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# 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 - **Conda**: Ensure you have Conda installed (Miniconda or Anaconda). Download from [conda.io](https://conda.io).
- Install anaconda (or your preferred tool for environment management)
### Using conda ## 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 ```bash
conda env create -f environment.yml conda env create -f environment.yaml
conda activate pynkode ```
- This will install all dependencies specified in `environment.yaml`.
## Activating the Environment
To activate the `evilnkode` environment, run:
```bash
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 ```bash
# Ensure your environment is activated python -m cli.visualnkode
# For conda: conda activate pynkode
# For pyenv: (should be automatic if in the directory)
# Start the Jupyter Notebook server
jupyter notebook
``` ```
### 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 ```bash
# Ensure your environment is activated python -m cli.visualnkode -help
# Start JupyterLab
jupyter lab
``` ```
## Notebooks ### Running `cli.benchmark_histogram`
- [evilnkode](notebooks/evilkode.ipynb)
To execute the `benchmark_histogram` CLI script:
```bash
python -m cli.benchmark_histogram
```
- 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.

0
cli/__init__.py Normal file
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115
cli/benchmark_histogram.py Normal file
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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()

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@@ -1,46 +1,41 @@
import json import json
from typing import Iterable
from dataclasses import dataclass, asdict from dataclasses import dataclass, asdict
from evilkode import Observation from src.evilnkode import Observation
from utils import observations, passcode_generator, ShuffleTypes from src.utils import observations, passcode_generator
from pathlib import Path from pathlib import Path
from PIL import Image, ImageDraw, ImageFont from PIL import Image, ImageDraw, ImageFont
from typing import Iterable from src.keypad.keypad import (
BaseKeypad,
SlidingSplitShuffleKeypad,
SlidingTowerShuffleKeypad,
RandomShuffleKeypad,
RandomSplitShuffleKeypad,
)
import argparse
# Project root = parent of *this* file's directory
PROJECT_ROOT = Path(__file__).resolve().parent.parent
BASE_DIR = PROJECT_ROOT / "example"
PNG_DIR = PROJECT_ROOT / "example" / "obs_png"
@dataclass @dataclass
class ObservationSequence: class ObservationSequence:
target_passcode: list[int] target_passcode: list[int]
observations: list[Observation] observations: list[Observation]
def new_observation_sequence( def new_observation_sequence(
number_of_keys: int, keypad: BaseKeypad,
properties_per_key: int,
passcode_len: int, passcode_len: int,
complexity: int, complexity: int,
disparity: int, disparity: int,
numb_runs: int, numb_runs: int,
shuffle_type: ShuffleTypes
) -> ObservationSequence: ) -> ObservationSequence:
passcode = passcode_generator(number_of_keys, properties_per_key, passcode_len, complexity, disparity) passcode = passcode_generator(keypad.k, keypad.p, passcode_len, complexity, disparity)
obs_seq = ObservationSequence(target_passcode=passcode, observations=[])
obs_gen = observations( obs_gen = observations(
keypad=keypad,
target_passcode=passcode, target_passcode=passcode,
number_of_keys=number_of_keys,
properties_per_key=properties_per_key,
min_complexity=complexity,
min_disparity=disparity,
shuffle_type=shuffle_type,
number_of_observations=numb_runs, number_of_observations=numb_runs,
) )
for obs in obs_gen: return ObservationSequence(target_passcode=passcode, observations=[obs for obs in obs_gen])
obs.keypad = obs.keypad.tolist()
obs_seq.observations.append(obs)
return obs_seq
def _next_json_filename(base_dir: Path) -> Path: def _next_json_filename(base_dir: Path) -> Path:
"""Find the next available observation_X.json file in base_dir.""" """Find the next available observation_X.json file in base_dir."""
