Use the command line

The nwqlib command, also available as python -m nwqlib, lists the Methods, shows each Method's scope and parameters, checks a Method you wrote, and prints a saved Result. Solving, reanalysis, search, saving, loading and verification are Python operations. The NWQ-Sim runner has its own build command.

Discover methods

python -m nwqlib algorithms

adapt_gcim@4: eigenvalue
chebyshev_lanczos@5: eigenvalue
finite_pauli_expectation@2: normalized_expectation, quadratic_form
fixed_gcim@4: eigenvalue
lchs@3: solution, state_vector, norm_squared, quadratic_form, normalized_expectation, samples
qcels@1: eigenphase, eigenvalue
qhd@2: optimization_candidate
qls@2: solution, state_vector, norm_squared, quadratic_form, normalized_expectation, samples
rfe@2: eigenphase, eigenvalue
rwpe@2: eigenphase, eigenvalue
spe@2: eigenphase, eigenvalue
Declared scope only; discovery does not establish scientific or backend qualification.

Each line gives a Method name, its version after @, and the outputs it can return (Choose a problem and output). card prints one Method's declared problems, outputs, input forms, limitations and references as JSON:

python -m nwqlib card qls

{
  ...
  "descriptor": {
    ...
    "problem_families": [
      "linear_system"
    ],
    ...
    "access_families": [
      "dense",
      "pauli",
      "periodic_stencil",
      "bound_block_encoding"
    ],
    ...
    "limitations": [
      "complete propagated physical error and native rounding remain unknown",
      "shortcut supplies a unit direction; classical norm models do not supply physical x"
    ],
    "references": [
      {
        ...
        "reference": "selected inverse Chebyshev QSVT and Dalzell arXiv:2406.12086v2 kernel-reflection methods",
        ...

algorithms --json prints every card as JSON. options prints the JSON schema of a Method's configuration, including required scientific fields and current defaults:

python -m nwqlib algorithms --json
python -m nwqlib options adapt_gcim

These commands show what each Method declares. They do not show that a Method applies to your problem, runs on a given backend or reaches a given accuracy. options creates no Method and plans no workload.

--version VERSION selects an exact Method version for card or options, and an unknown or ambiguous name is an error. --third-party also lists the Methods that installed packages declare through entry points, without running their code. Their scope, cards and schemas are therefore unavailable from these commands.

Check a Method you wrote

python -m nwqlib check-method MODULE:case

MODULE is your importable module, and case is a function in it that returns a MethodCase. The MethodCase holds your Method, a Problem for the check and three functions. evaluate runs the Method, accepts tests the Result against an independently known answer, and invalid_result makes a wrong Result for the same Plan. check-method then checks the following, as Add a method defines:

1. The Result that evaluate returns satisfies accepts, the Method's error model matches its Plan, and the Method names the Result type it returns.
2. The wrong Result from invalid_result is rejected by the Method's own check of the Plan and Result.
3. The correct Result saves, reloads unchanged and still satisfies accepts.

The reference Hadamard Method supplies a complete case. It runs one two-qubit circuit, checks that the Y expectation of |+i> is 1, and saves and reloads the Result. On it, check-method prints "status": "CONFORMANT" with the scope of the check.

check-method imports and runs the case you name, including any circuit execution it declares, so it is not a sandbox. It adds no reference study of its own. A failed or unsupported case exits with a nonzero status. A pass establishes this one case only, not general scientific accuracy or backend support.

Python discovery

In Python, methods() returns the registration record of each built-in Method:

from nwqlib import methods

registrations = methods()
for registration in registrations:
    print(registration.source.name, registration.source.version)

For formatted declarations and configuration schemas, use the algorithms, card and options commands. Listing Methods neither runs nor tests them.

Read a saved report

Save a Result in Python, then print it without loading its Method or binary data:

result.save("my-result")

python -m nwqlib report my-result

The JSON output holds the saved Plan with its Method name (selection), the scientific fields, observations, preparation records and trace. report checks the format version and returns this metadata. Method names are shown as text, and no Method code is imported. Use nwqlib.load_result(path, method=...) to reconstruct a Result and access its saved arrays and circuits.