From 05eed51e7dbe010ebe3bbe696aaf358eee92e722 Mon Sep 17 00:00:00 2001 From: Henrik Jess Nielsen Date: Tue, 26 May 2026 22:21:27 +0200 Subject: [PATCH] First commit --- .env | 15 + .gitignore | 1 + Makefile | 68 ++ __pycache__/analyze.cpython-314.pyc | Bin 0 -> 25670 bytes __pycache__/dashboard.cpython-314.pyc | Bin 0 -> 15883 bytes __pycache__/db.cpython-314.pyc | Bin 0 -> 20112 bytes __pycache__/ground_news.cpython-314.pyc | Bin 0 -> 29102 bytes __pycache__/portfolio.cpython-314.pyc | Bin 0 -> 22145 bytes __pycache__/report.cpython-314.pyc | Bin 0 -> 13393 bytes __pycache__/rss_feeds.cpython-314.pyc | Bin 0 -> 12587 bytes __pycache__/runner.cpython-314.pyc | Bin 0 -> 10537 bytes __pycache__/saxo_auth.cpython-314.pyc | Bin 0 -> 12036 bytes __pycache__/saxo_broker.cpython-314.pyc | Bin 0 -> 14923 bytes __pycache__/signals.cpython-314.pyc | Bin 0 -> 23430 bytes analyze.py | 562 +++++++++++++ c25.json | 339 ++++++++ dashboard.py | 327 ++++++++ db.py | 491 ++++++++++++ ground-news-ext/extension.xpi | Bin 0 -> 535653 bytes ground-news-ext/src/128.png | Bin 0 -> 1587 bytes ground-news-ext/src/16.png | Bin 0 -> 305 bytes ground-news-ext/src/32.png | Bin 0 -> 562 bytes ground-news-ext/src/48.png | Bin 0 -> 796 bytes ground-news-ext/src/META-INF/cose.manifest | 277 +++++++ ground-news-ext/src/META-INF/cose.sig | Bin 0 -> 3116 bytes ground-news-ext/src/META-INF/manifest.mf | 287 +++++++ ground-news-ext/src/META-INF/mozilla.rsa | Bin 0 -> 4383 bytes ground-news-ext/src/META-INF/mozilla.sf | 4 + .../src/fonts/UniversalSans-480.ttf | Bin 0 -> 75156 bytes .../src/fonts/UniversalSans-480.woff | Bin 0 -> 30244 bytes .../src/fonts/UniversalSans-680.ttf | Bin 0 -> 75104 bytes .../src/fonts/UniversalSans-680.woff | Bin 0 -> 30392 bytes .../src/fonts/UniversalSans-800.ttf | Bin 0 -> 75072 bytes .../src/fonts/UniversalSans-800.woff | Bin 0 -> 30284 bytes ground-news-ext/src/frame.html | 18 + ground-news-ext/src/ground-symbol.png | Bin 0 -> 7549 bytes ground-news-ext/src/ground-symbol.svg | 17 + ground-news-ext/src/icons/access-block.png | Bin 0 -> 9076 bytes ground-news-ext/src/icons/bar-chart-2.svg | 5 + .../src/icons/book-open-1-black.svg | 4 + .../src/icons/bookmark-1-black.svg | 3 + .../src/icons/bookmark-1-white.svg | 3 + .../src/icons/bookmark-all-white.svg | 3 + .../src/icons/circle-dashed-black.svg | 5 + ground-news-ext/src/icons/close.svg | 4 + ground-news-ext/src/icons/copy.svg | 4 + ground-news-ext/src/icons/facebook.svg | 1 + .../src/icons/factuality-graph.svg | 17 + ground-news-ext/src/icons/info.svg | 5 + ground-news-ext/src/icons/linkedin.svg | 1 + ground-news-ext/src/icons/lock.svg | 5 + .../src/icons/question-solid-white.svg | 1 + ground-news-ext/src/icons/question-solid.svg | 1 + ground-news-ext/src/icons/reddit.svg | 1 + .../src/icons/triangle-exclamation-solid.svg | 1 + ground-news-ext/src/icons/twitter.svg | 1 + ground-news-ext/src/js/background.js | 1 + ground-news-ext/src/js/bluesky.css | 405 ++++++++++ ground-news-ext/src/js/bluesky.js | 1 + ground-news-ext/src/js/content_script.css | 405 ++++++++++ ground-news-ext/src/js/content_script.js | 1 + ground-news-ext/src/js/facebook.css | 405 ++++++++++ ground-news-ext/src/js/facebook.js | 1 + ground-news-ext/src/js/ground.js | 1 + ground-news-ext/src/js/index.js | 0 ground-news-ext/src/js/linkedin.css | 405 ++++++++++ ground-news-ext/src/js/linkedin.js | 1 + ground-news-ext/src/js/menu.js | 2 + ground-news-ext/src/js/menu.js.LICENSE.txt | 28 + ground-news-ext/src/js/options.js | 0 ground-news-ext/src/js/popup.js | 1 + ground-news-ext/src/js/reddit.css | 405 ++++++++++ ground-news-ext/src/js/reddit.js | 1 + ground-news-ext/src/js/twitter.css | 405 ++++++++++ ground-news-ext/src/js/twitter.js | 1 + ground-news-ext/src/manifest.json | 153 ++++ ground-news-ext/src/menu.html | 750 ++++++++++++++++++ ground-news-ext/src/options.html | 27 + ground-news-ext/src/popup.html | 17 + ground_news.db | Bin 0 -> 8806400 bytes ground_news.py | 559 +++++++++++++ logs/dashboard.log | 35 + logs/runner_2026-05-26.log | 224 ++++++ portfolio.py | 369 +++++++++ report.py | 241 ++++++ rss_feeds.py | 244 ++++++ runner.py | 235 ++++++ saxo_auth.py | 220 +++++ saxo_broker.py | 322 ++++++++ signals.py | 354 +++++++++ 90 files changed, 8690 insertions(+) create mode 100644 .env create mode 100644 .gitignore create mode 100644 Makefile create mode 100644 __pycache__/analyze.cpython-314.pyc create mode 100644 __pycache__/dashboard.cpython-314.pyc create mode 100644 __pycache__/db.cpython-314.pyc create mode 100644 __pycache__/ground_news.cpython-314.pyc create mode 100644 __pycache__/portfolio.cpython-314.pyc create mode 100644 __pycache__/report.cpython-314.pyc create mode 100644 __pycache__/rss_feeds.cpython-314.pyc create mode 100644 __pycache__/runner.cpython-314.pyc create mode 100644 __pycache__/saxo_auth.cpython-314.pyc create mode 100644 __pycache__/saxo_broker.cpython-314.pyc create mode 100644 __pycache__/signals.cpython-314.pyc create mode 100644 analyze.py create mode 100644 c25.json create mode 100644 dashboard.py create mode 100644 db.py create mode 100644 ground-news-ext/extension.xpi create mode 100644 ground-news-ext/src/128.png create mode 100644 ground-news-ext/src/16.png create mode 100644 ground-news-ext/src/32.png create mode 100644 ground-news-ext/src/48.png create mode 100644 ground-news-ext/src/META-INF/cose.manifest create mode 100644 ground-news-ext/src/META-INF/cose.sig create mode 100644 ground-news-ext/src/META-INF/manifest.mf create mode 100644 ground-news-ext/src/META-INF/mozilla.rsa create mode 100644 ground-news-ext/src/META-INF/mozilla.sf create mode 100644 ground-news-ext/src/fonts/UniversalSans-480.ttf create mode 100644 ground-news-ext/src/fonts/UniversalSans-480.woff create mode 100644 ground-news-ext/src/fonts/UniversalSans-680.ttf create mode 100644 ground-news-ext/src/fonts/UniversalSans-680.woff create mode 100644 ground-news-ext/src/fonts/UniversalSans-800.ttf create mode 100644 ground-news-ext/src/fonts/UniversalSans-800.woff create mode 100644 ground-news-ext/src/frame.html create mode 100644 ground-news-ext/src/ground-symbol.png create mode 100644 ground-news-ext/src/ground-symbol.svg create mode 100644 ground-news-ext/src/icons/access-block.png create mode 100644 ground-news-ext/src/icons/bar-chart-2.svg create mode 100644 ground-news-ext/src/icons/book-open-1-black.svg create mode 100644 ground-news-ext/src/icons/bookmark-1-black.svg create mode 100644 ground-news-ext/src/icons/bookmark-1-white.svg create mode 100644 ground-news-ext/src/icons/bookmark-all-white.svg create mode 100644 ground-news-ext/src/icons/circle-dashed-black.svg create mode 100644 ground-news-ext/src/icons/close.svg create mode 100644 ground-news-ext/src/icons/copy.svg create mode 100644 ground-news-ext/src/icons/facebook.svg create mode 100644 ground-news-ext/src/icons/factuality-graph.svg create mode 100644 ground-news-ext/src/icons/info.svg create mode 100644 ground-news-ext/src/icons/linkedin.svg create mode 100644 ground-news-ext/src/icons/lock.svg create mode 100644 ground-news-ext/src/icons/question-solid-white.svg create mode 100644 ground-news-ext/src/icons/question-solid.svg create mode 100644 ground-news-ext/src/icons/reddit.svg create mode 100644 ground-news-ext/src/icons/triangle-exclamation-solid.svg create mode 100644 ground-news-ext/src/icons/twitter.svg create mode 100644 ground-news-ext/src/js/background.js create mode 100644 ground-news-ext/src/js/bluesky.css create mode 100644 ground-news-ext/src/js/bluesky.js create mode 100644 ground-news-ext/src/js/content_script.css create mode 100644 ground-news-ext/src/js/content_script.js create mode 100644 ground-news-ext/src/js/facebook.css create mode 100644 ground-news-ext/src/js/facebook.js create mode 100644 ground-news-ext/src/js/ground.js create mode 100644 ground-news-ext/src/js/index.js create mode 100644 ground-news-ext/src/js/linkedin.css create mode 100644 ground-news-ext/src/js/linkedin.js create mode 100644 ground-news-ext/src/js/menu.js create mode 100644 ground-news-ext/src/js/menu.js.LICENSE.txt create mode 100644 ground-news-ext/src/js/options.js create mode 100644 ground-news-ext/src/js/popup.js create mode 100644 ground-news-ext/src/js/reddit.css create mode 100644 ground-news-ext/src/js/reddit.js create mode 100644 ground-news-ext/src/js/twitter.css create mode 100644 ground-news-ext/src/js/twitter.js create mode 100644 ground-news-ext/src/manifest.json create mode 100644 ground-news-ext/src/menu.html create mode 100644 ground-news-ext/src/options.html create mode 100644 ground-news-ext/src/popup.html create mode 100644 ground_news.db create mode 100644 ground_news.py create mode 100644 logs/dashboard.log create mode 100644 logs/runner_2026-05-26.log create mode 100644 portfolio.py create mode 100644 report.py create mode 100644 rss_feeds.py create mode 100644 runner.py create mode 