visualize_logs

A Python library and command line tool that creates interactive visualizations for log data analysis with zoom and navigation capabilities.

142

Security Operations

0

visualize_logs

A Python library and command line tool that creates interactive visualizations for log data analysis with zoom and navigation capabilities.

Security Operations•Security Information and Event Management

Visualization Python Data Analysis

142stars

GitHub Stars

12 Nov

Last commit

0

Updated 12 Oct 25

visualize_logs Description

visualize_logs is a Python library and command line tool designed for log visualization and analysis. The tool generates interactive plots that allow users to examine log data through visual representations. Users can select specific areas of interest by drawing borders around plot sections to zoom into particular data ranges. Double-clicking functionality enables users to zoom back out for broader data views. The visualization requires JavaScript to be enabled in the browser for proper functionality. Plot controls are positioned in the upper right corner of the display interface. The appearance and behavior of the plots may vary depending on the browser type and window size being used. The tool provides both programmatic access through its Python library interface and direct usage via command line tools, making it suitable for different workflow preferences and integration scenarios.

visualize_logs Description

visualize_logs is a Python library and command line tool designed for log visualization and analysis. The tool generates interactive plots that allow users to examine log data through visual representations. Users can select specific areas of interest by drawing borders around plot sections to zoom into particular data ranges. Double-clicking functionality enables users to zoom back out for broader data views. The visualization requires JavaScript to be enabled in the browser for proper functionality. Plot controls are positioned in the upper right corner of the display interface. The appearance and behavior of the plots may vary depending on the browser type and window size being used. The tool provides both programmatic access through its Python library interface and direct usage via command line tools, making it suitable for different workflow preferences and integration scenarios.

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