OHLCV

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.

Method signature

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

Parameters

Parameter	Type	Required	Notes
source	str	Yes	Source ID
market	str	Yes	Normalized market or instrument ID
from_	str/datetime/date/int	Yes	Inclusive start time (ISO 8601, datetime, date, or epoch microseconds)
to	str/datetime/date/int	Yes	Exclusive end time (same formats as from_)
interval	str	Yes	Duration token such as `1m`, `5m`, `1h`
format	str	No	Response 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().

Return value

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

Example response

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

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 and the bar-specific fields live under the nested data object.

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])

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': [...]}

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.

Trades if you need execution-level data instead of bars
Snapshots for bulk historical standardized files
Authentication

Getting Started

SDKs

Data Schemas

Reference

Resources

Method signature

Parameters

Return value

Example response

Fields

Example

TradingView format

How it works

​Method signature

​Parameters

​Return value

​Example response

​Fields

​Example

​TradingView format

​How it works

​Related documentation

Method signature

Parameters

Return value

Example response

Fields

Example

TradingView format

How it works

Related documentation