Utilities

qiskit.utils

Deprecations

add_deprecation_to_docstring

qiskit.utils.add_deprecation_to_docstring(func, msg, *, since, pending)

GitHub

Dynamically insert the deprecation message into func ’s docstring.

Parameters

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?

deprecate_arg

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

GitHub

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.

Parameters

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”.

Returns

The decorated callable.

Return type

Callable

deprecate_arguments

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

GitHub

Deprecated. Instead, use @deprecate_arg.

Parameters

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.

Returns

The decorated callable.

Return type

Callable

deprecate_func

qiskit.utils.deprecate_func(*, since, additional_msg=None, pending=False, package_name='qiskit', removal_timeline='no earlier than 3 months after the release date', is_property=False, stacklevel=2)

GitHub

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.

Parameters

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.)
stacklevel (int) – Stack level passed to warnings.warn().

Returns

The decorated callable.

Return type

Callable

deprecate_function

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

GitHub

Deprecated. Instead, use @deprecate_func.

Parameters

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.

Returns

The decorated, deprecated callable.

Return type

Callable

SI unit conversion

apply_prefix

qiskit.utils.apply_prefix(value, unit)

GitHub

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

Parameters

value (float |ParameterExpression) – The number to apply prefix to.
unit (str) – String prefix.

Returns

Converted value.

Return type

float | ParameterExpression

Note

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

Raises

ValueError - If the units aren’t recognized.

Return type

float | ParameterExpression

detach_prefix

qiskit.utils.detach_prefix(value, decimal=None)

GitHub

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).

Example

>>> value, prefix = detach_prefix(1e4)
>>> print(f"{value} {prefix}Hz")
10 kHz

Parameters

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.

Returns

A tuple of scaled value and prefix.

Return type

tuple [float, str]

Note

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

Raises

ValueError – If the value is out of range.
ValueError – If the value is not real number.

Return type

tuple [float, str]

Class tools

wrap_method

qiskit.utils.wrap_method(cls, name, *, before=None, after=None)

GitHub

Wrap the functionality the instance- or class method cls.name with additional behavior 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.

Parameters

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.

Raises

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

Multiprocessing

local_hardware_info

qiskit.utils.local_hardware_info()

GitHub

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.

Returns

The hardware information.

Return type

dict

is_main_process

qiskit.utils.is_main_process()

GitHub

Checks whether the current process is the main one

A helper function for calling a custom function with Python ProcessPoolExecutor . Tasks can be executed in parallel using this function.

parallel_map

qiskit.utils.parallel_map(task, values, task_args=(), task_kwargs={}, num_processes=2)

GitHub

Parallel execution of a mapping of values to the function task. This is functionally equivalent to:

result = [task(value, *task_args, **task_kwargs) for value in values]

This will parallelise the results if the number of values is greater than one, and the current system configuration permits parallelization.

Parameters

task (func) – Function that is to be called for each value in values.
values (array_like) – List or array of values for which the task function is to be evaluated.
task_args (list) – Optional additional arguments to the task function.
task_kwargs (dict) – Optional additional keyword argument to the task function.
num_processes (int) – Number of processes to spawn.

Returns

The result list contains the value of task(value, *task_args, **task_kwargs) for each value in values .

Return type

result

Raises

QiskitError - If user interrupts via keyboard.

Examples

import time
from qiskit.utils import parallel_map
def func(_):
        time.sleep(0.1)
        return 0
parallel_map(func, list(range(10)));

Optional Dependency Checkers

Qiskit has several features that are enabled only if certain optional dependencies are satisfied. This module, qiskit.utils.optionals, has 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 < https://qiskit.github.io/qiskit-aer/ > provides high-performance simulators for the quantum circuits constructed within Qiskit.

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 is a constraint satisfaction problem solver, used in the 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. This is no longer by Qiskit, but it weas historically and the optional remains for backwards compatibility.

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, this is no longer by Qiskit, but it weas historically and the optional remains for backwards compatibility.

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 visualizations 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 provides several visualization 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 Qiskit. 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 visualizations, 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 provides several visualization 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 Parameter s if available.

qiskit.utils.optionals.HAS_TESTTOOLS

Qiskit’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’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 visualizations, Qiskit uses the GraphViz visualization tool via its pydot interface (see HAS_PYDOT).

qiskit.utils.optionals.HAS_PDFLATEX

Visualization 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

Visualization tools that convert LaTeX-generated files into rasterized 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

LazyDependencyManager

class qiskit.utils.LazyDependencyManager(*, name=None, callback=None, install=None, msg=None)

GitHub

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.

Parameters

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.

_is_available

abstract_is_available()

GitHub

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.

Return type

bool

disable_locally

disable_locally()

GitHub

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

require_in_call(feature_or_callable: Callable) \to Callable

require_in_call(feature_or_callable: str) \to Callable[[Callable], Callable]

GitHub

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

Parameters

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.

Returns

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

Return type

Callable

require_in_instance

require_in_instance(feature_or_class: Type) \to Type

require_in_instance(feature_or_class: str) \to Callable[[Type], Type]

GitHub

A class decorator that requires the dependency is available when the class is initialized. This decorator can be used even if the class does not define an__init__method.

Parameters

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.

Returns

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

Return type

Callable

require_now

require_now(feature)

GitHub

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

Parameters

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

Raises

MissingOptionalLibraryError - if the dependencies cannot be imported.

LazyImportTester

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

GitHub

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.

Parameters

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.

Raises

ValueError - if no modules are given.

LazySubprocessTester

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

GitHub

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.

Parameters

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

Raises

ValueError - if an empty command is given.

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