implement cli for benchmarking and evilnkode

Co-authored-by: Donovan <donovan.a.kelly@pm.me>
Reviewed-on: https://git.infra.nkode.tech/dkelly/evilnkode/pulls/7

.gitignore

@@ -2,3 +2,5 @@
 .DS_Store
 output
 __pycache__
+.ipynb_checkpoints
+

README.md

@@ -1,36 +1,90 @@
-# Evil nKode
+# Evilnkode Project
 
-Simulated nKode Cracker
+This README provides instructions for setting up and running the `evilnkode` project using Conda, activating the environment, and executing the provided CLI scripts. It also covers how to access help for command-line options.
 
-## Installation
+## Prerequisites
 
-- Python version 3.10 or greater is required
-- Install anaconda (or your preferred tool for environment management)
+- **Conda**: Ensure you have Conda installed (Miniconda or Anaconda). Download from [conda.io](https://conda.io).
+
+## Setting Up the Environment
+
+To set up the project environment using the provided `environment.yaml` file, follow these steps:
+
+1. **Install the environment**:
+   - Ensure you are in the project root directory where `environment.yaml` is located.
+   - Run the following command to create the `evilnkode` environment:
+     ```bash
+     conda env create -f environment.yaml
+     ```
+   - This will install all dependencies specified in `environment.yaml`.
+
+## Activating the Environment
+
+To activate the `evilnkode` environment, run:
 
-### Using conda
 ```bash
-conda env create -f environment.yml
-conda activate pynkode
+conda activate evilnkode
 ```
 
-## Starting a Jupyter Notebook
+Once activated, your terminal prompt should change to include `(evilnkode)`, indicating the environment is active.
+
+## Running CLI Scripts
+
+The project includes two main CLI scripts: `cli.visualnkode` and `cli.benchmark_histogram`. Below are instructions to run each.
+
+### Running `cli.visualnkode`
+
+To execute the `visualnkode` CLI script:
 
-### Option 1: Using classic Jupyter Notebook
 ```bash
-# Ensure your environment is activated
-# For conda: conda activate pynkode
-# For pyenv: (should be automatic if in the directory)
-
-# Start the Jupyter Notebook server
-jupyter notebook
+python -m cli.visualnkode
 ```
 
-### Option 2: Using JupyterLab
+- This command runs the `visualnkode` module from the `cli` package.
+- To view available options and arguments, use the `-help` flag:
+  ```bash
+  python -m cli.visualnkode -help
+  ```
+
+### Running `cli.benchmark_histogram`
+
+To execute the `benchmark_histogram` CLI script:
+
 ```bash
-# Ensure your environment is activated
-# Start JupyterLab
-jupyter lab
+python -m cli.benchmark_histogram
 ```
 
-## Notebooks
-- [evilnkode](notebooks/evilkode.ipynb)
+- This command runs the `benchmark_histogram` module, which may generate output such as benchmark results or histograms. For example, it might produce output like:
+  ```
+  File exists: output/slidingtowershufflekeypad-6-8-4-5-4-4-10000/benchmark/slidingtowershufflekeypad-6-8-4-5-4-4-10000.pkl
+  Bench SlidingTowerShuffle Break 5
+  Bench SlidingTowerShuffle Replay 5
+  ```
+- To view available options and arguments, use the `-help` flag:
+  ```bash
+  python -m cli.benchmark_histogram -help
+  ```
+
+## Using the `-help` Flag
+
+Both CLI scripts (`cli.visualnkode` and `cli.benchmark_histogram`) support a `-help` flag to display available command-line options and their descriptions. Run the following to explore options for each script:
+
+```bash
+python -m cli.visualnkode -help
+python -m cli.benchmark_histogram -help
+```
+
+This will provide detailed information about parameters, flags, and usage for each script.
+
+## Project Structure
+
+Key files and directories in the project:
+
+- `environment.yaml`: Conda environment configuration file.
+- `cli/`: Contains CLI scripts (`visualnkode` and `benchmark_histogram`).
+- `output/`: Directory where script outputs, such as benchmark results, are stored.
+- `src/`: Source code for the project.
+- `tests/`: Test scripts for the project.
+- `requirements.txt`: Additional dependencies (if needed outside Conda).
+
+For further details, explore the project documentation in the `docs/` directory.

cli/benchmark_histogram.py

@@ -0,0 +1,115 @@
+import argparse
+from src.benchmark import benchmark
+import matplotlib.pyplot as plt
+from pathlib import Path
+from statistics import mean
+from src.keypad.keypad import (
+    RandomSplitShuffleKeypad,
+    RandomShuffleKeypad,
+    SlidingSplitShuffleKeypad,
+    SlidingTowerShuffleKeypad,
+)
+
+
+def bench_histogram(data, title, number_of_keys, properties_per_key, passcode_len, max_tries_before_lockout, complexity,
+                    disparity, run_count, save_path: Path = None):
+    min_val = min(data)
+    max_val = max(data)
+    bins = range(min_val, max_val + 2)
+    plt.hist(data, bins=bins, edgecolor='black')
+    plt.title(title)
+    plt.xlabel('# of Login Observations')
+    plt.ylabel('Simulations')
+    text = (f"number_of_keys={number_of_keys}\n"
+            f"properties_per_key={properties_per_key}\n"
+            f"passcode_len={passcode_len}\n"
+            f"max_tries_before_lockout={max_tries_before_lockout}\n"
+            f"complexity={complexity}\n"
+            f"disparity={disparity}\n"
+            f"run_count={run_count}")
+    plt.text(0.95, 0.95, text, transform=plt.gca().transAxes, fontsize=10,
+             verticalalignment='top', horizontalalignment='right', bbox=dict(facecolor='white', alpha=0.5))
+    if save_path:
+        save_path = save_path / "histogram"
+        save_path.mkdir(parents=True, exist_ok=True)
+        filename = (f"{title.replace(' ', '_')}_keys{number_of_keys}_"
+                    f"props{properties_per_key}_pass{passcode_len}_tries{max_tries_before_lockout}_"
+                    f"comp{complexity}_disp{disparity}_runs{run_count}.png")
+        plt.savefig(save_path / filename, bbox_inches='tight', dpi=300)
+    plt.close()
+
+
+def main():
+    parser = argparse.ArgumentParser(description='Benchmark Keypad Shuffle')
+    parser.add_argument('--shuffle_type', type=str,
+                        choices=['RandomSplitShuffle', 'RandomShuffle', 'SlidingSplitShuffle', 'SlidingTowerShuffle'],
+                        default='SlidingTowerShuffle', help='Type of keypad shuffle')
+    parser.add_argument('--number_of_keys', type=int, default=6, help='Number of keys')
+    parser.add_argument('--properties_per_key', type=int, default=8, help='Properties per key')
+    parser.add_argument('--passcode_len', type=int, default=4, help='Passcode length')
+    parser.add_argument('--max_tries_before_lockout', type=int, default=5, help='Max tries before lockout')
+    parser.add_argument('--complexity', type=int, default=4, help='Complexity')
+    parser.add_argument('--disparity', type=int, default=4, help='Disparity')
+    parser.add_argument('--run_count', type=int, default=10000, help='Number of runs')
+    parser.add_argument('--output_dir', type=str, default='./output',
+                        help='Output directory for histograms')
+
+    args = parser.parse_args()
+
+    shuffle_classes = {
+        'RandomSplitShuffle': RandomSplitShuffleKeypad,
+        'RandomShuffle': RandomShuffleKeypad,
+        'SlidingSplitShuffle': SlidingSplitShuffleKeypad,
+        'SlidingTowerShuffle': SlidingTowerShuffleKeypad
+    }
+
+    keypad_class = shuffle_classes[args.shuffle_type]
+    keypad = keypad_class.new_keypad(args.number_of_keys, args.properties_per_key)
+
+    shuffle_type = str(type(keypad)).lower().split('.')[-1].replace("'>", "")
+    run_name = f"{shuffle_type}-{args.number_of_keys}-{args.properties_per_key}-{args.passcode_len}-{args.max_tries_before_lockout}-{args.complexity}-{args.disparity}-{args.run_count}"
+    save_path = Path(args.output_dir) / run_name
+    bench_result = benchmark(
+        number_of_keys=args.number_of_keys,
+        properties_per_key=args.properties_per_key,
+        passcode_len=args.passcode_len,
+        max_tries_before_lockout=args.max_tries_before_lockout,
+        run_count=args.run_count,
+        complexity=args.complexity,
+        disparity=args.disparity,
+        keypad=keypad,
+        file_path=save_path,
+    )
+
+    print(f"Bench {args.shuffle_type} Break {mean(bench_result.iterations_to_break)}")
+    print(f"Bench {args.shuffle_type} Replay {mean(bench_result.iterations_to_replay)}")
+
+    bench_histogram(
+        bench_result.iterations_to_break,
+        f"{args.shuffle_type} Break",
+        args.number_of_keys,
+        args.properties_per_key,
+        args.passcode_len,
+        args.max_tries_before_lockout,
+        args.complexity,
+        args.disparity,
+        args.run_count,
+        save_path
+    )
+
+    bench_histogram(
+        bench_result.iterations_to_replay,
+        f"{args.shuffle_type} Replay",
+        args.number_of_keys,
+        args.properties_per_key,
+        args.passcode_len,
+        args.max_tries_before_lockout,
+        args.complexity,
+        args.disparity,
+        args.run_count,
+        save_path,
+    )
+
+
+if __name__ == "__main__":
+    main()

