implement cli for benchmarking and evilnkode

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/evilnkode.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.