100644 saxo_auth.py create mode 100644 saxo_broker.py create mode 100644 signals.py diff --git a/.env b/.env new file mode 100644 index 0000000..ae851c3 --- /dev/null +++ b/.env @@ -0,0 +1,15 @@ +anthropic_api_key=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 + +# Saxo Bank SIM API - 24 hour token (refresh daily at developer.saxobank.com/openapi/token) +SAXO_TOKEN=eyJhbGciOiJFUzI1NiIsIng1dCI6IjY3NEM0MjFEMzZEMUE1OUNFNjFBRTIzMjMyOTVFRTAyRTc3MDMzNTkifQ.eyJvYWEiOiI3Nzc3NSIsImlzcyI6Im9hIiwiYWlkIjoiMTA5IiwidWlkIjoiYVFHTDhPUTR2LUU1cjRnTVVFUlltQT09IiwiY2lkIjoiYVFHTDhPUTR2LUU1cjRnTVVFUlltQT09IiwiaXNhIjoiRmFsc2UiLCJ0aWQiOiIyMDAyIiwic2lkIjoiNjE4ZjdjY2YwM2QyNDI0ZTgwMjUyOGM2NjQzYmE3ZjciLCJkZ2kiOiI4NCIsImV4cCI6IjE3Nzk3NTMxNzkiLCJvYWwiOiIxRiIsImlpZCI6ImRmMTdkNTZkMmNkYTRlZmE2ZTM5MDhkZWI4YjExZDYxIn0.F1ltcLpAr_724NqYYpa1Th4A-ibftPpYHcI7vAFQBI-wbOY_VNqakRuCFLAcNN73A_dV99RF-lz6vrrXoIyFkQ +SAXO_BASE=https://gateway.saxobank.com/sim/openapi + +# Saxo OAuth2 App credentials (MoneyMakerHJess) +SAXO_APP_KEY=bce4a7d403b84bc1b000461b25b2824a +SAXO_APP_SECRET_1=43d67cc692c6470796db3e81e493b12e +SAXO_APP_SECRET_2=9ef4f78b87eb4d948c2abdeaea920f14 +SAXO_AUTH_URL=https://sim.logonvalidation.net/authorize +SAXO_TOKEN_URL=https://sim.logonvalidation.net/token +SAXO_REDIRECT=http://localhost:8765/callback +MM_DB_PASS=919129fd5326dfc7817be588 +DATABASE_URL=postgresql://moneymaker:919129fd5326dfc7817be588@int.i80.dk:5432/moneymaker diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..a3eff6c --- /dev/null +++ b/.gitignore @@ -0,0 +1 @@ +.saxo_token.json diff --git a/Makefile b/Makefile new file mode 100644 index 0000000..73e9ac0 --- /dev/null +++ b/Makefile @@ -0,0 +1,68 @@ +PY := .venv/bin/python + +.PHONY: help run signals buy fetch rss analyze force dry company saxo saxo-buy saxo-sell saxo-login saxo-status + +help: + @echo "" + @echo " make → fetch + analyze new articles + vis board" + @echo " make run → samme som make" + @echo " make force → gen-analyser ALLE artikler (med Claude)" + @echo " make dry → dry-run uden at gemme noget" + @echo " make signals → vis signal board" + @echo " make buy → vis kun køb-kandidater" + @echo " make fetch → hent nye artikler fra Ground News" + @echo " make rss → hent danske RSS feeds (Børsen, Finans, Politiken)" + @echo " make orders → vis dagens køb/sælg/hold forslag" + @echo " make portfolio → vis åbne positioner + P&L" + @echo " make company → TICKER=NOVO-B make company" + @echo " make saxo → vis Saxo SIM konto status + positioner" + @echo " make saxo-buy → TICKER=NOVO-B N=5 make saxo-buy" + @echo " make saxo-sell → TICKER=NOVO-B N=5 make saxo-sell" + @echo "" + +run: analyze signals + +analyze: + $(PY) analyze.py + +force: + $(PY) analyze.py --force + +dry: + $(PY) analyze.py --dry-run --force + +signals: + $(PY) signals.py board + +buy: + $(PY) signals.py buy + +fetch: + $(PY) -c "from ground_news import fetch_all, get_db; db=get_db(); fetch_all(db, force=True); print('Done')" + +rss: + $(PY) rss_feeds.py + +orders: + $(PY) portfolio.py orders + +portfolio: + $(PY) portfolio.py status + +company: + $(PY) signals.py company $(TICKER) + +saxo-login: + $(PY) saxo_auth.py login + +saxo-status: + $(PY) saxo_auth.py status + +saxo: + $(PY) saxo_broker.py status + +saxo-buy: + $(PY) saxo_broker.py buy $(TICKER) $(N) + +saxo-sell: + $(PY) saxo_broker.py sell $(TICKER) $(N) diff --git a/__pycache__/analyze.cpython-314.pyc b/__pycache__/analyze.cpython-314.pyc new file mode 100644 index 0000000000000000000000000000000000000000..ea2a72726a4dbf0f3145ab78b7732a5bb74cc439 GIT binary patch literal 25670 zcmb_^dt6)Bo#)m2i3Es;cwgQKgD@{Y@Ph&dgC8JYupGx=MMeT-15&PpAEar?Os18a zbS*c@1gFWzWXEa9ZabyZ_EYa?vop@N-FhCoBO)-0NFq8C)lmHnaQL{ho7m zC1De%{p?)Ox#ynyJLjIq@BGg1bFRXJr$GKlzHMjnS&X&BBh~S{YnovSnUP$Sp3mvIw4KR5EJWJY{l7;n zEqNEq6>FHz^t3a~1(X&j4wQ@(+d7i4Voc1#8FoF!Fyk^(lfxKW&bak=cVi6VP}>=1 zq-1L-&RB&H9LD!FOffSew{?o&OWtkW$+#Fh&5V?z#h=^HVhfX4gE33*tLUu^RQ6T{ 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Financial Signal Extractor + +Pipeline (v2): + 1. Alias screen on title+desc for C25 mentions + 2. Coverage-spread filter: skip low-quality / one-sided articles + 3. NER upgrade: BERT-NER to confirm and expand matches + 4. Full-text fetch + re-screen + 5. FinBERT: quick sentiment — drop neutral < FINBERT_MIN_CONF + 6. Claude: structured extraction (tickers, magnitude, timeframe) + 7. yfinance: momentum check — direction alignment + 8. signal_score = sentiment_confidence × coverage_spread × momentum_alignment + 9. Alert if signal_score > ALERT_THRESHOLD + +Usage: + python3 analyze.py # analyze new articles only + python3 analyze.py --force # re-analyze everything + python3 analyze.py --limit 20 # limit to 20 articles + python3 analyze.py --dry-run # show matches without storing + python3 analyze.py --no-claude # skip Claude step (no API cost) +""" + +import re +import os +import sys +import json +import time +import math +import sqlite3 +import logging +import warnings +from pathlib import Path + +# Silence transformer noise before importing +os.environ.setdefault("TRANSFORMERS_VERBOSITY", "error") +os.environ.setdefault("HF_HUB_DISABLE_PROGRESS_BARS", "1") +warnings.filterwarnings("ignore") +logging.getLogger("transformers").setLevel(logging.ERROR) + +import torch +from transformers import pipeline +from dotenv import load_dotenv + +# Load .env (supports both ANTHROPIC_API_KEY and anthropic_api_key) +_env_file = Path(__file__).parent / ".env" +if _env_file.exists(): + load_dotenv(_env_file, override=False) + for _k, _v in list(os.environ.items()): + if _k.lower() == "anthropic_api_key" and "ANTHROPIC_API_KEY" not in os.environ: + os.environ["ANTHROPIC_API_KEY"] = _v + +# Ground News helpers +sys.path.insert(0, str(Path(__file__).parent)) +from ground_news import get_db, fetch_article_text, fetch_all +from rss_feeds import fetch_all_rss + +# --------------------------------------------------------------------------- +# Config +# --------------------------------------------------------------------------- + +C25_PATH = Path(__file__).parent / "c25.json" +_c25_raw = json.loads(C25_PATH.read_text()) +C25: dict[str, dict] = {k: v for k, v in _c25_raw.items() if not k.startswith("_")} + +# Build alias → ticker lookup (lower-cased for matching) +ALIAS_MAP: dict[str, str] = {} +for _ticker, _data in C25.items(): + for _alias in _data["aliases"]: + al = _alias.lower() + if al not in ALIAS_MAP: # first alias wins (most specific first in c25.json) + ALIAS_MAP[al] = _ticker + +DEVICE = -1 # always CPU — Quadro P400 (CC 6.1) too old + too little VRAM for these models + +# Quality thresholds +MIN_SOURCES = 1 # coverage_spread naturally weights single-source articles near zero +MIN_COVERAGE_SPREAD = 0.0 # disabled: signal_score naturally zeros out single-source articles +FINBERT_MIN_CONF = 0.70 # drop neutral articles below this FinBERT confidence +ALERT_THRESHOLD = 0.35 # signal_score > this → alert + + +# --------------------------------------------------------------------------- +# Model loading +# --------------------------------------------------------------------------- + +_ner_model = None +_finbert_model = None + + +def get_ner(): + global _ner_model + if _ner_model is None: + print("[analyze] Loading dslim/bert-base-NER …", flush=True) + _ner_model = pipeline( + "ner", + model="dslim/bert-base-NER", + aggregation_strategy="simple", + device=DEVICE, + ) + return _ner_model + + +def get_finbert(): + global _finbert_model + if _finbert_model is None: + print("[analyze] Loading ProsusAI/finbert …", flush=True) + _finbert_model = pipeline( + "sentiment-analysis", + model="ProsusAI/finbert", + device=DEVICE, + truncation=True, + max_length=512, + ) + return _finbert_model + + +# --------------------------------------------------------------------------- +# C25 alias matching +# --------------------------------------------------------------------------- + +def match_c25(text: str) -> dict[str, float]: + """ + Find C25 companies mentioned in text. + Returns {ticker: confidence_score}. + """ + text_lower = text.lower() + matches: dict[str, float] = {} + + for alias_lower, ticker in ALIAS_MAP.items(): + if ticker in matches: + continue # already found this company + + # Always use word boundaries — prevents "sonic" matching "hypersonic", + # "net" matching "internet", "iss" matching "mission", etc. + pat = r"(? dict[str, float]: + """ + Cross-reference NER ORG entities with alias map. + Requires whole-token match to avoid 'EMA' matching 'd-ema-nt'. + """ + merged = dict(base) + for ent in ner_result: + if ent.get("entity_group") not in ("ORG", "PER"): + continue + word_tokens = set(re.split(r"[\s\-_/]+", ent["word"].lower().strip("##"))) + for alias_lower, ticker in ALIAS_MAP.items(): + if len(alias_lower) < 4: + continue + alias_tokens = set(re.split(r"[\s\-_/]+", alias_lower)) + # Need significant token overlap, not just