| name | moexalgo-supercandles |
| description | Python moexalgo library workflows for SuperCandles DataFrames, .env session.TOKEN setup, Market.tradestats, Market.orderstats, Market.obstats, Ticker.tradestats, Ticker.orderstats, Ticker.obstats, field interpretation, offset pagination, pivots, groupbys, and EQ/FO/FX analytics. |
MOEXAlgo SuperCandles
Overview
Use this skill when the user wants SuperCandles through the moexalgo Python package and DataFrame analysis.
Access note: Promo includes SuperCandles. 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 os
from dotenv import load_dotenv
from moexalgo import session, Market, Ticker
load_dotenv()
session.TOKEN = os.environ["APIKEY"]
eq = Market("EQ")
trades_all = eq.tradestats(date="2025-01-10")
orders_all = eq.orderstats(date="2025-01-10")
book_latest = eq.obstats(date="2025-01-10", latest=True)
sber = Ticker("SBER")
trades = sber.tradestats(start="2025-01-01", end="2025-01-31")
orders = sber.orderstats(start="2025-01-01", end="2025-01-31")
book = sber.obstats(start="2025-01-01", end="2025-01-31")
Core Workflow
- Use
Market("EQ"|"FO"|"FX") for all instruments by date.
- Use
Ticker(...) for one instrument over start and end.
- Choose
tradestats, orderstats, or obstats based on the metric the user needs.
- Analyze with pandas groupbys, pivots, ratios, or plots according to the user's requested output.
- Use library
offset for pagination where supported; do not pass raw REST start to library methods.
- Keep DataFrames as the default; mention
native=True only when the user explicitly asks for dict iterators.
References
Read references/supercandles.md for method signatures, fields, interpretation notes, and DataFrame analysis examples.
Boundary
For raw endpoint URLs, curl, JSON/CSV, or no-Python answers, use the direct SuperCandles skill instead.
