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https://github.com/msoedov/agentic_security.git
synced 2026-06-24 06:09:55 +02:00
Add missing documentation in report_chart.py
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@@ -13,6 +13,16 @@ from .primitives import Table
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def plot_security_report(table: Table) -> io.BytesIO:
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"""
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Generates a polar plot representing the security report based on the given data.
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Args:
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table (Table): The input data table containing security metrics.
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Returns:
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io.BytesIO: A buffer containing the generated plot image in PNG format.
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Returns an empty buffer in case of an error.
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"""
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try:
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return _plot_security_report(table=table)
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except (TypeError, ValueError, OverflowError, IndexError, Exception) as e:
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@@ -21,6 +31,15 @@ def plot_security_report(table: Table) -> io.BytesIO:
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def generate_identifiers(data: pd.DataFrame) -> list[str]:
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"""
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Generates unique identifiers for the given dataset.
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Args:
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data (pd.DataFrame): A pandas DataFrame containing security-related data.
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Returns:
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list[str]: A list of generated identifiers. Returns a list with an empty string in case of an error.
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"""
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try:
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_generate_identifiers(data=data)
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except (TypeError, ValueError, Exception) as e:
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@@ -29,6 +48,21 @@ def generate_identifiers(data: pd.DataFrame) -> list[str]:
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def _plot_security_report(table: Table) -> io.BytesIO:
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"""
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Generates a polar plot-based security report visualizing the failure rates for different modules.
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This function processes the input data, sorts it by failure rate, and generates a polar plot
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where each bar represents the failure rate for a specific module. The plot includes identifiers,
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color-coding based on token count, failure rate values on the bars, and a table listing the modules
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and their corresponding failure rates.
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Args:
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table (Table): A table-like structure (e.g., pandas DataFrame) containing security report data
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with columns for failure rate, tokens, and modules.
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Returns:
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io.BytesIO: A buffer containing the generated plot image in PNG format.
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"""
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# Data preprocessing
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logger.info("Data preprocessing started.")
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@@ -162,6 +196,21 @@ def _plot_security_report(table: Table) -> io.BytesIO:
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def _generate_identifiers(data: pd.DataFrame) -> list[str]:
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"""
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Generates a list of unique identifiers for each row in the given DataFrame.
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The identifiers are based on the English alphabet, with each identifier consisting
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of a letter followed by a number. The letter represents the "group" of identifiers
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(using a letter from A to Z) and the number is a counter within that group. For example:
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- A1, A2, ..., A26, B1, B2, ..., Z1, Z2, ...
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Args:
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data (pd.DataFrame): The input DataFrame containing data for which identifiers
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are to be generated.
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Returns:
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list[str]: A list of unique identifiers as strings, one for each row in the DataFrame.
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"""
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data_length = len(data)
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alphabet = string.ascii_uppercase
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