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Use client.ohlcv() when you want interval-based bar data instead of raw executions. This method aggregates OHLCV bars from standardized trade data. OHLCV data is interval-aligned and deterministic: candle boundaries are fixed to UTC intervals, which keeps joins and cross-venue aggregation consistent.

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Method signature

ohlcv(source, market, from_, to, interval, format=None)

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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_)
intervalstrYesDuration token such as 1m, 5m, 1h
formatstrNoResponse format: None (default JSON), "tradingview" for TV-compatible JSON
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

  • Default: List of OHLCV bar dictionaries
  • With format="tradingview": Dictionary with candles and volumes arrays

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Example response

[
    {
        'timestamp': 1704067200000000,
        'open': 43250.00,
        'high': 43260.00,
        'low': 43245.00,
        'close': 43255.00,
        'volume': 12.5,
        'trades': 45,
        'interval': '1m'
    }
]

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Fields

The default response is a list of bar dictionaries with these fields:
  • timestamp: bar open time in UTC microseconds since the Unix epoch
  • open, high, low, close: interval prices
  • volume: traded base volume for the bar
  • trades: number of trades aggregated into the bar
  • interval: duration token such as 1m, 5m, or 1h
When OHLCV appears inside /events or snapshot files, it uses the standard event envelope (see Standardised formats) and the bar-specific fields live under the nested data object.

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Example

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

end = datetime.now(timezone.utc)
start = end - timedelta(hours=6)

with PolarisClient() as client:
    bars = client.ohlcv(
        source="hyperliquid",
        market="SPX",
        from_=start,
        to=end,
        interval="1m",
    )

print(bars[:2])

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TradingView format

If you pass format="tradingview", the response uses these fields:
  • candles[].time: Unix seconds
  • candles[].open, candles[].high, candles[].low, candles[].close
  • volumes[].time: Unix seconds
  • volumes[].value: bar volume
with PolarisClient() as client:
    tv_data = client.ohlcv(
        source="hyperliquid",
        market="SPX",
        from_=start,
        to=end,
        interval="1m",
        format="tradingview",
    )

print(tv_data)
# {'candles': [...], 'volumes': [...]}

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How it works

client.ohlcv() aggregates bars from standardized trade data using snapshot-first replay. The SDK queries the /snapshots endpoint for historical data, reads from local cached files when available, and derives OHLCV bars from the underlying trade events. The SDK handles pagination and data derivation automatically. For more details on snapshot-based queries, see Snapshots.