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crawler.py
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from binance.client import Client
from binance.websockets import BinanceSocketManager
from google.cloud import bigquery
import json
import time
with open('config.json', 'r') as f:
config = json.load(f)
BINANCE_API_KEY = config['DEFAULT']['BINANCE']['API_KEY']
BINANCE_SECRET_KEY = config['DEFAULT']['BINANCE']['SECRET_KEY']
PROJECT_ID = config['DEFAULT']['BQ']['PROJECT_ID']
DATASET_ID = config['DEFAULT']['BQ']['DATASET_ID']
bq_client = bigquery.Client()
client = Client(BINANCE_API_KEY, BINANCE_SECRET_KEY)
class Stream:
def __init__(self, name, table_id, create_table=False):
self.name = name
self.table_id = table_id
if create_table:
table = bigquery.Table('%s.%s.%s' % (PROJECT_ID, DATASET_ID, table_id), schema=self.schema)
self.table = bq_client.create_table(table)
else:
self.table = bq_client.dataset(DATASET_ID).table(self.table_id)
def write_to_bq(self, data):
errors = bq_client.insert_rows(self.table, data, selected_fields=self.schema)
class AggregateTradeStream(Stream):
def __init__(self, symbol, create_table=False):
self.schema = [
bigquery.SchemaField('time', 'TIMESTAMP'),
bigquery.SchemaField('agg_trade_id', 'INTEGER'),
bigquery.SchemaField('price', 'FLOAT'),
bigquery.SchemaField('quantity', 'FLOAT'),
bigquery.SchemaField('first_trade_id', 'INTEGER'),
bigquery.SchemaField('last_trade_id', 'INTEGER'),
bigquery.SchemaField('trade_time', 'TIMESTAMP'),
bigquery.SchemaField('is_buyer_market_maker', 'BOOLEAN')
]
Stream.__init__(self, '%s@aggTrade' % symbol, '%s_agg_trade' % symbol, create_table)
def process(self, msg):
return [(
int(msg['E']) / 1000., # Event time
msg['a'], # Aggregate trade ID
msg['p'], # Price
msg['q'], # Quantity
msg['f'], # First trade ID
msg['l'], # Last trade ID
msg['T'] / 1000., # Trade time
msg['m'] == 'true' # Is the buyer the market maker ?
)]
class TradeStream(Stream):
def __init__(self, symbol, create_table=False):
self.schema = [
bigquery.SchemaField('time', 'TIMESTAMP'),
bigquery.SchemaField('trade_id', 'INTEGER'),
bigquery.SchemaField('price', 'FLOAT'),
bigquery.SchemaField('quantity', 'FLOAT'),
bigquery.SchemaField('buyer_order_id', 'INTEGER'),
bigquery.SchemaField('seller_order_id', 'INTEGER'),
bigquery.SchemaField('trade_time', 'TIMESTAMP'),
bigquery.SchemaField('is_buyer_market_maker', 'BOOLEAN')
]
Stream.__init__(self, '%s@trade' % symbol, '%s_trade' % symbol, create_table)
def process(self, msg):
return [(
int(msg['E']) / 1000., # Event time
msg['t'], # Trade ID
msg['p'], # Price
msg['q'], # Quantity
msg['b'], # Buyer order ID
msg['a'], # Seller order ID
int(msg['T']) / 1000., # Trade time
msg['m'] == 'true' # Is the buyer the market maker ?
)]
class KlineCandlestickStream(Stream):
def __init__(self, symbol, interval, create_table=False):
self.schema = [
bigquery.SchemaField('time', 'TIMESTAMP'),
bigquery.SchemaField('kline_start_time', 'TIMESTAMP'),
bigquery.SchemaField('kline_close_time', 'TIMESTAMP'),
bigquery.SchemaField('interval', 'STRING'),
bigquery.SchemaField('first_trade_id', 'INTEGER'),
bigquery.SchemaField('last_trade_id', 'INTEGER'),
bigquery.SchemaField('open_price', 'FLOAT'),
bigquery.SchemaField('close_price', 'FLOAT'),
bigquery.SchemaField('high_price', 'FLOAT'),
bigquery.SchemaField('low_price', 'FLOAT'),
bigquery.SchemaField('base_volume', 'FLOAT'),
bigquery.SchemaField('nb_trades', 'INTEGER'),
bigquery.SchemaField('is_closed', 'BOOLEAN'),
bigquery.SchemaField('quote_volume', 'FLOAT'),
bigquery.SchemaField('taker_buy_base_volume', 'FLOAT'),
bigquery.SchemaField('taker_buy_quote_volume', 'FLOAT')
]
Stream.__init__(self, '%s@kline_%s' % (symbol, interval), '%s_kline_%s' % (symbol, interval), create_table)
def process(self, msg):
return [(
int(msg['E']) / 1000., # Event time
int(msg['k']['t']) / 1000., # Kline start time
int(msg['k']['T']) / 1000., # Kline close time
msg['k']['i'], # Interval
msg['k']['f'], # First trade ID
msg['k']['L'], # Last trade ID
msg['k']['o'], # Open price
msg['k']['c'], # Close price
msg['k']['h'], # High price
msg['k']['l'], # Low price
msg['k']['v'], # Base asset volume
msg['k']['n'], # Number of trades
msg['k']['x'] == 'true', # Is this kline closed ?
