---
title: optionals (latest version)
description: API reference for qiskit_fermions.utils.optionals in the latest version of qiskit-fermions
source: https://quantum.cloud.ibm.com/docs/en/api/qiskit-fermions/utils-optionals
---

# Optional Dependencies

This module defines lazy availability testers for optional third-party dependencies. The checkers are instances of [`LazyImportTester`](/docs/api/qiskit/utils#qiskit.utils.LazyImportTester) and can be used as booleans (evaluated lazily), or to raise a [`MissingOptionalLibraryError`](/docs/api/qiskit/exceptions#qiskit.exceptions.MissingOptionalLibraryError) when a dependency is required.

## Available Testers

### HAS\_FFSIM

Default value: `<qiskit.utils.lazy_tester.LazyImportTester object>`

[ffsim](https://github.com/qiskit-community/ffsim) is a high-performance simulator for fermionic quantum circuits that exploits particle-number and spin-Z conservation.

[`FermionicCircuit`](/docs/api/qiskit-fermions/circuit-fermionic-circuit#qiskit_fermions.circuit.FermionicCircuit "qiskit_fermions.circuit.FermionicCircuit") instances can be simulated using [`ffsim.apply_unitary()`](https://qiskit-community.github.io/ffsim/api/stubs/ffsim.apply_unitary.html#ffsim.apply_unitary "(in ffsim)").

> **Note**
>
> `ffsim` does not support Windows, which is why it is an optional dependency.

> **See also**
>
> [`LazyDependencyManager`](/docs/api/qiskit/utils#qiskit.utils.LazyDependencyManager) for usage examples and the available methods of this object.

### HAS\_PYOMO

Default value: `<qiskit.utils.lazy_tester.LazyImportTester object>`

[Pyomo](https://www.pyomo.org/) is a Python-based optimization modeling language used to build linear and mixed-integer programs (LP/MILP) for classical solvers.

> **See also**
>
> [`LazyDependencyManager`](/docs/api/qiskit/utils#qiskit.utils.LazyDependencyManager) for usage examples and the available methods of this object.

### HAS\_QISKIT\_ADDON\_SQD

Default value: `<qiskit.utils.lazy_tester.LazyImportTester object>`

[qiskit-addon-sqd](https://github.com/Qiskit/qiskit-addon-sqd) implements sample-based quantum diagonalization (SQD): it projects a Hamiltonian onto the subspace spanned by measured computational- basis configurations and iteratively refines that subspace via *configuration recovery*.

> **Note**
>
> `qiskit-addon-sqd` pulls in PySCF, which does not support Windows, which is why it is an optional dependency.

> **See also**
>
> [`LazyDependencyManager`](/docs/api/qiskit/utils#qiskit.utils.LazyDependencyManager) for usage examples and the available methods of this object.