Transactions

Contents

• Transactions in Block

• Mempool Transaction Count

• Transaction Count Entered Mempool 1 Minute

Transactions in Block

Definition

The count of all transactions within the most recent block processed.

Dictionary

Name	MetricID	Unit	Interval
Transactions in Block	block_tx_count	Count of transactions	1b

Methodology

The most recent block we processed within a 1-minute window is evaluated and the number of transactions within the block are counted. For UTXO based currencies, this includes the coinbase transaction.

Available Assets

Bitcoin (BTC), Ethereum (ETH)

Sample Query

https://api.coinmetrics.io/v4/timeseries/asset-metrics?api_key=%3Cyour_key%3E&assets=eth&frequency=1b&metrics=block_tx_count&pretty=trueapi.coinmetrics.io

Mempool Transaction Count

Definition

The count of all mempool transactions at a point in time.

Dictionary

Name	MetricID	Unit	Interval
Mempool Transaction Count	mempool_count	Transaction	1m

Methodology

The mempool is evaluated and all transactions indexed. All unprocessed mempool transactions at a point in time are then counted.

Available Assets

Bitcoin (BTC)

Sample Query

https://api.coinmetrics.io/v4/timeseries/asset-metrics?api_key=%3Cyour_key%3E&assets=btc&frequency=1m&limit_per_asset=1&metrics=mempool_count&pretty=trueapi.coinmetrics.io

Transaction Count Entered Mempool 1 Minute

Definition

The count of all transactions that have entered the mempool over the course of a 1-minute aggregation window. The beginning of this time window is noted in the “time” field of the response.

Dictionary

Name	MetricID	Unit	Interval
Transaction Count entered mempool 1 minute	mempool_count_entered_1m	Transaction	1m

Methodology

The mempool is evaluated and all transactions that have been entered (new transactions broadcasted by users) since a point in time are counted.

Available Assets

Bitcoin (BTC)

Sample Query

https://api.coinmetrics.io/v4/timeseries/asset-metrics?api_key=%3Cyour_key%3E&assets=btc&frequency=1m&limit_per_asset=1&metrics=mempool_count_entered_1m&pretty=trueapi.coinmetrics.io

API Endpoints

Transactions metrics can be accessed using these endpoints:

• timeseries/asset-metrics

and by passing in the metric ID's block_tx_count* and mempool_count_* in the metrics parameter.

Asset metrics

Returns requested metrics for specified assets. Results for block by block metrics (1b frequency) are ordered by tuple (asset, height, block_hash), all other metrics are ordered by tuple (asset, time). You can change the sorting using sort query parameter. Supported output formats are json (default) and csv, use format query parameter to override it. To fetch the next page of results use next_page_url JSON response field or x-next-page-url CSV HTTP header if present. If multiple metrics are requested in the same time the strict policy for partially available metrics among requested ones is applied:

GEThttps://api.coinmetrics.io/v4/timeseries/asset-metrics

Authorization

api_key

Query parameters

Response

200400401403414

Time series of metrics for an asset.

Body

application/jsontext/csv

data*any

next_page_tokenNextPageToken (string)

Token of the next page results for a given request.

next_page_urlNextPageUrl (string)

URL of the next page results for a given request.

Request

ShellPython

curl --compressed "https://api.coinmetrics.io/v4/timeseries/asset-metrics?assets=btc&metrics=PriceUSD,FlowInGEMUSD&frequency=1d&pretty=true&api_key=<your_key>"

Response

{
  "next_page_token": "text",
  "next_page_url": "text"
}

Shell

curl --compressed "https://api.coinmetrics.io/v4/timeseries/asset-metrics?metrics=block_tx_count&assets=btc&pretty=true&api_key=<your_key>"

Python

import requests
response = requests.get('https://api.coinmetrics.io/v4/timeseries/asset-metrics?metrics=block_tx_count&assets=btc&pretty=true&api_key=<your_key>').json()
print(response)

Python Client

from coinmetrics.api_client import CoinMetricsClient

api_key = "<API_KEY>"
client = CoinMetricsClient(api_key)

print(
    client.get_asset_metrics(
        metrics="block_tx_count", 
        assets="btc",
    ).to_dataframe()
)