mirror of
https://github.com/agessaman/meshcore-bot.git
synced 2026-11-04 11:57:16 +00:00
agessaman
e30cc8a498
_get_tracking_data, _get_contact_detail and _calculate_distance move to modules/web_viewer/tracking.py (ContactTrackingMixin); the database statistics, table info and description, optimization and cache view move to modules/web_viewer/database_admin.py (DatabaseAdminMixin). All nine bodies are verbatim; BotDataViewer inherits both. tracking.py joins app.py on mypy's suppressed list, since the moved code carries the type errors mypy never checked in app.py. app.py keeps validate_sql_identifier and humanize_span imported so those module attributes still resolve. No test patched anything these methods use. app.py drops to about 5,800 lines, from 9,095 at the start of the refactor.
632 lines
34 KiB
Python
632 lines
34 KiB
Python
"""Contact tracking data for the web viewer: the contacts table, contact detail and distances."""
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from __future__ import annotations
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from typing import Any
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class ContactTrackingMixin:
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"""Mixed into BotDataViewer."""
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_bucket_hop_chunks: Any
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_compute_path_encoding_badge: Any
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_db_connection: Any
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_get_cached_contact_multibyte_hop_chunks: Any
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config: Any
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logger: Any
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def _get_tracking_data(
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self,
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since='30d',
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include_detail=False,
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page: int | None = None,
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page_size: int | None = None,
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search: str = '',
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path_bytes: str = '',
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device_role: str = '',
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hop_filter: str = '',
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location_filter: str = '',
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starred: str = '',
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sort: str = 'last_seen',
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direction: str = 'desc',
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):
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"""Get contact tracking data. since: 24h, 7d, 30d, 90d, or all (heard in that window).
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include_detail=False (the interactive /api/contacts list) omits per-contact ``all_paths``
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and ``raw_advert_data`` to keep the payload small; the UI fetches those on demand via
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/api/contact-detail. The interactive route supplies ``page`` and ``page_size`` so path
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enrichment is limited to visible contacts. include_detail=True (the export endpoint)
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keeps the legacy full-result behavior and full fields.
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"""
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try:
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with self._db_connection() as conn:
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cursor = conn.cursor()
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# Get bot location from config
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bot_lat = self.config.getfloat('Bot', 'bot_latitude', fallback=None)
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bot_lon = self.config.getfloat('Bot', 'bot_longitude', fallback=None)
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# Filter by last_heard (default: last 30 days). last_heard is stored as ISO-text
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# datetime in LOCAL time (e.g. '2026-06-16 09:03:49.606966', written by datetime.now()),
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# so the cutoff must also be local: datetime('now', 'localtime', ...). Using bare
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# datetime('now', ...) computes the cutoff in UTC and shaves the local UTC offset off
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# the window (e.g. a "24h" filter only returns ~17h of data in US/Pacific).
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datetime_offsets = {
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'24h': "'-24 hours'",
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'7d': "'-7 days'",
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'30d': "'-30 days'",
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'90d': "'-90 days'",
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}
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where_parts = []
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where_params: list[Any] = []
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# A node can have more than one observed advert path. Treat its byte class as
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# the widest path encoding seen for it, with the contact's current out-path as a
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# fallback for databases that have not retained an observed path yet. This gives
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# the list one stable, sortable value instead of placing the same node in several
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# byte buckets. Only count rows with a known 1/2/3 encoding so NULL/invalid
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# observations do not collapse to "1-byte" and block the out-path fallback.
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path_bytes_expression = """COALESCE((
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SELECT MAX(op.bytes_per_hop)
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FROM observed_paths op
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WHERE op.public_key = c.public_key
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AND op.packet_type = 'advert'
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AND op.path_hex IS NOT NULL AND op.path_hex != ''
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AND op.bytes_per_hop IN (1, 2, 3)
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), CASE WHEN c.out_bytes_per_hop IN (1, 2, 3)
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THEN c.out_bytes_per_hop ELSE 0 END)"""
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if since in datetime_offsets:
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where_parts.append(
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f"c.last_heard >= datetime('now', 'localtime', {datetime_offsets[since]})"
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)
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search = (search or '').strip().lower()[:100]
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if search and not include_detail:
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# Match the former client-side behavior: public keys are prefix-only,
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# while names, roles, device types, and locations match anywhere.