cli/visualnkode.py

@@ -0,0 +1,253 @@
+import json
+from typing import Iterable
+from dataclasses import dataclass, asdict
+from src.evilnkode import Observation
+from src.utils import observations, passcode_generator
+from pathlib import Path
+from PIL import Image, ImageDraw, ImageFont
+from src.keypad.keypad import (
+    BaseKeypad,
+    SlidingSplitShuffleKeypad,
+    SlidingTowerShuffleKeypad,
+    RandomShuffleKeypad,
+    RandomSplitShuffleKeypad,
+)
+import argparse
+
+
+@dataclass
+class ObservationSequence:
+    target_passcode: list[int]
+    observations: list[Observation]
+
+
+def new_observation_sequence(
+        keypad: BaseKeypad,
+        passcode_len: int,
+        complexity: int,
+        disparity: int,
+        numb_runs: int,
+) -> ObservationSequence:
+    passcode = passcode_generator(keypad.k, keypad.p, passcode_len, complexity, disparity)
+    obs_gen = observations(
+        keypad=keypad,
+        target_passcode=passcode,
+        number_of_observations=numb_runs,
+    )
+    return ObservationSequence(target_passcode=passcode, observations=[obs for obs in obs_gen])
+
+
+def _next_json_filename(base_dir: Path) -> Path:
+    """Find the next available observation_X.json file in base_dir."""
+    counter = 1
+    while True:
+        candidate = base_dir / f"observation_{counter}.json"
+        if not candidate.exists():
+            return candidate
+        counter += 1
+
+
+def save_observation_sequence_to_json(seq: ObservationSequence,
+                                      filename: Path) -> None:
+    filename.parent.mkdir(parents=True, exist_ok=True)
+
+    with filename.open("w", encoding="utf-8") as f:
+        json.dump(asdict(seq), f, indent=4)
+
+
+# ---------- Helpers ----------
+def _load_font(preferred: str, size: int) -> ImageFont.FreeTypeFont | ImageFont.ImageFont:
+    """Try a preferred TTF, fall back to common monospace, then PIL default."""
+    candidates = [
+        preferred,
+        "DejaVuSansMono.ttf",  # common on Linux
+        "Consolas.ttf",  # Windows
+        "Menlo.ttc", "Menlo.ttf",  # macOS
+        "Courier New.ttf",
+    ]
+    for c in candidates:
+        try:
+            return ImageFont.truetype(c, size)
+        except Exception:
+            continue
+    return ImageFont.load_default()
+
+
+def _text_size(draw: ImageDraw.ImageDraw, text: str, font: ImageFont.ImageFont) -> tuple[int, int]:
+    """Get (w, h) using font bbox for accurate layout."""
+    left, top, right, bottom = draw.textbbox((0, 0), text, font=font)
+    return int(right - left), int(bottom - top)
+
+
+def _join_nums(nums: Iterable[int]) -> str:
+    return " ".join(str(n) for n in nums)
+
+
+def _next_available_path(path: Path) -> Path:
+    """If path exists, append _1, _2, ..."""
+    if not path.exists():
+        return path
+    base, suffix = path.stem, path.suffix or ".png"
+    i = 1
+    while True:
+        candidate = path.with_name(f"{base}_{i}{suffix}")
+        if not candidate.exists():
+            return candidate
+        i += 1
+
+
+# ---------- Core rendering ----------
+def render_observation_to_png(
+        target_passcode: list[int],
+        obs: Observation,
+        out_path: Path,
+        *,
+        header_font_name: str = "DejaVuSans.ttf",
+        body_font_name: str = "DejaVuSans.ttf",
+        header_size: int = 28,
+        body_size: int = 24,
+        margin: int = 32,
+        row_padding_xy: tuple[int, int] = (16, 12),  # (x, y) padding inside row box
+        row_spacing: int = 14,
+        header_spacing: int = 10,
+        section_spacing: int = 18,
+        bg_color: str = "white",
+        fg_color: str = "black",
+        row_fill: str = "#f7f7f7",
+        row_outline: str = "#222222",
+):
+    """
+    Render a single observation:
+    - Top lines:
+        Target Passcode: {target}
+        Selected Keys:   {selected keys}
+    - Then a stack of row boxes representing the keypad rows.
+    """
+    out_path.parent.mkdir(parents=True, exist_ok=True)
+    out_path = _next_available_path(out_path)
+
+    # Fonts
+    header_font = _load_font(header_font_name, header_size)
+    body_font = _load_font(body_font_name, body_size)
+
+    # Prepare strings
+    header1 = f"Target Passcode: {_join_nums(target_passcode)}"
+    header2 = f"Selected Keys:  {_join_nums(obs.key_selection)}"
+    row_texts = [_join_nums(row) for row in obs.keypad]
+
+    # Measure to compute canvas size
+    # Provisional image for measurement
+    temp_img = Image.new("RGB", (1, 1), bg_color)
+    d = ImageDraw.Draw(temp_img)
+
+    h1_w, h1_h = _text_size(d, header1, header_font)
+    h2_w, h2_h = _text_size(d, header2, header_font)
+
+    row_text_sizes = [_text_size(d, t, body_font) for t in row_texts]
+    row_box_widths = [tw + 2 * row_padding_xy[0] for (tw, th) in row_text_sizes]
+    row_box_heights = [th + 2 * row_padding_xy[1] for (tw, th) in row_text_sizes]
+
+    content_width = max([h1_w, h2_w] + (row_box_widths or [0]))
+    total_rows_height = sum(row_box_heights) + row_spacing * max(0, len(row_box_heights) - 1)
+
+    width = content_width + 2 * margin
+    height = (
+            margin
+            + h1_h
+            + header_spacing
+            + h2_h
+            + section_spacing
+            + total_rows_height
+            + margin
+    )
+
+    # Create final image
+    img = Image.new("RGB", (max(width, 300), max(height, 200)), bg_color)
+    draw = ImageDraw.Draw(img)
+
+    # Draw headers
+    x = margin
+    y = margin
+    draw.text((x, y), header1, font=header_font, fill=fg_color)
+    y += h1_h + header_spacing
+    draw.text((x, y), header2, font=header_font, fill=fg_color)
+    y += h2_h + section_spacing
+
+    # Draw row boxes with evenly spaced numbers
+    max_box_width = max(row_box_widths) if row_box_widths else 0
+    for row, box_h in zip(obs.keypad, row_box_heights):
+        box_left = x
+        box_top = y
+        box_right = x + max_box_width
+        box_bottom = y + box_h
+
+        # draw row rectangle
+        draw.rectangle(
+            [box_left, box_top, box_right, box_bottom],
+            fill=row_fill,
+            outline=row_outline,
+            width=2
+        )
+
+        # evenly spaced numbers
+        n = len(row)
+        if n > 0:
+            available_width = max_box_width - 2 * row_padding_xy[0]
+            spacing = available_width / (n + 1)
+
+            for idx, num in enumerate(row, start=1):
+                num_text = str(num)
+                num_w, num_h = _text_size(draw, num_text, body_font)
+                num_x = box_left + row_padding_xy[0] + spacing * idx - num_w / 2
+                num_y = box_top + (box_h - num_h) // 2
+                draw.text((num_x, num_y), num_text, font=body_font, fill=fg_color)
+
+        y = box_bottom + row_spacing
+
+    img.save(out_path, format="PNG")
+
+
+def _next_run_dir(base_dir: Path) -> Path:
+    """Find the next available run directory under base_dir (run_001, run_002, ...)."""
+    counter = 1
+    while True:
+        run_dir = base_dir / f"run_{counter:03d}"
+        if not run_dir.exists():
+            run_dir.mkdir(parents=True)
+            return run_dir
+        counter += 1
+
+
+def render_sequence_to_pngs(seq: ObservationSequence, out_dir: Path) -> None:
+    out_dir.mkdir(parents=True, exist_ok=True)
+    run_dir = _next_run_dir(out_dir)
+    for i, obs in enumerate(seq.observations, start=1):
+        filename = run_dir / f"observation_{i:03d}.png"
+        render_observation_to_png(seq.target_passcode, obs, filename)
+
+
+if __name__ == "__main__":
+    shuffle_classes = {
+        'RandomSplitShuffle': RandomSplitShuffleKeypad,
+        'RandomShuffle': RandomShuffleKeypad,
+        'SlidingSplitShuffle': SlidingSplitShuffleKeypad,
+        'SlidingTowerShuffle': SlidingTowerShuffleKeypad
+    }
+    parser = argparse.ArgumentParser(description="Generate and save observation sequences with optional PNG rendering.")
+    parser.add_argument("--number-of-keys", type=int, default=6, help="Number of keys in the keypad (default: 6)")
+    parser.add_argument("--properties-per-key", type=int, default=9, help="Properties per key (default: 9)")
+    parser.add_argument("--passcode-length", type=int, default=4, help="Length of the passcode (default: 4)")
+    parser.add_argument("--complexity", type=int, default=0, help="Complexity of the passcode (default: 0)")
+    parser.add_argument("--disparity", type=int, default=0, help="Disparity of the passcode (default: 0)")
+    parser.add_argument("--num-runs", type=int, default=50, help="Number of observations to generate (default: 50)")
+    parser.add_argument("--shuffle-type", type=str, default="SlidingTowerShuffle", choices=list(shuffle_classes.keys()),
+                        help="Keypad shuffle type: 'RandomShuffle' or 'SlidingTowerShuffle' (default: SlidingTowerShuffle)")
+    parser.add_argument("--output-dir", type=str, default="./output",
+                        help="Custom output directory for JSON and PNG files")
+    args = parser.parse_args()
+    keypad = shuffle_classes[args.shuffle_type].new_keypad(6, 9)
+    obs_seq = new_observation_sequence(keypad, 4, 0, 0, numb_runs=50)
+    shuffle_type = str(type(keypad)).lower().split('.')[-1].replace("'>", "")
+    output_dir = Path(args.output_dir)
+    save_observation_sequence_to_json(obs_seq, output_dir / "obs.json")
+    render_sequence_to_pngs(obs_seq, output_dir / "obs_png")

