Rename PatternLab to Pattern Analyzer

All references to PatternLab have been updated to Pattern Analyzer across code, documentation, and configuration files. Source code directories and modules were renamed, and related test, CI, and usage instructions were updated to reflect the new project name. Benchmark result files and report artifacts were added for statistical test validation.

Author: EdgeTypE

.github/workflows/ci.yml

@@ -40,7 +40,7 @@ jobs:
         run: |
           ruff check .
           black --check .
-          mypy patternlab || true
+          mypy patternanalyzer || true
 
       - name: Run tests with coverage
         run: |

.gitignore

@@ -184,3 +184,4 @@ pattern.txt
 report.json
 report.html
 report.json
+/bench_results

LICENSE

@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2024 PatternLab Team
+Copyright (c) 2025 EdgeTypE
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

README.md

@@ -1,6 +1,6 @@
-# PatternLab
+# Pattern Analyzer
 
-PatternLab is a comprehensive, plugin-based framework for binary data analysis in Python. It provides a powerful engine to apply statistical tests, cryptographic analysis, and structural format detection on any binary data source.
+Pattern Analyzer is a comprehensive, plugin-based framework for binary data analysis in Python. It provides a powerful engine to apply statistical tests, cryptographic analysis, and structural format detection on any binary data source.
 
 ## Features
 
@@ -10,16 +10,16 @@ PatternLab is a comprehensive, plugin-based framework for binary data analysis i
   - **Cryptographic Analysis**: Detects ECB mode encryption, repeating-key XOR patterns, and searches for known constants like AES S-boxes.
   - **Structural Analysis**: Basic parsers for formats like ZIP, PNG, and PDF.
   - **Machine Learning**: Anomaly detection using Autoencoders, LSTMs, and pre-trained classifiers.
-- **Multiple Interfaces**: Use PatternLab the way you want:
+- **Multiple Interfaces**: Use Pattern Analyzer the way you want:
   - **Command-Line Interface (CLI)** for scripting and automation.
   - **Web User Interface (Streamlit)** for interactive analysis and visualization.
   - **Text-based User Interface (TUI)** for terminal-based interaction.
-  - **REST API (FastAPI)** to integrate PatternLab into other services.
+  - **REST API (FastAPI)** to integrate Pattern Analyzer into other services.
 - **High-Performance Engine**: Supports parallel test execution, streaming analysis for large files, and sandboxed plugin execution for security and stability.
 
 ## Installation
 
-It is recommended to install PatternLab in a virtual environment.
+It is recommended to install Pattern Analyzer in a virtual environment.
 
 ```bash
 # Clone the repository
@@ -46,21 +46,21 @@ The optional dependencies are:
 Analyze a binary file using a default set of tests and save the report.
 
 ```bash
-patternlab analyze test.bin --out report.json
+patternanalyzer analyze test.bin --out report.json
 ```
 
 Use a specific configuration profile for a focused analysis (e.g., cryptographic tests).
 
 ```bash
-patternlab analyze encrypted.bin --profile crypto --out crypto_report.json
+patternanalyzer analyze encrypted.bin --profile crypto --out crypto_report.json
 ```
 
 ### Python API
 
 Programmatically run an analysis pipeline.
 
 ```python
-from patternlab.engine import Engine
+from patternanalyzer.engine import Engine
 
 # Initialize the analysis engine
 engine = Engine()
@@ -89,7 +89,7 @@ print(json.dumps(output, indent=2))
 
 ```
 pattern-analyzer/
-├── patternlab/               # Main source code for the framework
+├── patternanalyzer/               # Main source code for the framework
 │   ├── plugins/              # Built-in analysis and transform plugins
 │   ├── __init__.py
 │   ├── engine.py             # The core analysis engine

app.py

@@ -2,9 +2,9 @@
 import base64
 import pandas as pd
 import json
-from patternlab.engine import Engine
+from patternanalyzer.engine import Engine
 
-st.set_page_config(page_title="PatternLab Analizi", layout="wide", page_icon="🔬")
+st.set_page_config(page_title="Pattern Analyzer Analizi", layout="wide", page_icon="🔬")
 
 engine = Engine()
 
@@ -50,10 +50,10 @@ def main():
     # Language support
     if 'language' not in st.session_state:
         st.session_state.language = "tr"
-
+    # TO DO (P3): Load language strings from an external file
     lang = {
         "tr": {
-            "main_title": "🔬 PatternLab Analiz Platformu",
+            "main_title": "🔬 Pattern Analyzer Analiz Platformu",
             "main_desc": "Bu platform, verilerinizde rastgelelik paternlerini analiz etmek için güçlü istatistiksel testler sunar. Dosya yükleyin veya doğrudan veri girin ve kapsamlı bir analiz raporu elde edin.",
             "results_title": "📊 Analiz Sonuçları",
             "control_panel": "⚙️ Kontrol Paneli",
@@ -161,7 +161,7 @@ def main():
             }
         },
         "en": {
-            "main_title": "🔬 PatternLab Analysis Platform",
+            "main_title": "🔬 Pattern Analyzer Analysis Platform",
             "main_desc": "This platform offers powerful statistical tests to analyze randomness patterns in your data. Upload a file or enter data directly and get a comprehensive analysis report.",
             "results_title": "📊 Analysis Results",
             "control_panel": "⚙️ Control Panel",

debug_bmr.py

@@ -1,5 +1,5 @@
-from patternlab.plugin_api import BytesView
-from patternlab.plugins.binary_matrix_rank import BinaryMatrixRankTest
+from patternanalyzer.plugin_api import BytesView
+from patternanalyzer.plugins.binary_matrix_rank import BinaryMatrixRankTest
 
 def inspect_rows(m=8, num_matrices=1):
     bits_per_matrix = m * m

debug_engine.py

@@ -1,5 +1,5 @@
-from patternlab.engine import Engine
-from patternlab.plugin_api import TestPlugin, TestResult
+from patternanalyzer.engine import Engine
+from patternanalyzer.plugin_api import TestPlugin, TestResult
 
 class ObsTest(TestPlugin):
     def describe(self): return "Observ"
@@ -11,8 +11,8 @@ def run(self, data, params):
 e.register_test("obs_test", ObsTest())
 out = e.analyze(b"\x00\x01\x02", {"tests":[{"name":"obs_test","params":{}}]})
 print("analyze returned:", repr(out))
-import inspect, patternlab.engine
-src = inspect.getsource(patternlab.engine)
+import inspect, patternanalyzer.engine
+src = inspect.getsource(patternanalyzer.engine)
 print("\n--- source slice 1000..1320 ---")
 for i, line in enumerate(src.splitlines(), start=1):
     if 1000 <= i <= 1320:

docs/api-reference.md

@@ -1,17 +1,17 @@
 # API Reference
 
-This page provides a reference for the programmatic use of the PatternLab Python API. It is intended for developers who want to integrate PatternLab's analysis capabilities into their own applications.
+This page provides a reference for the programmatic use of the Pattern Analyzer Python API. It is intended for developers who want to integrate Pattern Analyzer's analysis capabilities into their own applications.
 
 ## Core Components
 
-The API revolves around a few key classes defined in `patternlab.engine` and `patternlab.plugin_api`.
+The API revolves around a few key classes defined in `patternanalyzer.engine` and `patternanalyzer.plugin_api`.
 
 ### `Engine`
 
 The `Engine` class is the main entry point for all analysis tasks.
 
