Utilities (qiskit.utils)#

qiskit.utils.add_deprecation_to_docstring(func, msg, *, since, pending)[소스]#

Dynamically insert the deprecation message into func’s docstring.

매개변수:
  • func (Callable) – The function to modify.

  • msg (str) – The full deprecation message.

  • since (str | None) – The version the deprecation started at.

  • pending (bool) – Is the deprecation still pending?

qiskit.utils.deprecate_arg(name, *, since, additional_msg=None, deprecation_description=None, pending=False, package_name='qiskit-terra', new_alias=None, predicate=None, removal_timeline='no earlier than 3 months after the release date')[소스]#

Decorator to indicate an argument has been deprecated in some way.

This decorator may be used multiple times on the same function, once per deprecated argument. It should be placed beneath other decorators like @staticmethod and property decorators.

매개변수:
  • name (str) – The name of the deprecated argument.

  • since (str) – The version the deprecation started at. If the deprecation is pending, set the version to when that started; but later, when switching from pending to deprecated, update since to the new version.

  • deprecation_description (str | None) – What is being deprecated? E.g. “Setting my_func()’s my_arg argument to None.” If not set, will default to “{func_name}’s argument {name}”.

  • additional_msg (str | None) – Put here any additional information, such as what to use instead (if new_alias is not set). For example, “Instead, use the argument new_arg, which is similar but does not impact the circuit’s setup.”

  • pending (bool) – Set to True if the deprecation is still pending.

  • package_name (str) – The PyPI package name, e.g. “qiskit-nature”.

  • new_alias (str | None) – If the arg has simply been renamed, set this to the new name. The decorator will dynamically update the kwargs so that when the user sets the old arg, it will be passed in as the new_alias arg.

  • predicate (Callable[[Any], bool] | None) – Only log the runtime warning if the predicate returns True. This is useful to deprecate certain values or types for an argument, e.g. lambda my_arg: isinstance(my_arg, dict). Regardless of if a predicate is set, the runtime warning will only log when the user specifies the argument.

  • removal_timeline (str) – How soon can this deprecation be removed? Expects a value like “no sooner than 6 months after the latest release” or “in release 9.99”.

반환:

The decorated callable.

반환 형식:

Callable

qiskit.utils.deprecate_arguments(kwarg_map, category=<class 'DeprecationWarning'>, *, since=None)[소스]#

Deprecated. Instead, use @deprecate_arg.

매개변수:
  • kwarg_map (Dict[str, str | None]) – A dictionary of the old argument name to the new name.

  • category (Type[Warning]) – Usually either DeprecationWarning or PendingDeprecationWarning.

  • since (str | None) – The version the deprecation started at. Only Optional for backwards compatibility - this should always be set. If the deprecation is pending, set the version to when that started; but later, when switching from pending to deprecated, update since to the new version.

반환:

The decorated callable.

반환 형식:

Callable

qiskit.utils.deprecate_func(*, since, additional_msg=None, pending=False, package_name='qiskit-terra', removal_timeline='no earlier than 3 months after the release date', is_property=False)[소스]#

Decorator to indicate a function has been deprecated.

It should be placed beneath other decorators like @staticmethod and property decorators.

When deprecating a class, set this decorator on its __init__ function.

매개변수:
  • since (str) – The version the deprecation started at. If the deprecation is pending, set the version to when that started; but later, when switching from pending to deprecated, update since to the new version.

  • additional_msg (str | None) – Put here any additional information, such as what to use instead. For example, “Instead, use the function new_func from the module <my_module>.<my_submodule>, which is similar but uses GPU acceleration.”

  • pending (bool) – Set to True if the deprecation is still pending.

  • package_name (str) – The PyPI package name, e.g. “qiskit-nature”.

  • removal_timeline (str) – How soon can this deprecation be removed? Expects a value like “no sooner than 6 months after the latest release” or “in release 9.99”.

  • is_property (bool) – If the deprecated function is a @property, set this to True so that the generated message correctly describes it as such. (This isn’t necessary for property setters, as their docstring is ignored by Python.)

반환:

The decorated callable.

반환 형식:

Callable

qiskit.utils.deprecate_function(msg, stacklevel=2, category=<class 'DeprecationWarning'>, *, since=None)[소스]#

Deprecated. Instead, use @deprecate_func.

매개변수:
  • msg (str) – Warning message to emit.

  • stacklevel (int) – The warning stacklevel to use, defaults to 2.

  • category (Type[Warning]) – Usually either DeprecationWarning or PendingDeprecationWarning.