@@ -51,22 +46,15 @@ def _next_json_filename(base_dir: Path) -> Path:
return candidate return candidate
counter += 1 counter += 1
def save_observation_sequence_to_json(seq: ObservationSequence, shuffle_type: ShuffleTypes, filename: Path | None = None) -> None:
""" def save_observation_sequence_to_json(seq: ObservationSequence,
Save ObservationSequence to JSON. filename: Path) -> None:
- If filename is None, put it under PROJECT_ROOT/output/obs_json/ as observation_{n}.json
- Creates directory if needed
"""
if filename is None:
base_dir = BASE_DIR / shuffle_type.name / "obs_json"
base_dir.mkdir(parents=True, exist_ok=True)
filename = _next_json_filename(base_dir)
else:
filename.parent.mkdir(parents=True, exist_ok=True) filename.parent.mkdir(parents=True, exist_ok=True)
with filename.open("w", encoding="utf-8") as f: with filename.open("w", encoding="utf-8") as f:
json.dump(asdict(seq), f, indent=4) json.dump(asdict(seq), f, indent=4)
# ---------- Helpers ---------- # ---------- Helpers ----------
def _load_font(preferred: str, size: int) -> ImageFont.FreeTypeFont | ImageFont.ImageFont: def _load_font(preferred: str, size: int) -> ImageFont.FreeTypeFont | ImageFont.ImageFont:
"""Try a preferred TTF, fall back to common monospace, then PIL default.""" """Try a preferred TTF, fall back to common monospace, then PIL default."""
@@ -84,14 +72,17 @@ def _load_font(preferred: str, size: int) -> ImageFont.FreeTypeFont | ImageFont.
continue continue
return ImageFont.load_default() return ImageFont.load_default()
def _text_size(draw: ImageDraw.ImageDraw, text: str, font: ImageFont.ImageFont) -> tuple[int, int]: def _text_size(draw: ImageDraw.ImageDraw, text: str, font: ImageFont.ImageFont) -> tuple[int, int]:
"""Get (w, h) using font bbox for accurate layout.""" """Get (w, h) using font bbox for accurate layout."""
left, top, right, bottom = draw.textbbox((0, 0), text, font=font) left, top, right, bottom = draw.textbbox((0, 0), text, font=font)
return right - left, bottom - top return int(right - left), int(bottom - top)
def _join_nums(nums: Iterable[int]) -> str: def _join_nums(nums: Iterable[int]) -> str:
return " ".join(str(n) for n in nums) return " ".join(str(n) for n in nums)
def _next_available_path(path: Path) -> Path: def _next_available_path(path: Path) -> Path:
"""If path exists, append _1, _2, ...""" """If path exists, append _1, _2, ..."""
if not path.exists(): if not path.exists():
@@ -104,6 +95,7 @@ def _next_available_path(path: Path) -> Path:
return candidate return candidate
i += 1 i += 1
# ---------- Core rendering ---------- # ---------- Core rendering ----------
def render_observation_to_png( def render_observation_to_png(
target_passcode: list[int], target_passcode: list[int],
@@ -214,6 +206,7 @@ def render_observation_to_png(
img.save(out_path, format="PNG") img.save(out_path, format="PNG")
def _next_run_dir(base_dir: Path) -> Path: def _next_run_dir(base_dir: Path) -> Path:
"""Find the next available run directory under base_dir (run_001, run_002, ...).""" """Find the next available run directory under base_dir (run_001, run_002, ...)."""
counter = 1 counter = 1
@@ -224,22 +217,37 @@ def _next_run_dir(base_dir: Path) -> Path:
return run_dir return run_dir
counter += 1 counter += 1
def render_sequence_to_pngs(seq: ObservationSequence, shuffle_type: ShuffleTypes, out_dir: Path | None = None) -> None:
"""
Render each observation to its own PNG inside a fresh run directory.
