Use case

Execute smarter

Know when liquidity is deep, when spreads are wide, and when flow turns toxic.

Shown: the median perpetual’s book depth across the top 25 levels, as a share of its 20:00–20:45 average, per venue, 18:00–01:00 UTC on 10 Oct 2025; minutes under half of normal take the strong tone, and the lowest of all, OKX’s 8.5% at 22:06, is orange · built with l2_liquidity 1m

Featured notebook

Timing execution around liquidity

Execution cost is not constant through the day. Spreads widen, depth thins, and order flow turns adverse together around stressed periods. For a moderate-frequency order, when you execute can matter more than shaving microseconds off the route. This notebook measures when liquidity is deep, spreads are narrow, and flow is least toxic, then ranks the hours by modelled execution cost and cross-checks that ranking against measured slippage.

Loading notebook…

Or have your agent rerun this notebook and tell you what it finds. Start in Claude Claude Code Codex See the prompt

From notebook to production

Pick the metrics

Browse the catalog and pull point-in-time microstructure metrics — no L2 reconstruction, no tick archive to maintain.

Run the notebook

Every notebook runs end to end on preview data with a free account, in the browser or through the CLI.

Plug it into your stack

Swap the preview key for your own and the same code pulls every year your plan includes through the Python package or the API.

Metrics in this use case

More notebooks for this use case

Related notebook

Intro to Aperiodic L1 Price Metrics

Execute smarter

This notebook explores top-of-book (L1) pricing with Aperiodic's `l1_price` metric for Binance BTC perpetuals from September 1, 2025 through February 28, 2026 at 5-minute granularity.

View notebook

Execute smarter

Know when liquidity is deep, when spreads are wide, and when flow turns toxic.

Explore real-time streaming Book a call (Institutional)

Or create a free account to run the notebooks on preview data.

Shown: minute lows of the 465 Binance perpetuals, 20:40–22:00 UTC on 10 Oct 2025, with BTC’s path traced · built with ohlcv 1m

L1 Price

L1 (Top of Book)

L1 Price

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

See it on real data

Need the ticks behind this metric? Prime + Raw includes raw quotes.

Sample CSV Start in Claude

Shown: quote_update_frequency, hourly, 1–31 January 2024, from this page's Sample CSV · extreme: 69355.000, 3 Jan, 12:00 UTC · built with l1_price

low

high

extreme

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)
Built from: Raw quotes →
Intervals: 1m5m15m30m1h4h1d
Requires Institutional: 15s30s
Exchanges: binance-futuresokx-perpshyperliquid-perps

Fields

Field	Name	Description
`ask_price`	Ask Price	Last best ask price in the interval
`bid_price`	Bid Price	Last best bid price in the interval
`ask_amount`	Ask Amount	Last best ask quantity in the interval
`bid_amount`	Bid Amount	Last best bid quantity in the interval
`quote_update_frequency`	Quote Update Frequency	Number of top-of-book quote updates in the interval
`avg_update_interval`	Avg Update Interval	Average milliseconds between top-of-book quote updates
`midprice`	Mid Price	Midpoint between the last best bid and ask prices
`weighted_midprice`	Weighted Mid Price	Midprice weighted by the opposite-side top-of-book quantity
`bid_price_twap`	Bid Price TWAP	Average best bid price in the interval
`ask_price_twap`	Ask Price TWAP	Average best ask price in the interval
`bid_price_vwap`	Bid Price VWAP	Bid-price average weighted by best bid quantity
`ask_price_vwap`	Ask Price VWAP	Ask-price average weighted by best ask quantity

Example Request

# Install the Aperiodic CLI into ~/.local/bin
mkdir -p "$HOME/.local/bin"
curl -fsSL https://raw.githubusercontent.com/aperiodic-io/cli/main/install.sh | INSTALL_DIR="$HOME/.local/bin" bash
export PATH="$HOME/.local/bin:$PATH"

# Free preview — no API key required
aperiodic l1_price --preview \
  --exchange binance-futures \
  --symbol perpetual-BTC-USDT:USDT \
  --interval 5m \
  --timestamp exchange \
  --start-date 2025-05-01 \
  --end-date 2025-05-31 \
  --output-dir ./data && echo "Saved to $PWD/data"

Live Stream

Every new row as it is computed, over WebSocket at wss://stream.aperiodic.io/v1/stream. Authenticate with your API key in the X-API-KEY header and subscribe to channels named l1_price.<exchange>.<interval>, on intervals 15s, 30s, 1m, 5m, 15m, 30m, 1h, 4h, 1d (15s and 30s on Institutional Live only). Streaming is included on Live plans.

pip install "aperiodic[stream]"

pypi ↗

import os

from aperiodic import stream

for message in stream(
    api_key=os.environ["APERIODIC_API_KEY"],
    dataset="l1_price",
    exchange="binance-futures",
    interval="1m",
    symbols=["perpetual-BTC-USDT:USDT"],  # omit for every symbol on your plan
):
    print(message.channel, message.snapshot, message.data)

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. Sub-minute intervals (15s, 30s) require an Institutional plan.