  • since (str | None) – The version the deprecation started at. Only Optional for backwards compatibility - this should always be set. If the deprecation is pending, set the version to when that started; but later, when switching from pending to deprecated, update since to the new version.

반환:

The decorated, deprecated callable.

반환 형식:

Callable

qiskit.utils.local_hardware_info()[소스]#

Basic hardware information about the local machine.

Gives actual number of CPU’s in the machine, even when hyperthreading is turned on. CPU count defaults to 1 when true count can’t be determined.

반환:

The hardware information.

반환 형식:

dict

qiskit.utils.is_main_process()[소스]#

Checks whether the current process is the main one

qiskit.utils.apply_prefix(value, unit)[소스]#

Given a SI unit prefix and value, apply the prefix to convert to standard SI unit.

매개변수:
반환:

Converted value.

반환 형식:

float

참고

This may induce tiny value error due to internal representation of float object. See https://docs.python.org/3/tutorial/floatingpoint.html for details.

예외 발생:

ValueError – If the units aren’t recognized.

반환 형식:

float

qiskit.utils.detach_prefix(value, decimal=None)[소스]#

Given a SI unit value, find the most suitable prefix to scale the value.

For example, the value = 1.3e8 will be converted into a tuple of (130.0, "M"), which represents a scaled value and auxiliary unit that may be used to display the value. In above example, that value might be displayed as 130 MHz (unit is arbitrary here).

예제

>>> value, prefix = detach_prefix(1e4)
>>> print(f"{value} {prefix}Hz")
10 kHz
매개변수:
  • value (float) – The number to find prefix.

  • decimal (int | None) – Optional. An arbitrary integer number to represent a precision of the value. If specified, it tries to round the mantissa and adjust the prefix to rounded value. For example, 999_999.91 will become 999.9999 k with decimal=4, while 1.0 M with decimal=3 or less.

반환:

A tuple of scaled value and prefix.

반환 형식:

Tuple[float, str]

참고

This may induce tiny value error due to internal representation of float object. See https://docs.python.org/3/tutorial/floatingpoint.html for details.

예외 발생:
반환 형식:

Tuple[float, str]

qiskit.utils.wrap_method(cls, name, *, before=None, after=None)[소스]#

Wrap the functionality the instance- or class method cls.name with additional behaviour before and after.

This mutates cls, replacing the attribute name with the new functionality. This is useful when creating class decorators. The method is allowed to be defined on any parent class instead.

If either before or after are given, they should be callables with a compatible signature to the method referred to. They will be called immediately before or after the method as appropriate, and any return value will be ignored.

매개변수:
  • cls (Type) – the class to modify.

  • name (str) – the name of the method on the class to wrap.

  • before (Callable | None) – a callable that should be called before the method that is being wrapped.

  • after (Callable | None) – a callable that should be called after the method that is being wrapped.

예외 발생:

ValueError – if the named method is not defined on the class or any parent class.

Algorithm Utilities#

qiskit.utils.summarize_circuits(circuits)[소스]#
Summarize circuits based on QuantumCircuit, and five metrics are summarized.
  • Number of qubits

  • Number of classical bits

  • Number of operations

  • Depth of circuits

  • Counts of different gate operations

The average statistic of the first four is provided if multiple circuits are provided.

매개변수:

circuits (QuantumCircuit or [QuantumCircuit]) – the to-be-summarized circuits

반환:

a formatted string records the summary

반환 형식:

str

qiskit.utils.get_entangler_map(map_type, num_qubits, offset=0)[소스]#

Utility method to get an entangler map among qubits.

매개변수:
  • map_type (str) – ‘full’ entangles each qubit with all the subsequent ones ‘linear’ entangles each qubit with the next ‘sca’ (shifted circular alternating entanglement) is a circular entanglement where the ‘long’ entanglement is shifted by one position every block and every block the role or control/target qubits alternate

  • num_qubits (int) – Number of qubits for which the map is needed

  • offset (int) – Some map_types (e.g. ‘sca’) can shift the gates in the entangler map by the specified integer offset.

반환:

A map of qubit index to an array of indexes to which this should be entangled

반환 형식:

list

예외 발생:

ValueError – if map_type is not valid.

qiskit.utils.validate_entangler_map(entangler_map, num_qubits, allow_double_entanglement=False)[소스]#

Validate a user supplied entangler map and converts entries to ints.

