bases: Validator[List[Any]]

Validator for lists

Parameters

elt_validator – Used to validate the individual elements of the list.

Methods:

validate(value[, context])

Validate if list else raises error.

Attributes:

is_numeric
valid_values

validate(value: List[Anything], context: str = '') → None

Validate if list else raises error.

Parameters

• value – A list.

• context – Context for validation.

Raises

TypeError – If not list.

is_numeric = False

property valid_values: Tuple[T, ...]

class qcodes.validators.Multiples(divisor: int = 1, **kwargs: Any)

Bases: Ints

A validator that checks if a value is an integer multiple of a fixed divisor. This class extends validators.Ints such that the value is also checked for being integer between an optional min_value and max_value. Furthermore this validator checks that the value is an integer multiple of an fixed, integer divisor. (i.e. value % divisor == 0)

Parameters

• divisor – the value need the be a multiple of this divisor

• max_value – value must be <= max_value

• min_value – value must be >= min_value

Methods:

validate(value[, context])

Validates if the value is a integer multiple of divisor else raises error.

Attributes:

is_numeric
inttypes(*args, **kwargs)	alias of Union[int, integer]
valid_values
validtypes

validate(value: Union[int, integer[Any]], context: str = '') → None

Validates if the value is a integer multiple of divisor else raises error.

Parameters

• value – An integer.

• context – Context for validation.

Raises

ValueError – If not a multiple of a divisor.

is_numeric = True

inttypes(*args, **kwargs)

alias of Union[int, integer]

property valid_values: Tuple[T, ...]

validtypes = (<class 'int'>, <class 'numpy.integer'>)

class qcodes.validators.MultiType(*validators: Validator[Any], combiner: Literal['OR', 'AND'] = 'OR')

Bases: Validator[Any]

Allow the combination of several different validators. By default, the resulting validator acts as a logical OR between the different validators. Pass combiner=’AND’ to require all validators to return True instead of atleast one returning True.

Examples

1. To allow numbers as well as “off”:

>>> MultiType(Numbers(), Enum("off"))

or:

>>> MultiType(Numbers(), Enum("off"), combiner='OR')

2. To require values that are divisible by 0.001 while >=0.002 and <=50000.0

>>> MultiType(PermissiveMultiples(divisor=1e-3),
>>>           Numbers(min_value=2e-3, max_value=5e4),
>>>           combiner='AND')

Raises

TypeError – If no validators provided. Or if any of the provided argument is not a valid validator. Or if combiner is not in [‘OR’, ‘AND’].

Attributes:

is_numeric
valid_values

Methods:

validate(value[, context])

is_numeric = False

validate(value: Any, context: str = '') → None

property valid_values: Tuple[T, ...]

class qcodes.validators.MultiTypeAnd(*validators: Validator[Any])

Bases: MultiType

Allow the combination of several different validators. The resulting validator acts as a logical AND between the different validators.

Example

To require values that are divisible by 0.001 while >=0.002 and <=50000.0

>>> MultiType(PermissiveMultiples(divisor=1e-3),
>>>           Numbers(min_value=2e-3, max_value=5e4),
>>>           combiner='AND')

Raises

TypeError – If no validators provided. Or if any of the provided argument is not a valid validator.

Attributes:

is_numeric
valid_values

Methods:

validate(value[, context])

is_numeric = False

property valid_values: Tuple[T, ...]

validate(value: Any, context: str = '') → None

class qcodes.validators.MultiTypeOr(*validators: Validator[Any])

Bases: MultiType

Allow the combination of several different validators. The resulting validator acts as a logical OR between the different validators.

Example

To allow numbers as well as “off”:

>>> MultiTypeOr(Numbers(), Enum("off"))

Raises

TypeError – If no validators provided. Or if any of the provided argument is not a valid validator.

Attributes:

is_numeric
valid_values

Methods:

validate(value[, context])

is_numeric = False

property valid_values: Tuple[T, ...]

validate(value: Any, context: str = '') → None

class qcodes.validators.Nothing(reason: str)

Bases: Validator[Any]

Allow no value to pass.

Methods:

validate(value[, context])

Attributes:

is_numeric
valid_values

validate(value: Any, context: str = '') → None

is_numeric = False

property valid_values: Tuple[T, ...]

class qcodes.validators.Numbers(min_value: Union[float, int, floating, integer] = - inf, max_value: Union[float, int, floating, integer] = inf)

Bases: Validator[Union[float, int, floating, integer]]

Requires a number of type int, float, numpy.integer or numpy.floating.

Parameters

• min_value – Minimal value allowed, default -inf.

• max_value – Maximal value allowed, default inf.

Raises

TypeError – If min or max value not a number. Or if min_value is larger than the max_value.

Attributes:

validtypes
is_numeric
valid_values

Methods:

validate(value[, context])

Validate if number else raises error.

validtypes = (<class 'float'>, <class 'int'>, <class 'numpy.integer'>, <class 'numpy.floating'>)

validate(value: Union[float, int, floating, integer], context: str = '') → None

Validate if number else raises error.

Parameters

• value – A number.

• context – Context for validation.

Raises

• TypeError – If not int or float.

