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style: apply ruff-format to entire codebase

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First-time run of ruff-format via pre-commit hook normalises quote
style, trailing commas, and whitespace across 188 Python files.
No logic changes.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
James Smith
2026-07-05 14:48:11 +01:00
parent 82e64104fe
commit 96172ca593
189 changed files with 19883 additions and 19552 deletions
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utils/correlation.py
+42 -69
View File
@@ -15,12 +15,13 @@ from typing import Any
from utils.database import add_correlation
from utils.database import get_correlations as db_get_correlations
logger = logging.getLogger('intercept.correlation')
logger = logging.getLogger("intercept.correlation")
@dataclass
class DeviceObservation:
"""A single observation of a device."""
mac: str
first_seen: datetime
last_seen: datetime
@@ -39,12 +40,7 @@ class DeviceCorrelator:
3. They share the same OUI/manufacturer (bonus confidence)
"""
def __init__(
self,
time_window_seconds: int = 30,
min_confidence: float = 0.5,
rssi_threshold: int = 20
):
def __init__(self, time_window_seconds: int = 30, min_confidence: float = 0.5, rssi_threshold: int = 20):
"""
Initialize correlator.
@@ -57,11 +53,7 @@ class DeviceCorrelator:
self.min_confidence = min_confidence
self.rssi_threshold = rssi_threshold
def correlate(
self,
wifi_devices: dict[str, dict[str, Any]],
bt_devices: dict[str, dict[str, Any]]
) -> list[dict]:
def correlate(self, wifi_devices: dict[str, dict[str, Any]], bt_devices: dict[str, dict[str, Any]]) -> list[dict]:
"""
Find correlations between WiFi and Bluetooth devices.
@@ -75,26 +67,28 @@ class DeviceCorrelator:
correlations = []
for wifi_mac, wifi_data in wifi_devices.items():
wifi_obs = self._to_observation(wifi_mac, wifi_data, 'wifi')
wifi_obs = self._to_observation(wifi_mac, wifi_data, "wifi")
if not wifi_obs:
continue
for bt_mac, bt_data in bt_devices.items():
bt_obs = self._to_observation(bt_mac, bt_data, 'bluetooth')
bt_obs = self._to_observation(bt_mac, bt_data, "bluetooth")
if not bt_obs:
continue
confidence = self._calculate_confidence(wifi_obs, bt_obs)
if confidence >= self.min_confidence:
correlations.append({
'wifi_mac': wifi_mac,
'wifi_name': wifi_obs.name,
'bt_mac': bt_mac,
'bt_name': bt_obs.name,
'confidence': round(confidence, 2),
'reason': self._get_correlation_reason(wifi_obs, bt_obs)
})
correlations.append(
{
"wifi_mac": wifi_mac,
"wifi_name": wifi_obs.name,
"bt_mac": bt_mac,
"bt_name": bt_obs.name,
"confidence": round(confidence, 2),
"reason": self._get_correlation_reason(wifi_obs, bt_obs),
}
)
# Persist high-confidence correlations
if confidence >= 0.7:
@@ -103,73 +97,56 @@ class DeviceCorrelator:
wifi_mac=wifi_mac,
bt_mac=bt_mac,
confidence=confidence,
metadata={
'wifi_name': wifi_obs.name,
'bt_name': bt_obs.name
}
metadata={"wifi_name": wifi_obs.name, "bt_name": bt_obs.name},
)
except Exception as e:
logger.debug(f"Failed to persist correlation: {e}")
# Sort by confidence (highest first)
correlations.sort(key=lambda x: x['confidence'], reverse=True)
correlations.sort(key=lambda x: x["confidence"], reverse=True)
return correlations
def _to_observation(
self,
mac: str,
data: dict[str, Any],
device_type: str
) -> DeviceObservation | None:
def _to_observation(self, mac: str, data: dict[str, Any], device_type: str) -> DeviceObservation | None:
"""Convert device dict to observation."""
