Containerised macro-strategy dashboard: 4-panel web UI (indicators, portfolio, flash news, AI strategic log), MariaDB store, hourly ingestion jobs, OpenRouter-backed AI analysis. Ports the four prototype scripts in the parent dir (market_pulse, flash_news, trading212, strategic_log) into async services backed by a persistent DB and served via FastAPI + Jinja2 + HTMX. APScheduler runs as a separate compose service for crash-safety and easier restarts. Portfolio composition + position names come live from Trading 212; news per-ticker headlines reuse those names. Tone (NOVICE/INTERMEDIATE/ PRO) and analysis style (DRY/SPECULATIVE) are env-configurable and stored on each log row so historical entries show what produced them. Default model is deepseek/deepseek-v4-flash (overridable via env). Light/dark theme toggle, sans-serif for prose surfaces, monospace for data. Bearer-token auth, OpenRouter monthly cost cap, RSS feeds auto- disabled on consecutive failures. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
35 lines
1.1 KiB
Python
35 lines
1.1 KiB
Python
"""structlog setup — JSON to stdout, ready for Docker json-file driver."""
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from __future__ import annotations
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import logging
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import sys
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import structlog
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def configure_logging(level: str = "INFO") -> None:
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logging.basicConfig(
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format="%(message)s",
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stream=sys.stdout,
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level=getattr(logging, level.upper(), logging.INFO),
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)
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structlog.configure(
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processors=[
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structlog.contextvars.merge_contextvars,
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structlog.processors.add_log_level,
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structlog.processors.TimeStamper(fmt="iso", utc=True),
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structlog.processors.StackInfoRenderer(),
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structlog.processors.format_exc_info,
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structlog.processors.JSONRenderer(),
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],
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wrapper_class=structlog.make_filtering_bound_logger(
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getattr(logging, level.upper(), logging.INFO)
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),
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context_class=dict,
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logger_factory=structlog.PrintLoggerFactory(),
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cache_logger_on_first_use=True,
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)
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def get_logger(name: str | None = None) -> structlog.stdlib.BoundLogger:
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return structlog.get_logger(name)
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