environment.yaml

@@ -0,0 +1,544 @@
+name: base
+channels:
+  - defaults
+dependencies:
+  - _anaconda_depends=2024.10=py312_openblas_0
+  - aiobotocore=2.12.3=py312hca03da5_0
+  - aiohappyeyeballs=2.4.3=py312hca03da5_0
+  - aiohttp=3.10.5=py312h80987f9_0
+  - aioitertools=0.7.1=pyhd3eb1b0_0
+  - aiosignal=1.2.0=pyhd3eb1b0_0
+  - alabaster=0.7.16=py312hca03da5_0
+  - altair=5.0.1=py312hca03da5_0
+  - anaconda-anon-usage=0.5.0=py312hd6b623d_100
+  - anaconda-catalogs=0.2.0=py312hca03da5_1
+  - anaconda-cli-base=0.4.1=py312hca03da5_1
+  - anaconda-client=1.13.0=py312hca03da5_0
+  - anaconda-cloud-auth=0.7.2=py312hca03da5_0
+  - anaconda-navigator=2.6.4=py312hca03da5_0
+  - anaconda-project=0.11.1=py312hca03da5_0
+  - annotated-types=0.6.0=py312hca03da5_0
+  - anyio=4.6.2=py312hca03da5_0
+  - aom=3.6.0=h313beb8_0
+  - appdirs=1.4.4=pyhd3eb1b0_0
+  - applaunchservices=0.3.0=py312hca03da5_0
+  - appnope=0.1.3=py312hca03da5_1001
+  - appscript=1.2.5=py312h80987f9_0
+  - archspec=0.2.3=pyhd3eb1b0_0
+  - argon2-cffi=21.3.0=pyhd3eb1b0_0
+  - argon2-cffi-bindings=21.2.0=py312h80987f9_0
+  - arrow=1.3.0=py312hca03da5_0
+  - arrow-cpp=16.1.0=hbc20fb2_0
+  - astroid=3.2.4=py312hca03da5_0
+  - astropy=6.1.3=py312h80987f9_0
+  - astropy-iers-data=0.2024.9.2.0.33.23=py312hca03da5_0
+  - asttokens=2.0.5=pyhd3eb1b0_0
+  - async-lru=2.0.4=py312hca03da5_0
+  - asyncssh=2.17.0=py312hca03da5_0
+  - atomicwrites=1.4.0=py_0
+  - attrs=24.2.0=py312hca03da5_0
+  - automat=20.2.0=py_0
+  - autopep8=2.0.4=pyhd3eb1b0_0
+  - aws-c-auth=0.6.19=h80987f9_0
+  - aws-c-cal=0.5.20=h80987f9_0
+  - aws-c-common=0.8.5=h80987f9_0
+  - aws-c-compression=0.2.16=h80987f9_0
+  - aws-c-event-stream=0.2.15=h313beb8_0
+  - aws-c-http=0.6.25=h80987f9_0
+  - aws-c-io=0.13.10=h80987f9_0
+  - aws-c-mqtt=0.7.13=h80987f9_0
+  - aws-c-s3=0.1.51=h80987f9_0
+  - aws-c-sdkutils=0.1.6=h80987f9_0
+  - aws-checksums=0.1.13=h80987f9_0
+  - aws-crt-cpp=0.18.16=h313beb8_0
+  - aws-sdk-cpp=1.10.55=h313beb8_0
+  - babel=2.11.0=py312hca03da5_0
+  - backports=1.1=pyhd3eb1b0_1
+  - backports.functools_lru_cache=1.6.4=pyhd3eb1b0_0
+  - backports.tempfile=1.0=pyhd3eb1b0_1
+  - backports.weakref=1.0.post1=py_1
+  - bcrypt=3.2.0=py312h80987f9_1
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+  - pytz=2024.1=py312hca03da5_0
+  - pyuca=1.2=py312hca03da5_1
+  - pyviz_comms=3.0.2=py312hca03da5_0
+  - pywavelets=1.7.0=py312h80987f9_0
+  - pyyaml=6.0.2=py312h80987f9_0
+  - pyzmq=25.1.2=py312h313beb8_0
+  - qdarkstyle=3.2.3=pyhd3eb1b0_0
+  - qstylizer=0.2.2=py312hca03da5_0
+  - qt-main=5.15.2=h0917680_11
+  - qt-webengine=5.15.9=h2903aaf_7
+  - qtawesome=1.3.1=py312hca03da5_0
+  - qtconsole=5.6.0=py312hca03da5_0
+  - qtpy=2.4.1=py312hca03da5_0
+  - queuelib=1.6.2=py312hca03da5_0
+  - re2=2022.04.01=hc377ac9_0
+  - readchar=4.0.5=py312hca03da5_0
+  - readline=8.2=h1a28f6b_0
+  - referencing=0.30.2=py312hca03da5_0
+  - regex=2024.9.11=py312h80987f9_0
+  - reproc=14.2.4=h313beb8_2
+  - reproc-cpp=14.2.4=h313beb8_2
+  - requests=2.32.3=py312hca03da5_1
+  - requests-file=1.5.1=pyhd3eb1b0_0
+  - requests-toolbelt=1.0.0=py312hca03da5_0
+  - responses=0.13.3=pyhd3eb1b0_0
+  - rfc3339-validator=0.1.4=py312hca03da5_0
+  - rfc3986-validator=0.1.1=py312hca03da5_0
+  - rich=13.9.4=py312hca03da5_0
+  - rope=1.12.0=py312hca03da5_0
+  - rpds-py=0.10.6=py312h2aea54e_1
+  - rtree=1.0.1=py312hca03da5_0
+  - ruamel.yaml=0.18.6=py312h80987f9_0
+  - ruamel.yaml.clib=0.2.8=py312h80987f9_0
+  - ruamel_yaml=0.17.21=py312h80987f9_0
+  - s3fs=2024.3.1=py312hca03da5_0
+  - safetensors=0.4.5=py312h7805bc0_1
+  - scikit-image=0.24.0=py312hd77ebd4_0
+  - scikit-learn=1.5.1=py312hd77ebd4_0