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escaped = search.replace('\\', '\\\\').replace('%', '\\%').replace('_', '\\_')
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where_parts.append(
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"("
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"LOWER(COALESCE(c.public_key, '')) LIKE ? ESCAPE '\\' OR "
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"LOWER(COALESCE(c.name, '')) LIKE ? ESCAPE '\\' OR "
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"LOWER(COALESCE(c.role, '')) LIKE ? ESCAPE '\\' OR "
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"LOWER(COALESCE(c.device_type, '')) LIKE ? ESCAPE '\\' OR "
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"LOWER(COALESCE(c.city, '')) LIKE ? ESCAPE '\\' OR "
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"LOWER(COALESCE(c.state, '')) LIKE ? ESCAPE '\\' OR "
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"LOWER(COALESCE(c.country, '')) LIKE ? ESCAPE '\\'"
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")"
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)
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where_params.extend([f'{escaped}%'] + [f'%{escaped}%'] * 6)
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path_bytes = str(path_bytes or '').strip()
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if path_bytes in ('1', '2', '3'):
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where_parts.append(f'{path_bytes_expression} = ?')
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where_params.append(int(path_bytes))
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elif path_bytes == 'unknown':
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where_parts.append(f'{path_bytes_expression} = 0')
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device_role = str(device_role or '').strip().lower()
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if device_role in ('companion', 'repeater', 'roomserver', 'sensor'):
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where_parts.append("LOWER(COALESCE(c.role, '')) = ?")
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where_params.append(device_role)
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elif device_role == 'other':
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where_parts.append("LOWER(COALESCE(c.role, '')) NOT IN ('companion', 'repeater', 'roomserver', 'sensor')")
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if hop_filter in ('0', '1', '2', '3'):
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where_parts.append(
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'COALESCE(c.hop_count, 0) = ?' if hop_filter == '0'
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else 'COALESCE(c.hop_count, 0) >= ?'
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)
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where_params.append(int(hop_filter))
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has_location_expression = (
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"((c.city IS NOT NULL AND c.city != '') OR "
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"(c.state IS NOT NULL AND c.state != '') OR "
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"(c.country IS NOT NULL AND c.country != '') OR "
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"(c.latitude IS NOT NULL AND c.longitude IS NOT NULL "
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"AND c.latitude != 0 AND c.longitude != 0))"
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)
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if location_filter == 'known':
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where_parts.append(has_location_expression)
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elif location_filter == 'unknown':
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where_parts.append(f'NOT {has_location_expression}')
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if starred == 'yes':
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where_parts.append('COALESCE(c.is_starred, 0) = 1')
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elif starred == 'no':
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where_parts.append('COALESCE(c.is_starred, 0) = 0')
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where_clause = (' WHERE ' + ' AND '.join(where_parts)) if where_parts else ''
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pagination = None
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filtered_stats = None
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if page is not None and page_size is not None and not include_detail:
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page_size = max(1, min(200, int(page_size)))
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page = max(1, int(page))
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cursor.execute(
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"""
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SELECT
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COUNT(*) AS total_items,
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SUM(CASE WHEN c.last_heard >= datetime('now', 'localtime', '-24 hours') THEN 1 ELSE 0 END) AS contacts_24h,
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SUM(CASE WHEN c.last_heard >= datetime('now', 'localtime', '-7 days') THEN 1 ELSE 0 END) AS contacts_7d,
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SUM(CASE WHEN c.first_heard >= datetime('now', 'localtime', '-7 days')
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AND LOWER(COALESCE(c.device_type, '')) LIKE '%companion%' THEN 1 ELSE 0 END) AS new_companions,
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SUM(CASE WHEN c.first_heard >= datetime('now', 'localtime', '-7 days')
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AND LOWER(COALESCE(c.device_type, '')) LIKE '%repeater%' THEN 1 ELSE 0 END) AS new_repeaters,
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SUM(CASE WHEN c.first_heard >= datetime('now', 'localtime', '-7 days')
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AND (LOWER(COALESCE(c.device_type, '')) LIKE '%room%'
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OR LOWER(COALESCE(c.device_type, '')) LIKE '%server%') THEN 1 ELSE 0 END) AS new_room_servers
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FROM complete_contact_tracking c
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""" + where_clause,
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tuple(where_params),
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)
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aggregate = cursor.fetchone()
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total_items = int(aggregate['total_items'] or 0)
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total_pages = max(1, (total_items + page_size - 1) // page_size)
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page = min(page, total_pages)
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pagination = {
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'page': page,
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'page_size': page_size,
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'total_items': total_items,
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'total_pages': total_pages,
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'has_previous': page > 1,
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'has_next': page < total_pages,
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}
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filtered_stats = {
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'contacts_24h': int(aggregate['contacts_24h'] or 0),
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'contacts_7d': int(aggregate['contacts_7d'] or 0),
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'contacts_total': total_items,
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'new_companions': int(aggregate['new_companions'] or 0),
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'new_repeaters': int(aggregate['new_repeaters'] or 0),
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'new_room_servers': int(aggregate['new_room_servers'] or 0),
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}
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# Fetch contacts directly (no join/group-by). The recent paths per contact are
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# loaded in a second query below and assembled in Python. This avoids materializing
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# a window-function CTE over all of observed_paths and grouping by every contact
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# column (incl. the raw_advert_data blob) on every request. last_advert_timestamp is
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# the per-contact value, so it matches the old MAX(...) over a single contact's rows.