Default: PROJECT_ROOT/output/obs_png/run_XXX/observation_001.png
"""
base_dir = BASE_DIR / shuffle_type.name / "obs_png" if out_dir is None else out_dir
base_dir.mkdir(parents=True, exist_ok=True)
# Create a fresh run dir
run_dir = _next_run_dir(base_dir)
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): for i, obs in enumerate(seq.observations, start=1):
filename = run_dir / f"observation_{i:03d}.png" filename = run_dir / f"observation_{i:03d}.png"
render_observation_to_png(seq.target_passcode, obs, filename) render_observation_to_png(seq.target_passcode, obs, filename)
if __name__ == "__main__": if __name__ == "__main__":
shuffle_type = ShuffleTypes.TOWER_SHUFFLE shuffle_classes = {
obs_seq = new_observation_sequence(6, 9,4,0,0 ,numb_runs=50, shuffle_type=shuffle_type) 'RandomSplitShuffle': RandomSplitShuffleKeypad,
save_observation_sequence_to_json(obs_seq, shuffle_type) 'RandomShuffle': RandomShuffleKeypad,
render_sequence_to_pngs(obs_seq, shuffle_type) '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")

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environment.yaml Normal file
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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
- beautifulsoup4=4.12.3=py312hca03da5_0
- binaryornot=0.4.4=pyhd3eb1b0_1
- black=24.8.0=py312hca03da5_0
- blas=1.0=openblas
- bleach=6.2.0=py312hca03da5_0
- blinker=1.6.2=py312hca03da5_0
- blosc=1.21.3=h313beb8_0
- bokeh=3.6.0=py312hca03da5_0
- boltons=23.0.0=py312hca03da5_0
- boost-cpp=1.82.0=h48ca7d4_2
- botocore=1.34.69=py312hca03da5_0
- bottleneck=1.4.2=py312ha86b861_0
- brotli=1.0.9=h80987f9_8
- brotli-bin=1.0.9=h80987f9_8
- brotli-python=1.0.9=py312h313beb8_8
- brunsli=0.1=hc377ac9_1
- bzip2=1.0.8=h80987f9_6
- c-ares=1.19.1=h80987f9_0
- c-blosc2=2.12.0=h7df6c2f_0
- ca-certificates=2024.11.26=hca03da5_0
- cachetools=5.3.3=py312hca03da5_0
- cctools=949.0.1=hc179dcd_25
- cctools_osx-arm64=949.0.1=h332cad3_25
- certifi=2024.8.30=py312hca03da5_0
- cffi=1.17.1=py312h3eb5a62_0
- cfitsio=3.470=h7f6438f_7
- chardet=4.0.0=py312hca03da5_1003
- charls=2.2.0=hc377ac9_0
- charset-normalizer=3.3.2=pyhd3eb1b0_0
- click=8.1.7=py312hca03da5_0
- cloudpickle=3.0.0=py312hca03da5_0
- colorama=0.4.6=py312hca03da5_0
- colorcet=3.1.0=py312hca03da5_0
- comm=0.2.1=py312hca03da5_0
- conda=24.11.0=py312hca03da5_0
- conda-build=24.11.2=py312hca03da5_0
- conda-content-trust=0.2.0=py312hca03da5_1
- conda-index=0.5.0=py312hca03da5_0
- conda-libmamba-solver=24.9.0=pyhd3eb1b0_0
- conda-pack=0.6.0=pyhd3eb1b0_0
- conda-package-handling=2.4.0=py312hca03da5_0
- conda-package-streaming=0.11.0=py312hca03da5_0
- conda-repo-cli=1.0.114=py312hca03da5_0
- conda-token=0.4.0=pyhd3eb1b0_0
- conda-verify=3.4.2=py_1
- constantly=23.10.4=py312hca03da5_0
- contourpy=1.3.1=py312h48ca7d4_0
- cookiecutter=2.6.0=py312hca03da5_0
- cryptography=43.0.3=py312h8026fc7_1
- cssselect=1.2.0=py312hca03da5_0
- curl=8.9.1=h02f6b3c_0
- cycler=0.11.0=pyhd3eb1b0_0
- cyrus-sasl=2.1.28=h9131b1a_1
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- tqdm=4.66.5=py312h989b03a_0
- traitlets=5.14.3=py312hca03da5_0
- transformers=4.45.2=py312hca03da5_0
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- tzdata=2024b=h04d1e81_0
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- watchdog=4.0.1=py312h80987f9_0
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- 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
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- 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:
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- svgwrite==1.4.3
prefix: /opt/homebrew/anaconda3

View File

@@ -1,125 +0,0 @@
name: evilnkode
channels:
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dependencies:
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- 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
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- defusedxml=0.7.1=pyhd3eb1b0_0
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- python-dateutil=2.9.0post0=py312hca03da5_2
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- pyzmq=25.1.2=py312h313beb8_0
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- 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
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- terminado=0.17.1=py312hca03da5_0
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- 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
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- zlib=1.2.13=h18a0788_1
- pip:
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- fonttools==4.55.3
- iniconfig==2.0.0
- kiwisolver==1.4.7
- matplotlib==3.9.3
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- pytest==8.3.4

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