moexalgo-mega-alerts

name	moexalgo-mega-alerts
description	Python moexalgo library workflows for Mega Alerts DataFrames, .env session.TOKEN setup, Market.alerts, Ticker.alerts, alert_type analysis, threshold and value comparison, reference JSON parsing, EQ/FO anomaly alerts, offset pagination, groupbys, pivots, and historical post-alert context.

MOEXAlgo Mega Alerts

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.