substring containment + overlap = alias_tokens & word_tokens + if overlap and len(overlap) / max(len(alias_tokens), len(word_tokens)) >= 0.5: + score = ent.get("score", 0.7) + if score > merged.get(ticker, 0): + merged[ticker] = score + return merged + + + + +# --------------------------------------------------------------------------- +# Coverage spread scoring +# --------------------------------------------------------------------------- + +def coverage_spread_score(row) -> float: + """ + Quality score (0–1) based on source count and bias diversity. + High = many sources from left + right + centre. Low = few or echo chamber. + """ + src = row["source_count"] or 0 + left = row["left_src_count"] or 0 + right = row["right_src_count"] or 0 + ctr = row["ctr_src_count"] or 0 + + if src < MIN_SOURCES: + return 0.0 + + quantity = min(1.0, math.log(max(1, src)) / math.log(50)) + fl, fr, fc = left / src, right / src, ctr / src + diversity = min(1.0, (fl * fr * fc) ** (1 / 3) * 9) # peaks at equal thirds + + return round(quantity * 0.6 + diversity * 0.4, 3) + + +# --------------------------------------------------------------------------- +# Claude structured extraction +# --------------------------------------------------------------------------- + +def claude_extract(title: str, text: str, tickers: list[str]) -> dict: + """ + Use Claude Haiku to extract structured financial signal. + Returns {"confirmed_tickers", "magnitude", "timeframe", "reasoning"}. + """ + import anthropic + + api_key = os.environ.get("ANTHROPIC_API_KEY") + if not api_key: + return {"confirmed_tickers": tickers, "magnitude": 5, "timeframe": "days", "reasoning": "(no API key)"} + + client = anthropic.Anthropic(api_key=api_key) + ticker_ctx = "\n".join( + f" {t}: {C25[t]['name']} ({C25[t]['sector']})" for t in tickers if t in C25 + ) + + prompt = f"""You are a financial analyst specializing in Scandinavian equities. + +Analyze this news article and assess its financial impact on the listed Danish C25 companies. + +## Companies to analyze: +{ticker_ctx} + +## Article: +Title: {title} +{text[:1500]} + +Respond ONLY with valid JSON (no markdown fences): +{{ + "confirmed_tickers": ["NOVO-B"], + "magnitude": 7, + "timeframe": "days", + "reasoning": "Two sentences max on financial impact and direction." +}} + +Fields: +- confirmed_tickers: only companies truly affected (can be []) +- magnitude: 1–10 (1=irrelevant, 10=major market mover) +- timeframe: "hours", "days", "weeks", or "months" +- reasoning: brief analyst note""" + + try: + msg = client.messages.create( + model="claude-haiku-4-5", + max_tokens=256, + messages=[{"role": "user", "content": prompt}], + ) + raw = msg.content[0].text.strip() + raw = re.sub(r"^```(?:json)?\n?", "", raw) + raw = re.sub(r"\n?```$", "", raw) + return json.loads(raw) + except Exception as e: + print(f" [warn] Claude failed: {e}") + return {"confirmed_tickers": tickers, "magnitude": 5, "timeframe": "days", "reasoning": str(e)[:120]} + + +# --------------------------------------------------------------------------- +# yfinance momentum +# --------------------------------------------------------------------------- + +_momentum_cache: dict[str, dict] = {} + + +def momentum_check(ticker: str) -> dict: + """5-day price momentum for a C25 ticker via yfinance.""" + if ticker in _momentum_cache: + return _momentum_cache[ticker] + + import yfinance as yf + + company = C25.get(ticker, {}) + yahoo_ticker = company.get("yahoo_ticker", ticker + ".CO") + result: dict = {"direction": "unknown", "pct_5d": 0.0, "pct_20d": 0.0} + + try: + hist = yf.Ticker(yahoo_ticker).history(period="1mo", auto_adjust=True) + if len(hist) >= 5: + close = hist["Close"] + pct_5d = float((close.iloc[-1] / close.iloc[-5] - 1) * 100) + pct_20d = float((close.iloc[-1] / close.iloc[0] - 1) * 100) if len(hist) >= 20 else 0.0 + direction = "up" if pct_5d > 1.5 else ("down" if pct_5d < -1.5 else "flat") + result = {"direction": direction, "pct_5d": round(pct_5d, 2), "pct_20d": round(pct_20d, 2)} + except Exception: + pass + + _momentum_cache[ticker] = result + return result + + +# --------------------------------------------------------------------------- +# Signal score +# --------------------------------------------------------------------------- + +def calc_signal_score(sent_score: float, sentiment: str, coverage: float, momentum: dict) -> float: + """signal_score = sentiment_confidence × coverage_spread × momentum_alignment""" + d = momentum.get("direction", "unknown") + if d == "unknown": + alignment = 0.5 + elif d == "flat": + alignment = 0.7 + elif (sentiment == "positive" and d == "up") or (sentiment == "negative" and d == "down"): + alignment = 1.0 + else: + alignment = 0.4 # contrarian + + return round(sent_score * coverage * alignment, 3) + + +# --------------------------------------------------------------------------- +# DB schema migration +# --------------------------------------------------------------------------- + +def migrate_db(db) -> None: + """Apply schema migrations for SQLite. No-op for Postgres (schema managed by db.py).""" + if hasattr(db, "db_type") and db.db_type == "postgres": + return + existing = {row[1] for row in db.execute("PRAGMA table_info(article_signals)").fetchall()} + new_cols = [ + ("coverage_spread", "REAL DEFAULT 0"), + ("claude_tickers", "TEXT"), + ("claude_magnitude", "INTEGER DEFAULT 5"), + ("claude_timeframe", "TEXT"), + ("claude_reasoning", "TEXT"), + ("momentum_dir", "TEXT"), + ("momentum_pct_5d", "REAL DEFAULT 0"), + ("signal_score", "REAL DEFAULT 0"), + ("alert", "INTEGER DEFAULT 0"), + ] + for col_name, col_def in new_cols: + if col_name not in existing: + db.execute(f"ALTER TABLE article_signals ADD COLUMN {col_name} {col_def}") + db.commit() + + +# --------------------------------------------------------------------------- +# Main pipeline +# --------------------------------------------------------------------------- + +def analyze_articles( + *, + force: bool = False, + limit: int | None = None, + dry_run: bool = False, + use_claude: bool = True, + auto_fetch: bool = True, +) -> None: + db = get_db() + migrate_db(db) + + # Auto-refresh articles (respects 30-min cache TTL) + if auto_fetch and not dry_run: + before = db.execute("SELECT COUNT(*) AS cnt FROM articles").fetchone()["cnt"] + print("[analyze] Refreshing Ground News feed …") + fetch_all(db) + print("[analyze] Henter danske RSS feeds …") + fetch_all_rss(db) + after = db.execute("SELECT COUNT(*) AS cnt FROM articles").fetchone()["cnt"] + if after > before: + print(f"[analyze] +{after - before} new articles") + + base_q = """ + SELECT slug, title, description, source_count, + left_src_count, right_src_count, ctr_src_count, + left_pct, right_pct, ctr_pct + FROM articles {where} + ORDER BY source_count DESC + """ + rows = db.execute( + base_q.format(where="" if force else + "WHERE slug NOT IN (SELECT DISTINCT article_slug FROM article_signals)") + ).fetchall() + if limit: + rows = rows[:limit] + + total = len(rows) + print(f"[analyze] {total} articles to process (force={force} dry_run={dry_run} claude={use_claude})") + if total == 0: + print("[analyze] Nothing to do.") + db.close() + return + + # ------------------------------------------------------------------ + # Phase 1 — Alias screen + coverage spread filter + # ------------------------------------------------------------------ + print("[analyze] Phase 1: alias screen + coverage filter …") + screened: list[tuple] = [] + dropped_cov = 0 + + for row in rows: + cov = coverage_spread_score(row) + if cov < MIN_COVERAGE_SPREAD: + dropped_cov += 1 + continue + text = f"{row['title']}. {row['description'] or ''}" + matches = match_c25(text) + if matches: + screened.append((row, matches, cov)) + + print(f"[analyze] {len(screened)}/{total} passed ({dropped_cov} dropped by coverage filter)") + if not screened: + db.close() + return + + # ------------------------------------------------------------------ + # Phase 2 — NER upgrade + # ------------------------------------------------------------------ + print("[analyze] Phase 2: NER upgrade …") + ner = get_ner() + texts = [f"{r['title']}. {r['description'] or ''}" for r, _, _ in screened] + + BATCH = 16 + all_ner = [] + for i in range(0, len(texts), BATCH): + all_ner.extend(ner(texts[i : i + BATCH])) + + enriched = [ + (row, merge_ner_matches(ner_res, base), cov) + for (row, base, cov), ner_res in zip(screened, all_ner) + ] + + # ------------------------------------------------------------------ + # Phase 3 — Full text + re-screen + # ------------------------------------------------------------------ + print(f"[analyze] Phase 3: fetching full text for {len(enriched)} articles …") + final: list[tuple] = [] + + for idx, (row, matches, cov) in enumerate(enriched, 1): + slug = row["slug"] + if idx % 5 == 0 or idx == len(enriched): + print(f" {idx}/{len(enriched)}: {slug[:55]}") + + # RSS artikler har teksten gemt i page_cache som "rss:{slug}" + cats = row["categories"] if "categories" in row.keys() else "" + if cats and cats.startswith("rss:"): + cache_row = db.execute( + "SELECT content FROM page_cache WHERE url = ?", + (f"rss:{slug}",), + ).fetchone() + full_text = cache_row["content"] if cache_row else f"{row['title']}. {row['description'] or ''}" + else: + full_text = fetch_article_text(slug, db) + + full_matches = match_c25(full_text) + for ticker, score in full_matches.items(): + if score > matches.get(ticker, 0): + matches[ticker] = score + if matches: + final.append((row, matches, cov, full_text)) + + print(f"[analyze] {len(final)} articles with confirmed C25 mentions") + + # ------------------------------------------------------------------ + # Phase 4 — FinBERT sentiment (confidence filter) + # ------------------------------------------------------------------ + print("[analyze] Phase 4: FinBERT sentiment …") + finbert = get_finbert() + now = int(time.time()) + signals_written = 0 + alerts_triggered = 0 + + for row, matches, cov, full_text in final: + slug = row["slug"] + title = row["title"] + + try: + fb = finbert(" ".join(full_text.split()[:400]))[0] + sentiment = fb["label"].lower() + sent_score = round(fb["score"], 4) + except Exception as e: + print(f" [warn] FinBERT: {e}") + sentiment, sent_score = "neutral", 0.5 + + if sentiment == "neutral" and sent_score < FINBERT_MIN_CONF: + continue # drop low-confidence neutral noise + + # ------------------------------------------------------------------ + # Phase 5 — Claude extraction + # ------------------------------------------------------------------ + claude_data: dict = {} + if use_claude and not dry_run and os.environ.get("ANTHROPIC_API_KEY"): + print(f" [claude] {slug[:50]}") + claude_data = claude_extract(title, full_text, list(matches.keys())) + + # ------------------------------------------------------------------ + # Phase 6 — yfinance momentum + scoring + # ------------------------------------------------------------------ + for ticker, entity_score in matches.items(): + company = C25[ticker] + full_lower = full_text.lower() + mention_count = max(1, sum( + len(re.findall( + r"(? ALERT_THRESHOLD and sentiment != "neutral" + + if dry_run: + print( + f" DRY: {slug[:38]:<38} | {ticker:<8} | " + f"{sentiment:<8} {sent_score:.2f} | cov={cov:.2f} | sig={sig_score:.3f}" + f"{' ⚡' if alert else ''}" + ) + else: + db.upsert( + "article_signals", + ["article_slug", "ticker"], + [ + "article_slug", "ticker", "company_name", "sector", + "sentiment", "sentiment_score", "entity_score", + "mention_count", "full_text_used", "analyzed_at", + "coverage_spread", "claude_tickers", "claude_magnitude", + "claude_timeframe", "claude_reasoning", + "momentum_dir", "momentum_pct_5d", "signal_score", "alert", + ], + ( + slug, ticker, company["name"], company["sector"], + sentiment, float(sent_score), round(float(entity_score), 4), + mention_count, 1, now, + float(cov), + json.dumps(claude_data.get("confirmed_tickers", [])) or None, + claude_data.get("magnitude", 5), + claude_data.get("timeframe", "days"), + claude_data.get("reasoning", ""), + momentum.get("direction", "unknown"), + float(momentum.get("pct_5d", 0.0)), + float(sig_score), + int(alert), + ), + ) + signals_written += 1 + if alert: + alerts_triggered += 1 + icon = "↑" if sentiment == "positive" else "↓" + print( + f" ⚡ ALERT: {icon} {ticker} ({company['name']}) | " + f"{sentiment} {sent_score:.2f} | sig={sig_score:.3f} | {slug[:40]}" + ) + + if not dry_run: + db.commit() + print(f"[analyze] Done. {signals_written} signals written, {alerts_triggered} alerts triggered.") + else: + print(f"[analyze] Dry-run complete. {len(final)} articles matched.") + + db.close() + + +# --------------------------------------------------------------------------- +# CLI — brug Makefile i stedet for at huske flags +# --------------------------------------------------------------------------- + +def main() -> None: + import sys + force = "--force" in sys.argv + dry_run = "--dry" in sys.argv + analyze_articles(force=force, dry_run=dry_run) + + +if __name__ == "__main__": + main() diff --git a/c25.json b/c25.json new file mode 100644 index 0000000..a42d827 --- /dev/null +++ b/c25.json @@ -0,0 +1,339 @@ +{ + "_meta": { + "description": "C25 company universe with NER aliases, sector tags, price tiers, and leveraged instruments", + "updated": "2026-05-25", + "price_source": "Yahoo Finance (DKK, indicative — refresh with yfinance)", + "leveraged_source": "WisdomTree ETP catalogue (Xetra/Euronext Paris)", + "tiers": { + "budget": "< 200 DKK — buy directly, multiple shares", + "accessible": "200-500 DKK — buy 1-2 shares", + "expensive": "500-2000 DKK — consider leveraged ETP", + "inaccessible": "> 2000 DKK — leveraged ETP strongly recommended" + } + }, + + "AMBU-B": { + "name": "Ambu A/S", + "ticker_yahoo": "AMBU-B.CO", + "sector": "medtech", + "tier": "budget", + "price_dkk_approx": 68, + "aliases": [ + "Ambu", "Ambu A/S", "Ambu B", "AMBU" + ], + "keywords": ["endoscopy", "single-use", "endoscope", "bronchoscope", "disposable medical"], + "leveraged": [] + }, + + "GN": { + "name": "GN Store Nord A/S", + "ticker_yahoo": "GN.CO", + "sector": "medtech", + "tier": "budget", + "price_dkk_approx": 95, + "aliases": [ + "GN Store Nord", "GN Audio", "Jabra", "GN Group", "SteelSeries", "Beltone" + ], + "keywords": ["hearing aids", "headsets", "audio", "cochlear implants", "Jabra headset"], + "leveraged": [] + }, + + "TRYG": { + "name": "Tryg A/S", + "ticker_yahoo": "TRYG.CO", + "sector": "insurance", + "tier": "budget", + "price_dkk_approx": 156, + "aliases": [ + "Tryg", "Tryg Forsikring", "Tryg A/S", "TrygVesta" + ], + "keywords": ["insurance", "Danish insurance", "P&C insurance", "Nordic insurance"], + "leveraged": [] + }, + + "ORSTED": { + "name": "Ørsted A/S", + "ticker_yahoo": "ORSTED.CO", + "sector": "energy", + "tier": "budget", + "price_dkk_approx": 167, + "aliases": [ + "Ørsted", "Orsted", "DONG Energy", "Ørsted A/S", "Oersted" + ], + "keywords": ["offshore wind", "wind energy", "renewable energy", "green energy", + "wind farm", "hydrogen", "North Sea wind"], + "leveraged": [ + {"ticker": "3ORE", "name": "WisdomTree Ørsted 3x Daily Long", "exchange": "Xetra", "direction": "long"}, + {"ticker": "SORE", "name": "WisdomTree Ørsted -3x Daily Short", "exchange": "Xetra", "direction": "short"} + ] + }, + + "ROCK-B": { + "name": "Rockwool International B", + "ticker_yahoo": "ROCK-B.CO", + "sector": "materials", + "tier": "budget", + "price_dkk_approx": 192, + "aliases": [ + "Rockwool", "ROCKWOOL", "Rockwool International", "Rockfon", "Roxul" + ], + "keywords": ["insulation", "stone wool", "building materials", "energy efficiency", + "fire safety insulation"], + "leveraged": [] + }, + + "VWS": { + "name": "Vestas Wind Systems A/S", + "ticker_yahoo": "VWS.CO", + "sector": "energy", + "tier": "budget", + "price_dkk_approx": 195, + "aliases": [ + "Vestas", "Vestas Wind", "Vestas Wind Systems", "VWS" + ], + "keywords": ["wind turbines", "wind power", "offshore wind", "onshore wind", + "turbine manufacturer", "renewable energy"], + "leveraged": [ + {"ticker": "3VWS", "name": "WisdomTree Vestas Wind Systems 3x Daily Long", "exchange": "Xetra", "direction": "long"}, + {"ticker": "SVWS", "name": "WisdomTree Vestas Wind Systems -3x Daily Short", "exchange": "Xetra", "direction": "short"} + ] + }, + + "BAVA": { + "name": "Bavarian Nordic A/S", + "ticker_yahoo": "BAVA.CO", + "sector": "pharma", + "tier": "budget", + "price_dkk_approx": 197, + "aliases": [ + "Bavarian Nordic", "BavNordic", "BAVA", "Imvamune", "Imvanex", "Jynneos", + "BN Biopharma" + ], + "keywords": ["vaccines", "mpox vaccine", "smallpox vaccine", "RSV vaccine", + "cancer immunotherapy", "monkeypox"], + "leveraged": [] + }, + + "DEMANT": { + "name": "Demant A/S", + "ticker_yahoo": "DEMANT.CO", + "sector": "medtech", + "tier": "accessible", + "price_dkk_approx": 247, + "aliases": [ + "Demant", "William Demant", "Oticon", "Bernafon", "Sonic", "Philips Hearing" + ], + "keywords": ["hearing aids", "hearing implants", "audiological equipment", + "cochlear implants", "Oticon hearing"], + "leveraged": [] + }, + + "ISS": { + "name": "ISS A/S", + "ticker_yahoo": "ISS.CO", + "sector": "services", + "tier": "accessible", + "price_dkk_approx": 265, + "aliases": [ + "ISS", "ISS A/S", "ISS World Services", "ISS Facility Services" + ], + "keywords": ["facility services", "cleaning services", "facility management", + "workplace services"], + "leveraged": [] + }, + + "NOVO-B": { + "name": "Novo Nordisk B", + "ticker_yahoo": "NOVO-B.CO", + "sector": "pharma", + "tier": "accessible", + "price_dkk_approx": 289, + "aliases": [ + "Novo