action failure fix, and black and ruff

Author: SidRichardsQuantum

.github/workflows/tests.yml

@@ -5,6 +5,31 @@ on:
   pull_request:
 
 jobs:
+  lint:
+    name: Lint and Format
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Check out repository
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
+          cache: pip
+
+      - name: Install lint tools
+        run: |
+          python -m pip install --upgrade pip
+          python -m pip install -e ".[dev]"
+
+      - name: Ruff
+        run: ruff check .
+
+      - name: Black
+        run: black --check .
+
   tests:
     name: Tests Python ${{ matrix.python-version }}
     runs-on: ubuntu-latest

examples/benchmark_runtime.py

@@ -1,6 +1,5 @@
 from shors_algorithm_simulation.plotting.runtime import benchmark_runtime_table
 
-
 if __name__ == "__main__":
     """Benchmark selected deterministic cases and save a CSV summary."""
     benchmark_cases = [

examples/circuit_diagrams_example.py

@@ -1,5 +1,4 @@
 from shors_algorithm_simulation.quantum.circuits import main
 
-
 if __name__ == "__main__":
     main()

examples/factorisation_example.py

@@ -1,7 +1,6 @@
 from shors_algorithm_simulation import compute_probs, shors_simulation
 from shors_algorithm_simulation.plotting.probabilities import plot_probs
 
-
 if __name__ == "__main__":
     """Run a deterministic factorisation example with plot output."""
     result = shors_simulation(N=35, a=2, sparse=True, mode="distribution")

examples/multiple_cases_example.py

@@ -1,6 +1,5 @@
 from shors_algorithm_simulation import shors_simulation
 
-
 if __name__ == "__main__":
     """Run multiple semiprime examples with fixed bases for quick experimentation."""
     cases = [
@@ -15,10 +14,14 @@
         print(f"Running example with N={N}, a={a}, mode={mode}")
         print("=" * 60)
         result = shors_simulation(N=N, a=a, sparse=True, mode=mode)
-        print(f"Structured result: success={result['success']}, factors={result['factors']}, period={result['period']}")
+        print(
+            f"Structured result: success={result['success']}, factors={result['factors']}, period={result['period']}"
+        )
 
     print("\n" + "=" * 60)
     print("Expected retry case with N=33, a=2")
     print("=" * 60)
     result = shors_simulation(N=33, a=2, sparse=True, mode="distribution")
-    print(f"Structured result: success={result['success']}, message={result['message']}")
+    print(
+        f"Structured result: success={result['success']}, message={result['message']}"
+    )

examples/no_plot_example.py

@@ -1,6 +1,5 @@
 from shors_algorithm_simulation import shors_simulation
 
-
 if __name__ == "__main__":
     """Run a deterministic example without opening plots."""
     result = shors_simulation(N=21, a=2, sparse=True, mode="distribution")

examples/runtimes_test.py

@@ -1,39 +1,40 @@
 from shors_algorithm_simulation.plotting.runtime import run_runtime_analysis
 