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detail_cols = "c.raw_advert_data," if include_detail else ""
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sort_expressions = {
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'username': "LOWER(COALESCE(c.name, ''))",
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'device_type': "LOWER(COALESCE(c.device_type, ''))",
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'location': (
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"LOWER(CASE "
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"WHEN c.city IS NOT NULL AND c.city != '' AND c.state IS NOT NULL AND c.state != '' "
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"THEN c.city || ', ' || c.state "
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"WHEN c.city IS NOT NULL AND c.city != '' THEN c.city "
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"WHEN c.latitude IS NOT NULL AND c.longitude IS NOT NULL "
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"AND c.latitude != 0 AND c.longitude != 0 THEN printf('%s, %s', c.latitude, c.longitude) "
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"ELSE '' END)"
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),
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'snr': 'COALESCE(c.snr, 0)',
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'hop_count': 'COALESCE(c.hop_count, 0)',
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'path_bytes': path_bytes_expression,
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'first_heard': "COALESCE(c.first_heard, '')",
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'last_seen': "COALESCE(c.last_heard, '')",
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'advert_count': 'COALESCE(c.advert_count, 0)',
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}
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sort = sort if sort in (*sort_expressions.keys(), 'distance') else 'last_seen'
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direction = 'asc' if direction == 'asc' else 'desc'
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if sort == 'distance':
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if bot_lat is None or bot_lon is None:
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sort_expression = '0'
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else:
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conn.create_function('contacts_distance_km', 2, lambda lat, lon: (
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self._calculate_distance(bot_lat, bot_lon, lat, lon)
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if lat is not None and lon is not None else 0
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))
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sort_expression = 'contacts_distance_km(c.latitude, c.longitude)'
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else:
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sort_expression = sort_expressions[sort]
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query_params = list(where_params)
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limit_clause = ''
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if pagination is not None:
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limit_clause = ' LIMIT ? OFFSET ?'
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query_params.extend([page_size, (page - 1) * page_size])
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cursor.execute("""
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SELECT
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c.public_key, c.name, c.role, c.device_type,
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c.latitude, c.longitude, c.city, c.state, c.country,
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c.snr, c.hop_count, c.first_heard, c.last_heard,
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c.advert_count, c.is_currently_tracked,
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""" + detail_cols + """
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c.signal_strength,
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c.is_starred, c.out_path, c.out_path_len, c.out_bytes_per_hop,
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""" + path_bytes_expression + """ AS path_bytes_per_hop,
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c.last_advert_timestamp as last_message
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FROM complete_contact_tracking c
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""" + where_clause + """
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ORDER BY """ + sort_expression + f" {direction.upper()}, c.public_key ASC" + limit_clause,
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tuple(query_params),
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)
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main_rows = cursor.fetchall()
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paths_by_key = {}
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path_rows = []
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if main_rows:
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path_params: list[Any] = []
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page_key_clause = ''
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if pagination is not None:
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# The interactive list enriches only the visible page. At most 200 keys are
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# supplied, staying comfortably below SQLite's parameter limit and turning
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# the former all-history window scan into targeted index lookups.