 ```python
-from patternlab.engine import Engine
+from patternanalyzer.engine import Engine
 
 # Initialize the engine. This automatically discovers installed plugins.
 engine = Engine()
@@ -57,7 +57,7 @@ Returns a list of names of all registered test plugins.
 A memory-efficient wrapper for binary data passed to plugins. It's the primary data type used within the `run` method of plugins.
 
 ```python
-from patternlab.plugin_api import BytesView
+from patternanalyzer.plugin_api import BytesView
 
 data = BytesView(b'\xAA\xBB\xCC')
 
@@ -74,7 +74,7 @@ bits = data.bit_view()
 A dataclass used by `TestPlugin` instances to return their findings.
 
 ```python
-from patternlab.plugin_api import TestResult
+from patternanalyzer.plugin_api import TestResult
 
 # Example of creating a TestResult within a plugin
 result = TestResult(
@@ -90,7 +90,7 @@ result = TestResult(
 This example demonstrates initializing the engine, defining a custom analysis pipeline, and running the analysis.
 
 ```python
-from patternlab.engine import Engine
+from patternanalyzer.engine import Engine
 import json
 import os
 

docs/configs/README.md

@@ -1,6 +1,6 @@
 # Configuration Examples
 
-This directory contains example configuration files for PatternLab in both `JSON` and `YAML` formats. These files demonstrate how to customize an analysis pipeline.
+This directory contains example configuration files for Pattern Analyzer in both `JSON` and `YAML` formats. These files demonstrate how to customize an analysis pipeline.
 
 ## Files
 
@@ -25,8 +25,8 @@ You can run an analysis using one of the example configuration files like this:
 
 ```bash
 # Using the YAML configuration
-patternlab analyze my_data.bin --config docs/configs/example.yml
+patternanalyzer analyze my_data.bin --config docs/configs/example.yml
 
 # Using the JSON configuration
-patternlab analyze my_data.bin --config docs/configs/example.json
+patternanalyzer analyze my_data.bin --config docs/configs/example.json
 ```

docs/getting-started.md

@@ -1,6 +1,6 @@
 # Getting Started
 
-This guide will walk you through the basic steps to set up PatternLab and perform your first analysis.
+This guide will walk you through the basic steps to set up Pattern Analyzer and perform your first analysis.
 
 ## Prerequisites
 
@@ -25,15 +25,15 @@ python -m venv .venv
 pip install -e .[test,ml,ui]
 ```
 
-This command installs PatternLab and all dependencies required for the user interfaces, machine learning plugins, and running tests.
+This command installs Pattern Analyzer and all dependencies required for the user interfaces, machine learning plugins, and running tests.
 
 ## Running Your First Analysis (CLI)
 
 The Command-Line Interface (CLI) is the quickest way to analyze a file. Let's analyze the provided `test.bin` file.
 
 ```bash
 # Run analysis on a file and save the output to report.json
-patternlab analyze test.bin --out report.json
+patternanalyzer analyze test.bin --out report.json
 ```
 
 After the command completes, a `report.json` file will be created in your directory. It contains a detailed breakdown of the results from all default tests.
@@ -60,12 +60,12 @@ After the command completes, a `report.json` file will be created in your direct
 
 ## Using the Python API
 
-For more advanced use cases, you can integrate PatternLab directly into your Python scripts.
+For more advanced use cases, you can integrate Pattern Analyzer directly into your Python scripts.
 
 Create a file named `example.py` with the following content:
 
 ```python
-from patternlab.engine import Engine
+from patternanalyzer.engine import Engine
 import json
 
 # 1. Initialize the analysis engine
@@ -99,7 +99,7 @@ python example.py
 
 ## Launching the Web UI
 
-PatternLab includes a user-friendly web interface built with Streamlit for interactive analysis.
+Pattern Analyzer includes a user-friendly web interface built with Streamlit for interactive analysis.
 
 To start it, run the following command in your terminal: