fd2e61dc48
When Trump posts an actionable buy/short signal, instantly tweet the call (entry/direction, hard time window, "ratio me" hook), then post a result follow-up X_FOLLOWUP_MINUTES later reporting the realised 15-min move plus a recent hit-rate brag with the site link. - New app/services/x_poster.py: OAuth 1.0a signed (stdlib hmac, no new dep, httpx reused). Fire-and-forget, fully degradable — no-op unless X creds + x_enabled. Dry-run logs tweet text. In-memory UTC-daily cap. 280-char hard cap on all templates (no Premium). - Gated to source=truth buy/short above x_min_confidence; scanner signals excluded (don't fit the "Trump just posted" format). - Hooked next to notify_signal in /signals/ingest + both Trump pollers (dedup via unique external_id → single tweet per post). - config.py + .env.example: X_API_KEY/SECRET, X_ACCESS_TOKEN/SECRET, X_ENABLED, X_MIN_CONFIDENCE, X_DAILY_CAP, X_FOLLOWUP_MINUTES, X_LINK_URL. 72 tests pass. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
298 lines
12 KiB
Python
298 lines
12 KiB
Python
"""
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Trump Truth Social scraper — CNN public archive
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Source: https://ix.cnn.io/data/truth-social/truth_archive.json
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Updated every ~5 minutes by CNN.
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"""
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import hashlib
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import html
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import logging
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import re
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from datetime import datetime, timezone
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from typing import Optional
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import httpx
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from sqlalchemy import select
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.models import Post, iso_utc
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from app.services.analysis import analyze_post
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from app.services.price_store import price_store
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from app.ws.manager import manager
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logger = logging.getLogger(__name__)
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ARCHIVE_URL = "https://ix.cnn.io/data/truth-social/truth_archive.json"
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# Liveness tracker — updated every successful poll (even when no new posts).
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# Read by /api/health to detect a dead scraper. None = never ran yet.
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last_successful_poll_at: Optional[datetime] = None
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last_poll_error: Optional[str] = None
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def _strip_html(text: str) -> str:
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text = re.sub(r"<[^>]+>", " ", text)
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text = html.unescape(text)
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return re.sub(r"\s+", " ", text).strip()
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def _parse_dt(iso: str) -> datetime:
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"""Parse Truth Social's ISO timestamp into a naive-UTC datetime.
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IMPORTANT: must convert to UTC *before* stripping tzinfo. Otherwise an
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input like '2026-04-24T15:07:48-04:00' would be stored as naive
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15:07:48 and later mis-read as UTC — a silent 4-hour shift.
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"""
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try:
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dt = datetime.fromisoformat(iso.replace("Z", "+00:00"))
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if dt.tzinfo is not None:
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dt = dt.astimezone(timezone.utc)
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return dt.replace(tzinfo=None)
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except Exception:
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return datetime.now(timezone.utc).replace(tzinfo=None)
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async def _fetch_archive() -> Optional[list]:
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headers = {
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"User-Agent": "Mozilla/5.0 (compatible; TrumpSignal/1.0)",
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"Accept": "application/json",
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}
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try:
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async with httpx.AsyncClient(timeout=30, follow_redirects=True) as client:
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resp = await client.get(ARCHIVE_URL, headers=headers)
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resp.raise_for_status()
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return resp.json()
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except Exception as exc:
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# Include type name — httpx often raises bare ConnectError/TimeoutException
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# with empty .args, which used to log as just "Failed to fetch CNN archive:"
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# with no body, making outages impossible to diagnose.
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logger.error("Failed to fetch CNN archive: %s (%s)",
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type(exc).__name__, exc)
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return None
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async def _process_entry(entry: dict, db: AsyncSession) -> Optional[Post]:
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external_id = hashlib.md5(str(entry["id"]).encode()).hexdigest()
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result = await db.execute(select(Post).where(Post.external_id == external_id))
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if result.scalar_one_or_none():
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return None
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text = _strip_html(entry.get("content") or "").strip()
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if not text:
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return None
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published_at = _parse_dt(entry.get("created_at", ""))
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# ── Deterministic entry pre-filter (saves AI spend + blocks 80% of noise) ──
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# The 13-trade backtest showed AI confidence ≥ 85 still lets through pure
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# rhetoric and second-derivative news. Hard-coded action-marker + future-
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# tense + dedup check rejects those BEFORE the AI call. Failing posts are
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# still saved to DB (so we have a record) but stamped as non-actionable.
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from app.database import AsyncSessionLocal
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from app.services.entry_filter import passes_entry_filter
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filter_ok, filter_reason = await passes_entry_filter(text, AsyncSessionLocal)
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if not filter_ok:
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logger.info("Entry filter rejected post (id=%s): %s — %s",
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entry.get("id"), filter_reason, text[:80])
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# Insert a stub row so we don't keep re-fetching the same post from
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# the upstream archive. Signal=hold, no AI call, no analysis.
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stub = Post(
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external_id=external_id, text=text, source="truth",
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published_at=published_at,
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sentiment="neutral", ai_confidence=0,
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relevant=False, signal="hold",
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prefilter_reason=filter_reason[:32],
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analysis_version="entry_filter_rejected",
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)
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db.add(stub)
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await db.flush()
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return None # don't broadcast, don't trade
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analysis = await analyze_post(text)
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asset = analysis["asset"]
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# `tracked_asset`: the asset whose price impact we measure and display.
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# Use target_asset (the perp we actually trade — may be SOL/TRUMP/etc.)
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# when available; fall back to the sentiment asset (BTC/ETH) otherwise.
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# Bug fix: previously always used `asset` (BTC/ETH), which measured the
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# wrong price move when the bot traded a different perp.
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tracked_asset = analysis.get("target_asset") or asset
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# Only capture the price AT post time. The m5/m15/m1h peaks are filled in
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# asynchronously by price_impact_monitor as the windows elapse — avoids
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# recording 0.00% because future candles don't exist yet at entry time.
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price_at_post = None
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if tracked_asset and analysis["relevant"]:
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price_at_post = price_store.get_price_at(tracked_asset, published_at)
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post = Post(
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external_id=external_id,
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text=text,
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source="truth",
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published_at=published_at,
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sentiment=analysis["sentiment"],
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signal=analysis.get("signal"),
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ai_confidence=analysis["confidence"],
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ai_reasoning=analysis.get("reasoning"),
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prefilter_reason=analysis.get("prefilter_reason"),
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analysis_version=analysis.get("analysis_version"),
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relevant=analysis["relevant"],
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# Track the actually-traded asset (target_asset ?? sentiment_asset).
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price_impact_asset=tracked_asset if analysis["relevant"] else None,
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price_impact_m5=None, # filled by price_impact_monitor after 5 m
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price_impact_m15=None, # filled by price_impact_monitor after 15 m
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price_impact_m1h=None, # filled by price_impact_monitor after 1 h
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price_at_post=price_at_post,
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# v5 routing: AI decides the actual perp to trade. May be SOL/TRUMP/etc.
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target_asset=analysis.get("target_asset"),
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category=analysis.get("category"),
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expected_move_pct=analysis.get("expected_move_pct"),
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)
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db.add(post)
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await db.flush()
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# Register with the live peak tracker so it starts watching immediately.
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if tracked_asset and analysis["relevant"] and price_at_post:
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from app.services.price_impact_monitor import register_post
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register_post(
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post_id=post.id,
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asset=tracked_asset,
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signal=analysis.get("signal"),
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entry_price=price_at_post,
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published_at=published_at,
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)
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return post
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def _post_to_ws_payload(post: Post) -> dict:
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price_impact = None
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if post.price_impact_asset and post.price_at_post is not None:
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# At broadcast time all windows are open — values are null until
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# price_impact_monitor fills them in. Frontend treats null as "pending".