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page_keys = [row['public_key'] for row in main_rows]
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placeholders = ','.join('?' for _ in page_keys)
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page_key_clause = f' AND public_key IN ({placeholders})'
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path_params.extend(page_keys)
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cursor.execute("""
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WITH recent_paths AS (
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SELECT public_key, path_hex, path_length, bytes_per_hop,
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observation_count, last_seen,
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ROW_NUMBER() OVER (PARTITION BY public_key ORDER BY last_seen DESC) as rn
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FROM observed_paths
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WHERE packet_type = 'advert' AND public_key IS NOT NULL
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""" + page_key_clause + """
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)
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SELECT public_key, path_hex, path_length, bytes_per_hop, observation_count, last_seen
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FROM recent_paths WHERE rn <= 50
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ORDER BY public_key, last_seen DESC
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""", tuple(path_params))
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path_rows = cursor.fetchall()
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for prow in path_rows:
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if not prow['path_hex']: # Skip empty paths
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continue
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bph = None
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if prow['bytes_per_hop'] is not None:
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try:
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bph = int(prow['bytes_per_hop'])
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if bph not in (1, 2, 3):
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bph = 1
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except (TypeError, ValueError):
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bph = 1
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paths_by_key.setdefault(prow['public_key'], []).append({
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'path_hex': prow['path_hex'],
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'path_length': int(prow['path_length']) if prow['path_length'] is not None else 0,
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'bytes_per_hop': bph,
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'observation_count': int(prow['observation_count']) if prow['observation_count'] is not None else 1,
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'last_seen': prow['last_seen'] if prow['last_seen'] is not None else None
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})
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multibyte_hop_chunks = self._get_cached_contact_multibyte_hop_chunks(cursor)
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chunk_buckets = self._bucket_hop_chunks(multibyte_hop_chunks)
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tracking = []
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for row in main_rows:
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# Calculate distance if both bot and contact have coordinates
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distance = None
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if (bot_lat is not None and bot_lon is not None and
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row['latitude'] is not None and row['longitude'] is not None):
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distance = self._calculate_distance(bot_lat, bot_lon, row['latitude'], row['longitude'])
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# Recent paths for this contact (grouped from the second query above). The full
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# path objects are NOT sent in the list payload (they were ~70% of its size and
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# are only used in the per-contact modal); the UI fetches them on demand via
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# /api/contact-detail. The list only needs the count and the badge.
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all_paths = paths_by_key.get(row['public_key'], [])
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paths_count = len(all_paths)
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# Preserve the legacy total_messages value: it was COUNT(*) over the LEFT-JOINed
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# path rows, i.e. the number of paths, or 1 when a contact had no paths.
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total_messages = max(1, paths_count)
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path_encoding_badge = self._compute_path_encoding_badge(
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row, all_paths, chunk_buckets
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)
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# The badge/tooltip decodes out_path (the "primary" path) using out_bytes_per_hop.
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# The contact column can be stale (e.g. left at 1 while the primary path is a 3-byte
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# path), which makes a multi-byte path render as twice/three-times as many 1-byte
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# hops. Index the encoding on the primary observed path itself, which carries the
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# authoritative bytes_per_hop, falling back to the contact column when unmatched.
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out_path_val = row['out_path'] if row['out_path'] is not None else ''
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out_bytes_per_hop_val = row['out_bytes_per_hop'] if row['out_bytes_per_hop'] is not None else None
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if out_path_val:
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primary_path = next((p for p in all_paths if p['path_hex'] == out_path_val), None)
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if primary_path and primary_path.get('bytes_per_hop') in (1, 2, 3):
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out_bytes_per_hop_val = primary_path['bytes_per_hop']
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entry = {
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'user_id': row['public_key'],
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'username': row['name'],
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'role': row['role'],
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'device_type': row['device_type'],
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'latitude': row['latitude'],
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'longitude': row['longitude'],
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'city': row['city'],
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'state': row['state'],
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'country': row['country'],
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'snr': row['snr'],
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'hop_count': row['hop_count'],
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'first_heard': row['first_heard'],
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'last_seen': row['last_heard'],
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'advert_count': row['advert_count'],
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'is_currently_tracked': row['is_currently_tracked'],
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'signal_strength': row['signal_strength'],
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'total_messages': total_messages,
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'last_message': row['last_message'],
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'distance': distance,
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'is_starred': bool(row['is_starred'] if row['is_starred'] is not None else 0),
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'out_path': out_path_val,
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'out_path_len': row['out_path_len'] if row['out_path_len'] is not None else -1,
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'out_bytes_per_hop': out_bytes_per_hop_val,
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'path_bytes_per_hop': int(row['path_bytes_per_hop'] or 0),
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'paths_count': paths_count,
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'path_encoding_badge': path_encoding_badge,
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}
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if include_detail:
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# Full fidelity for the export endpoint (size-tolerant, infrequent download).
