Coin Metrics Python API v4 client library¶
This is an official Python API client for Coin Metrics API v4.
Installation and Updates¶
To install the client you can run the following command:
pip install coinmetrics-api-client
To update your version, run the following command:
pip install coinmetrics-api-client -U
You can use this client for querying all kinds of data with your API.
To initialize the client you should use your API key, and the CoinMetricsClient class like the following.
from coinmetrics.api_client import CoinMetricsClient client = CoinMetricsClient("<cm_api_key>") # or to use community API: client = CoinMetricsClient()
After that you can use the client object for getting stuff like available markets:
or to query all available assets along with what is available for those assets, like metrics, markets:
you can also use filters for the catalog endpoints like this:
You can use this client to connect to our API v4 and get catalog or timeseries data from python environment. It natively supports paging over the data so you can use it to iterate over timeseries entries seamlessly.
The client can be used to query both pro and community data.
The full list of methods can be found in the API Client Spec.
The API Client allows you to chain together workflows for importing, transforming, then exporting Coin Metrics data. Below are examples of common use-cases that can be altered to tailor your specific needs.
walkthrough_community.ipynb: Walks through the basic functionality available using the community client.
bbb_metrics_csv_exporter_using_plain_requests.py: Queries block-by-block metrics using the
requestslibrary and exports the output into a CSV file.
bbb_metrics_json_exporter.py: Queries block-by-block metrics and exports the output into a JSON file.
eod_metrics_csv_exporter.py: Exports a set of user-defined metrics and assets published at end-of-day and exports the output into a CSV file.
reference_rates_json_exporter.py: Queries Coin Metrics Reference Rates at a user-defined frequency for a set of assets, then exports the output into a JSON file.
books_json_exporter.py: Queries market orderbook data then exports the output into a JSON file.
candles_json_exporter.py: Queries market candles data then exports the output into a JSON file.
funding_rates_json_exporter.py: Queries market funding rates data then exports the output into a JSON file.
trades_csv_exporter.py: Queries market trades data then exports the output into a CSV file.
trades_json_exporter.py: Queries market trades data then exports the output into a JSON file.
Getting timeseries data¶
For getting timeseries data you want to use methods of the client class that start with
For example if you want to get a bunch of market data trades for coinbase btc-usd pair you can run something similar to the following:
for trade in client.get_market_trades( markets='coinbase-btc-usd-spot', start_time='2020-01-01', end_time='2020-01-03', limit_per_market=10 ): print(trade)
Or if you want to see daily btc asset metrics you can use something like this:
for metric_data in client.get_asset_metrics(assets='btc', metrics=['ReferenceRateUSD', 'BlkHgt', 'AdrActCnt', 'AdrActRecCnt', 'FlowOutBFXUSD'], frequency='1d', limit_per_asset=10): print(metric_data)
(New in >=
Timeseries data can be transformed into a pandas dataframe by using the
to_dataframe() method. The code snippet below shows how:
import pandas as pd from coinmetrics.api_client import CoinMetricsClient from os import environ client = CoinMetricsClient() trades = client.get_market_trades( markets='coinbase-btc-usd-spot', start_time='2021-09-19T00:00:00Z', limit_per_market=10 ) trades_df = trades.to_dataframe() print(trades_df.head())
- This only works with requests that return the type
catalogrequests, which return lists cannot be returned as dataframes. Please see the API Client Spec for a full list of requests and their return types.
- API restrictions apply. Some requests may return empty results due to limited access to the API from you API key.
You can make the datapoints to iterate from start or from end (default).
for that you should use a paging_from argument like the following:
from coinmetrics.api_client import CoinMetricsClient from coinmetrics.constants import PagingFrom client = CoinMetricsClient() for metric_data in client.get_asset_metrics(assets='btc', metrics=['ReferenceRateUSD'], paging_from=PagingFrom.START): print(metric_data)
PagingFrom.END: is available but it is also a default value also, so you might not want to set it.
SSL Certs verification¶
Sometimes your organization network have special rules on SSL certs verification and in this case you might face the following error when running the script:
SSLError: HTTPSConnectionPool(host='api.coinmetrics.io', port=443): Max retries exceeded with url: <some_url_path> (Caused by SSLError(SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self signed certificate in certificate chain (_ssl.c:1123)')))
In this case, you can pass an option during client initialization to disable ssl verification for requests like this:
client = CoinMetricsClient(verify_ssl_certs=False)
We don't recommend setting it to False by default and you should make sure you understand the security risks of disabling SSL certs verification.
For more information about the available methods in the client please reference API Client Spec