• ValueError – If number is not between the min and the max value.

is_numeric = True

property valid_values: Tuple[T, ...]

class qcodes.validators.OnOff

Bases: Validator[str]

Requires either the string ‘on’ or ‘off’.

Methods:

validate(value[, context])

Attributes:

is_numeric
valid_values

validate(value: str, context: str = '') → None

is_numeric = False

property valid_values: Tuple[T, ...]

class qcodes.validators.PermissiveInts(min_value: Union[int, integer] = - 1000000000000000000, max_value: Union[int, integer] = 1000000000000000000)

Bases: Ints

Requires an integer or a float close to an integer optional parameters min_value and max_value enforce min_value <= value <= max_value. Note that you probably always want to use this with a set_parser that converts the float repr to an actual int.

Methods:

validate(value[, context])

Validates if int or close to int (remainder to the rounded value is less than 1e-5) else raises error.

Attributes:

inttypes(*args, **kwargs)	alias of Union[int, integer]
is_numeric
valid_values
validtypes

validate(value: Union[float, int, floating, integer], context: str = '') → None

Validates if int or close to int (remainder to the rounded value is less than 1e-5) else raises error.

Parameters

• value – Integer or close to integer.

• context – Context for validation.

Raises

TypeError – If not an int or close to it.

inttypes(*args, **kwargs)

alias of Union[int, integer]

is_numeric = True

property valid_values: Tuple[T, ...]

validtypes = (<class 'int'>, <class 'numpy.integer'>)

class qcodes.validators.PermissiveMultiples(divisor: Union[float, int, floating, integer], precision: float = 1e-09)

Bases: Validator[Union[float, int, floating, integer]]

A validator that checks whether a value is an integer multiple of a fixed divisor (to within some precision). If both value and divisor are integers, the (exact) Multiples validator is used.

We also allow negative values, meaning that zero by construction is always a valid value.

Parameters

• divisor – The number that the validated value should be an integer multiple of.

• precision – The maximally allowed absolute error between the value and the nearest true multiple.

Raises

ValueError – If divisor is zero.

Methods:

validate(value[, context])

Validate the given value.

Attributes:

is_numeric
valid_values

validate(value: Union[float, int, floating, integer], context: str = '') → None

Validate the given value. Note that this validator does not use context for anything.

Raises

ValueError – If value is not the multiple of divisor.

is_numeric = True

property valid_values: Tuple[T, ...]

class qcodes.validators.Sequence(elt_validator: ~qcodes.validators.validators.Validator[~typing.Any] = <Anything>, length: ~typing.Optional[int] = None, require_sorted: bool = False)

Bases: Validator[Sequence[Any]]

Validator for Sequences.

Parameters

• elt_validator – Used to validate the individual elements of the Sequence.

• length – Length of sequence.

• require_sorted – True or False.

Methods:

validate(value[, context])

Validates if sequence else raise typeerror.

Attributes:

is_numeric
valid_values

validate(value: Sequence[Any], context: str = '') → None

Validates if sequence else raise typeerror.

Parameters

• value – A sequence.

• context – Context for validation.

Raises

• TypeError – If not a sequence.

• ValueError – If not of given length or if not sorted.

is_numeric = False

property valid_values: Tuple[T, ...]

class qcodes.validators.Strings(min_length: int = 0, max_length: int = 1000000000)

Bases: Validator[str]

Requires a string optional parameters min_length and max_length limit the allowed length to min_length <= len(value) <= max_length

Raises

TypeError – If min_length or max_length negative. Or max_length lower than min_length.

Methods:

validate(value[, context])

Validates if string else raises error.

Attributes:

is_numeric
valid_values

validate(value: str, context: str = '') → None

Validates if string else raises error.

Parameters

• value – A string.

• context – Context for validation.

Raises

• TypeError – If not a string.

• ValueError – If length is not between min_length and max_length.

is_numeric = False

property valid_values: Tuple[T, ...]

class qcodes.validators.Validator

Bases: Generic[T]

Base class for all value validators each validator should implement:

__init__:

Here a private attribute, _valid_values, should be set. _valid_values must be a tuple of at least one valid value. If possible, it should include all valid values. The purpose of this attribute is to make it possible to find a valid value for a Parameter, given its validator.

validate:

Function of two args: value, context value is what you’re testing. context is a string identifying the caller better.

Raises an error (TypeError or ValueError) if the value fails.

is_numeric:

A boolean flag that marks if this a numeric type.

The base class implements,

valid_values:

A property exposing _valid_values, which is a tuple of examples of valid values. For very simple validators, like Bool or Enum, the tuple contains all valid values, but in general it just holds SOME valid values. These example values are intended to be useful when simulating instruments.

Alternatively you may override _valid_values and provide your own implementation of getting valid values.

Attributes:

is_numeric
valid_values

Methods:

validate(value[, context])

is_numeric = False

validate(value: T, context: str = '') → None

property valid_values: Tuple[T, ...]

qcodes.validators.validate_all(*args: Tuple[Validator[Any], Any], context: str = '') → None

Takes a list of (validator, value) couplets and tests whether they are all valid, raising ValueError otherwise.

Parameters

context – keyword-only arg with a string to include in the error message giving the user context for the error.