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raw_advert_data = row['raw_advert_data']
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raw_advert_data_parsed = None
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if raw_advert_data:
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try:
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import json
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raw_advert_data_parsed = json.loads(raw_advert_data)
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except Exception:
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raw_advert_data_parsed = None
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entry['all_paths'] = all_paths
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entry['raw_advert_data'] = raw_advert_data
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entry['raw_advert_data_parsed'] = raw_advert_data_parsed
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tracking.append(entry)
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# Get server statistics for daily tracking using direct database queries
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server_stats = {}
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try:
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# Check if daily_stats table exists
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cursor.execute("SELECT name FROM sqlite_master WHERE type='table' AND name='daily_stats'")
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if cursor.fetchone():
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# 24h: Last 24 hours of advertisements
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cursor.execute("""
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SELECT SUM(advert_count) FROM daily_stats
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WHERE date >= date('now', 'localtime', '-1 day')
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""")
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server_stats['advertisements_24h'] = cursor.fetchone()[0] or 0
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# 7d: Previous 6 days (excluding today)
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cursor.execute("""
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SELECT SUM(advert_count) FROM daily_stats
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WHERE date >= date('now', 'localtime', '-7 days') AND date < date('now', 'localtime')
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""")
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server_stats['advertisements_7d'] = cursor.fetchone()[0] or 0
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# All: Everything
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cursor.execute("""
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SELECT SUM(advert_count) FROM daily_stats
|
|
""")
|
|
server_stats['total_advertisements'] = cursor.fetchone()[0] or 0
|
|
|
|
# Nodes per day statistics
|
|
# Calculate today's unique nodes from complete_contact_tracking
|
|
# (last_heard in last 24 hours) since daily_stats might not have today's data yet
|
|
cursor.execute("""
|
|
SELECT COUNT(DISTINCT public_key) FROM complete_contact_tracking
|
|
WHERE last_heard >= datetime('now', 'localtime', '-24 hours')
|
|
""")
|
|
server_stats['nodes_24h'] = cursor.fetchone()[0] or 0
|
|
|
|
# Get today's unique nodes by role for the stacked chart
|
|
cursor.execute("""
|
|
SELECT role, COUNT(DISTINCT public_key) as count
|
|
FROM complete_contact_tracking
|
|
WHERE last_heard >= datetime('now', 'localtime', '-24 hours')
|
|
AND role IS NOT NULL AND role != ''
|
|
GROUP BY role
|
|
""")
|
|
today_by_role = {}
|
|
for row in cursor.fetchall():
|
|
role = row[0].lower() if row[0] else 'unknown'
|
|
count = row[1]
|
|
today_by_role[role] = count
|
|
|
|
server_stats['nodes_24h_by_role'] = {
|
|
'companion': today_by_role.get('companion', 0),
|
|
'repeater': today_by_role.get('repeater', 0),
|
|
'roomserver': today_by_role.get('roomserver', 0),
|
|
'sensor': today_by_role.get('sensor', 0),
|
|
'other': sum(v for k, v in today_by_role.items() if k not in ['companion', 'repeater', 'roomserver', 'sensor'])
|
|
}
|
|
|
|
cursor.execute("""
|
|
SELECT COUNT(DISTINCT public_key) FROM daily_stats
|
|
WHERE date >= date('now', 'localtime', '-7 days') AND date < date('now', 'localtime')