-
 if __name__ == "__main__":
     """Choose coprime (N, a) for non-trivial runs"""
     test_cases = [
-    (15, 2),   # 3 * 5
-    (21, 2),   # 3 * 7
-    (33, 5),   # 3 * 11
-    (35, 2),   # 5 * 7
-    (39, 2),   # 3 * 13
-    (51, 2),   # 3 * 17
-    (55, 2),   # 5 * 11
-    (57, 5),   # 3 * 19
-    (65, 3),   # 5 * 13
-    (69, 2),   # 3 * 23
-    (77, 2),   # 7 * 11
-    (85, 2),   # 5 * 17
-    (87, 2),   # 3 * 29
-    (91, 5),   # 7 * 13
-    (93, 2),   # 3 * 31
-    (95, 2),   # 5 * 19
-    (111, 2),  # 3 * 37
-    (115, 2),  # 5 * 23
-    (119, 2),  # 7 * 17
-    (123, 2),  # 3 * 41
-    (129, 7),  # 3 * 43
-    (133, 2),  # 7 * 19
-    (141, 2),  # 3 * 47
-    (161, 6),  # 7 * 23
-]
+        (15, 2),  # 3 * 5
+        (21, 2),  # 3 * 7
+        (33, 5),  # 3 * 11
+        (35, 2),  # 5 * 7
+        (39, 2),  # 3 * 13
+        (51, 2),  # 3 * 17
+        (55, 2),  # 5 * 11
+        (57, 5),  # 3 * 19
+        (65, 3),  # 5 * 13
+        (69, 2),  # 3 * 23
+        (77, 2),  # 7 * 11
+        (85, 2),  # 5 * 17
+        (87, 2),  # 3 * 29
+        (91, 5),  # 7 * 13
+        (93, 2),  # 3 * 31
+        (95, 2),  # 5 * 19
+        (111, 2),  # 3 * 37
+        (115, 2),  # 5 * 23
+        (119, 2),  # 7 * 17
+        (123, 2),  # 3 * 41
+        (129, 7),  # 3 * 43
+        (133, 2),  # 7 * 19
+        (141, 2),  # 3 * 47
+        (161, 6),  # 7 * 23
+    ]
 
     try:
-        N_vals, qubits, times, stds = run_runtime_analysis(test_cases, 3, sparse=True, mode="distribution")
+        N_vals, qubits, times, stds = run_runtime_analysis(
+            test_cases, 3, sparse=True, mode="distribution"
+        )
         print("\nAnalysis complete!")
-        
+
     except KeyboardInterrupt:
         print("\nAnalysis interrupted by user.")
 

examples/shots_sweep_example.py

@@ -8,7 +8,6 @@
 from shors_algorithm_simulation import shors_simulation
 from shors_algorithm_simulation.plotting.matplotlib_helpers import get_pyplot
 
-
 DEFAULT_SHOTS = (16, 32, 64, 128, 256, 512, 1024)
 
 
@@ -49,7 +48,10 @@ def run_shots_sweep(
 
     csv_path = os.path.join(output_dir, f"shots_sweep_N={N}_a={a}_trials={trials}.csv")
     with open(csv_path, "w", newline="", encoding="utf-8") as handle:
-        writer = csv.DictWriter(handle, fieldnames=["N", "a", "shots", "trials", "successes", "success_rate"])
+        writer = csv.DictWriter(
+            handle,
+            fieldnames=["N", "a", "shots", "trials", "successes", "success_rate"],
+        )
         writer.writeheader()
         writer.writerows(rows)
 
@@ -80,13 +82,32 @@ def _plot_shots_sweep(rows: list[dict[str, object]], output_file: str) -> None:
 
 
 def parse_args() -> argparse.Namespace:
-    parser = argparse.ArgumentParser(description="Plot sampled-measurement success rate versus shots.")
-    parser.add_argument("--N", type=int, default=21, help="Composite integer to factor.")
-    parser.add_argument("--a", type=int, default=2, help="Base for modular exponentiation.")
-    parser.add_argument("--shots", nargs="+", type=int, default=list(DEFAULT_SHOTS), help="Shot counts to test.")
+    parser = argparse.ArgumentParser(
+        description="Plot sampled-measurement success rate versus shots."
+    )
+    parser.add_argument(
+        "--N", type=int, default=21, help="Composite integer to factor."
+    )
+    parser.add_argument(
+        "--a", type=int, default=2, help="Base for modular exponentiation."
+    )
+    parser.add_argument(
+        "--shots",
+        nargs="+",
+        type=int,
+        default=list(DEFAULT_SHOTS),
+        help="Shot counts to test.",
+    )
     parser.add_argument("--trials", type=int, default=20, help="Trials per shot count.")
-    parser.add_argument("--seed", type=int, default=0, help="Base random seed for reproducible sampling.")
-    parser.add_argument("--output-dir", default="images", help="Directory for generated CSV and plot.")
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=0,
+        help="Base random seed for reproducible sampling.",
+    )
+    parser.add_argument(
+        "--output-dir", default="images", help="Directory for generated CSV and plot."
+    )
     return parser.parse_args()
 