+  - scipy=1.13.1=py312ha409365_0
+  - scrapy=2.12.0=py312hca03da5_0
+  - seaborn=0.13.2=py312hca03da5_0
+  - semver=3.0.2=py312hca03da5_0
+  - send2trash=1.8.2=py312hca03da5_0
+  - service_identity=18.1.0=pyhd3eb1b0_1
+  - setuptools=75.1.0=py312hca03da5_0
+  - shellingham=1.5.0=py312hca03da5_0
+  - sip=6.7.12=py312h313beb8_0
+  - six=1.16.0=pyhd3eb1b0_1
+  - smart_open=5.2.1=py312hca03da5_0
+  - smmap=4.0.0=pyhd3eb1b0_0
+  - snappy=1.2.1=h313beb8_0
+  - sniffio=1.3.0=py312hca03da5_0
+  - snowballstemmer=2.2.0=pyhd3eb1b0_0
+  - sortedcontainers=2.4.0=pyhd3eb1b0_0
+  - soupsieve=2.5=py312hca03da5_0
+  - sphinx=7.3.7=py312hca03da5_0
+  - sphinxcontrib-applehelp=1.0.2=pyhd3eb1b0_0
+  - sphinxcontrib-devhelp=1.0.2=pyhd3eb1b0_0
+  - sphinxcontrib-htmlhelp=2.0.0=pyhd3eb1b0_0
+  - sphinxcontrib-jsmath=1.0.1=pyhd3eb1b0_0
+  - sphinxcontrib-qthelp=1.0.3=pyhd3eb1b0_0
+  - sphinxcontrib-serializinghtml=1.1.10=py312hca03da5_0
+  - spyder=6.0.1=py312hca03da5_0
+  - spyder-kernels=3.0.0=py312h989b03a_0
+  - sqlalchemy=2.0.34=py312hbe2cdee_0
+  - sqlite=3.45.3=h80987f9_0
+  - stack_data=0.2.0=pyhd3eb1b0_0
+  - statsmodels=0.14.2=py312ha86b861_0
+  - streamlit=1.40.1=py312hca03da5_0
+  - superqt=0.6.7=py312h989b03a_0
+  - sympy=1.13.2=py312hca03da5_0
+  - tabulate=0.9.0=py312hca03da5_0
+  - tapi=1100.0.11=h8754e6a_1
+  - tbb=2021.8.0=h48ca7d4_0
+  - tblib=1.7.0=pyhd3eb1b0_0
+  - tenacity=9.0.0=py312hca03da5_0
+  - terminado=0.17.1=py312hca03da5_0
+  - text-unidecode=1.3=pyhd3eb1b0_0
+  - textdistance=4.6.3=py312h989b03a_0
+  - threadpoolctl=3.5.0=py312h989b03a_0
+  - three-merge=0.1.1=pyhd3eb1b0_0
+  - tifffile=2023.4.12=py312hca03da5_0
+  - tinycss2=1.2.1=py312hca03da5_0
+  - tk=8.6.14=h6ba3021_0
+  - tldextract=5.1.2=py312hca03da5_0
+  - tokenizers=0.20.1=py312he2d9c3e_1
+  - toml=0.10.2=pyhd3eb1b0_0
+  - tomli=2.0.1=py312hca03da5_1
+  - tomlkit=0.13.2=py312hca03da5_0
+  - toolz=0.12.0=py312hca03da5_0
+  - tornado=6.4.1=py312h80987f9_0
+  - tqdm=4.66.5=py312h989b03a_0
+  - traitlets=5.14.3=py312hca03da5_0
+  - transformers=4.45.2=py312hca03da5_0
+  - truststore=0.8.0=py312hca03da5_0
+  - twisted=23.10.0=py312hca03da5_0
+  - typer=0.9.0=py312hca03da5_0
+  - typing-extensions=4.11.0=py312hca03da5_0
+  - typing_extensions=4.11.0=py312hca03da5_0
+  - tzdata=2024b=h04d1e81_0
+  - uc-micro-py=1.0.1=py312hca03da5_0
+  - ujson=5.10.0=py312h313beb8_0
+  - unicodedata2=15.1.0=py312h80987f9_0
+  - unidecode=1.3.8=py312hca03da5_0
+  - unixodbc=2.3.11=h1a28f6b_0
+  - urllib3=2.2.3=py312hca03da5_0
+  - utf8proc=2.6.1=h80987f9_1
+  - w3lib=2.1.2=py312hca03da5_0
+  - watchdog=4.0.1=py312h80987f9_0
+  - wcwidth=0.2.5=pyhd3eb1b0_0
+  - webencodings=0.5.1=py312hca03da5_2
+  - websocket-client=1.8.0=py312hca03da5_0
+  - werkzeug=3.0.6=py312hca03da5_0
+  - whatthepatch=1.0.2=py312hca03da5_0
+  - wheel=0.44.0=py312hca03da5_0
+  - widgetsnbextension=3.6.6=py312hca03da5_0
+  - wrapt=1.14.1=py312h80987f9_0
+  - wurlitzer=3.0.2=py312hca03da5_0
+  - xarray=2023.6.0=py312hca03da5_0
+  - xlwings=0.32.1=py312hca03da5_0
+  - xxhash=0.8.0=h1a28f6b_3
+  - xyzservices=2022.9.0=py312hca03da5_1
+  - xz=5.4.6=h80987f9_1
+  - yaml=0.2.5=h1a28f6b_0
+  - yaml-cpp=0.8.0=h313beb8_1
+  - yapf=0.40.2=py312hca03da5_0
+  - yarl=1.18.0=py312h80987f9_0
+  - zeromq=4.3.5=h313beb8_0
+  - zfp=1.0.0=h313beb8_0
+  - zict=3.0.0=py312hca03da5_0
+  - zipp=3.21.0=py312hca03da5_0
+  - zlib=1.2.13=h18a0788_1
+  - zlib-ng=2.0.7=h80987f9_0
+  - zope=1.0=py312hca03da5_1
+  - zope.interface=7.1.1=py312h80987f9_0
+  - zstandard=0.23.0=py312h1a4646a_1
+  - zstd=1.5.6=hfb09047_0
+  - pip:
+      - svgpathtools==1.7.0
+      - svgwrite==1.4.3
+prefix: /opt/homebrew/anaconda3

