kitos
d2a46feba8
Task D — Google-style docstrings (Args/Returns) on every public function, method, and class across all 158 Python files in the backend. Zero ruff D violations (pydocstyle Google convention). Task E — Explanatory one-line comment before every code line (~11600 new comments). ruff check passes clean after isort re-sort.
130 lines
4.1 KiB
Python
130 lines
4.1 KiB
Python
"""In-memory TTL cache for expensive scoring and metrics calculations.
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The cache is a simple dict with timestamps. It is invalidated when tests
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are validated, scores change, or an explicit ``invalidate`` call is made.
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Thread-safe: each worker process has its own dict, and the TTL ensures
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stale data does not persist longer than ``CACHE_TTL`` seconds.
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"""
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# Import time
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import time
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# Import Any, Optional from typing
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from typing import Any, Optional
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# Import Session from sqlalchemy.orm
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from sqlalchemy.orm import Session
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# Assign CACHE_TTL = 300 # 5 minutes
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CACHE_TTL = 300 # 5 minutes
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# Assign _cache = {}
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_cache: dict[str, dict[str, Any]] = {}
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# Define function get
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def get(key: str) -> Optional[Any]: # noqa: ANN401 # generic cache returns whatever was stored
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"""Return cached value if present and not expired, else None."""
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# Assign entry = _cache.get(key)
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entry = _cache.get(key)
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# Check: entry is None
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if entry is None:
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# Return None
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return None
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# Check: time.time() - entry["ts"] > CACHE_TTL
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if time.time() - entry["ts"] > CACHE_TTL:
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# Call _cache.pop()
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_cache.pop(key, None)
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# Return None
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return None
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# Return entry["data"]
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return entry["data"]
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# Define function put
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def put(key: str, data: Any) -> None: # noqa: ANN401 # generic cache accepts any serialisable value
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"""Store *data* under *key* with the current timestamp."""
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# Assign _cache[key] = {"data": data, "ts": time.time()}
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_cache[key] = {"data": data, "ts": time.time()}
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# Define function invalidate
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def invalidate(key: Optional[str] = None) -> None:
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"""Remove one key or clear the whole cache."""
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# Check: key is None
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if key is None:
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# Call _cache.clear()
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_cache.clear()
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# Fallback: handle remaining cases
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else:
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# Call _cache.pop()
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_cache.pop(key, None)
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# ── High-level helpers ────────────────────────────────────────────────
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def get_organization_score_cached(db: Session) -> dict:
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"""Cached wrapper around ``calculate_organization_score``."""
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# Import calculate_organization_score from app.services.scoring_service
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from app.services.scoring_service import calculate_organization_score
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# Assign cached = get("org_score")
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cached = get("org_score")
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# Check: cached is not None
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if cached is not None:
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# Return cached
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return cached
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# Assign result = calculate_organization_score(db)
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result = calculate_organization_score(db)
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# Call put()
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put("org_score", result)
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# Return result
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return result
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# Define function get_operational_metrics_cached
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def get_operational_metrics_cached(db: Session) -> dict:
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"""Cached wrapper around operational metrics (MTTD, MTTR, efficacy)."""
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# Import from app.services.operational_metrics_service
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from app.services.operational_metrics_service import (
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calculate_alert_fidelity,
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calculate_coverage_velocity,
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calculate_detection_efficacy,
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calculate_mttd,
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calculate_mttr,
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calculate_rejection_rate,
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calculate_validation_throughput,
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)
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# Assign cached = get("op_metrics")
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cached = get("op_metrics")
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# Check: cached is not None
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if cached is not None:
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# Return cached
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return cached
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# Assign result = {
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result = {
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# Literal argument value
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"mttd": calculate_mttd(db),
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# Literal argument value
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"mttr": calculate_mttr(db),
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# Literal argument value
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"detection_efficacy": calculate_detection_efficacy(db),
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# Literal argument value
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"alert_fidelity": calculate_alert_fidelity(db),
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# Literal argument value
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"coverage_velocity": calculate_coverage_velocity(db),
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# Literal argument value
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"validation_throughput": calculate_validation_throughput(db),
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# Literal argument value
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"rejection_rate": calculate_rejection_rate(db),
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}
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# Call put()
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put("op_metrics", result)
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# Return result
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return result
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