15s30s1m5m15m30m1h4h1d

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). A metric series starts on the first day of the raw series it is computed from (see /metadata/raw); raw trades and quotes start binance-futures from 2020-01-01, okx-perps from 2019-09-01, hyperliquid-perps from 2025-01-01. Earlier days return no files. How far back you can go depends on the plan: 5 years on Pro, full history on Prime, Prime + Raw and Institutional. An earlier start_date than the plan reaches returns 403.

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 every existing file covering the range from the series' published start — one per month before 2026-08-01, one per day from 2026-08-01 onwards

Schema

filesobject[]required

Files covering the requested date range, in chronological order. Data before 2026-08-01 is split by month (one file per calendar month, no `day`); data from 2026-08-01 onwards is split by day (one file per calendar day, with `day` set). The changeover falls on a month boundary, so a given month is served entirely one way or the other; a range spanning it returns the earlier months as monthly files followed by a daily file per day.

yearintegerrequired

Year of the data file

monthintegerrequired

Month of the data file (1-12)

dayinteger

Day of the data file (1-31). Present only on daily files, i.e. those covering 2026-08-01 onwards. Absent on monthly files, which cover an entire calendar month.

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": 2026,
      "month": 6,
      "url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2026-06.parquet?X-Amz-Expires=300&..."
    },
    {
      "year": 2026,
      "month": 7,
      "url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2026-07.parquet?X-Amz-Expires=300&..."
    },
    {
      "year": 2026,
      "month": 8,
      "day": 1,
      "url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2026-08-01.parquet?X-Amz-Expires=300&..."
    },
    {
      "year": 2026,
      "month": 8,
      "day": 2,
      "url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2026-08-02.parquet?X-Amz-Expires=300&..."
    }
  ]
}

Try It

Prefilled with the shared DEMO-KEY and a free preview slice — send the request to see live data, no account required.

timestamp*

interval*

exchange*

symbol*

Suggestions shown — any valid value accepted

start_date*

Suggestions shown — any valid value accepted

end_date*

Suggestions shown — any valid value accepted

Authentication

X-API-KEY*

GET

/api/v1/data/preview/l1_price?timestamp=exchange&interval=5m&exchange=binance-futures&symbol=perpetual-BTC-USDT%3AUSDT&start_date=2025-05-01&end_date=2025-05-31

Response will appear here

Use case

Execute smarter

Know when liquidity is deep, when spreads are wide, and when flow turns toxic.

Featured notebook

Timing execution around liquidity

Loading notebook…

Or have your agent rerun this notebook and tell you what it finds. Start in Claude Claude Code Codex See the prompt

From notebook to production

Pick the metrics

Browse the catalog and pull point-in-time microstructure metrics — no L2 reconstruction, no tick archive to maintain.

Run the notebook

Every notebook runs end to end on preview data with a free account, in the browser or through the CLI.

Plug it into your stack

Swap the preview key for your own and the same code pulls every year your plan includes through the Python package or the API.

Metrics in this use case

More notebooks for this use case

Related notebook

Intro to Aperiodic L1 Price Metrics

Execute smarter

This notebook explores top-of-book (L1) pricing with Aperiodic's `l1_price` metric for Binance BTC perpetuals from September 1, 2025 through February 28, 2026 at 5-minute granularity.

View notebook

Execute smarter

Know when liquidity is deep, when spreads are wide, and when flow turns toxic.

Explore real-time streaming Book a call (Institutional)

Or create a free account to run the notebooks on preview data.

Shown: minute lows of the 465 Binance perpetuals, 20:40–22:00 UTC on 10 Oct 2025, with BTC’s path traced · built with ohlcv 1m

L1 Price

L1 (Top of Book)

L1 Price

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

See it on real data

Need the ticks behind this metric? Prime + Raw includes raw quotes.