Nordisk", "Novo", "NVO", "NNO", "NovoNordisk", + "Ozempic", "Wegovy", "Rybelsus", "Victoza", "Semaglutide", + "Tresiba", "Levemir", "NovoLog", "Fiasp" + ], + "keywords": ["GLP-1", "diabetes", "obesity", "insulin", "semaglutide", + "weight loss drug", "FDA approval", "EMA approval", + "weight management", "cardiovascular"], + "leveraged": [ + {"ticker": "3NOV", "name": "WisdomTree Novo Nordisk 3x Daily Long", "exchange": "Xetra", "direction": "long"}, + {"ticker": "SNOV", "name": "WisdomTree Novo Nordisk -3x Daily Short", "exchange": "Xetra", "direction": "short"} + ] + }, + + "ZEAL": { + "name": "Zealand Pharma A/S", + "ticker_yahoo": "ZEAL.CO", + "sector": "pharma", + "tier": "accessible", + "price_dkk_approx": 318, + "aliases": [ + "Zealand Pharma", "Zealand", "ZEAL", "Zegalogue", "Dasiglucagon", + "Petrelintide", "Glepaglutide" + ], + "keywords": ["peptide drugs", "GLP-1", "obesity", "short bowel syndrome", + "glucagon", "clinical trials", "FDA"], + "leveraged": [] + }, + + "DANSKE": { + "name": "Danske Bank A/S", + "ticker_yahoo": "DANSKE.CO", + "sector": "finance", + "tier": "accessible", + "price_dkk_approx": 332, + "aliases": [ + "Danske Bank", "Danske", "Danica Pension", "Northern Bank", + "Realkredit Danmark" + ], + "keywords": ["Danish bank", "banking", "mortgage", "money laundering", + "Nordic finance", "interest rates"], + "leveraged": [] + }, + + "NETC": { + "name": "Netcompany Group A/S", + "ticker_yahoo": "NETC.CO", + "sector": "technology", + "tier": "accessible", + "price_dkk_approx": 340, + "aliases": [ + "Netcompany", "NETC", "Netcompany Group" + ], + "keywords": ["IT consulting", "digital transformation", "public sector IT", + "cloud services", "Danish IT"], + "leveraged": [] + }, + + "COLO-B": { + "name": "Coloplast B", + "ticker_yahoo": "COLO-B.CO", + "sector": "medtech", + "tier": "accessible", + "price_dkk_approx": 404, + "aliases": [ + "Coloplast", "Coloplast B", "COLO", "Coloplast A/S" + ], + "keywords": ["ostomy", "wound care", "continence care", "urology", + "medical devices", "stoma"], + "leveraged": [] + }, + + "FLS": { + "name": "FLSmidth & Co. A/S", + "ticker_yahoo": "FLS.CO", + "sector": "industrials", + "tier": "expensive", + "price_dkk_approx": 516, + "aliases": [ + "FLSmidth", "FL Smidth", "FLS", "FLSmidth & Co" + ], + "keywords": ["cement equipment", "mining equipment", "green transition mining", + "cement plant", "copper mining"], + "leveraged": [] + }, + + "PNDORA": { + "name": "Pandora A/S", + "ticker_yahoo": "PNDORA.CO", + "sector": "retail", + "tier": "expensive", + "price_dkk_approx": 556, + "aliases": [ + "Pandora", "Pandora A/S", "Pandora jewelry", "Pandora charms", + "Pandora bracelet" + ], + "keywords": ["jewelry", "silver jewelry", "charm bracelets", + "luxury goods", "consumer discretionary"], + "leveraged": [] + }, + + "CARL-B": { + "name": "Carlsberg B", + "ticker_yahoo": "CARL-B.CO", + "sector": "beverages", + "tier": "expensive", + "price_dkk_approx": 878, + "aliases": [ + "Carlsberg", "Carlsberg B", "Carlsberg Group", "Tuborg", + "Kronenbourg", "1664", "Baltika", "Astra" + ], + "keywords": ["beer", "brewery", "lager", "alcohol", "beverage company", + "Western European beer", "Eastern European beer"], + "leveraged": [ + {"ticker": "3CAR", "name": "WisdomTree Carlsberg 3x Daily Long", "exchange": "Xetra", "direction": "long"}, + {"ticker": "SCAR", "name": "WisdomTree Carlsberg -3x Daily Short", "exchange": "Xetra", "direction": "short"} + ] + }, + + "NKT": { + "name": "NKT A/S", + "ticker_yahoo": "NKT.CO", + "sector": "industrials", + "tier": "expensive", + "price_dkk_approx": 1112, + "aliases": [ + "NKT", "NKT A/S", "NKT Cables", "NKT cable" + ], + "keywords": ["power cables", "high voltage cables", "offshore cables", + "subsea cables", "grid infrastructure", "energy transition"], + "leveraged": [] + }, + + "DSV": { + "name": "DSV A/S", + "ticker_yahoo": "DSV.CO", + "sector": "logistics", + "tier": "inaccessible", + "price_dkk_approx": 1522, + "aliases": [ + "DSV", "DSV A/S", "DSV Panalpina", "Panalpina", "DSV Air & Sea", + "DSV Road", "Schenker", "DB Schenker" + ], + "keywords": ["freight", "logistics", "supply chain", "air freight", + "sea freight", "global logistics", "3PL"], + "leveraged": [ + {"ticker": "3DSV", "name": "WisdomTree DSV 3x Daily Long", "exchange": "Xetra", "direction": "long"}, + {"ticker": "SDSV", "name": "WisdomTree DSV -3x Daily Short", "exchange": "Xetra", "direction": "short"} + ] + }, + + "GMAB": { + "name": "Genmab A/S", + "ticker_yahoo": "GMAB.CO", + "sector": "pharma", + "tier": "inaccessible", + "price_dkk_approx": 1724, + "aliases": [ + "Genmab", "GMAB", "Genmab A/S", "Darzalex", "Daratumumab", + "Epkinly", "Epcoritamab", "Kesimpta", "Ofatumumab" + ], + "keywords": ["antibody drugs", "oncology", "multiple myeloma", + "cancer treatment", "bispecific antibodies", "FDA approval"], + "leveraged": [ + {"ticker": "3GEN", "name": "WisdomTree Genmab 3x Daily Long", "exchange": "Xetra", "direction": "long"}, + {"ticker": "SGEN", "name": "WisdomTree Genmab -3x Daily Short", "exchange": "Xetra", "direction": "short"} + ] + }, + + "MAERSK-B": { + "name": "A.P. Møller - Mærsk B", + "ticker_yahoo": "MAERSK-B.CO", + "sector": "shipping", + "tier": "inaccessible", + "price_dkk_approx": 15280, + "aliases": [ + "Mærsk", "Maersk", "A.P. Moller", "A.P. Møller", "AP Moller", + "Møller-Mærsk", "Moller-Maersk", "APM", "APM Terminals", + "Maersk Line", "Mærsk Line", "Sealand" + ], + "keywords": ["container shipping", "shipping rates", "ocean freight", + "logistics", "Red Sea", "Suez Canal", "port congestion", + "supply chain", "container rates", "spot rates"], + "leveraged": [ + {"ticker": "3MRS", "name": "WisdomTree A.P. Møller-Mærsk 3x Daily Long", "exchange": "Xetra", "direction": "long"}, + {"ticker": "SMRS", "name": "WisdomTree A.P. Møller-Mærsk -3x Daily Short", "exchange": "Xetra", "direction": "short"} + ] + } +} diff --git a/dashboard.py b/dashboard.py new file mode 100644 index 0000000..a4345a0 --- /dev/null +++ b/dashboard.py @@ -0,0 +1,327 @@ +""" +dashboard.py — MoneyMaker live monitoring dashboard. + +Usage: + python dashboard.py # starts on http://localhost:5001 + python dashboard.py --port 5002 + +Auto-refreshes every 60 seconds. Shows: + • Portfolio P&L + C25 benchmark + • Open positions with live prices + • Closed trades (win/loss) + • Signal accuracy + • Recent runner log tail +""" +import argparse +import json +import time +from datetime import datetime, timezone +from pathlib import Path + +import yfinance as yf +from flask import Flask, render_template_string + +from db import get_conn, DB_TYPE +from report import _c25_day_return, _unrealised_pnl, _realised_pnl, _total_fees, _signal_accuracy + +CAPITAL = 10_000 +LOG_DIR = Path(__file__).parent / "logs" +REFRESH = 60 # seconds + +app = Flask(__name__) + +# ── HTML template ──────────────────────────────────────────────────────────── + +TEMPLATE = """ + + + + + + + MoneyMaker Dashboard + + + +

📈 MoneyMaker

+
DB: {{ db_type }}  ·  Opdateret: {{ now }}  ·  Refresh om {{ refresh }}s
+ + +
+
+
Net P&L
+
{{ "{:+,.0f}".format(net_pnl) }} kr
+
{{ "{:+.2f}%".format(net_pct) }}
+
+
+
Urealiseret
+
{{ "{:+,.0f}".format(unreal) }} kr
+
{{ open_count }} åben{{ 'e' if open_count != 1 else '' }} position{{ 'er' if open_count != 1 else '' }}
+
+
+
Realiseret
+
{{ "{:+,.0f}".format(realised) }} kr
+
Gebyrer: {{ "{:,.0f}".format(fees) }} kr
+
+
+
C25 i dag
+ {% if c25_ret is not none %} +
{{ "{:+.2f}%".format(c25_ret) }}
+
+ vs benchmark: {{ "{:+.2f}%".format(vs_bench) if vs_bench is not none else "—" }} +
+ {% else %} +
—
+
Marked lukket?
+ {% endif %} +
+
+
Signal accuracy
+ {% if sig.total_trades > 0 %} +
{{ "{:.0f}%".format(sig.accuracy_pct) }}
+
{{ sig.correct }} / {{ sig.total_trades }} handler korrekte
+ {% else %} +
—
+
Ingen lukkede handler
+ {% endif %} +
+
+
Kapital
+
{{ "{:,.0f}".format(capital) }} kr
+
Kontant: {{ "{:,.0f}".format(cash) }} kr
+
+
+ + +
+
📊 Åbne positioner
+ {% if positions %} + + + {% for p in positions %} + + + + + + + + + + + + {% endfor %} +
TickerAntalKøbtNuP&LÆndringStopTakeStatus
{{ p.ticker }}{{ "{:.0f}".format(p.shares) }}{{ "{:,.0f}".format(p.entry) }}{{ "{:,.0f}".format(p.last) }}{{ "{:+,.0f}".format(p.unreal) }}{{ "{:+.1f}%".format(p.pct) }}{{ "{:,.0f}".format(p.stop) }}{{ "{:,.0f}".format(p.take) }} + {% if p.stop_hit %}🔴 STOP + {% elif p.take_hit %}🟡 TAKE + {% else %}⏳ HOLD{% endif %} +
+ {% else %} +

Ingen åbne positioner.

+ {% endif %} +
+ + +
+
🏁 Lukkede handler
+ {% if trades %} + + + {% for t in trades %} + + + + + + + + + + + {% endfor %} +
TickerHandlingAntalKursTotalP&LSignalDato
{{ t.ticker }}{{ t.action.upper() }}{{ "{:.0f}".format(t.shares) }}{{ "{:,.0f}".format(t.price) }}{{ "{:,.0f}".format(t.total_dkk) }} + {{ "{:+,.0f}".format(t.pnl_dkk) if t.pnl_dkk is not none else "—" }} + + {% if t.signal_correct == 1 %}✅ korrekt + {% elif t.signal_correct == 0 %}❌ forkert + {% else %}—{% endif %} + {{ t.event_date }}
+ {% else %} +

Ingen handler endnu.