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price_impact = {
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"asset": post.price_impact_asset,
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"m5": post.price_impact_m5, # None = not yet measured
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"m15": post.price_impact_m15,
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"m1h": post.price_impact_m1h,
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"price_at_post": post.price_at_post,
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}
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return {
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"type": "new_post",
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"post": {
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"id": post.id,
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"text": post.text,
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"source": post.source,
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"published_at": iso_utc(post.published_at),
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"sentiment": post.sentiment,
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"signal": post.signal,
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"ai_confidence": post.ai_confidence,
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"ai_reasoning": post.ai_reasoning,
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"relevant": post.relevant,
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"target_asset": post.target_asset,
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"category": post.category,
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"expected_move_pct": post.expected_move_pct,
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"price_impact": price_impact,
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},
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}
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async def poll_truth_social(db_session_factory) -> None:
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global last_successful_poll_at, last_poll_error
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logger.info("Polling CNN Truth Social archive...")
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entries = await _fetch_archive()
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if not entries:
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last_poll_error = "fetch_archive returned empty"
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return
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# Only process the latest 50 entries each poll (archive has 30k+ posts)
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recent = entries[:50]
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logger.info("Checking %d recent entries...", len(recent))
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async with db_session_factory() as db:
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try:
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new_posts = []
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for entry in recent:
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try:
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post = await _process_entry(entry, db)
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if post:
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new_posts.append(post)
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except Exception as exc:
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logger.error("Error processing entry %s: %s", entry.get("id"), exc)
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if new_posts:
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await db.commit()
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for post in new_posts:
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await manager.broadcast(_post_to_ws_payload(post))
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logger.info("Saved new post id=%d: %s", post.id, post.text[:60])
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# Telegram fan-out (fire-and-forget). _dispatch filters
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# internally: buy/short → per-subscriber + public channel;
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# relevant-but-hold → public channel only; noise → dropped.
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try:
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from app.services.telegram import notify_signal
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notify_signal(post)
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except Exception as exc:
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logger.warning("Telegram notify failed for post %d: %s", post.id, exc)
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try:
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from app.services.x_poster import notify_x_signal
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notify_x_signal(post)
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except Exception as exc:
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logger.warning("X notify failed for post %d: %s", post.id, exc)
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try:
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from app.services.bot_engine import process_post
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await process_post(post, db)
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except Exception as exc:
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logger.error("process_post failed for post %d: %s", post.id, exc)
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else:
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logger.info("No new posts found.")
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# Mark a successful poll cycle (separate from "found new posts").
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last_successful_poll_at = datetime.now(timezone.utc)
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last_poll_error = None
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except Exception as exc:
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logger.error("Transaction error: %s", exc)
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last_poll_error = f"transaction_error: {exc}"
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await db.rollback()
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async def backfill_history(db_session_factory, limit: int = 500) -> None:
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"""One-time backfill of historical posts (no Claude analysis, no price impact)."""
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logger.info("Starting historical backfill (limit=%d)...", limit)
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entries = await _fetch_archive()
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if not entries:
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logger.error("Backfill failed: could not fetch archive")
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return
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to_process = entries[:limit]
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saved = 0
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async with db_session_factory() as db:
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try:
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for entry in to_process:
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external_id = hashlib.md5(str(entry["id"]).encode()).hexdigest()
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result = await db.execute(select(Post).where(Post.external_id == external_id))
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if result.scalar_one_or_none():
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continue
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text = _strip_html(entry.get("content") or "").strip()
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if not text:
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continue
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post = Post(
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external_id=external_id,
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text=text,
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source="truth",
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published_at=_parse_dt(entry.get("created_at", "")),
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sentiment="neutral",
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ai_confidence=0,
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relevant=False,
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)
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db.add(post)
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saved += 1
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await db.commit()
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logger.info("Backfill complete: saved %d posts", saved)
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except Exception as exc:
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logger.error("Backfill error: %s", exc)
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await db.rollback()
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