매개변수:
  • entangler_map (list[list]) – An entangler map, keys are source qubit index (int), value is array of target qubit index(es) (int)

  • num_qubits (int) – Number of qubits

  • allow_double_entanglement (bool) – If we allow in two qubits can be entangled each other

반환:

Validated/converted map

반환 형식:

list

예외 발생:
  • TypeError – entangler map is not list type or list of list

  • ValueError – the index of entangler map is out of range

  • ValueError – the qubits are cross-entangled.

qiskit.utils.has_ibmq()[소스]#

Check if IBMQ is installed.

버전 0.24.0부터 폐지됨: The function qiskit.utils.backend_utils.has_ibmq() is deprecated as of qiskit-terra 0.24.0. It will be removed no earlier than 3 months after the release date. For code migration guidelines, visit https://qisk.it/qi_migration.

qiskit.utils.has_aer()[소스]#

Check if Aer is installed.

버전 0.24.0부터 폐지됨: The function qiskit.utils.backend_utils.has_aer() is deprecated as of qiskit-terra 0.24.0. It will be removed no earlier than 3 months after the release date. For code migration guidelines, visit https://qisk.it/qi_migration.

qiskit.utils.name_args(mapping, skip=0)[소스]#

Decorator to convert unnamed arguments to named ones.

Can be used to deprecate old signatures of a function, e.g.

old_f(a: TypeA, b: TypeB, c: TypeC)
new_f(a: TypeA, d: TypeD, b: TypeB=None, c: TypeC=None)

Then, to support the old signature this decorator can be used as

@name_args([
    ('a'),  # stays the same
    ('d', {TypeB: 'b'}),  # if arg is of type TypeB, call if 'b' else 'd'
    ('b', {TypeC: 'c'})
])
def new_f(a: TypeA, d: TypeD, b: TypeB=None, c: TypeC=None):
    if b is not None:
        # raise warning, this is deprecated!
    if c is not None:
        # raise warning, this is deprecated!
qiskit.utils.algorithm_globals = <qiskit.utils.algorithm_globals.QiskitAlgorithmGlobals object>#

Class for global properties.

QuantumInstance

Deprecated: Quantum Backend including execution setting.

A QuantumInstance holds the Qiskit backend as well as a number of compile and runtime parameters controlling circuit compilation and execution. Quantum algorithms are run on a device or simulator by passing a QuantumInstance setup with the desired backend etc.

Optional Dependency Checkers (qiskit.utils.optionals)#

Qiskit Terra, and many of the other Qiskit components, have several features that are enabled only if certain optional dependencies are satisfied. This module is a collection of objects that can be used to test if certain functionality is available, and optionally raise MissingOptionalLibraryError if the functionality is not available.

Available Testers#

Qiskit Components#

qiskit.utils.optionals.HAS_AER#

Qiskit Aer provides high-performance simulators for the quantum circuits constructed within Qiskit Terra.

qiskit.utils.optionals.HAS_IBMQ#

The Qiskit IBMQ Provider is used for accessing IBM Quantum hardware in the IBM cloud.

qiskit.utils.optionals.HAS_IGNIS#

Qiskit Ignis provides tools for quantum hardware verification, noise characterization, and error correction.

qiskit.utils.optionals.HAS_TOQM#

Qiskit TOQM provides transpiler passes for the Time-optimal Qubit mapping algorithm.

External Python Libraries#

qiskit.utils.optionals.HAS_CONSTRAINT#

python-constraint <https://github.com/python-constraint/python-constraint>__ is a constraint satisfaction problem solver, used in the :class:`~.CSPLayout transpiler pass.

qiskit.utils.optionals.HAS_CPLEX#

The IBM CPLEX Optimizer is a high-performance mathematical programming solver for linear, mixed-integer and quadratic programming. It is required by the BIPMapping transpiler pass.

qiskit.utils.optionals.HAS_CVXPY#

CVXPY is a Python package for solving convex optimization problems. It is required for calculating diamond norms with quantum_info.diamond_norm().

qiskit.utils.optionals.HAS_DOCPLEX#

IBM Decision Optimization CPLEX Modelling is a library for prescriptive analysis. Like CPLEX, it is required for the BIPMapping transpiler pass.

qiskit.utils.optionals.HAS_FIXTURES#

The test suite has additional features that are available if the optional fixtures module is installed. This generally also needs HAS_TESTTOOLS as well. This is generally only needed for Qiskit developers.

qiskit.utils.optionals.HAS_IPYTHON#

If the IPython kernel is available, certain additional visualisations and line magics are made available.

qiskit.utils.optionals.HAS_IPYWIDGETS#

Monitoring widgets for jobs running on external backends can be provided if ipywidgets is available.