+ {% endif %} +
+ + +
+
🔬 NLP signal pipeline
+ + + + + + + +
Analyserede signalerAlert-triggers (≥threshold)Gns. score
{{ sig.total }}{{ sig.alerts }}{{ "{:.3f}".format(sig.avg_score) }}
+
+ + + {% if log_tail %} +
+
📋 Seneste log ({{ log_file }})
+ 
{{ log_tail }}
+
+ {% endif %} + +
MoneyMaker · {{ db_type }} · hjess-desktop · auto-refresh {{ refresh }}s
+ + +""" + + +# ── Data helpers ───────────────────────────────────────────────────────────── + +def _latest_log_tail(lines: int = 40) -> tuple[str, str]: + """Return (filename, last N lines) from most recent runner log.""" + if not LOG_DIR.exists(): + return "", "" + logs = sorted(LOG_DIR.glob("runner_*.log"), reverse=True) + if not logs: + return "", "" + path = logs[0] + try: + content = path.read_text(errors="replace") + tail = "\n".join(content.splitlines()[-lines:]) + return path.name, tail + except Exception: + return path.name, "" + + +def _open_positions_live(db) -> list[dict]: + """Fetch open positions with live yfinance prices.""" + rows = db.execute("SELECT * FROM positions").fetchall() + result = [] + for p in rows: + ticker = p["ticker"] + from report import C25 + yf_ticker = C25.get(ticker, {}).get("ticker_yahoo", ticker + ".CO") + try: + last = yf.Ticker(yf_ticker).fast_info.get("lastPrice") or p["entry_price"] + except Exception: + last = p["entry_price"] + entry = float(p["entry_price"]) + shares = float(p["shares"]) + pct = (last - entry) / entry * 100 + result.append({ + "ticker": ticker, + "shares": shares, + "entry": entry, + "last": last, + "unreal": shares * (last - entry), + "pct": pct, + "stop": float(p["stop_loss"]), + "take": float(p["take_profit"]), + "stop_hit": last <= p["stop_loss"], + "take_hit": last >= p["take_profit"], + }) + return result + + +def _closed_trades(db, limit: int = 20) -> list[dict]: + rows = db.execute(""" + SELECT ticker, action, shares, price, total_dkk, pnl_dkk, signal_correct, event_date + FROM position_events + ORDER BY id DESC LIMIT ? + """, (limit,)).fetchall() + return [dict(r) for r in rows] + + +# ── Routes ──────────────────────────────────────────────────────────────────── + +@app.route("/") +def index(): + db = get_conn() + try: + positions = _open_positions_live(db) + trades = _closed_trades(db) + unreal = sum(p["unreal"] for p in positions) + invested = sum(p["shares"] * p["entry"] for p in positions) + realised = _realised_pnl(db) + fees = _total_fees(db) + sig = _signal_accuracy(db) + c25_ret = _c25_day_return() + net_pnl = realised + unreal - fees + net_pct = net_pnl / CAPITAL * 100 + vs_bench = (net_pct - c25_ret) if c25_ret is not None else None + cash = CAPITAL - invested + log_file, log_tail = _latest_log_tail() + now = datetime.now(timezone.utc).strftime("%d %b %Y %H:%M UTC") + + return render_template_string( + TEMPLATE, + now=now, + db_type=DB_TYPE, + refresh=REFRESH, + capital=CAPITAL, + cash=cash, + unreal=unreal, + realised=realised, + fees=fees, + net_pnl=net_pnl, + net_pct=net_pct, + c25_ret=c25_ret, + vs_bench=vs_bench, + positions=positions, + open_count=len(positions), + trades=trades, + sig=type("Sig", (), sig)(), + log_file=log_file, + log_tail=log_tail, + ) + finally: + db.close() + + +@app.route("/health") +def health(): + return {"status": "ok", "db": DB_TYPE, "ts": time.time()} + + +# ── Main ────────────────────────────────────────────────────────────────────── + +def main(): + parser = argparse.ArgumentParser(description="MoneyMaker Dashboard") + parser.add_argument("--port", type=int, default=5001) + parser.add_argument("--host", default="0.0.0.0") + args = parser.parse_args() + print(f"\n MoneyMaker Dashboard → http://localhost:{args.port}\n") + app.run(host=args.host, port=args.port, debug=False) + + +if __name__ == "__main__": + main() diff --git a/db.py b/db.py new file mode 100644 index 0000000..55235c3 --- /dev/null +++ b/db.py @@ -0,0 +1,491 @@ +""" +db.py — Database abstraction layer for MoneyMaker. + +Supports both PostgreSQL (production, int.i80.dk) and SQLite (local dev). + +Usage: + from db import get_conn, DB_TYPE + + conn = get_conn() + rows = conn.execute("SELECT * FROM articles").fetchall() + conn.commit() + conn.close() + +Set DATABASE_URL in .env to use PostgreSQL: + DATABASE_URL=postgresql://moneymaker:pass@int.i80.dk:5432/moneymaker + +Without DATABASE_URL, falls back to SQLite (ground_news.db). +""" +import os +import sqlite3 +from pathlib import Path +from dotenv import load_dotenv + +load_dotenv() + +DATABASE_URL = os.getenv("DATABASE_URL", "") +SQLITE_PATH = Path(__file__).parent / "ground_news.db" +DB_TYPE = "postgres" if DATABASE_URL else "sqlite" + + +# ── DBConn wrapper ──────────────────────────────────────────────────────────── + +class DBConn: + """ + Unified connection wrapper for SQLite and PostgreSQL. + + - execute(sql, params): normalises ? → %s for Postgres; returns dict-row cursor + - upsert(table, pk, cols, vals): cross-DB INSERT OR REPLACE / ON CONFLICT DO UPDATE + - commit() / rollback() / close() + """ + + def __init__(self, conn, db_type: str): + self._conn = conn + self.db_type = db_type + + def _sql(self, sql: str) -> str: + """Translate ? placeholders to %s for Postgres.""" + if self.db_type == "postgres": + return sql.replace("?", "%s") + return sql + + def execute(self, sql: str, params=None): + sql = self._sql(sql) + if self.db_type == "postgres": + import psycopg2.extras + cur = self._conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor) + cur.execute(sql, params) + return cur + else: + return self._conn.execute(sql, params) + + def executemany(self, sql: str, seq): + sql = self._sql(sql) + if self.db_type == "postgres": + cur = self._conn.cursor() + cur.executemany(sql, seq) + else: + self._conn.executemany(sql, seq) + + def upsert(self, table: str, pk, cols: list, vals: tuple): + """ + Cross-DB upsert. + + pk: single column name (str) or list of column names for composite PK. + SQLite: INSERT OR REPLACE INTO table (cols) VALUES (?,...) + Postgres: INSERT INTO table (cols) VALUES (%s,...) ON CONFLICT (pk) DO UPDATE SET ... + """ + if isinstance(pk, str): + pk = [pk] + if self.db_type == "postgres": + col_sql = ", ".join(cols) + val_sql = ", ".join(["%s"] * len(cols)) + non_pk = [c for c in cols if c not in pk] + pk_sql = ", ".join(pk) + if non_pk: + update = ", ".join(f"{c}=EXCLUDED.{c}" for c in non_pk) + sql = ( + f"INSERT INTO {table} ({col_sql}) VALUES ({val_sql}) " + f"ON CONFLICT ({pk_sql}) DO UPDATE SET {update}" + ) + else: + sql = ( + f"INSERT INTO {table} ({col_sql}) VALUES ({val_sql}) " + f"ON CONFLICT ({pk_sql}) DO NOTHING" + ) + cur = self._conn.cursor() + cur.execute(sql, vals) + else: + col_sql = ", ".join(cols) + val_sql = ", ".join(["?"] * len(cols)) + self._conn.execute( + f"INSERT OR REPLACE INTO {table} ({col_sql}) VALUES ({val_sql})", + vals, + ) + + def commit(self): + self._conn.commit() + + def rollback(self): + self._conn.rollback() + + def close(self): + self._conn.close() + + def __enter__(self): + return self + + def __exit__(self, exc_type, *_): + if exc_type: + self.rollback() + else: + self.commit() + self.close() + + +# ── Placeholder helpers (kept for legacy usage) ─────────────────────────────── + +def ph(n: int = 1) -> str: + """Return query placeholder: %s for postgres, ? for sqlite.""" + return "%s" if DB_TYPE == "postgres" else "?" + + +def placeholders(n: int) -> str: + """Return comma-separated placeholders for n values.""" + p = ph() + return ", ".join([p] * n) + + +# ── Connection ──────────────────────────────────────────────────────────────── + +def get_conn() -> DBConn: + """Return a DBConn wrapper (Postgres or SQLite).""" + if DB_TYPE == "postgres": + import psycopg2 + conn = psycopg2.connect(DATABASE_URL) + conn.autocommit = False + return DBConn(conn, "postgres") + else: + conn = sqlite3.connect(str(SQLITE_PATH)) + conn.row_factory = sqlite3.Row + return DBConn(conn, "sqlite") + + +# ── Schema ──────────────────────────────────────────────────────────────────── + +SCHEMA_SQLITE = """ +CREATE TABLE IF NOT EXISTS page_cache ( + url TEXT PRIMARY KEY, + page_type TEXT NOT NULL, + fetched_at INTEGER NOT NULL, + content TEXT NOT NULL +); + +CREATE TABLE IF NOT EXISTS rss_feed_cache ( + feed_id TEXT PRIMARY KEY, + fetched_at INTEGER NOT NULL +); + +CREATE TABLE IF NOT EXISTS articles ( + slug TEXT PRIMARY KEY, + story_id TEXT, + title TEXT NOT NULL, + description TEXT, + start_date TEXT, + source_count INTEGER, + bias_src_count INTEGER, + left_pct REAL, + ctr_pct REAL, + right_pct REAL, + left_src_count INTEGER, + ctr_src_count INTEGER, + right_src_count INTEGER, + overall_bias REAL, + blindspot TEXT, + factuality_json TEXT, + interests_json TEXT, + categories TEXT, + first_seen INTEGER, + last_seen INTEGER +); + +CREATE TABLE IF NOT EXISTS article_signals ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + article_slug TEXT NOT NULL, + ticker TEXT NOT NULL, + company_name TEXT NOT NULL, + sector TEXT, + sentiment TEXT, + sentiment_score REAL, + entity_score REAL, + mention_count INTEGER, + full_text_used INTEGER, + analyzed_at INTEGER NOT NULL, + coverage_spread REAL, + claude_tickers TEXT, + claude_magnitude INTEGER, + claude_timeframe TEXT, + claude_reasoning TEXT, + momentum_dir TEXT, + momentum_pct_5d REAL, + signal_score REAL, + alert INTEGER +); + +CREATE TABLE IF NOT EXISTS positions ( + ticker TEXT PRIMARY KEY, + shares REAL NOT NULL, + entry_price REAL NOT NULL, + entry_date TEXT NOT NULL, + stop_loss REAL NOT NULL, + take_profit REAL NOT NULL, + note TEXT +); + +CREATE TABLE IF NOT EXISTS position_events ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + ticker TEXT NOT NULL, + action TEXT NOT NULL, + shares REAL NOT NULL, + price REAL NOT NULL, + total_dkk REAL NOT NULL, + fee_dkk REAL, + pnl_dkk REAL, + signal_correct INTEGER, + event_date TEXT NOT NULL +); + +CREATE TABLE IF NOT EXISTS saxo_orders ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + ticker TEXT NOT NULL, + direction TEXT NOT NULL, + shares REAL NOT NULL, + price_dkk REAL, + total_dkk REAL, + fee_dkk REAL, + saxo_order_id TEXT, + status TEXT NOT NULL, + signal_score REAL, + analyst_rec TEXT, + placed_at TEXT NOT NULL, + filled_at TEXT, + note TEXT +); +""" + +SCHEMA_POSTGRES = """ +CREATE TABLE IF NOT EXISTS page_cache ( + url TEXT PRIMARY KEY, + page_type TEXT NOT NULL, + fetched_at BIGINT NOT NULL, + content TEXT NOT NULL +); + +CREATE TABLE IF NOT EXISTS rss_feed_cache ( + feed_id TEXT PRIMARY KEY, + fetched_at BIGINT NOT NULL +); + +CREATE TABLE IF NOT EXISTS articles ( + slug TEXT PRIMARY KEY, + story_id TEXT, + title TEXT NOT NULL, + description TEXT, + start_date TEXT, + source_count INTEGER, + bias_src_count INTEGER, + left_pct REAL, + ctr_pct REAL, + right_pct REAL, + left_src_count INTEGER, + ctr_src_count INTEGER, + right_src_count INTEGER, + overall_bias REAL, + blindspot TEXT, + factuality_json TEXT, + interests_json TEXT, + categories TEXT, + first_seen BIGINT, + last_seen BIGINT +); + +CREATE TABLE IF NOT EXISTS article_signals ( + id SERIAL PRIMARY KEY, + article_slug TEXT NOT NULL, + ticker TEXT NOT NULL, + company_name TEXT NOT NULL, + sector TEXT, + sentiment TEXT, + sentiment_score REAL, + entity_score REAL, + mention_count INTEGER, + full_text_used INTEGER, + analyzed_at BIGINT NOT NULL, + coverage_spread REAL, + claude_tickers TEXT, + claude_magnitude INTEGER, + claude_timeframe TEXT, + claude_reasoning TEXT, + momentum_dir TEXT, + momentum_pct_5d REAL, + signal_score REAL, + alert INTEGER, + UNIQUE(article_slug, ticker) +); + +CREATE TABLE IF NOT EXISTS positions ( + ticker TEXT PRIMARY KEY, + shares REAL NOT NULL, + entry_price REAL NOT NULL, + entry_date TEXT NOT NULL, + stop_loss REAL NOT NULL, + take_profit REAL NOT NULL, + note TEXT +); + +CREATE TABLE IF NOT EXISTS position_events ( + id SERIAL PRIMARY KEY, + ticker TEXT NOT NULL, + action TEXT NOT NULL, + shares REAL NOT NULL, + price REAL NOT NULL, + total_dkk REAL NOT NULL, + fee_dkk REAL, + pnl_dkk REAL, + signal_correct SMALLINT, + event_date TEXT NOT NULL +); + +CREATE TABLE IF NOT EXISTS saxo_orders ( + id SERIAL PRIMARY KEY, + ticker TEXT NOT NULL, + direction TEXT NOT NULL, + shares REAL NOT NULL, + price_dkk REAL, + total_dkk REAL, + fee_dkk REAL, + saxo_order_id TEXT, + status TEXT NOT NULL, + signal_score REAL, + analyst_rec TEXT, + placed_at TIMESTAMPTZ NOT NULL DEFAULT NOW(), + filled_at TIMESTAMPTZ, + note TEXT +); +""" + + +def init_schema(): + """Create all tables if they don't exist. Safe to run multiple times.""" + if DB_TYPE == "postgres": + import psycopg2 + conn = psycopg2.connect(DATABASE_URL) + cur = conn.cursor() + for stmt in SCHEMA_POSTGRES.split(";"): + stmt = stmt.strip() + if stmt: + cur.execute(stmt) + # Add UNIQUE constraint for article_signals (article_slug, ticker) if missing + cur.execute(""" + SELECT 1 FROM pg_constraint + WHERE conname = 'uq_article_ticker' + AND conrelid = 'article_signals'::regclass + """) + if not cur.fetchone(): + cur.execute( + "ALTER TABLE article_signals " + "ADD CONSTRAINT uq_article_ticker UNIQUE (article_slug, ticker)" + ) + conn.commit() + cur.close() + conn.close() + else: + conn = sqlite3.connect(str(SQLITE_PATH)) + conn.executescript(SCHEMA_SQLITE) + conn.commit() + conn.close() + print(f" Schema initialiseret ({DB_TYPE})") + + +# ── SQLite → Postgres migration ─────────────────────────────────────────────── + +def migrate_sqlite_to_postgres(): + """ + One-time migration: copy all data from local SQLite to Postgres. + Safe to run multiple times (uses INSERT OR IGNORE / ON CONFLICT DO NOTHING). + """ + if DB_TYPE != "postgres": + print("DATABASE_URL ikke sat — kører ikke migration") + return + + import psycopg2 + sqlite_conn = sqlite3.connect(str(SQLITE_PATH)) + sqlite_conn.row_factory = sqlite3.Row + pg_conn = get_conn() + pg_cur = pg_conn.cursor() + + tables = [ + "page_cache", "rss_feed_cache", "articles", + "article_signals", "positions", "position_events" + ] + + for table in tables: + rows = sqlite_conn.execute(f"SELECT * FROM {table}").fetchall() + if not rows: + print(f" {table}: 0 rækker — skip") + continue + + cols = list(rows[0].keys()) + cols_sql = ", ".join(cols) + vals_sql = ", ".join(["%s"] * len(cols)) + + # SERIAL columns (id) — let Postgres auto-assign + insert_cols = [c for c in cols if c != "id"] if "id" in cols else cols + insert_vals = ", ".join(["%s"] * len(insert_cols)) + insert_cols_sql = ", ".join(insert_cols) + + inserted = 0 + skipped = 0 + for row in rows: + # Coerce bytes (SQLite blob) to float/None for Postgres REAL columns + values = [] + for c in insert_cols: + v = row[c] + if isinstance(v, (bytes, bytearray)): + try: + import struct + v = struct.unpack('d', v)[0] + except Exception: + v = None + values.append(v) + values = tuple(values) + try: + pg_cur.execute( + f"INSERT INTO {table} ({insert_cols_sql}) VALUES ({insert_vals}) " + f"ON CONFLICT DO NOTHING", + values + ) + if pg_cur.rowcount > 0: + inserted += 1 + else: + skipped += 1 + except Exception as e: + skipped += 1 + + pg_conn.commit() + print(f" {table}: {inserted} indsat, {skipped} sprunget over") + + sqlite_conn.close() + pg_conn.close() + print(" Migration færdig!") + + +if __name__ == "__main__": + import sys + cmd = sys.argv[1] if len(sys.argv) > 1 else "status" + + if cmd == "init": + init_schema() + elif cmd == "migrate": + print(f"Migrerer SQLite → PostgreSQL ...") + init_schema() + migrate_sqlite_to_postgres() + elif cmd == "status": + conn = get_conn() + if DB_TYPE == "postgres": + raw = conn._conn.cursor() + raw.execute("SELECT tablename FROM pg_tables WHERE schemaname='public'") + tables = [r[0] for r in raw.fetchall()] + for t in sorted(tables): + raw.execute(f"SELECT COUNT(*) FROM {t}") + print(f" {t}: {raw.fetchone()[0]} rækker") + raw.close() + else: + tables = conn.execute("SELECT name FROM sqlite_master WHERE type='table'").fetchall() + for t in tables: + n = conn.execute(f"SELECT COUNT(*) AS cnt FROM {t['name']}").fetchone()["cnt"] + print(f" {t['name']}: {n} rækker") + conn.close() + print(f"\n DB type: {DB_TYPE}") + else: + print("Brug: python db.py [init|migrate|status]") diff --git a/ground-news-ext/extension.xpi b/ground-news-ext/extension.xpi new file mode 100644 index 0000000000000000000000000000000000000000..2ff406f3991df65801c1c6dc97887223d21e1f45 GIT binary patch literal 535653 zcmaHSWmFu|)@9?a!QF#rM?nSx5(5DHx&7ZCq|XDkhIW=_rp_*mR?hZzjmc9n1zf0u7jGC?L!}Ub zCW^mys@0q`uyLB=Sj4sg&8FDjwW>N^hF@7+dT&vqoqjB+tG@fhIQVp+Zo_E>xRGpd 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+.tw-bg-dark { + --tw-bg-opacity: 1 !important; + background-color: rgb(38 38 38 / var(--tw-bg-opacity)) !important; +} +.tw-bg-farLeft { + --tw-bg-opacity: 1 !important; + background-color: rgb(77 109 158 / var(--tw-bg-opacity)) !important; +} +.tw-bg-farRight { + --tw-bg-opacity: 1 !important; + background-color: rgb(153 82 82 / var(--tw-bg-opacity)) !important; +} +.tw-bg-focus { + --tw-bg-opacity: 1 !important; + background-color: rgb(209 189 145 / var(--tw-bg-opacity)) !important; +} +.tw-bg-leanLeft { + --tw-bg-opacity: 1 !important; + background-color: rgb(210 219 231 / var(--tw-bg-opacity)) !important; +} +.tw-bg-leanRight { + --tw-bg-opacity: 1 !important; + background-color: rgb(217 190 190 / var(--tw-bg-opacity)) !important; +} +.tw-bg-left { + --tw-bg-opacity: 1 !important; + background-color: rgb(144 164 195 / var(--tw-bg-opacity)) !important; +} +.tw-bg-light { + --tw-bg-opacity: 1 !important; + background-color: rgb(238 239 233 / var(--tw-bg-opacity)) !important; +} +.tw-bg-right { + --tw-bg-opacity: 1 !important; + background-color: rgb(192 147 147 / var(--tw-bg-opacity)) !important; +} +.tw-bg-center { + background-position: center !important; +} +.tw-bg-left { + background-position: left !important; +} +.tw-bg-right { + background-position: right !important; +} +.tw-fill-dark { + fill: #262626 !important; +} +.tw-fill-light { + fill: #EEEFE9 !important; +} +.tw-p-\[20px\] { + padding: 20px !important; +} +.tw-px-2 { + padding-left: 0.5rem !important; + padding-right: 0.5rem !important; +} +.tw-px-\[5px\] { + padding-left: 5px !important; + padding-right: 5px !important; +} +.tw-text-center { + text-align: center !important; +} +.tw-align-middle { + vertical-align: middle !important; +} +.tw-font-ground { + font-family: UniversalSans !important; +} +.tw-text-\[10px\] { + font-size: 10px !important; +} +.tw-text-\[12px\] { + font-size: 12px !important; +} +.tw-text-\[15px\] { + font-size: 15px !important; +} +.tw-text-\[18px\] { + font-size: 18px !important; +} +.tw-text-\[20px\] { + font-size: 20px !important; +} +.tw-text-\[30px\] { + font-size: 30px !important; +} +.tw-font-\[480\] { + font-weight: 480 !important; +} +.tw-font-\[600\] { + font-weight: 600 !important; +} +.tw-leading-\[20px\] { + line-height: 20px !important; +} +.tw-leading-\[25px\] { + line-height: 25px !important; +} +.tw-leading-\[30px\] { + line-height: 30px !important; +} +.tw-leading-\[54px\] { + line-height: 54px !important; +} +.tw-text-center { + --tw-text-opacity: 1 !important; + color: rgb(255 255 255 / var(--tw-text-opacity)) !important; +} +.tw-text-dark { + --tw-text-opacity: 1 !important; + color: rgb(38 38 38 / var(--tw-text-opacity)) !important; +} +.tw-text-light { + --tw-text-opacity: 1 !important; + color: rgb(238 239 233 / var(--tw-text-opacity)) !important; +} +.tw-opacity-0 { + opacity: 0 !important; +} +.tw-opacity-100 { + opacity: 1 !important; +} +.tw-transition-\[width\,background-color\,color\] { + transition-property: width,background-color,color !important; + transition-timing-function: cubic-bezier(0.4, 0, 0.2, 1) !important; + transition-duration: 150ms !important; +} +.tw-transition-all { + transition-property: all !important; + transition-timing-function: cubic-bezier(0.4, 0, 0.2, 1) !important; + transition-duration: 150ms !important; +} +.tw-transition-opacity { + transition-property: opacity !important; + transition-timing-function: cubic-bezier(0.4, 0, 0.2, 1) !important; + transition-duration: 150ms !important; +} +.tw-duration-300 { + transition-duration: 300ms !important; +} +.tw-duration-500 { + transition-duration: 500ms !important; +} +.tw-ease-in-out { + transition-timing-function: cubic-bezier(0.4, 0, 0.2, 1) !important; +} +.\[top\:-108px\] { + top: -108px !important; +} +.\[top\:0px\] { + top: 0px !important; +} +.