| name | moexalgo-market-data |
| description | Python moexalgo library workflows for Market and Ticker market data, .env session.TOKEN setup, pandas DataFrames, tickers metadata, marketdata quotes, info, candles, trades, orderbook, market aliases, board overrides, field selection, offset pagination, native-mode escape hatches, and basic EQ/FO/FX data analysis. |
MOEXAlgo Market Data
Overview
Use this skill when the user wants the moexalgo Python package, pandas-style DataFrames, or Market/Ticker helpers for market data.
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")
tickers = eq.tickers("ticker", "shortname", "minstep")
quotes = eq.marketdata("ticker", "last", "bid", "offer", "updatetime")
sber = Ticker("SBER")
info = sber.info("ticker", "title", "market", "engine", "decimals")
candles = sber.candles(start="2025-01-01", end="2025-01-31", period="1h")
trades = sber.trades(latest=True)
book = sber.orderbook()
Core Workflow
- Install
moexalgo[dataframe] and python-dotenv for DataFrame output and .env loading.
- Store
APIKEY in .env, call load_dotenv(), then set session.TOKEN from os.environ["APIKEY"] for plan-entitled access. Стартовый / Starter free-token access includes 15-minute delayed candles and trades; Promo includes online order books, candles, and trades.
- Use
Market("EQ"|"FO"|"FX") for market-wide rows and Ticker("SBER") for one instrument.
- Keep metadata and quotes separate:
tickers(...) reads the ISS securities block, while marketdata(...) reads the ISS marketdata block.
- Pass explicit field names for compact DataFrames; use
tickers("*") for all securities fields and marketdata("*") for all marketdata fields.
- Use
board=... only after metadata shows a non-default board is required.
References
Read references/market-data.md for signatures, aliases, securities versus marketdata fields, candle periods, board caveats, pagination, and DataFrame examples.
Boundary
For raw REST URLs, curl, ISS pagination mechanics, or non-Python integrations, use the direct ISS/API skills instead.
