# =============================================================================
# File: get_coin_data.py
# Author: Andre Brener
# Created: 08 May 2017
# Last Modified: 02 Jul 2017
# Description: description
# =============================================================================
import json
import time
import requests
import pandas as pd
from constants import COIN_DATA_DAYS, COIN_DATA_DF
def get_current_prices(coin_list, currency='BTC'):
coin_list_string = ','.join(coin_list)
price_now_url = 'https://min-api.cryptocompare.com/data/pricemulti?fsyms={}&tsyms={}'.format(
coin_list_string, currency)
response_text = requests.get(price_now_url).text
d = json.loads(response_text)
coin_prices = [[coin, val[currency]] for coin, val in d.items()]
return coin_prices
def get_df_from_api(url):
response_text = requests.get(url).text
d = json.loads(response_text)
df = pd.DataFrame(d['Data'])
return df
def get_price_history(coin_list, end_date, currency='BTC'):
ts = time.mktime(end_date.timetuple())
df_list = []
btc_url = 'https://min-api.cryptocompare.com/data/histoday?fsym=BTC&tsym=USD&toTs={}&limit={}'.format(
ts, COIN_DATA_DAYS)
btc_df = get_df_from_api(btc_url)
btc_df['coin'] = 'BTC'
df_list.append(btc_df)
for l in coin_list:
url = 'https://min-api.cryptocompare.com/data/histoday?fsym={}&tsym={}&toTs={}&limit={}'.format(
l, currency, ts, COIN_DATA_DAYS)
df = get_df_from_api(url)
if df.empty:
continue
df = df[['time', 'close']]
df['coin'] = l
df_list.append(df)
total_df = pd.concat(df_list)
total_df = total_df.pivot(
index='time', columns='coin', values='close').reset_index()
total_df['date'] = pd.to_datetime(total_df['time'], unit='s')
cols = [col for col in total_df.columns if col not in ['time', 'coin']]
total_df = total_df[cols]
total_df['date'] = pd.to_datetime(total_df['date'])
return total_df
def get_graph(df, coin_name, day_interval, dates=True):
import matplotlib.dates as mdates
from matplotlib import pyplot as plt
fig, ax = plt.subplots(figsize=(10, 5))
plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%a'))
if dates:
plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%d-%b'))
plt.gca().xaxis.set_major_locator(mdates.DayLocator(interval=day_interval))
plt.gcf().autofmt_xdate()
plt.xlabel('Date', fontsize=14)
plt.ylabel('Price', fontsize=14)
plt.title('{} Price History'.format(coin_name))
y = df[coin_name]
plt.plot(df['date'], y)
def plot_graphs(df, day_interval, dates=True):
cols = [col for col in df.columns if col not in ['time', 'date']]
for coin_name in cols:
get_graph(df, coin_name, day_interval)
if __name__ == '__main__':
from datetime import date, timedelta
coin_list = list(COIN_DATA_DF['coin'].unique())
end_date = date.today() - timedelta(1)
df = get_price_history(coin_list, end_date)
df.to_csv('historical_data.csv', index=False)