 

examples/visualizations_example.py

@@ -9,14 +9,22 @@
     plot_oracle_period_pattern,
 )
 
-
 PLOT_CHOICES = ["oracle", "marked", "continued", "comparison", "all"]
 
 
 def parse_args():
-    parser = argparse.ArgumentParser(description="Generate Shor period-finding visualizations.")
-    parser.add_argument("--N", type=int, default=21, help="Semiprime for oracle/probability/candidate plots.")
-    parser.add_argument("--a", type=int, default=2, help="Base for oracle/probability/candidate plots.")
+    parser = argparse.ArgumentParser(
+        description="Generate Shor period-finding visualizations."
+    )
+    parser.add_argument(
+        "--N",
+        type=int,
+        default=21,
+        help="Semiprime for oracle/probability/candidate plots.",
+    )
+    parser.add_argument(
+        "--a", type=int, default=2, help="Base for oracle/probability/candidate plots."
+    )
     parser.add_argument(
         "--mode",
         choices=["distribution", "matrix"],
@@ -30,11 +38,34 @@ def parse_args():
         default=["all"],
         help="Plots to generate.",
     )
-    parser.add_argument("--output-dir", default="images", help="Directory for generated plots and CSV files.")
-    parser.add_argument("--top-n", type=int, default=12, help="Number of continued-fraction candidates to plot.")
-    parser.add_argument("--comparison-N", type=int, default=15, help="N for matrix/distribution comparison.")
-    parser.add_argument("--comparison-a", type=int, default=2, help="a for matrix/distribution comparison.")
-    parser.add_argument("--dense-comparison", action="store_true", help="Use dense matrices for comparison plot.")
+    parser.add_argument(
+        "--output-dir",
+        default="images",
+        help="Directory for generated plots and CSV files.",
+    )
+    parser.add_argument(
+        "--top-n",
+        type=int,
+        default=12,
+        help="Number of continued-fraction candidates to plot.",
+    )
+    parser.add_argument(
+        "--comparison-N",
+        type=int,
+        default=15,
+        help="N for matrix/distribution comparison.",
+    )
+    parser.add_argument(
+        "--comparison-a",
+        type=int,
+        default=2,
+        help="a for matrix/distribution comparison.",
+    )
+    parser.add_argument(
+        "--dense-comparison",
+        action="store_true",
+        help="Use dense matrices for comparison plot.",
+    )
     return parser.parse_args()
 
 
@@ -47,7 +78,9 @@ def selected_plots(plot_args):
 
 def print_output(name, value):
     if isinstance(value, dict):
-        print(f"{name}: plot={value['plot']}, csv={value['csv']}, rows={len(value['rows'])}")
+        print(
+            f"{name}: plot={value['plot']}, csv={value['csv']}, rows={len(value['rows'])}"
+        )
     else:
         print(f"{name}: {value}")
 
@@ -62,7 +95,9 @@ def main():
         probabilities = compute_probs(args.N, args.a, mode=args.mode)
 
     if "oracle" in plots:
-        outputs["oracle"] = plot_oracle_period_pattern(args.N, args.a, output_dir=args.output_dir)
+        outputs["oracle"] = plot_oracle_period_pattern(
+            args.N, args.a, output_dir=args.output_dir
+        )
 
     if "continued" in plots:
         outputs["continued"] = plot_continued_fraction_diagnostics(

main.py

@@ -1,5 +1,4 @@
 from shors_algorithm_simulation.cli import main
 
-
 if __name__ == "__main__":
     raise SystemExit(main())