qiskit.utils.optionals.HAS_JAX#

Some methods of gradient calculation within opflow.gradients require JAX for autodifferentiation.

qiskit.utils.optionals.HAS_JUPYTER#

Some of the tests require a complete Jupyter installation to test interactivity features.

qiskit.utils.optionals.HAS_MATPLOTLIB#

Qiskit Terra provides several visualisation tools in the visualization module. Almost all of these are built using Matplotlib, which must be installed in order to use them.

qiskit.utils.optionals.HAS_NETWORKX#

No longer used by Terra. Internally, Qiskit now uses the high-performance rustworkx library as a core dependency, and during the change-over period, it was sometimes convenient to convert things into the Python-only NetworkX format. Some tests of application modules, such as Qiskit Nature still use NetworkX.

qiskit.utils.optionals.HAS_NLOPT#

NLopt is a nonlinear optimization library, used by the global optimizers in the algorithms.optimizers module.

qiskit.utils.optionals.HAS_PIL#

PIL is a Python image-manipulation library. Qiskit actually uses the pillow fork of PIL if it is available when generating certain visualizations, for example of both QuantumCircuit and DAGCircuit in certain modes.

qiskit.utils.optionals.HAS_PYDOT#

For some graph visualisations, Qiskit uses pydot as an interface to GraphViz (see HAS_GRAPHVIZ).

qiskit.utils.optionals.HAS_PYGMENTS#

Pygments is a code highlighter and formatter used by many environments that involve rich display of code blocks, including Sphinx and Jupyter. Qiskit uses this when producing rich output for these environments.

qiskit.utils.optionals.HAS_PYLATEX#

Various LaTeX-based visualizations, especially the circuit drawers, need access to the pylatexenc project to work correctly.

qiskit.utils.optionals.HAS_QASM3_IMPORT#

The functions qasm3.load() and qasm3.loads() for importing OpenQASM 3 programs into QuantumCircuit instances use an external importer package.

qiskit.utils.optionals.HAS_SEABORN#

Qiskit Terra provides several visualisation tools in the visualization module. Some of these are built using Seaborn, which must be installed in order to use them.

qiskit.utils.optionals.HAS_SKLEARN#

Some of the gradient functions in opflow.gradients use regularisation methods from Scikit Learn.

qiskit.utils.optionals.HAS_SKQUANT#

Some of the optimisers in algorithms.optimizers are based on those found in Scikit Quant, which must be installed to use them.

qiskit.utils.optionals.HAS_SQSNOBFIT#

SQSnobFit is a library for the “stable noisy optimization by branch and fit” algorithm. It is used by the SNOBFIT optimizer.

qiskit.utils.optionals.HAS_SYMENGINE#

Symengine is a fast C++ backend for the symbolic-manipulation library Sympy. Qiskit uses special methods from Symengine to accelerate its handling of Parameters if available.

qiskit.utils.optionals.HAS_TESTTOOLS#

Qiskit Terra’s test suite has more advanced functionality available if the optional testtools library is installed. This is generally only needed for Qiskit developers.

qiskit.utils.optionals.HAS_TWEEDLEDUM#

Tweedledum is an extension library for synthesis and optimization of circuits that may involve classical oracles. Qiskit Terra’s PhaseOracle uses this, which is used in turn by amplification algorithms via the AmplificationProblem.

qiskit.utils.optionals.HAS_Z3#

Z3 is a theorem prover, used in the CrosstalkAdaptiveSchedule and HoareOptimizer transpiler passes.

External Command-Line Tools#

qiskit.utils.optionals.HAS_GRAPHVIZ#

For some graph visualisations, Qiskit uses the GraphViz visualisation tool via its pydot interface (see HAS_PYDOT).

qiskit.utils.optionals.HAS_PDFLATEX#

Visualisation tools that use LaTeX in their output, such as the circuit drawers, require pdflatex to be available. You will generally need to ensure that you have a working LaTeX installation available, and the qcircuit.tex package.

qiskit.utils.optionals.HAS_PDFTOCAIRO#

Visualisation tools that convert LaTeX-generated files into rasterised images use the pdftocairo tool. This is part of the Poppler suite of PDF tools.

Lazy Checker Classes#

Each of the lazy checkers is an instance of LazyDependencyManager in one of its two subclasses: LazyImportTester and LazySubprocessTester. These should be imported from utils directly if required, such as:

from qiskit.utils import LazyImportTester
class qiskit.utils.LazyDependencyManager(*, name=None, callback=None, install=None, msg=None)[소스]#

A mananger for some optional features that are expensive to import, or to verify the existence of.