|
|
""")
|
|
server_stats['nodes_7d'] = cursor.fetchone()[0] or 0
|
|
|
|
# Calculate day-over-day and period-over-period comparisons
|
|
# Today vs 7 days ago (single day comparison)
|
|
cursor.execute("""
|
|
SELECT COUNT(DISTINCT public_key) FROM daily_stats
|
|
WHERE date = date('now', 'localtime', '-7 days')
|
|
""")
|
|
result = cursor.fetchone()
|
|
server_stats['nodes_7d_ago'] = result[0] if result and result[0] else 0
|
|
|
|
# Last 7 days vs previous 7 days (days 8-14 ago)
|
|
cursor.execute("""
|
|
SELECT COUNT(DISTINCT public_key) FROM daily_stats
|
|
WHERE date >= date('now', 'localtime', '-14 days') AND date < date('now', 'localtime', '-7 days')
|
|
""")
|
|
result = cursor.fetchone()
|
|
server_stats['nodes_prev_7d'] = result[0] if result and result[0] else 0
|
|
|
|
# Last 30 days vs previous 30 days (days 31-60 ago)
|
|
cursor.execute("""
|
|
SELECT COUNT(DISTINCT public_key) FROM daily_stats
|
|
WHERE date >= date('now', 'localtime', '-60 days') AND date < date('now', 'localtime', '-30 days')
|
|
""")
|
|
result = cursor.fetchone()
|
|
server_stats['nodes_prev_30d'] = result[0] if result and result[0] else 0
|
|
|
|
# Also get current period totals for comparison
|
|
cursor.execute("""
|
|
SELECT COUNT(DISTINCT public_key) FROM daily_stats
|
|
WHERE date >= date('now', 'localtime', '-7 days')
|
|
""")
|
|
server_stats['nodes_7d'] = cursor.fetchone()[0] or 0
|
|
|
|
cursor.execute("""
|
|
SELECT COUNT(DISTINCT public_key) FROM daily_stats
|
|
WHERE date >= date('now', 'localtime', '-30 days')
|
|
""")
|
|
server_stats['nodes_30d'] = cursor.fetchone()[0] or 0
|
|
|
|
cursor.execute("""
|
|
SELECT COUNT(DISTINCT public_key) FROM daily_stats
|
|
""")
|
|
server_stats['nodes_all'] = cursor.fetchone()[0] or 0
|
|
|
|
# Get daily unique node counts by role for the last 30 days for the stacked graph
|
|
# Join daily_stats with complete_contact_tracking to get role information
|
|
# This gives us accurate historical daily counts by role
|
|
cursor.execute("""
|
|
SELECT ds.date, c.role, COUNT(DISTINCT ds.public_key) as daily_count
|
|
FROM daily_stats ds
|
|
LEFT JOIN complete_contact_tracking c ON ds.public_key = c.public_key
|
|
WHERE ds.date >= date('now', 'localtime', '-30 days') AND ds.date <= date('now', 'localtime')
|
|
AND (c.role IS NOT NULL AND c.role != '')
|
|
GROUP BY ds.date, c.role
|
|
ORDER BY ds.date ASC, c.role ASC
|
|
""")
|
|
daily_data_by_role = cursor.fetchall()
|
|
|
|
# Organize data by date and role
|
|
daily_by_role = {}
|
|
for row in daily_data_by_role:
|
|
date_str = row[0]
|
|
role = (row[1] or 'unknown').lower()
|
|
count = row[2]
|
|
|
|
if date_str not in daily_by_role:
|
|
daily_by_role[date_str] = {}
|
|
daily_by_role[date_str][role] = count
|
|
|
|
# Convert to array format with all roles for each date
|
|
server_stats['daily_nodes_30d_by_role'] = []
|
|
for date_str in sorted(daily_by_role.keys()):
|
|
roles_data = daily_by_role[date_str]
|
|
server_stats['daily_nodes_30d_by_role'].append({
|
|
'date': date_str,
|
|
'companion': roles_data.get('companion', 0),
|
|
'repeater': roles_data.get('repeater', 0),
|
|
'roomserver': roles_data.get('roomserver', 0),
|
|
'sensor': roles_data.get('sensor', 0),
|
|
'other': sum(v for k, v in roles_data.items() if k not in ['companion', 'repeater', 'roomserver', 'sensor'])
|
|
})
|
|
|
|
# Also keep the total count for backward compatibility
|
|
cursor.execute("""
|
|
SELECT date, COUNT(DISTINCT public_key) as daily_count
|
|
FROM daily_stats
|
|
WHERE date >= date('now', 'localtime', '-30 days') AND date <= date('now', 'localtime')
|
|
GROUP BY date
|
|
ORDER BY date ASC
|
|
""")
|
|
daily_data = cursor.fetchall()
|
|
server_stats['daily_nodes_30d'] = [
|
|
{'date': row[0], 'count': row[1]}
|
|
for row in daily_data
|
|
]
|
|
|
|
except Exception as e:
|
|
self.logger.debug(f"Could not get server stats: {e}")
|
|
|
|
result = {
|
|
'tracking_data': tracking,
|
|
'server_stats': server_stats
|
|
}
|
|
if pagination is not None:
|
|
result['pagination'] = pagination
|
|
result['filtered_stats'] = filtered_stats
|
|
return result
|
|
except Exception as e:
|
|
self.logger.error(f"Error getting tracking data: {e}")
|
|
return {'error': str(e)}
|
|
|
|
def _get_contact_detail(self, public_key: str) -> dict:
|
|
"""Per-contact detail loaded on demand by the contacts UI modals.
