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Use client.mark_prices() when you need mark price data for perpetual contracts. This method returns a time series of mark prices used for basis analysis, mark tracking, and liquidation-related research.

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Method signature

mark_prices(source, market, from_, to, limit=1000)

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Parameters

ParameterTypeRequiredNotes
sourcestrYesSource ID
marketstrYesNormalized market or instrument ID
from_str/datetime/date/intYesInclusive start time (ISO 8601, datetime, date, or epoch microseconds)
tostr/datetime/date/intYesExclusive end time (same formats as from_)
limitintNoPage size (default: 1000)
Note: API key required for historical ranges. Set POLARIS_API_KEY environment variable or pass api_key to PolarisClient().

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Return value

List of mark price point series rows.

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Example response

[
    {
        'timestamp': 1704067200000000,
        'venue': 'binance',
        'symbol': 'BTCUSDT',
        'mark_price': 43250.75
    }
]

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Fields

Mark price records include:
  • timestamp: observation time in UTC microseconds since the Unix epoch
  • venue: exchange identifier
  • symbol: normalized instrument symbol
  • mark_price: the mark price used for margin and liquidation calculations

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Example

from datetime import datetime, timedelta, timezone
from polaris_data import PolarisClient

end = datetime.now(timezone.utc)
start = end - timedelta(days=7)

with PolarisClient() as client:
    prices = client.mark_prices(
        source="binance",
        market="BTCUSDT",
        from_=start,
        to=end,
    )

print(prices[:2])

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How it works

client.mark_prices() uses snapshot-first replay: it queries the /snapshots endpoint for historical data and reads from local cached files when available. Mark prices are extracted from standardized datapoint events with the index_price or mark price labels. For more details on snapshot-based queries, see Snapshots.