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Data Catalog

Browse our curated market data catalog across exchanges and asset types.

19 datasets

Trades

Derivatives

Market Data

L1 (Top of Book)

L2 (Order Book)

Preview Data

No subscription required

The following datasets are available to any authenticated user — even without a paid plan. Pass preview=True in the Python client, or call /api/v1/data/preview/:metric_id directly.

DatasetExchangeSymbolIntervalTimestampDate range
Candlesticksbinance-futuresperpetual-BTC-USDT:USDT5mexchange2025-05-01 — 2025-05-31
L2 Order Book Imbalancebinance-futuresperpetual-BTC-USDT:USDT5mexchange2025-05-01 — 2025-05-31
L1 Price

L1 Price

Best bid and ask prices with quantities, midprice, quantity-weighted midprice, time/volume-weighted averages, and quote update frequency.

CodeAPI DocsTry It

midprice

Mid Price

Mid Price is the center of the best bid and best ask, making it the cleanest instantaneous fair-value proxy at the top of book.

Because it strips out half-spread noise, it is widely used for microstructure research, marking, and short-horizon return calculations.

weighted_midprice

Weighted Mid Price

Weighted Mid Price tilts the simple midpoint by the relative size resting at the best bid and ask.

That gives it a predictive flavor because it incorporates which side of the top of book is showing more immediate depth.

quote_update_frequency

Quote Update Frequency

Quote Update Frequency measures how actively the top of book was refreshing during the interval.

A high reading often means the market was competitive, reactive, or unstable enough to force frequent repricing.

avg_update_interval

Avg Update Interval

Average Update Interval is the time counterpart to quote frequency, showing how quickly the best quotes changed on average.

Shorter intervals imply a faster and more responsive book, while longer intervals suggest a calmer or less actively managed top of book.

bid_price_vwap

Bid Price VWAP

Bid Price VWAP summarizes where the best bid spent its time with volume-sensitive weighting.

It offers a richer picture than a single snapshot because it reflects how quoted buying interest evolved across the bar.

Endpoint

/api/v1/data/l1_price

Category

L1 (Top of Book)

Intervals
1m5m15m30m1h4h1d
Requires Prime
1s

Requires timestamp=true

Exchanges
binance-futuresokx-perpshyperliquid-perps
Fields12
ask_priceAsk PriceLast best ask price in the interval
bid_priceBid PriceLast best bid price in the interval
ask_amountAsk AmountLast best ask quantity in the interval
bid_amountBid AmountLast best bid quantity in the interval
quote_update_frequencyQuote Update FrequencyNumber of top-of-book quote updates in the interval
avg_update_intervalAvg Update IntervalAverage milliseconds between top-of-book quote updates
midpriceMid PriceMidpoint between the last best bid and ask prices
weighted_midpriceWeighted Mid PriceMidprice weighted by the opposite-side top-of-book quantity
bid_price_twapBid Price TWAPAverage best bid price in the interval
ask_price_twapAsk Price TWAPAverage best ask price in the interval
bid_price_vwapBid Price VWAPBid-price average weighted by best bid quantity
ask_price_vwapAsk Price VWAPAsk-price average weighted by best ask quantity
Example Request
from datetime import date
from aperiodic import get_metrics
df = get_metrics(
    api_key="YOUR_API_KEY",
    metric="l1_price",
    exchange="binance-futures",
    symbol="perpetual-BTC-USDT:USDT",
    interval="1d",
    start_date=date(2024, 1, 1),
    end_date=date(2024, 3, 1),
)
print(df.head())

Query Parameters

timestampreqstring
string

Timestamp source. 'exchange' uses the exchange-reported timestamp, 'true' uses actual arrival time at our servers.

exchangetrue
intervalreqstring
string

Aggregation time interval for the data.

1m5m15m30m1h4h1d
exchangereqstring
string

Source exchange for the data.

binance-futuresokx-perpshyperliquid-perps
symbolreqstring
string

Trading pair symbol in the format of Atlas' universal symbology: https://github.com/aperiodic-io/atlas

start_datereqstring<date>
string<date>

Start date for the data range (YYYY-MM-DD format). Data is partitioned by year and month.

end_datereqstring<date>
string<date>

End date for the data range (YYYY-MM-DD format). Must be greater than or equal to start_date.

Successful response with download URLs for each monthly file

Schema
filesobject[]required

Array of file information for each month in the requested date range

yearintegerrequired

Year of the data file

monthintegerrequired

Month of the data file (1-12)

urlstring<uri>required

Presigned URL for direct file download (valid for 5 minutes). URLs are served from dataset-specific subdomains, e.g. ohlcv.aperiodic.io, trade-metrics.aperiodic.io, l1-metrics.aperiodic.io, l2-metrics.aperiodic.io, derivative-metrics.aperiodic.io.

Example
{
  "files": [
    {
      "year": 2024,
      "month": 1,
      "url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2024-01.parquet?X-Amz-Expires=300&..."
    },
    {
      "year": 2024,
      "month": 2,
      "url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2024-02.parquet?X-Amz-Expires=300&..."
    }
  ]
}
Try It
Suggestions shown — any valid value accepted
Suggestions shown — any valid value accepted
Suggestions shown — any valid value accepted
Authentication
An API key is required to send requests.Sign up
GET/api/v1/data/l1_price?timestamp=exchange&interval=1m&exchange=binance-futures
Response will appear here
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