|
|
|
|
Returns the recent advert paths (same shape as the old list ``all_paths``) and the raw
|
|
advertisement data. Both are excluded from the /api/contacts list payload — they were
|
|
~85% of its size and are only needed when a single contact is opened.
|
|
"""
|
|
try:
|
|
with self._db_connection() as conn:
|
|
cursor = conn.cursor()
|
|
|
|
# Recent advert paths (most-recent 50). The idx_observed_paths_advert_pk_seen covering
|
|
# index serves WHERE public_key=? AND packet_type='advert' ORDER BY last_seen DESC directly.
|
|
all_paths: list[dict[str, Any]] = []
|
|
cursor.execute("SELECT name FROM sqlite_master WHERE type='table' AND name='observed_paths'")
|
|
if cursor.fetchone():
|
|
cursor.execute("""
|
|
SELECT path_hex, path_length, bytes_per_hop, observation_count, last_seen
|
|
FROM observed_paths
|
|
WHERE packet_type = 'advert' AND public_key = ?
|
|
ORDER BY last_seen DESC
|
|
LIMIT 50
|
|
""", (public_key,))
|
|
for prow in cursor.fetchall():
|
|
if not prow['path_hex']:
|
|
continue
|
|
bph = None
|
|
if prow['bytes_per_hop'] is not None:
|
|
try:
|
|
bph = int(prow['bytes_per_hop'])
|
|
if bph not in (1, 2, 3):
|
|
bph = 1
|
|
except (TypeError, ValueError):
|
|
bph = 1
|
|
all_paths.append({
|
|
'path_hex': prow['path_hex'],
|
|
'path_length': int(prow['path_length']) if prow['path_length'] is not None else 0,
|
|
'bytes_per_hop': bph,
|
|
'observation_count': int(prow['observation_count']) if prow['observation_count'] is not None else 1,
|
|
'last_seen': prow['last_seen'] if prow['last_seen'] is not None else None,
|
|
})
|
|
|
|
# Raw advertisement data for the "Advertisement Data" modal.
|
|
raw_advert_data = None
|
|
raw_advert_data_parsed = None
|
|
cursor.execute("""
|
|
SELECT raw_advert_data FROM complete_contact_tracking
|
|
WHERE public_key = ? ORDER BY last_heard DESC LIMIT 1
|
|
""", (public_key,))
|
|
rad_row = cursor.fetchone()
|
|
if rad_row and rad_row['raw_advert_data']:
|
|
raw_advert_data = rad_row['raw_advert_data']
|
|
try:
|
|
import json
|
|
raw_advert_data_parsed = json.loads(raw_advert_data)
|
|
except Exception:
|
|
raw_advert_data_parsed = None
|
|
|
|
return {
|
|
'all_paths': all_paths,
|
|
'raw_advert_data': raw_advert_data,
|
|
'raw_advert_data_parsed': raw_advert_data_parsed,
|
|
}
|
|
except Exception as e:
|
|
self.logger.error(f"Error getting contact detail: {e}")
|
|
return {'error': str(e)}
|
|
|
|
def _calculate_distance(self, lat1, lon1, lat2, lon2):
|
|
"""Calculate distance between two points using Haversine formula"""
|
|
import math
|
|
|
|
# Convert latitude and longitude from degrees to radians
|
|
lat1, lon1, lat2, lon2 = map(math.radians, [lat1, lon1, lat2, lon2])
|
|
|
|
# Haversine formula
|
|
dlat = lat2 - lat1
|
|
dlon = lon2 - lon1
|
|
a = math.sin(dlat/2)**2 + math.cos(lat1) * math.cos(lat2) * math.sin(dlon/2)**2
|
|
c = 2 * math.asin(math.sqrt(a))
|
|
|
|
# Radius of earth in kilometers
|
|
r = 6371
|
|
|
|
return c * r
|