Sample CSV Start in Claude

Shown: quote_update_frequency, hourly, 1–31 January 2024, from this page's Sample CSV · extreme: 69355.000, 3 Jan, 12:00 UTC · built with l1_price

low

high

extreme

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)
Built from: Raw quotes →
Intervals: 1m5m15m30m1h4h1d
Requires Institutional: 15s30s
Exchanges: binance-futuresokx-perpshyperliquid-perps

Fields

Field	Name	Description
`ask_price`	Ask Price	Last best ask price in the interval
`bid_price`	Bid Price	Last best bid price in the interval
`ask_amount`	Ask Amount	Last best ask quantity in the interval
`bid_amount`	Bid Amount	Last best bid quantity in the interval
`quote_update_frequency`	Quote Update Frequency	Number of top-of-book quote updates in the interval
`avg_update_interval`	Avg Update Interval	Average milliseconds between top-of-book quote updates
`midprice`	Mid Price	Midpoint between the last best bid and ask prices
`weighted_midprice`	Weighted Mid Price	Midprice weighted by the opposite-side top-of-book quantity
`bid_price_twap`	Bid Price TWAP	Average best bid price in the interval
`ask_price_twap`	Ask Price TWAP	Average best ask price in the interval
`bid_price_vwap`	Bid Price VWAP	Bid-price average weighted by best bid quantity
`ask_price_vwap`	Ask Price VWAP	Ask-price average weighted by best ask quantity

Example Request

# Install the Aperiodic CLI into ~/.local/bin
mkdir -p "$HOME/.local/bin"
curl -fsSL https://raw.githubusercontent.com/aperiodic-io/cli/main/install.sh | INSTALL_DIR="$HOME/.local/bin" bash
export PATH="$HOME/.local/bin:$PATH"

# Free preview — no API key required
aperiodic l1_price --preview \
  --exchange binance-futures \
  --symbol perpetual-BTC-USDT:USDT \
  --interval 5m \
  --timestamp exchange \
  --start-date 2025-05-01 \
  --end-date 2025-05-31 \
  --output-dir ./data && echo "Saved to $PWD/data"

Live Stream

pip install "aperiodic[stream]"

pypi ↗

import os

from aperiodic import stream

for message in stream(
    api_key=os.environ["APERIODIC_API_KEY"],
    dataset="l1_price",
    exchange="binance-futures",
    interval="1m",
    symbols=["perpetual-BTC-USDT:USDT"],  # omit for every symbol on your plan
):
    print(message.channel, message.snapshot, message.data)

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. Sub-minute intervals (15s, 30s) require an Institutional plan.

15s30s1m5m15m30m1h4h1d

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>

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 every existing file covering the range from the series' published start — one per month before 2026-08-01, one per day from 2026-08-01 onwards

Schema

filesobject[]required

yearintegerrequired

Year of the data file

monthintegerrequired

Month of the data file (1-12)

dayinteger

Day of the data file (1-31). Present only on daily files, i.e. those covering 2026-08-01 onwards. Absent on monthly files, which cover an entire calendar month.

urlstring<uri>required

Example

{
  "files": [
    {
      "year": 2026,
      "month": 6,
      "url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2026-06.parquet?X-Amz-Expires=300&..."
    },
    {
      "year": 2026,
      "month": 7,
      "url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2026-07.parquet?X-Amz-Expires=300&..."
    },
    {
      "year": 2026,
      "month": 8,
      "day": 1,
      "url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2026-08-01.parquet?X-Amz-Expires=300&..."
    },
    {
      "year": 2026,
      "month": 8,
      "day": 2,
      "url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2026-08-02.parquet?X-Amz-Expires=300&..."
    }
  ]
}

Try It

Prefilled with the shared DEMO-KEY and a free preview slice — send the request to see live data, no account required.

timestamp*

interval*

exchange*

symbol*

Suggestions shown — any valid value accepted

start_date*

Suggestions shown — any valid value accepted

end_date*

Suggestions shown — any valid value accepted

Authentication

X-API-KEY*

GET

/api/v1/data/preview/l1_price?timestamp=exchange&interval=5m&exchange=binance-futures&symbol=perpetual-BTC-USDT%3AUSDT&start_date=2025-05-01&end_date=2025-05-31

Response will appear here

Timing execution around liquidity

Pick the metrics

Run the notebook

Plug it into your stack

Spreads & top-of-book liquidity

Multi-level depth

Market impact

Flow toxicity

Intro to Aperiodic L1 Price Metrics

Execute smarter

Mid Price

Weighted Mid Price

Quote Update Frequency

Avg Update Interval

Bid Price VWAP

Fields

Example Request

Live Stream

API Reference

Query Parameters

Schema

Example

Try It

Timing execution around liquidity

Pick the metrics

Run the notebook

Plug it into your stack

Spreads & top-of-book liquidity

Multi-level depth

Market impact

Flow toxicity

Intro to Aperiodic L1 Price Metrics

Execute smarter

Mid Price

Weighted Mid Price

Quote Update Frequency

Avg Update Interval

Bid Price VWAP

Fields

Example Request

Live Stream

API Reference

Query Parameters

Schema

Example

Try It