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README.md

CoinMarketCap Historical Data Retrieval

Build StatusCoverage Status

Obtain USD price history data for CoinMarketCap-listed cryptocurrencies.

Use this library as a command-line script to obtain historical cryptocurrency data on the fly, or import the cmc library to obtain cryptocurrency data within your Python program.

Contents


Installation

Install coinmarketcap-history with pip:

$ pip install cmc

Usage

Command Line

The command line tool is useful for US tax reporting, among other things. If you wish to report the cost basis for a trade (or for coins acquired through mining), the IRS requires you to denominate that cost basis in USD. In the case of token-for-token trades (e.g. purchasing ETH with BTC), that requires you know the USD:BTC exchange rate at the time of the trade.

Rather than getting the exchange rate at the exact moment of your trade, which is generally not feasible, the IRS standard is to use the average of a stock's high and low price for the day. CoinMarketCap doesn't provide this figure, but this tool does.

Command Line Usage

To gather cryptocurrency data, open a terminal and run:

$ coinmarketcap <currency1> <start_date> <end_date>

where:

  • currency is the (case-insensitive) name of the currency / token as displayed on CoinMarketCap, with dashes in place of spaces (i.e. bitcoin).
  • start_date is the beginning of the range to fetch data for in yyyy-mm-dd format (i.e. 2017-10-01 for 2017 October 10th).
  • end_year is the end of the range to fetch data for in yyyy-mm-dd format.

Data is returned in the following tabular format:

Bitcoin
Date Open High Low Close Volume Market Cap Average
... ... ... ... ... ... ... ...

Data for multiple cryptocurrencies can be obtained with:

$ coinmarketcap <currency_1,currency_2,...,currency_n> <start_date> <end_date>

Note: currencies must be comma-separated, with no spaces in between.

Data for multiple cryptocurrencies is returned in the following tabular format:

Bitcoin Ripple
Date Open High Low Close Volume Market Cap Average Open High Low Close Volume Market Cap Average
... ... ... ... ... ... ... ... ... ... ... ... ... ... ...

The above information can also be found by running:

$ coinmarketcap -h

Write outputs to a file by running:

$ coinmarketcap <currency> <start_date> <end_date> > <output_filename>

For faster retrieval, cryptocurrency data can be gathered asynchronously by supplying the --asynchro flag:

$ coinmarketcap <currency> <start_date> <end_date> --asynchro

Running coinmarketcap asynchronously greatly reduces the amount of time required to obtain data for cryptocurrencies, especially when gathering data for multiple cryptocurrencies at a time:

Note: Asynchronous runtimes may vary according to CPU architecture. Benchmark performed with a 64-bit 6-core AMD processor.

Command Line Examples

Collecting data for one cryptocurrency:

$ coinmarketcap bitcoin 2017-01-01 2017-12-31

Collecting data for multiple cryptocurrencies:

$ coinmarketcap bitcoin,ripple,ethereum 2017-01-01 2017-12-31

Collecting data for multiple cryptocurrencies asynchronously(faster):

$ coinmarketcap bitcoin,ripple,ethereum 2017-01-01 2017-12-31 --asynchro

Writing output to a file:

$ coinmarketcap bitcoin 2017-01-01 2017-12-31 > bitcoin_history.csv

Writing output for multiple cryptocurrencies to a file:

$ python coinmarketcap.py bitcoin,ripple,ethereum 2017-01-01 2017-12-31 > bitcoin_ripple_ethereum_history.csv

Module

In addition to command-line functionality, coinmarketcap-history provides the cmc library, which allows users to obtain CoinMarketCap data from within a Python program. Historical is returned in the form of a Pandas DataFrame, which allows for easy use.

To get started with the cmc library, import it from within your program:

from cmc import coinmarketcap

Data for cryptocurrencies can be gathered using the getDataFor() method:

getDataFor()

  • params:
    • cryptocurrencies: string or list

      • crypto(s) to be scraped. supply a string for a single cryptocurrency, or supply a list of strings for multiple cryptocurrencies.
    • start_date: datetime object

      • datetime object for the beginning of the range to fetch data for. Must contain values for year, month, and day.
    • end_date: datetime object

      • datetime object for the ebd of the range to fetch data for. Must contain values for year, month, and day.
    • fields (optional): list

      • columns to obtain upon data retrieval. Options are:
        • ['Open','High','Low','Close','Volume','Market Cap','Average']
      • if fields is not specified, all fields are returned.
    • async (optional): boolean

      • if True, data is gathered asynchronously. This is especially useful when gathering data for multiple cryptocurrencies at a time, which can be slow when gathered synchronously. If async is not specified, data is gathered synchronously.
    • DOWNLOAD_DIR (optional): string

      • String of the relative path to save data to and load data from. If DOWNLOAD_DIR is not specified, no data is saved.
  • returns:
    • out: Pandas DataFrame
      • A DataFrame containing historical price information for the specified cryptocurrencies through the desired daterange.

Library Examples

Gathering data for a single cryptocurrency:

from cmc import coinmarketcap
from datetime import datetime

crypto = 'bitcoin'
start_date, end_date = datetime(2017,6,1), datetime(2018,6,1)

df_bitcoin = coinmarketcap.getDataFor(crypto, start_date, end_date)

Getting data for multiple cryptocurrencies:

from cmc import coinmarketcap
from datetime import datetime

cryptos = ['bitcoin','ripple','ethereum']
start_date, end_date = datetime(2017,6,1), datetime(2018,6,1)

df_cryptos = coinmarketcap.getDataFor(cryptos, start_date, end_date)

To cache retrieved data, simply supply a string for DOWNLOAD_DIR. The string should be a relative path to the desired download directory. Data is stored in the lightweight .msg format.

Saving data and pulling cached data:

from cmc import coinmarketcap
from datetime import datetime

cryptos = ['bitcoin','ripple','ethereum']
start_date, end_date = datetime(2017,6,1), datetime(2018,6,1)

# retrieves data and stores .msg files in DOWNLOAD_DIR
df_cryptos = coinmarketcap.getDataFor(cryptos, start_date, end_date, DOWNLOAD_DIR = 'data/coinmarketcap')

# does not retreive data. Instead, pulls cached data from DOWNLOAD_DIR
df_cryptos = coinmarketcap.getDataFor(cryptos, start_date, end_date, DOWNLOAD_DIR = 'data/coinmarketcap')

Pulling specified columns only:

from cmc import coinmarketcap
from datetime import datetime

cryptos = ['bitcoin','ripple','ethereum']
start_date, end_date = datetime(2017,6,1), datetime(2018,6,1)

df_cryptos = coinmarketcap.getDataFor(cryptos, start_date, end_date, fields = ['High','Low','Close'])

Legacy

Legacy code can be obtained from the coinmarketcap-history-legacy repository found here.


Updates

2.0.0 - July 6th, 2018

  • as of version 2, coinmarketcap-history now offers support for Python 3. Additionally, the cmc artifact allows for global use of the coinmarketcap command line tool, as well as dedicated support for in-program operations.

2.0.2 - May 30th, 2019

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