These objects can be used as Booleans, such as if x, and will evaluate True if the dependency they test for is available, and False if not. The presence of the dependency will only be tested when the Boolean is evaluated, so it can be used as a runtime test in functions and methods without requiring an import-time test.

These objects also encapsulate the error handling if their dependency is not present, so you can do things such as:

from qiskit.utils import LazyImportManager
HAS_MATPLOTLIB = LazyImportManager("matplotlib")

@HAS_MATPLOTLIB.require_in_call
def my_visualisation():
    ...

def my_other_visualisation():
    # ... some setup ...
    HAS_MATPLOTLIB.require_now("my_other_visualisation")
    ...

def my_third_visualisation():
    if HAS_MATPLOTLIB:
        from matplotlib import pyplot
    else:
        ...

In all of these cases, matplotlib is not imported until the functions are entered. In the case of the decorator, matplotlib is tested for import when the function is called for the first time. In the second and third cases, the loader attempts to import matplotlib when the require_now() method is called, or when the Boolean context is evaluated. For the require methods, an error is raised if the library is not available.

This is the base class, which provides the Boolean context checking and error management. The concrete classes LazyImportTester and LazySubprocessTester provide convenient entry points for testing that certain symbols are importable from modules, or certain command-line tools are available, respectively.

매개변수:
  • name – the name of this optional dependency.

  • callback – a callback that is called immediately after the availability of the library is tested with the result. This will only be called once.

  • install – how to install this optional dependency. Passed to MissingOptionalLibraryError as the pip_install parameter.

  • msg – an extra message to include in the error raised if this is required.

abstract _is_available()[소스]#

Subclasses of LazyDependencyManager should override this method to implement the actual test of availability. This method should return a Boolean, where True indicates that the dependency was available. This method will only ever be called once.

반환 형식:

bool

disable_locally()[소스]#

Create a context, during which the value of the dependency manager will be False. This means that within the context, any calls to this object will behave as if the dependency is not available, including raising errors. It is valid to call this method whether or not the dependency has already been evaluated. This is most useful in tests.

require_in_call(feature_or_callable: Callable) Callable[소스]#
require_in_call(feature_or_callable: str) Callable[[Callable], Callable]

Create a decorator for callables that requires that the dependency is available when the decorated function or method is called.

매개변수:

feature_or_callable (str or Callable) – the name of the feature that requires these dependencies. If this function is called directly as a decorator (for example @HAS_X.require_in_call as opposed to @HAS_X.require_in_call("my feature")), then the feature name will be taken to be the function name, or class and method name as appropriate.

반환:

a decorator that will make its argument require this dependency before it is called.

반환 형식:

Callable

require_in_instance(feature_or_class: Type) Type[소스]#
require_in_instance(feature_or_class: str) Callable[[Type], Type]

A class decorator that requires the dependency is available when the class is initialised. This decorator can be used even if the class does not define an __init__ method.

매개변수:

feature_or_class (str or Type) – the name of the feature that requires these dependencies. If this function is called directly as a decorator (for example @HAS_X.require_in_instance as opposed to @HAS_X.require_in_instance("my feature")), then the feature name will be taken as the name of the class.

반환:

a class decorator that ensures that the wrapped feature is present if the class is initialised.

반환 형식:

Callable

require_now(feature)[소스]#

Eagerly attempt to import the dependencies in this object, and raise an exception if they cannot be imported.

매개변수:

feature (str) – the name of the feature that is requiring these dependencies.

예외 발생:

MissingOptionalLibraryError – if the dependencies cannot be imported.

class qiskit.utils.LazyImportTester(name_map_or_modules, *, name=None, callback=None, install=None, msg=None)[소스]#

A lazy dependency tester for importable Python modules. Any required objects will only be imported at the point that this object is tested for its Boolean value.

매개변수:

name_map_or_modules (str | Dict[str, Iterable[str]] | Iterable[str]) – if a name map, then a dictionary where the keys are modules or packages, and the values are iterables of names to try and import from that module. It should be valid to write from <module> import <name1>, <name2>, .... If simply a string or iterable of strings, then it should be valid to write import <module> for each of them.

예외 발생:

ValueError – if no modules are given.

class qiskit.utils.LazySubprocessTester(command, *, name=None, callback=None, install=None, msg=None)[소스]#

A lazy checker that a command-line tool is available. The command will only be run once, at the point that this object is checked for its Boolean value.

매개변수:

command (str | Iterable[str]) – the strings that make up the command to be run. For example, ["pdflatex", "-version"].

예외 발생:

ValueError – if an empty command is given.