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import requests
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import json
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import os
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import time
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import datetime
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import pandas as pd
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import numpy as np
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import sqlite3
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def get_markets():
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url = 'https://api.bitvavo.com/v2/markets'
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response = requests.get(url)
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markets = response.json()
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return markets
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markets = get_markets()
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markets = pd.DataFrame(markets)
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markets.to_csv('markets.csv', index=False)
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def get_assets():
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url = 'https://api.bitvavo.com/v2/assets'
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response = requests.get(url)
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assets = response.json()
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return assets
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assets = get_assets()
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assets = pd.DataFrame(assets)
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assets.to_csv('assets.csv', index=False)
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print('Data downloaded and saved to assets.csv and markets.csv')
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if not os.path.exists('candles'):
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os.makedirs('candles')
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for market in markets['market']:
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print('Downloading', market)
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url = f'https://api.bitvavo.com/v2/{market}/candles?interval=1d&limit=1440'
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response = requests.get(url)
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data = response.json()
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data = pd.DataFrame(data, columns=['time', 'open', 'high', 'low', 'close', 'volume'])
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data['market'] = market
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data = data[['market', 'time', 'open', 'high', 'low', 'close', 'volume']]
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data.to_csv(f'candles/{market}.csv', index=False)
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time.sleep(0.5)
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candles = []
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for market in markets['market']:
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data = pd.read_csv(f'candles/{market}.csv')
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data['market'] = market
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candles.append(data)
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candles = pd.concat(candles)
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candles['time'] = pd.to_datetime(candles['time'], unit='ms')
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candles = candles.set_index(['market', 'time'])
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candles.to_csv('candles.csv')
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conn = sqlite3.connect('crypto_data.db')
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candles.to_sql('candles', conn, if_exists='replace')
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conn.close()
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print('Candles data saved to candles.csv and crypto_data.db') |
