nat.plugins.mcp.server.memory_profiler#

Memory profiling utilities for MCP frontend.

Attributes#

Classes#

MemoryProfiler

Memory profiler for tracking memory usage and potential leaks.

Module Contents#

logger#

class MemoryProfiler( enabled: bool = False, log_interval: int = 50, top_n: int = 10, log_level: str = 'DEBUG', )#

Memory profiler for tracking memory usage and potential leaks.

Initialize the memory profiler.

Args:: enabled: Whether memory profiling is enabled log_interval: Log stats every N requests top_n: Number of top allocations to log log_level: Log level for memory profiling output (e.g., “DEBUG”, “INFO”)

enabled = False#

log_interval#

top_n = 10#

log_level = 10#

request_count = 0#

baseline_snapshot = None#

_we_started_tracemalloc = False#

_log(message: str, *args: Any) → None#

Log a message at the configured log level.

Args:: message: Log message format string args: Arguments for the format string

on_request_complete() → None#: Called after each request completes.

_ensure_tracing() → bool#

Ensure tracemalloc is running if we started it originally.

Returns:: True if tracemalloc is active, False otherwise

_safe_traced_memory() → tuple[float, float] | None#: Return (current, peak usage in MB) if tracemalloc is active, else None.

_safe_snapshot() → tracemalloc.Snapshot | None#: Return a tracemalloc Snapshot if available, else None.

log_memory_stats() → dict[str, Any]#: Log current memory statistics and return them.

_count_instances_of_type(type_name: str) → int#: Count instances of a specific type in memory.

_safe_exporter_count() → int#

_safe_isolated_exporter_count() → int#

_safe_intermediate_step_manager_count() → int#

_safe_outstanding_step_count() → int#: Get total outstanding steps across all active IntermediateStepManager instances.

get_stats() → dict[str, Any]#: Get current memory statistics without logging.

reset_baseline() → None#: Reset the baseline snapshot to current state.