Sphinx and Autodoc generation

.gitignore

@@ -159,8 +159,8 @@ cython_debug/
 #  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
-#.idea/
-
+.idea/
+.vscode/
 
 *.json
 *.toml

docs/Makefile

@@ -0,0 +1,20 @@
+# Minimal makefile for Sphinx documentation
+#
+
+# You can set these variables from the command line, and also
+# from the environment for the first two.
+SPHINXOPTS    ?=
+SPHINXBUILD   ?= sphinx-build
+SOURCEDIR     = source
+BUILDDIR      = build
+
+# Put it first so that "make" without argument is like "make help".
+help:
+	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+
+.PHONY: help Makefile
+
+# Catch-all target: route all unknown targets to Sphinx using the new
+# "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
+%: Makefile
+	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

docs/make.bat

@@ -0,0 +1,35 @@
+@ECHO OFF
+
+pushd %~dp0
+
+REM Command file for Sphinx documentation
+
+if "%SPHINXBUILD%" == "" (
+	set SPHINXBUILD=sphinx-build
+)
+set SOURCEDIR=source
+set BUILDDIR=build
+
+%SPHINXBUILD% >NUL 2>NUL
+if errorlevel 9009 (
+	echo.
+	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
+	echo.installed, then set the SPHINXBUILD environment variable to point
+	echo.to the full path of the 'sphinx-build' executable. Alternatively you
+	echo.may add the Sphinx directory to PATH.
+	echo.
+	echo.If you don't have Sphinx installed, grab it from
+	echo.https://www.sphinx-doc.org/
+	exit /b 1
+)
+
+if "%1" == "" goto help
+
+%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+goto end
+
+:help
+%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+
+:end
+popd

docs/source/_static/css/custom.css

@@ -0,0 +1,7 @@
+@import 'material_sphinx.css';
+
+.sig.sig-object.py{
+    font-feature-settings: "kern";
+    font-family: "Roboto Mono", "Courier New", Courier, monospace;
+    background: #f8f8f8;
+}

docs/source/conf.py

@@ -0,0 +1,41 @@
+import os
+import sys
+sys.path.insert(0, os.path.abspath('../../masterbase'))
+
+# Configuration file for the Sphinx documentation builder.
+#
+# For the full list of built-in configuration values, see the documentation:
+# https://www.sphinx-doc.org/en/master/usage/configuration.html
+
+# -- Project information -----------------------------------------------------
+# https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information
+
+project = 'Masterbase'
+copyright = '2024 MegaAntiCheat'
+author = 'Jayce, Flenser, Lilith, meat🥩'
+release = '0.1'
+
+# -- General configuration ---------------------------------------------------
+# https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration
+
+extensions = [
+    'sphinx.ext.duration',
+    'sphinx.ext.doctest',
+    'sphinx.ext.autodoc',
+    'sphinx.ext.autosummary',
+    'sphinx.ext.napoleon',
+    'sphinx-pydantic'
+]
+
+templates_path = ['_templates']
+exclude_patterns = []
+
+# -- Options for HTML output -------------------------------------------------
+# https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output
+
+html_theme = 'alabaster'
+html_static_path = ['_static']
+
+
+def setup(app):
+    app.add_css_file('css/custom.css')

docs/source/index.rst

@@ -0,0 +1,20 @@
+.. Masterbase documentation master file, created by
+   sphinx-quickstart on Mon May 13 12:57:00 2024.
+   You can adapt this file completely to your liking, but it should at least
+   contain the root `toctree` directive.
+
+MegaAntiCheat Masterbase documentation
+======================================
+
+.. toctree::
+   :maxdepth: 2
+   :caption: Contents:
+
+   modules
+
+Indices and tables
+==================
+
+* :ref:`genindex`
+* :ref:`modindex`
+* :ref:`search`

docs/source/masterbase.rst

@@ -0,0 +1,61 @@
+masterbase package
+==================
+
+Submodules
+----------
+
+masterbase.anomaly module
+-------------------------
+
+.. automodule:: masterbase.anomaly
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+masterbase.app module
+---------------------
+
+.. automodule:: masterbase.app
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+masterbase.guards module
+------------------------
+
+.. automodule:: masterbase.guards
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+masterbase.lib module
+---------------------
+
+.. automodule:: masterbase.lib
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+masterbase.registers module
+---------------------------
+
+.. automodule:: masterbase.registers
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+masterbase.steam module
+-----------------------
+
+.. automodule:: masterbase.steam
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+Module contents
+---------------
+
+.. automodule:: masterbase
+   :members:
+   :undoc-members:
+   :show-inheritance:

docs/source/modules.rst

@@ -0,0 +1,7 @@
+masterbase
+==========
+
+.. toctree::
+   :maxdepth: 4
+
+   masterbase

masterbase/__init__.py

@@ -1 +1,3 @@
-"""Source code for API interaction."""
+"""
+Source code for API interaction.
+"""

masterbase/anomaly.py

@@ -1,19 +1,40 @@
-"""Anomaly detection for demo streams."""
+"""
+Anomaly detection for demo streams.
+
+Classes:
+- DetectionState
+
+Functions:
+- longest_zero_run
+- likelihood
+- nz_markov_likelihood
+- transition_freqs
+
+Misc variables:
+- S_hat
+"""
+
+__author__ = "Flenser, Jayce"
+__version__ = "1.0.0"
 
 import os
 
 import numpy as np
 from numpy.typing import NDArray
 from pydantic import BaseModel, Field
 