try:
# Handle different timestamp formats
first_seen = data.get('first_seen') or data.get('firstSeen')
last_seen = data.get('last_seen') or data.get('lastSeen')
first_seen = data.get("first_seen") or data.get("firstSeen")
last_seen = data.get("last_seen") or data.get("lastSeen")
if isinstance(first_seen, str):
first_seen = datetime.fromisoformat(first_seen.replace('Z', '+00:00'))
first_seen = datetime.fromisoformat(first_seen.replace("Z", "+00:00"))
elif isinstance(first_seen, (int, float)):
first_seen = datetime.fromtimestamp(first_seen / 1000)
else:
first_seen = datetime.now()
if isinstance(last_seen, str):
last_seen = datetime.fromisoformat(last_seen.replace('Z', '+00:00'))
last_seen = datetime.fromisoformat(last_seen.replace("Z", "+00:00"))
elif isinstance(last_seen, (int, float)):
last_seen = datetime.fromtimestamp(last_seen / 1000)
else:
last_seen = datetime.now()
# Get RSSI (different field names)
rssi = data.get('rssi') or data.get('power') or data.get('signal')
rssi = data.get("rssi") or data.get("power") or data.get("signal")
if rssi is not None:
rssi = int(rssi)
# Get name
name = data.get('name') or data.get('essid') or data.get('ssid')
name = data.get("name") or data.get("essid") or data.get("ssid")
# Get manufacturer
manufacturer = data.get('manufacturer') or data.get('vendor')
manufacturer = data.get("manufacturer") or data.get("vendor")
return DeviceObservation(
mac=mac,
first_seen=first_seen,
last_seen=last_seen,
rssi=rssi,
name=name,
manufacturer=manufacturer
mac=mac, first_seen=first_seen, last_seen=last_seen, rssi=rssi, name=name, manufacturer=manufacturer
)
except Exception as e:
logger.debug(f"Failed to parse device {mac}: {e}")
return None
def _calculate_confidence(
self,
wifi: DeviceObservation,
bt: DeviceObservation
) -> float:
def _calculate_confidence(self, wifi: DeviceObservation, bt: DeviceObservation) -> float:
"""
Calculate correlation confidence score.
@@ -227,11 +204,7 @@ class DeviceCorrelator:
return min(confidence, 1.0)
def _get_correlation_reason(
self,
wifi: DeviceObservation,
bt: DeviceObservation
) -> str:
def _get_correlation_reason(self, wifi: DeviceObservation, bt: DeviceObservation) -> str:
"""Generate human-readable reason for correlation."""
reasons = []
@@ -263,7 +236,7 @@ def get_correlations(
wifi_devices: dict[str, dict] | None = None,
bt_devices: dict[str, dict] | None = None,
min_confidence: float = 0.5,
include_historical: bool = True
include_historical: bool = True,
) -> list[dict]:
"""
Get device correlations.
@@ -291,23 +264,23 @@ def get_correlations(
for h in historical:
# Avoid duplicates
existing = next(
(r for r in results
if r['wifi_mac'] == h['wifi_mac'] and r['bt_mac'] == h['bt_mac']),
None
(r for r in results if r["wifi_mac"] == h["wifi_mac"] and r["bt_mac"] == h["bt_mac"]), None
)
if not existing:
results.append({
'wifi_mac': h['wifi_mac'],
'bt_mac': h['bt_mac'],
'confidence': h['confidence'],
'reason': 'historical correlation',
'first_seen': h['first_seen'],
'last_seen': h['last_seen']
})
results.append(
{
"wifi_mac": h["wifi_mac"],
"bt_mac": h["bt_mac"],
"confidence": h["confidence"],
"reason": "historical correlation",
"first_seen": h["first_seen"],
"last_seen": h["last_seen"],
}
)
except Exception as e:
logger.debug(f"Failed to get historical correlations: {e}")
# Sort by confidence
results.sort(key=lambda x: x['confidence'], reverse=True)
results.sort(key=lambda x: x["confidence"], reverse=True)
return results