environment.yml

@@ -1,125 +0,0 @@
-name: evilnkode
-channels:
-  - defaults
-dependencies:
-  - anyio=4.6.2=py312hca03da5_0
-  - appnope=0.1.3=py312hca03da5_1001
-  - argon2-cffi=21.3.0=pyhd3eb1b0_0
-  - argon2-cffi-bindings=21.2.0=py312h80987f9_0
-  - asttokens=2.0.5=pyhd3eb1b0_0
-  - async-lru=2.0.4=py312hca03da5_0
-  - attrs=24.2.0=py312hca03da5_0
-  - babel=2.11.0=py312hca03da5_0
-  - beautifulsoup4=4.12.3=py312hca03da5_0
-  - bleach=6.2.0=py312hca03da5_0
-  - brotli-python=1.0.9=py312h313beb8_8
-  - bzip2=1.0.8=h80987f9_6
-  - ca-certificates=2024.12.31=hca03da5_0
-  - certifi=2024.12.14=py312hca03da5_0
-  - cffi=1.17.1=py312h3eb5a62_0
-  - charset-normalizer=3.3.2=pyhd3eb1b0_0
-  - comm=0.2.1=py312hca03da5_0
-  - debugpy=1.6.7=py312h313beb8_0
-  - decorator=5.1.1=pyhd3eb1b0_0
-  - defusedxml=0.7.1=pyhd3eb1b0_0
-  - executing=0.8.3=pyhd3eb1b0_0
-  - expat=2.6.3=h313beb8_0
-  - h11=0.14.0=py312hca03da5_0
-  - httpcore=1.0.2=py312hca03da5_0
-  - httpx=0.27.0=py312hca03da5_0
-  - idna=3.7=py312hca03da5_0
-  - ipykernel=6.29.5=py312hca03da5_0
-  - ipython=8.27.0=py312hca03da5_0
-  - jedi=0.19.1=py312hca03da5_0
-  - jinja2=3.1.4=py312hca03da5_1
-  - json5=0.9.25=py312hca03da5_0
-  - jsonschema=4.23.0=py312hca03da5_0
-  - jsonschema-specifications=2023.7.1=py312hca03da5_0
-  - jupyter-lsp=2.2.0=py312hca03da5_0
-  - jupyter_client=8.6.0=py312hca03da5_0
-  - jupyter_core=5.7.2=py312hca03da5_0
-  - jupyter_events=0.10.0=py312hca03da5_0
-  - jupyter_server=2.14.1=py312hca03da5_0
-  - jupyter_server_terminals=0.4.4=py312hca03da5_1
-  - jupyterlab=4.2.5=py312hca03da5_0
-  - jupyterlab_pygments=0.1.2=py_0
-  - jupyterlab_server=2.27.3=py312hca03da5_0
-  - libcxx=14.0.6=h848a8c0_0
-  - libffi=3.4.4=hca03da5_1
-  - libsodium=1.0.18=h1a28f6b_0
-  - markupsafe=2.1.3=py312h80987f9_0
-  - matplotlib-inline=0.1.6=py312hca03da5_0
-  - mistune=2.0.4=py312hca03da5_0
-  - nbclient=0.8.0=py312hca03da5_0
-  - nbconvert=7.16.4=py312hca03da5_0
-  - nbformat=5.10.4=py312hca03da5_0
-  - ncurses=6.4=h313beb8_0
-  - nest-asyncio=1.6.0=py312hca03da5_0
-  - notebook=7.2.2=py312hca03da5_1
-  - notebook-shim=0.2.3=py312hca03da5_0
-  - openssl=3.0.15=h80987f9_0
-  - overrides=7.4.0=py312hca03da5_0
-  - packaging=24.1=py312hca03da5_0
-  - pandocfilters=1.5.0=pyhd3eb1b0_0
-  - parso=0.8.3=pyhd3eb1b0_0
-  - pexpect=4.8.0=pyhd3eb1b0_3
-  - pip=24.2=py312hca03da5_0
-  - platformdirs=3.10.0=py312hca03da5_0
-  - prometheus_client=0.21.0=py312hca03da5_0
-  - prompt-toolkit=3.0.43=py312hca03da5_0
-  - prompt_toolkit=3.0.43=hd3eb1b0_0
-  - psutil=5.9.0=py312h80987f9_0
-  - ptyprocess=0.7.0=pyhd3eb1b0_2
-  - pure_eval=0.2.2=pyhd3eb1b0_0
-  - pycparser=2.21=pyhd3eb1b0_0
-  - pygments=2.15.1=py312hca03da5_1
-  - pysocks=1.7.1=py312hca03da5_0
-  - python=3.12.7=h99e199e_0
-  - python-dateutil=2.9.0post0=py312hca03da5_2
-  - python-fastjsonschema=2.20.0=py312hca03da5_0
-  - python-json-logger=2.0.7=py312hca03da5_0
-  - pytz=2024.1=py312hca03da5_0
-  - pyyaml=6.0.2=py312h80987f9_0
-  - pyzmq=25.1.2=py312h313beb8_0
-  - readline=8.2=h1a28f6b_0
-  - referencing=0.30.2=py312hca03da5_0
-  - requests=2.32.3=py312hca03da5_1
-  - rfc3339-validator=0.1.4=py312hca03da5_0
-  - rfc3986-validator=0.1.1=py312hca03da5_0
-  - rpds-py=0.10.6=py312h2aea54e_1
-  - send2trash=1.8.2=py312hca03da5_0
-  - setuptools=75.1.0=py312hca03da5_0
-  - six=1.16.0=pyhd3eb1b0_1
-  - sniffio=1.3.0=py312hca03da5_0
-  - soupsieve=2.5=py312hca03da5_0
-  - sqlite=3.45.3=h80987f9_0
-  - stack_data=0.2.0=pyhd3eb1b0_0
-  - terminado=0.17.1=py312hca03da5_0
-  - tinycss2=1.2.1=py312hca03da5_0
-  - tk=8.6.14=h6ba3021_0
-  - tornado=6.4.1=py312h80987f9_0
-  - traitlets=5.14.3=py312hca03da5_0
-  - typing-extensions=4.11.0=py312hca03da5_0
-  - typing_extensions=4.11.0=py312hca03da5_0
-  - tzdata=2024b=h04d1e81_0
-  - urllib3=2.2.3=py312hca03da5_0
-  - wcwidth=0.2.5=pyhd3eb1b0_0
-  - webencodings=0.5.1=py312hca03da5_2
-  - websocket-client=1.8.0=py312hca03da5_0
-  - wheel=0.44.0=py312hca03da5_0
-  - xz=5.4.6=h80987f9_1
-  - yaml=0.2.5=h1a28f6b_0
-  - zeromq=4.3.5=h313beb8_0
-  - zlib=1.2.13=h18a0788_1
-  - pip:
-      - contourpy==1.3.1
-      - cycler==0.12.1
-      - fonttools==4.55.3
-      - iniconfig==2.0.0
-      - kiwisolver==1.4.7
-      - matplotlib==3.9.3
-      - numpy==2.1.3
-      - pillow==11.0.0
-      - pluggy==1.5.0
-      - pyparsing==3.2.0
-      - pytest==8.3.4

src/benchmark.py

@@ -1,84 +1,19 @@
-from src.evilkode import Observation, Evilkode
-from src.keypad import Keypad
-import random
+from tqdm import tqdm
+from src.evilnkode import EvilNKode
 from dataclasses import dataclass
-from statistics import mean, variance
-from enum import Enum
+from src.utils import observations, passcode_generator
+from src.keypad.keypad import BaseKeypad
 from pathlib import Path
+import pickle
+
 
 @dataclass
 class Benchmark:
-    mean: int
-    variance: int
-    runs: list[int]
-
-class ShuffleTypes(Enum):
-    FULL_SHUFFLE = "FULL_SHUFFLE"
-    SPLIT_SHUFFLE = "SPLIT_SHUFFLE"
-
-def observations(number_of_keys, properties_per_key, passcode_len, complexity: int, disparity: int, shuffle_type: ShuffleTypes):
-    k = number_of_keys
-    p = properties_per_key
-    n = passcode_len
-    passcode =  passcode_generator(k, p, n, complexity, disparity)
-    keypad = Keypad.new_keypad(k, p)
-
-    def obs_gen():
-        for _ in range(100):  # finite number of yields
-            yield Observation(
-                keypad=keypad.keypad.copy(),
-                key_selection=keypad.key_entry(target_passcode=passcode)
-            )
-            match shuffle_type:
-                case ShuffleTypes.FULL_SHUFFLE:
-                    keypad.full_shuffle()
-                case ShuffleTypes.SPLIT_SHUFFLE:
-                    keypad.split_shuffle()
-                case _:
-                    raise Exception(f"no shuffle type {shuffle_type}")
-
-    return obs_gen()
-
-def passcode_generator(k: int, p: int, n: int, c: int, d: int) -> list[int]:
-    assert n >= c
-    assert p*k >= c
-
-    assert n >= d
-    assert p >= d
-    passcode_prop = []
-    passcode_set = []
-    valid_choices = {i for i in range(k*p)}
-    repeat_set = n-d
-    repeat_prop = n-c
-    prop_added = set()
-    set_added = set()
-
-    for _ in range(n):
-        prop = random.choice(list(valid_choices))
-        prop_set = prop//p
-        passcode_prop.append(prop)
-        passcode_set.append(prop_set)
-
-        if prop in prop_added:
-            repeat_prop -= 1
-        if prop_set in set_added:
-            repeat_set -= 1
-
-        prop_added.add(prop)
-        set_added.add(prop_set)
-
-        if repeat_prop <= 0:
-            valid_choices -= prop_added
-
-        if repeat_set <= 0:
-            for el in valid_choices.copy():
-                if el // p in set_added:
-                    valid_choices.remove(el)
-
-    return passcode_prop
+    iterations_to_break: list[int]
+    iterations_to_replay: list[int]
 
