pythonprofilers/memory_profiler
Memory Profiler
This project is a diagnostic utility for monitoring and analyzing memory consumption in Python applications. It provides tools for tracking resource usage at the process level and performing detailed, line-by-line analysis to identify memory leaks and performance bottlenecks.
The tool distinguishes itself through its ability to aggregate memory metrics across entire process trees, capturing the total resource impact of both parent and child processes. It supports time-series visualization of memory usage over the duration of a script, allowing for the identification of long-term consumption patterns and unexpected resource spikes. Users can configure the underlying measurement methods to ensure accurate data collection across different operating systems and execution environments.
Beyond standard profiling, the software includes capabilities for automated memory debugging by allowing users to set specific resource thresholds. When these limits are exceeded, the tool can trigger an interactive debugger to pause execution and facilitate real-time troubleshooting. It also supports programmatic querying of memory statistics and integrates directly into interactive command environments for rapid benchmarking without requiring modifications to source code.
Features
- Python Profilers - Measures the memory footprint of Python scripts over time to detect performance bottlenecks and resource spikes.
- Memory Usage Analyzers - Analyzes line-by-line memory usage patterns to identify and resolve leaks and excessive consumption in Python applications.
- Line-Level Resource Monitors - Examines memory consumption for every individual line of code to pinpoint specific operations causing high resource usage.
- Time Series Analysis - Captures and visualizes memory usage over the duration of a process to identify performance trends and unexpected spikes.
- Child Process Memory Tracers - Traverses the OS process hierarchy to aggregate memory metrics from both parent and child processes.
- Bytecode Instrumentation Agents - Modifies Python bytecode at runtime to inject monitoring hooks for granular line-level memory tracking.
- Python Tooling - Identifies memory leaks and resource-heavy operations during the execution of Python scripts.
- Function Decorators - Wraps Python functions using the decorator syntax to intercept calls and trigger memory measurement routines.
- Resource Threshold Debuggers - Monitors memory metrics against user-defined limits to interrupt the execution flow and invoke an interactive debugger upon violation.
- Memory Threshold Alerting - Automates memory debugging by triggering diagnostic tools when resource limits are exceeded.
- System Resource Monitors - Tracks and aggregates memory allocation across parent and child processes to provide a complete system-level view.
- Process Memory Monitors - Tracks memory usage trends and peak consumption across parent and child processes in real-time.
