Overview
Use this skill when the user wants Mega Alerts through the moexalgo Python package and DataFrame analysis.
Access note: Promo includes Mega Alerts. Стартовый / Starter free-token availability is planned at T - 1 day; verify current access before promising it.
Quick Start
python -m pip install "moexalgo[dataframe]" python-dotenv
import json
import os
from dotenv import load_dotenv
from moexalgo import session, Market, Ticker
load_dotenv() session.TOKEN = os.environ["APIKEY"]
eq = Market("EQ") alerts = eq.alerts(date="2025-01-10")
sber = Ticker("SBER") sber_alerts = sber.alerts(start="2025-01-01", end="2025-03-30") parsed = sber_alerts["reference"].dropna().map(json.loads)
## Core Workflow
1. Use `Market("EQ"|"FO").alerts(date=...)` for market-wide alerts.
2. Use `Ticker(...).alerts(start=..., end=...)` for one instrument.
3. Group by `alert_type`, `ticker`, and date/time.
4. Use library `offset` for pagination where supported; do not pass raw REST `start` to library methods.
5. Parse `reference` only when historical post-alert context is needed.
6. Avoid forecast language and recommendations.
## References
Read `references/mega-alerts.md` for signatures, alert types, fields, reference parsing, and DataFrame examples.
## Boundary
For raw endpoint URLs, curl, JSON/CSV, or no-Python workflows, use the direct Mega Alerts skill instead.