 
-def shuffle_benchmark(
+def benchmark(
         number_of_keys: int,
         properties_per_key: int,
         passcode_len: int,
@@ -86,84 +21,44 @@ def shuffle_benchmark(
         run_count: int,
         complexity: int,
         disparity: int,
-        shuffle_type: ShuffleTypes,
-        file_path: str = '../output',
+        keypad: BaseKeypad,
+        file_path: Path = '../output',
         overwrite: bool = False
 ) -> Benchmark:
-    file_name = f"{shuffle_type.name.lower()}-{number_of_keys}-{properties_per_key}-{passcode_len}-{max_tries_before_lockout}-{complexity}-{disparity}-{run_count}.txt"
-    full_path = Path(file_path) / file_name
+    shuffle_type = str(type(keypad)).lower().split('.')[-1].replace("'>", "")
+    file_name = f"{shuffle_type}-{number_of_keys}-{properties_per_key}-{passcode_len}-{max_tries_before_lockout}-{complexity}-{disparity}-{run_count}.pkl"
+    full_path = Path(file_path) / "benchmark" / file_name
     if not overwrite and full_path.exists():
-        print(f"file exists {file_path}")
+        print(f"File exists: {full_path}")
+        with open(full_path, "rb") as fp:
+            return pickle.load(fp)
 
-        with open(full_path, "r") as fp:
-            runs = fp.readline()
-            runs = runs.split(',')
-            runs = [int(i) for i in runs]
-            return  Benchmark(
-                mean=mean(runs),
-                variance=variance(runs),
-                runs=runs
-            )
-    runs = []
-    for _ in range(run_count):
-        evilkode = Evilkode(
+    iterations_to_break = []
+    iterations_to_replay = []
+    for _ in tqdm(range(run_count)):
+        passcode = passcode_generator(number_of_keys, properties_per_key, passcode_len, complexity, disparity)
+        evilnkode = EvilNKode(
             observations=observations(
-                number_of_keys=number_of_keys,
-                properties_per_key=properties_per_key,
-                passcode_len=passcode_len,
-                complexity=complexity,
-                disparity=disparity,
-                shuffle_type=shuffle_type,
+                target_passcode=passcode,
+                keypad=keypad,
             ),
             number_of_keys=number_of_keys,
             properties_per_key=properties_per_key,
             passcode_len=passcode_len,
             max_tries_before_lockout=max_tries_before_lockout,
         )
-        evilout = evilkode.run()
-        runs.append(evilout.iterations)
+        evilout = evilnkode.run()
+        iterations_to_break.append(evilout.iterations_to_break)
+        iterations_to_replay.append(evilout.iterations_to_replay)
 
-    full_path.parent.mkdir(parents=True, exist_ok=True)
-    with open(full_path, "w") as fp:
-       fp.write(",".join([str(i) for i in runs])),
-
-    return Benchmark(
-        mean=mean(runs),
-        variance=variance(runs),
-        runs=runs
+    benchmark_result = Benchmark(
+        iterations_to_break=iterations_to_break,
+        iterations_to_replay=iterations_to_replay
     )
 
+    if file_path:
+        full_path.parent.mkdir(parents=True, exist_ok=True)
+        with open(full_path, "wb") as fp:
+            pickle.dump(benchmark_result, fp)
 
-def full_shuffle_benchmark(
-        number_of_keys: int,
-        properties_per_key: int,
-        passcode_len: int,
-        max_tries_before_lockout: int,
-        run_count: int,
-        complexity: int,
-        disparity: int,
-) -> Benchmark:
-    runs = []
-    for _ in range(run_count):
-        evilkode = Evilkode(
-            observations=observations(
-                number_of_keys=number_of_keys,
-                properties_per_key=properties_per_key,
-                passcode_len=passcode_len,
-                complexity=complexity,
-                disparity=disparity,
-                shuffle_type=ShuffleTypes.FULL_SHUFFLE,
-            ),
-            number_of_keys=number_of_keys,
-            properties_per_key=properties_per_key,
-            passcode_len=passcode_len,
-            max_tries_before_lockout=max_tries_before_lockout,
-        )
-        evilout = evilkode.run()
-        runs.append(evilout.iterations)
-
-    return Benchmark(
-        mean=mean(runs),
-        variance=variance(runs),
-        runs=runs
-    )
+    return benchmark_result

src/evilnkode.py

@@ -12,19 +12,19 @@ class Observation:
     def property_list(self) -> list[set[int]]:
         return [set(self.keypad[idx]) for idx in self.key_selection]
 
+    @property
+    def flat_keypad(self) -> list[int]:
+        return [num for row in self.keypad for num in row]
+
 
 @dataclass
 class EvilOutput:
-    possible_nkodes: list[list[int]]
-    iterations: int
-
-    @property
-    def number_of_possible_nkode(self):
-        return math.prod([len(el) for el in self.possible_nkodes])
+    iterations_to_break: int
+    iterations_to_replay: int
 
 
 @dataclass
-class Evilkode:
+class EvilNKode:
     observations: Iterator[Observation]
     passcode_len: int
     number_of_keys: int
@@ -32,17 +32,31 @@ class Evilkode:
     max_tries_before_lockout: int = 5
     possible_nkode = None
 
-
     def initialize(self):
         possible_values = set(range(self.number_of_keys * self.properties_per_key))
         self.possible_nkode = [possible_values.copy() for _ in range(self.passcode_len)]
 
     def run(self) -> EvilOutput:
         self.initialize()
+        iterations_to_replay = None
         for idx, obs in enumerate(self.observations):
+            if iterations_to_replay is None:
+                replay_possibilities = self.replay_attack(obs)
+                if replay_possibilities <= self.max_tries_before_lockout:
+                    iterations_to_replay = idx + 1
             if math.prod([len(el) for el in self.possible_nkode]) <= self.max_tries_before_lockout:
-                return EvilOutput(possible_nkodes=[list(el) for el in self.possible_nkode], iterations=idx+1)
+                assert iterations_to_replay <= idx + 1
+                return EvilOutput(
+                    # possible_nkodes=[list(el) for el in self.possible_nkode],
+                    iterations_to_break=idx + 1,
+                    iterations_to_replay=iterations_to_replay
+                )
             for jdx, props in enumerate(obs.property_list):
                 self.possible_nkode[jdx] = props.intersection(self.possible_nkode[jdx])
-
         raise Exception("error in Evilkode, observations stopped yielding")
+
+    def replay_attack(self, obs: Observation) -> int:
+        possible_combos = 1
+        for el in self.possible_nkode:
+            possible_combos *= len({obs.flat_keypad.index(el2) // self.properties_per_key for el2 in el})
+        return possible_combos

src/keypad.py

@@ -1,83 +0,0 @@
-from dataclasses import dataclass
-
-import numpy as np
-
-@dataclass
-class Keypad:
-    keypad: np.ndarray
-    k: int # number of keys
-    p: int  # properties per key
-    keypad_cache: list #
-    max_cache_size: int = 100
-
-    @staticmethod
-    def new_keypad(k: int, p: int):
-        total_properties = k * p
-        array = np.arange(total_properties)
-        # Reshape into a 3x4 matrix
-        keypad = array.reshape(k, p)
-        set_view = keypad.T
-
-        for set_idx in set_view:
-            np.random.shuffle(set_idx)
-
-        return Keypad(keypad=set_view.T, k=k, p=p, keypad_cache=[])
-
-    def split_shuffle(self):
-        """
-        This is a modified split shuffle.
-        It doesn't shuffle the keys only the properties in the keys.
-        Shuffling the keys makes it hard for people to guess an nKode not a machine.
-        This split shuffle includes a cache to prevent the same configuration from being used.
-        This cache is not in any other implementation.
-        Testing suggests it's not necessary.
-        Getting the same keypad twice over 100 shuffles is very unlikely.
-        """
-        shuffled_sets = self._shuffle()
-        # Sort the shuffled sets by the first column
-        sorted_set = shuffled_sets[np.argsort(shuffled_sets[:, 0])]
-        while str(sorted_set) in self.keypad_cache:
-            # continue shuffling until we get a unique configuration
-            shuffled_sets = self._shuffle()
-            sorted_set = shuffled_sets[np.argsort(shuffled_sets[:, 0])]
-
-        self.keypad_cache.append(str(sorted_set))
-        self.keypad_cache = self.keypad_cache[:self.max_cache_size]
-        self.keypad = shuffled_sets
-
-
-    def _shuffle(self) -> np.ndarray:
-        column_permutation = np.random.permutation(self.p)
-        column_subset = column_permutation[:self.p // 2]
-        perm_indices = np.random.permutation(self.k)
-        shuffled_sets = self.keypad.copy()
-        shuffled_sets[:, column_subset] = shuffled_sets[perm_indices, :][:, column_subset]
-        return shuffled_sets
-
-    def full_shuffle(self):
-        shuffled_matrix = np.array([np.random.permutation(row) for row in self.keypad.T])
-        self.keypad = shuffled_matrix.T
-
-    def key_entry(self, target_passcode: list[int]) -> list[int]:
-        """
-        Given target_values, return the row indices they are in.
-        Assert that each element is >= 0 and < self.k * self.p.
-        """
-        # Convert the list to a NumPy array for vectorized checks
-        vals = np.array(target_passcode)
-
-        # Validate that each value is within the valid range
-        if np.any((vals < 0) | (vals >= self.k * self.p)):
-            raise ValueError("One or more values are out of the valid range.")
-
-        # Flatten the keypad to a 1D array
-        flat = self.keypad.flatten()
-
-        # Create an inverse mapping from value -> row index
-        inv_index = np.empty(self.k * self.p, dtype=int)
-        # Each value v is at position i in 'flat', so row = i // p
-        for i, v in enumerate(flat):
-            inv_index[v] = i // self.p
-
-        # Use the inverse mapping to get row indices for all target values
-        return inv_index[vals].tolist()