-S_hat: NDArray = np.load(os.path.join("masterbase", "S_hat.npy"))
+
+S_hat: NDArray | None = None
 
 
 def longest_zero_run(data: bytes) -> int:
-    """Get the longest zero run of data.
+    """
+    Get the longest zero run of data.
 
-    Args:
-        data: Input data stream
+    :param data: Input data stream
+    :type data: bytes
+    :return: longest zero run
+    :rtype: int
     """
     array = np.frombuffer(data, dtype=np.uint8)
     zero_mask = array == 0
@@ -27,31 +48,46 @@ def longest_zero_run(data: bytes) -> int:
 
 
 def likelihood(p: NDArray, q: NDArray) -> float:
-    """Determine the likelihood of an empirical frequency distribution under a prior discrete probability distribution.
-
-    Args:
-        p: Discrete prior distribution
-        q: Observed empirical distribution, normalized
+    """
+    Determine the likelihood of an empirical frequency distribution under a prior discrete probability distribution.
+
+    :param p: Discrete prior distribution
+    :type p: NDArray
+    :param q: Observed empirical distribution, normalized
+    :type q: NDArray
+    :return: likelihood
+    :rtype: float
     """
     return np.exp(np.sum(np.log(p + 1e-5) * q))
 
 
 def nz_markov_likelihood(coocs: NDArray) -> float:
-    """Determine the Markov likelihood of all byte-pair transitions, between *nonzero* bytes, e.g., as determined by `transition_freqs`.
+    """
+    Determine the Markov likelihood of all byte-pair transitions, between *nonzero* bytes, 
+    e.g., as determined by `transition_freqs`.
 
-    Args:
-        coocs: cooccurrences of successive octets (transition frequencies).
+    :param coocs: cooccurrences of successive octets (transition frequencies).
+    :type coocs: NDArray
+    :return: likelihood
+    :rtype: float
     """  # noqa
+    global S_hat
+    if S_hat is None:
+        S_hat = np.load(os.path.join("data", "npy", "S_hat.npy"))
+
     _S_hat, coocs = map(lambda a: a.reshape(-1)[1:], (S_hat, coocs))  # noqa
     _S_hat, coocs = map(lambda a: a / a.sum(), (_S_hat, coocs))  # noqa
     return float(likelihood(_S_hat, coocs))
 
 
 def transition_freqs(data: bytes) -> NDArray:
-    """Count the cooccurrences of successive octets (transition frequencies).
+    """
+    Count the co-occurrences of successive octets (transition frequencies).
 
-    Args:
-        data: bytes, the input data stream
+    :param data: the input data stream
+    :type data: bytes
+    :return: Array of co-occurrences
+    :rtype: NDArray
     """
     array = np.frombuffer(data, dtype=np.uint8)
     i, j = array[:-1], array[1:]
@@ -61,23 +97,27 @@ def transition_freqs(data: bytes) -> NDArray:
 
 
 class DetectionState(BaseModel):
-    """Accumulate a trace of statistics for determining the likelihood of observed data under Markov transition frequencies present in valid data.
-
-    Args:
+    """
+    Accumulate a trace of statistics for determining the likelihood of observed data under Markov transition 
+    frequencies present in valid data.
+
+    Attributes:
         length: The cumulative length of all inputs thus far.
         likelihood: The cumulative probability of observing the input data under `S_hat` so far.
         longest_zero_run: The longest run of consecutive zeros observed in the input data chunks so far.
     """  # noqa
-
     length: int = Field(default=0)
     likelihood: float = Field(default=0.0)
     longest_zero_run: int = Field(default=0)
 
     def update(self, data: bytes) -> None:
-        """Update the current state trace with stats from the input data.
+        """
+        Update the current state trace with stats from the input data.
 
-        Args:
-            data: bytes, input data whose likelihood to compute under the prior transition matrix to accumulate into statistics for the stream.
+        :param data: input data whose likelihood to compute under the prior transition matrix to accumulate 
+                     into statistics for the stream.
+        :type data: bytes
+        :return: None
         """  # noqa
         new_length = len(data) + self.length
         new_likelihood = (
@@ -90,5 +130,10 @@ def update(self, data: bytes) -> None:
 
     @property
     def anomalous(self) -> bool:
-        """Return if the current state is anomalous or not."""
+        """
+        Return if the current state is anomalous or not.
+
+        :return: true if likelihood indicates anonymity
+        :rtype: bool
+        """
         return self.likelihood <= 3e-5 or self.longest_zero_run >= 384