Release v0.2.0

Release v0.2.0 - Memory Profiling

Release Date: April 15, 2020

💾 Memory Profiling

This release adds comprehensive memory tracking capabilities to the profiler.

✨ New Features

Memory Profiler

• 💾 Real-time memory usage tracking with psutil
• 📊 Peak memory detection using tracemalloc
• 📈 Memory change monitoring per function call
• 🔍 System memory information retrieval
• 📉 Average memory consumption tracking

API Enhancements

• MemoryProfiler class
• profile_memory decorator
• get_memory_info() for system stats
• Visual memory usage reporting

🔧 Improvements

• Enhanced profiling results display
• Better memory statistics formatting
• Process memory isolation

📦 Installation

pip install performance-profiler-optimizer==0.2.0

🚀 Usage Example

from performance_profiler import MemoryProfiler

memory_profiler = MemoryProfiler()
memory_profiler.enable()

@memory_profiler.profile_memory
def memory_intensive():
    return [i**2 for i in range(1000000)]

memory_intensive()
memory_profiler.print_results()

📊 Example Output

💾 Memory Profiling Results
========================================
Function: memory_intensive
  Calls: 3
  Total Memory Allocated: 38.45 MB
  Peak Memory: 45.23 MB
  Average Memory per Call: 12.82 MB
========================================

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Full Changelog: v0.1.0...v0.2.0