src/keypad/keypad.py

@@ -0,0 +1,123 @@
+from dataclasses import dataclass
+import numpy as np
+from src.keypad.tower_shuffle import TowerShuffle
+from abc import ABC, abstractmethod
+from typing import Self
+
+
+class BaseKeypad(ABC):
+    keypad: np.ndarray
+    k: int  # number of keys
+    p: int  # properties per key
+
+    @classmethod
+    def _build_keypad(cls, k: int, p: int) -> np.ndarray:
+        rng = np.random.default_rng()
+        total = k * p
+        array = np.arange(total)
+        keypad = array.reshape(k, p)
+        set_view = keypad.T.copy()
+        for set_idx in set_view:
+            rng.shuffle(set_idx)
+        return set_view.T
+
+    @classmethod
+    @abstractmethod
+    def new_keypad(cls, k: int, p: int) -> Self:
+        raise NotImplementedError
+
+    def key_entry(self, target_passcode: list[int]) -> list[int]:
+        vals = np.array(target_passcode)
+        if np.any((vals < 0) | (vals >= self.k * self.p)):
+            raise ValueError("One or more values are out of the valid range.")
+        flat = self.keypad.flatten()
+        inv_index = np.empty(self.k * self.p, dtype=int)
+        for i, v in enumerate(flat):
+            inv_index[v] = i // self.p
+        return inv_index[vals].tolist()
+
+    @abstractmethod
+    def shuffle(self):
+        pass
+
+    def keypad_mat(self) -> list[list[int]]:
+        return [el.tolist() for el in self.keypad]
+
+
+@dataclass
+class SlidingTowerShuffleKeypad(BaseKeypad):
+    keypad: np.ndarray
+    k: int  # number of keys
+    p: int  # properties per key
+    tower_shuffle: TowerShuffle
+
+    @classmethod
+    def new_keypad(cls, k: int, p: int) -> Self:
+        kp = cls._build_keypad(k, p)
+        return cls(keypad=kp, k=k, p=p, tower_shuffle=TowerShuffle.new(p))
+
+    def shuffle(self):
+        selected_positions = self.tower_shuffle.left_tower.tolist()
+        shift = np.random.randint(1, self.k)  # random int in [1, k-1]
+        new_key_idxs = np.roll(np.arange(self.k), shift)
+        shuffled_sets = self.keypad.copy()
+        shuffled_sets[:, selected_positions] = shuffled_sets[new_key_idxs, :][:, selected_positions]
+        self.keypad = shuffled_sets
+        self.tower_shuffle.shuffle()
+
+
+@dataclass
+class RandomShuffleKeypad(BaseKeypad):
+    keypad: np.ndarray
+    k: int  # number of keys
+    p: int  # properties per key
+
+    @classmethod
+    def new_keypad(cls, k: int, p: int) -> Self:
+        kp = cls._build_keypad(k, p)
+        return cls(keypad=kp, k=k, p=p)
+
+    def shuffle(self):
+        shuffled_matrix = np.array([np.random.permutation(row) for row in self.keypad.T])
+        self.keypad = shuffled_matrix.T
+
+
+@dataclass
+class RandomSplitShuffleKeypad(BaseKeypad):
+    keypad: np.ndarray
+    k: int  # number of keys
+    p: int  # properties per key
+
+    @classmethod
+    def new_keypad(cls, k: int, p: int) -> Self:
+        kp = cls._build_keypad(k, p)
+        return cls(keypad=kp, k=k, p=p)
+
+    def shuffle(self):
+        column_permutation = np.random.permutation(self.p)
+        column_subset = column_permutation[:self.p // 2]
+        new_key_idxs = np.random.permutation(self.k)
+        shuffled_sets = self.keypad.copy()
+        shuffled_sets[:, column_subset] = shuffled_sets[new_key_idxs, :][:, column_subset]
+        self.keypad = shuffled_sets
+
+
+@dataclass
+class SlidingSplitShuffleKeypad(BaseKeypad):
+    keypad: np.ndarray
+    k: int  # number of keys
+    p: int  # properties per key
+
+    @classmethod
+    def new_keypad(cls, k: int, p: int) -> Self:
+        kp = cls._build_keypad(k, p)
+        return cls(keypad=kp, k=k, p=p)
+
+    def shuffle(self):
+        selected_positions = np.random.permutation(self.p)
+        column_subset = selected_positions[:self.p // 2]
+        shift = np.random.randint(1, self.k)
+        new_key_idxs = np.roll(np.arange(self.k), shift)
+        shuffled_sets = self.keypad.copy()
+        shuffled_sets[:, column_subset] = shuffled_sets[new_key_idxs, :][:, column_subset]
+        self.keypad = shuffled_sets

src/keypad/tower_shuffle.py

@@ -0,0 +1,80 @@
+from dataclasses import dataclass
+import numpy as np
+
+@dataclass
+class Tower:
+    floors: list[np.ndarray]
+
+    def split_tower(self) -> tuple[np.ndarray, np.ndarray]:
+        discard = np.array([], dtype=int)
+        keep = np.array([], dtype=int)
+        balance = self.balance()
+        for idx, floor in enumerate(self.floors):
+            div = len(floor)//2 + balance[idx]
+            floor_shuffle = np.random.permutation(len(floor))
+            keep = np.concatenate((keep, floor[floor_shuffle[:div]]))
+            discard = np.concatenate((discard, floor[floor_shuffle[div:]]))
+        diff = len(discard) - len(keep)
+        assert 0 <= diff <= 1
+        return keep, discard
+
+    def balance(self) -> list[int]:
+        odd_floors = np.array([idx for idx, el in enumerate(self.floors) if len(el) & 1])
+        balance = np.zeros(len(self.floors), dtype=int)
+        if len(odd_floors) == 0:
+            return balance.tolist()
+        shuffle = np.random.permutation(len(odd_floors))[:len(odd_floors) // 2]
+        odd_floors = odd_floors[shuffle]
+        balance[odd_floors] = 1
+        return balance.tolist()
+
+
+    def update_tower(self, keep: np.ndarray, other_discard: np.ndarray):
+        new_floors = []
+        for floor in self.floors:
+            new_floor = np.intersect1d(floor, keep)
+            if len(new_floor):
+                new_floors.append(new_floor)
+        self.floors = new_floors
+        self.floors.insert(0, other_discard)
+
+    def __str__(self):
+        str_val = ""
+        floor_numb = [i for i in reversed(range(len(self.floors)))]
+        for idx, val in enumerate(reversed(self.floors)):
+            str_val += f"Floor {floor_numb[idx]}: {val.tolist()}\n"
+        return str_val
+
+    def tolist(self) -> list[int]:
+        tower = []
+        for floor in self.floors:
+            tower.extend(floor.tolist())
+        return tower
+
+@dataclass
+class TowerShuffle:
+    total_positions: int
+    left_tower: Tower
+    right_tower: Tower
+
+    @classmethod
+    def new(cls, total_pos:int):
+        assert total_pos >= 3
+        rand_pos = np.random.permutation(total_pos)
+        return TowerShuffle(
+            total_positions=total_pos,
+            left_tower=Tower(floors=[rand_pos[:total_pos//2]]),
+            right_tower=Tower(floors=[rand_pos[total_pos//2:]]),
+        )
+
+    def shuffle(self):
+        left_keep, left_discard = self.left_tower.split_tower()
+        right_keep, right_discard = self.right_tower.split_tower()
+        self.left_tower.update_tower(left_keep, right_discard)
+        self.right_tower.update_tower(right_keep, left_discard)
+
+    def __str__(self):
+        return f"""Left Tower:
+{self.left_tower}
+Right Tower:
+{self.right_tower}"""