\[transition\:top_500ms_cubic-bezier\(0\2c 0\2c 0\2c 1\)\] { + transition: top 500ms cubic-bezier(0,0,0,1) !important; +} +.hover\:tw-bg-dark:hover { + --tw-bg-opacity: 1 !important; + background-color: rgb(38 38 38 / var(--tw-bg-opacity)) !important; +} +.hover\:tw-bg-light:hover { + --tw-bg-opacity: 1 !important; + background-color: rgb(238 239 233 / var(--tw-bg-opacity)) !important; +} +.hover\:tw-text-dark:hover { + --tw-text-opacity: 1 !important; + color: rgb(38 38 38 / var(--tw-text-opacity)) !important; +} +.hover\:tw-text-light:hover { + --tw-text-opacity: 1 !important; + color: rgb(238 239 233 / var(--tw-text-opacity)) !important; +} +@media (max-width: 1340px) { + .max-\[1340px\]\:tw-hidden { + display: none !important; + } +} +@media (min-width: 1280px) { + .xl\:tw-inline-block { + display: inline-block !important; + } + .xl\:tw-gap-x-\[10px\] { + -moz-column-gap: 10px !important; + column-gap: 10px !important; + } +} +@media (min-width: 1341px) { + .min-\[1341px\]\:tw-hidden { + display: none !important; + } +} diff --git a/ground-news-ext/src/js/bluesky.js b/ground-news-ext/src/js/bluesky.js new file mode 100644 index 0000000..b9f29f8 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format('ttf'); + font-weight: 800; + } + @font-face { + font-family: 'UniversalSans'; + src: url('moz-extension://__MSG_@@extension_id__/fonts/UniversalSans-680.woff') format('woff'), + url('moz-extension://__MSG_@@extension_id__/fonts/UniversalSans-680.ttf') format('ttf'); + font-weight: 680; + } + @font-face { + font-family: 'UniversalSans'; + src: url('moz-extension://__MSG_@@extension_id__/fonts/UniversalSans-480.woff') format('woff'), + url('moz-extension://__MSG_@@extension_id__/fonts/UniversalSans-480.ttf') format('ttf'); + font-weight: 480; + } +.tw-static { + position: static !important; +} +.tw-fixed { + position: fixed !important; +} +.tw-absolute { + position: absolute !important; +} +.tw-relative { + position: relative !important; +} +.tw-left-0 { + left: 0px !important; +} +.tw-z-\[1000000000\] { + z-index: 1000000000 !important; +} +.tw-z-\[10000\] { + z-index: 10000 !important; +} +.tw-float-right { + float: right !important; +} +.tw-my-\[13px\] { + margin-top: 13px !important; + margin-bottom: 13px !important; +} +.tw-mb-0 { + margin-bottom: 0px !important; +} +.tw-mb-\[20px\] { + margin-bottom: 20px !important; +} +.tw-box-border { + box-sizing: border-box !important; +} +.tw-inline-block { + display: inline-block !important; +} +.tw-flex { + display: flex !important; +} +.tw-inline-flex { + display: inline-flex !important; +} +.tw-hidden { + display: none !important; +} +.tw-h-\[1px\] { + height: 1px !important; +} +.tw-h-\[20px\] { + height: 20px !important; +} +.tw-h-\[30px\] { + height: 30px !important; +} +.tw-h-\[35px\] { + height: 35px !important; +} +.tw-h-\[54px\] { + height: 54px !important; +} +.tw-h-full { + height: 100% !important; +} +.tw-min-h-\[30px\] { + min-height: 30px !important; +} +.tw-w-\[200px\] { + width: 200px !important; +} +.tw-w-\[20px\] { + width: 20px !important; +} +.tw-w-\[30px\] { + width: 30px !important; +} +.tw-w-\[35px\] { + width: 35px !important; +} +.tw-w-\[420px\] { + width: 420px !important; +} 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overflow: hidden !important; + text-overflow: ellipsis !important; + white-space: nowrap !important; +} +.tw-whitespace-nowrap { + white-space: nowrap !important; +} +.tw-rounded { + border-radius: 0.25rem !important; +} +.tw-rounded-full { + border-radius: 9999px !important; +} +.tw-rounded-md { + border-radius: 0.375rem !important; +} +.\!tw-border { + border-width: 1px !important; +} +.tw-border { + border-width: 1px !important; +} +.tw-border-0 { + border-width: 0px !important; +} +.tw-border-solid { + border-style: solid !important; +} +.\!tw-border-light { + --tw-border-opacity: 1 !important; + border-color: rgb(238 239 233 / var(--tw-border-opacity)) !important; +} +.tw-border-light { + --tw-border-opacity: 1 !important; + border-color: rgb(238 239 233 / var(--tw-border-opacity)) !important; +} +.\!tw-bg-light { + --tw-bg-opacity: 1 !important; + background-color: rgb(238 239 233 / var(--tw-bg-opacity)) !important; +} +.tw-bg-biasBarCenter { + --tw-bg-opacity: 1 !important; + background-color: rgb(255 255 255 / var(--tw-bg-opacity)) !important; +} +.tw-bg-biasBarLeft { + --tw-bg-opacity: 1 !important; + background-color: rgb(32 73 134 / var(--tw-bg-opacity)) !important; +} +.tw-bg-biasBarRight { + --tw-bg-opacity: 1 !important; + background-color: rgb(128 39 39 / var(--tw-bg-opacity)) !important; +} +.tw-bg-center { + --tw-bg-opacity: 1 !important; + background-color: rgb(255 255 255 / var(--tw-bg-opacity)) !important; +} +.tw-bg-dark { + --tw-bg-opacity: 1 !important; + background-color: rgb(38 38 38 / var(--tw-bg-opacity)) !important; +} +.tw-bg-farLeft { + --tw-bg-opacity: 1 !important; + background-color: rgb(77 109 158 / var(--tw-bg-opacity)) !important; +} +.tw-bg-farRight { + --tw-bg-opacity: 1 !important; + background-color: rgb(153 82 82 / var(--tw-bg-opacity)) !important; +} +.tw-bg-focus { + --tw-bg-opacity: 1 !important; + background-color: rgb(209 189 145 / var(--tw-bg-opacity)) !important; +} +.tw-bg-leanLeft { + --tw-bg-opacity: 1 !important; + background-color: rgb(210 219 231 / var(--tw-bg-opacity)) !important; +} +.tw-bg-leanRight { + --tw-bg-opacity: 1 !important; + background-color: rgb(217 190 190 / var(--tw-bg-opacity)) !important; +} +.tw-bg-left { + --tw-bg-opacity: 1 !important; + background-color: rgb(144 164 195 / var(--tw-bg-opacity)) !important; +} +.tw-bg-light { + --tw-bg-opacity: 1 !important; + background-color: rgb(238 239 233 / var(--tw-bg-opacity)) !important; +} +.tw-bg-right { + --tw-bg-opacity: 1 !important; + background-color: rgb(192 147 147 / var(--tw-bg-opacity)) !important; +} +.tw-bg-center { + background-position: center !important; +} +.tw-bg-left { + background-position: left !important; +} +.tw-bg-right { + background-position: right !important; +} +.tw-fill-dark { + fill: #262626 !important; +} +.tw-fill-light { + fill: #EEEFE9 !important; +} +.tw-p-\[20px\] { + padding: 20px !important; +} +.tw-px-2 { + padding-left: 0.5rem !important; + padding-right: 0.5rem !important; +} +.tw-px-\[5px\] { + padding-left: 5px !important; + padding-right: 5px !important; +} +.tw-text-center { + text-align: center !important; +} +.tw-align-middle { + vertical-align: middle !important; +} +.tw-font-ground { + font-family: UniversalSans !important; +} +.tw-text-\[10px\] { + font-size: 10px !important; +} +.tw-text-\[12px\] { + font-size: 12px !important; +} +.tw-text-\[15px\] { + font-size: 15px !important; +} +.tw-text-\[18px\] { + font-size: 18px !important; +} +.tw-text-\[20px\] { + font-size: 20px !important; +} +.tw-text-\[30px\] { + font-size: 30px !important; +} +.tw-font-\[480\] { + font-weight: 480 !important; +} +.tw-font-\[600\] { + font-weight: 600 !important; +} +.tw-leading-\[20px\] { + line-height: 20px !important; +} +.tw-leading-\[25px\] { + line-height: 25px !important; +} +.tw-leading-\[30px\] { + line-height: 30px !important; +} +.tw-leading-\[54px\] { + line-height: 54px !important; +} +.tw-text-center { + --tw-text-opacity: 1 !important; + color: rgb(255 255 255 / var(--tw-text-opacity)) !important; +} +.tw-text-dark { + --tw-text-opacity: 1 !important; + color: rgb(38 38 38 / var(--tw-text-opacity)) !important; +} +.tw-text-light { + --tw-text-opacity: 1 !important; + color: rgb(238 239 233 / var(--tw-text-opacity)) !important; +} +.tw-opacity-0 { + opacity: 0 !important; +} +.tw-opacity-100 { + opacity: 1 !important; +} +.tw-transition-\[width\,background-color\,color\] { + transition-property: width,background-color,color !important; + transition-timing-function: cubic-bezier(0.4, 0, 0.2, 1) !important; + transition-duration: 150ms !important; +} +.tw-transition-all { + transition-property: all !important; + transition-timing-function: cubic-bezier(0.4, 0, 0.2, 1) !important; + transition-duration: 150ms !important; +} +.tw-transition-opacity { + transition-property: opacity !important; + transition-timing-function: cubic-bezier(0.4, 0, 0.2, 1) !important; + transition-duration: 150ms !important; +} +.tw-duration-300 { + transition-duration: 300ms !important; +} +.tw-duration-500 { + transition-duration: 500ms !important; +} +.tw-ease-in-out { + transition-timing-function: cubic-bezier(0.4, 0, 0.2, 1) !important; +} +.\[top\:-108px\] { + top: -108px !important; +} +.\[top\:0px\] { + top: 0px !important; +} +.\[transition\:top_500ms_cubic-bezier\(0\2c 0\2c 0\2c 1\)\] { + transition: top 500ms cubic-bezier(0,0,0,1) !important; +} +.hover\:tw-bg-dark:hover { + --tw-bg-opacity: 1 !important; + background-color: rgb(38 38 38 / var(--tw-bg-opacity)) !important; +} +.hover\:tw-bg-light:hover { + --tw-bg-opacity: 1 !important; + background-color: rgb(238 239 233 / var(--tw-bg-opacity)) !important; +} +.hover\:tw-text-dark:hover { + --tw-text-opacity: 1 !important; + color: rgb(38 38 38 / var(--tw-text-opacity)) !important; +} +.hover\:tw-text-light:hover { + --tw-text-opacity: 1 !important; + color: rgb(238 239 233 / var(--tw-text-opacity)) !important; +} +@media (max-width: 1340px) { + 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opacity: 1 !important; +} +.tw-transition-\[width\,background-color\,color\] { + transition-property: width,background-color,color !important; + transition-timing-function: cubic-bezier(0.4, 0, 0.2, 1) !important; + transition-duration: 150ms !important; +} +.tw-transition-all { + transition-property: all !important; + transition-timing-function: cubic-bezier(0.4, 0, 0.2, 1) !important; + transition-duration: 150ms !important; +} +.tw-transition-opacity { + transition-property: opacity !important; + transition-timing-function: cubic-bezier(0.4, 0, 0.2, 1) !important; + transition-duration: 150ms !important; +} +.tw-duration-300 { + transition-duration: 300ms !important; +} +.tw-duration-500 { + transition-duration: 500ms !important; +} +.tw-ease-in-out { + transition-timing-function: cubic-bezier(0.4, 0, 0.2, 1) !important; +} +.\[top\:-108px\] { + top: -108px !important; +} +.\[top\:0px\] { + top: 0px !important; +} +.\[transition\:top_500ms_cubic-bezier\(0\2c 0\2c 0\2c 1\)\] { + 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