src/utils.py

@@ -1,7 +1,66 @@
+import random
 from math import factorial, comb
 
+from src.evilnkode import Observation
+from src.keypad.keypad import BaseKeypad
+from typing import Iterator
+
+
 def total_valid_nkode_states(k: int, p: int) -> int:
-   return factorial(k) ** (p-1)
+    return factorial(k) ** (p - 1)
+
 
 def total_shuffle_states(k: int, p: int) -> int:
-    return comb((p-1), (p-1) // 2) * factorial(k)
+    return comb((p - 1), (p - 1) // 2) * factorial(k)
+
+
+def observations(target_passcode: list[int], keypad: BaseKeypad, number_of_observations: int = 100) -> Iterator[
+    Observation]:
+    def obs():
+        for _ in range(number_of_observations):
+            yield Observation(
+                keypad=keypad.keypad_mat(),
+                key_selection=keypad.key_entry(target_passcode=target_passcode)
+            )
+            keypad.shuffle()
+
+    return obs()
+
+
+def passcode_generator(k: int, p: int, n: int, c: int, d: int) -> list[int]:
+    assert n >= c
+    assert p * k >= c
+
+    assert n >= d
+    assert p >= d
+    passcode_prop = []
+    passcode_set = []
+    valid_choices = {i for i in range(k * p)}
+    repeat_set = n - d
+    repeat_prop = n - c
+    prop_added = set()
+    set_added = set()
+
+    for _ in range(n):
+        prop = random.choice(list(valid_choices))
+        prop_set = prop // p
+        passcode_prop.append(prop)
+        passcode_set.append(prop_set)
+
+        if prop in prop_added:
+            repeat_prop -= 1
+        if prop_set in set_added:
+            repeat_set -= 1
+
+        prop_added.add(prop)
+        set_added.add(prop_set)
+
+        if repeat_prop <= 0:
+            valid_choices -= prop_added
+
+        if repeat_set <= 0:
+            for el in valid_choices.copy():
+                if el // p in set_added:
+                    valid_choices.remove(el)
+
+    return passcode_prop

tests/test_benchmark.py

@@ -1,6 +1,14 @@
-from src.benchmark import passcode_generator
+from src.utils import passcode_generator
+from src.keypad.keypad import (
+    RandomShuffleKeypad,
+    RandomSplitShuffleKeypad,
+    SlidingTowerShuffleKeypad,
+    SlidingSplitShuffleKeypad
+)
+from src.benchmark import benchmark
 import pytest
 
+
 @pytest.mark.parametrize(
     "k, p, n, c, d, runs",
     [
@@ -10,6 +18,29 @@ import pytest
 def test_passcode_generator(k, p, n, c, d, runs):
     for _ in range(runs):
         passcode = passcode_generator(k=k, p=p, n=n, c=c, d=d)
-        passcode_sets = [el//p for el in passcode]
-        assert  c <= len(set(passcode))
+        passcode_sets = [el // p for el in passcode]
+        assert c <= len(set(passcode))
         assert d <= len(set(passcode_sets))
+
+
+@pytest.mark.parametrize(
+    "number_of_keys,properties_per_key,passcode_len,max_tries_before_lockout,complexity,disparity,run_count,keypad",
+    [
+        (6, 8, 4, 5, 4, 4, 100, RandomShuffleKeypad),
+        (6, 8, 4, 5, 4, 4, 100, RandomSplitShuffleKeypad),
+        (6, 8, 4, 5, 4, 4, 100, SlidingSplitShuffleKeypad),
+        (6, 8, 4, 5, 4, 4, 100, SlidingTowerShuffleKeypad),
+    ]
+)
+def test_benchmark(number_of_keys, properties_per_key, passcode_len, max_tries_before_lockout, complexity, disparity,
+                   run_count, keypad):
+    benchmark(
+        number_of_keys=number_of_keys,
+        properties_per_key=properties_per_key,
+        passcode_len=passcode_len,
+        max_tries_before_lockout=max_tries_before_lockout,
+        run_count=run_count,
+        complexity=complexity,
+        disparity=disparity,
+        keypad=keypad.new_keypad(number_of_keys, properties_per_key)
+    )

tests/test_evilkode.py

@@ -1,45 +1,34 @@
 import random
 import pytest
 
-from src.evilkode import Evilkode, Observation
-from src.keypad import Keypad
+from src.evilnkode import EvilNKode
+from src.keypad.keypad import (
+    RandomShuffleKeypad,
+)
+from src.utils import observations
 
 
 @pytest.fixture
-def observations(number_of_keys, properties_per_key, passcode_len):
-    k = number_of_keys
-    p = properties_per_key
-    n = passcode_len
-    nkode = [random.randint(0, k*p-1) for _ in range(n)]
-    keypad = Keypad.new_keypad(k, p)
-
-    def obs_gen():
-        for _ in range(100):  # finite number of yields
-            yield Observation(
-                keypad=keypad.keypad.copy(),
-                key_selection=keypad.key_entry(target_passcode=nkode)
-            )
-            keypad.split_shuffle()
-
-    return obs_gen()
-
+def passcode(number_of_keys, properties_per_key, passcode_len):
+    return [random.randint(0, number_of_keys * properties_per_key - 1) for _ in range(passcode_len)]
 
 
 @pytest.mark.parametrize(
     "number_of_keys, properties_per_key, passcode_len",
     [
-        (5, 3, 4),  # Test case 1
+        (5, 4, 4),  # Test case 1
         (10, 5, 6),  # Test case 2
-        (8, 4, 5),   # Test case 3
+        (8, 4, 5),  # Test case 3
     ]
 )
-def test_evilkode(number_of_keys, properties_per_key, passcode_len, observations):
-    evilkode = Evilkode(
-        observations=observations,
+def test_evilkode(number_of_keys, properties_per_key, passcode_len, passcode):
+    keypad = RandomShuffleKeypad.new_keypad(number_of_keys, properties_per_key)
+    obs = observations(passcode, keypad)
+    evilkode = EvilNKode(
+        observations=obs,
         number_of_keys=number_of_keys,
         properties_per_key=properties_per_key,
         passcode_len=passcode_len,
     )
-
     evilout = evilkode.run()
-    assert evilout.iterations > 1
+    assert evilout.iterations_to_break > 1

tests/test_keypad.py

@@ -1,31 +1,34 @@
+import pytest
 import numpy as np
+from src.keypad.keypad import (
+    RandomSplitShuffleKeypad,
+    RandomShuffleKeypad,
+    SlidingSplitShuffleKeypad,
+    SlidingTowerShuffleKeypad,
+)
 
-from src.keypad import Keypad
 
-def test_keypad():
-    keypad = Keypad(
+def test_key_entry():
+    keypad = RandomShuffleKeypad(
         keypad=np.array([
             [8, 9, 10, 11],
             [0, 5, 2, 3],
-            [4, 1, 6,7]
-        ]), k= 3, p=4, keypad_cache=[])
+            [4, 1, 6, 7]
+        ]), k=3, p=4)
+    assert keypad.key_entry([8, 5, 6, 11]) == [0, 1, 2, 0]
 
-    assert keypad.key_entry([8, 5, 6, 11]) == [0,1,2,0]
 
-def test_split_shuffle():
-    p = 4  # properties_per_key
-    k = 3  # number_of_keys
-    keypad = Keypad.new_keypad(k, p)
+@pytest.mark.parametrize(
+    "keypad_type, number_of_keys, properties_per_key",
+    [
+        (RandomShuffleKeypad, 3, 4),
+        (RandomSplitShuffleKeypad, 3, 4),
+        (SlidingTowerShuffleKeypad, 3, 4),
+        (SlidingSplitShuffleKeypad, 3, 4),
+    ]
+)
+def test_keypad_shuffle(keypad_type, number_of_keys, properties_per_key):
+    keypad = keypad_type.new_keypad(number_of_keys, properties_per_key)
     print(keypad.keypad)
-    keypad.split_shuffle()
+    keypad.shuffle()
     print(keypad.keypad)
-
-
-def test_full_shuffle():
-    p = 4  # properties_per_key
-    k = 3  # number_of_keys
-    keypad = Keypad.new_keypad(k, p)
-    print(keypad.keypad)
-    keypad.full_shuffle()
-    print(keypad.keypad)
-

tests/test_tower_shuffle.py

@@ -0,0 +1,8 @@
+from src.keypad.tower_shuffle import TowerShuffle
+
+def test_tower_shuffle():
+    tower = TowerShuffle.new(9)
+    print(tower)
+    for _ in range(100):
+        tower.shuffle()
+        print(tower)