msg['k']['q'], # Quote asset volume
msg['k']['V'], # Taker buy base asset volume
msg['k']['Q'] # Taker buy quote asset volume
# msg['k']['B'] # Ignore
)]
class IndividualSymbolMiniTickerStream(Stream):
def __init__(self, symbol, create_table=False):
self.schema = [
bigquery.SchemaField('time', 'TIMESTAMP'),
bigquery.SchemaField('close_price', 'FLOAT'),
bigquery.SchemaField('open_price', 'FLOAT'),
bigquery.SchemaField('high_price', 'FLOAT'),
bigquery.SchemaField('low_price', 'FLOAT'),
bigquery.SchemaField('base_volume', 'FLOAT'),
bigquery.SchemaField('quote_volume', 'FLOAT')
]
Stream.__init__(self, '%s@miniTicker' % symbol, '%s_mini_ticker' % symbol, create_table)
def process(self, msg):
return [(
int(msg['E']) / 1000., # Event time
msg['c'], # Close price
msg['o'], # Open price
msg['h'], # High price
msg['l'], # Low price
msg['v'], # Total traded base asset volume
msg['q'], # Total traded quote asset volume
)]
class IndividualSymbolTickerStream(Stream):
def __init__(self, symbol, create_table=False):
self.schema = [
bigquery.SchemaField('time', 'TIMESTAMP'),
bigquery.SchemaField('price_change', 'FLOAT'),
bigquery.SchemaField('price_change_percent', 'FLOAT'),
bigquery.SchemaField('weighted_average_price', 'FLOAT'),
bigquery.SchemaField('first_trade', 'FLOAT'),
bigquery.SchemaField('last_trade', 'FLOAT'),
bigquery.SchemaField('last_quantity', 'FLOAT'),
bigquery.SchemaField('best_bid_price', 'FLOAT'),
bigquery.SchemaField('best_bid_quantity', 'FLOAT'),
bigquery.SchemaField('best_ask_price', 'FLOAT'),
bigquery.SchemaField('best_ask_quantity', 'FLOAT'),
bigquery.SchemaField('open_price', 'FLOAT'),
bigquery.SchemaField('high_price', 'FLOAT'),
bigquery.SchemaField('low_price', 'FLOAT'),
bigquery.SchemaField('traded_base_volume', 'FLOAT'),
bigquery.SchemaField('traded_quote_volume', 'FLOAT'),
bigquery.SchemaField('stats_open_time', 'TIMESTAMP'),
bigquery.SchemaField('stats_close_time', 'TIMESTAMP'),
bigquery.SchemaField('first_trade_id', 'INTEGER'),
bigquery.SchemaField('last_trade_id', 'INTEGER'),
bigquery.SchemaField('total_num_trades', 'INTEGER')
]
Stream.__init__(self, '%s@ticker' % symbol, '%s_ticker' % symbol, create_table)
def process(self, msg):
return [(
int(msg['E']) / 1000., # Event time
msg['p'], # Price change
msg['P'], # Price change percent
msg['w'], # Weighted average price
msg['x'], # First trade(F)-1 price (first trade before the 24hr rolling window)
msg['c'], # Last price
msg['Q'], # Last quantity
msg['b'], # Best bid price
msg['B'], # Best bid quantity
msg['a'], # Best ask price
msg['A'], # Best ask quantity
msg['o'], # Open price
msg['h'], # High price
msg['l'], # Low price
msg['v'], # Total traded base asset volume
msg['q'], # Total traded quote asset volume
msg['O'] / 1000., # Statistics open time
msg['C'] / 1000., # Statistics close time
msg['F'], # First trade ID
msg['L'], # Last trade Id
msg['n'] # Total number of trades
# msg['s'] # Symbol
)]
class PartialBookDepthStream(Stream):
def __init__(self, symbol, levels=None, create_table=False):
self.levels = levels
self.schema = [
bigquery.SchemaField('time', 'TIMESTAMP'),
bigquery.SchemaField('price_level', 'FLOAT'),
bigquery.SchemaField('quantity', 'FLOAT'),
bigquery.SchemaField('is_bid', 'BOOLEAN')
]
Stream.__init__(self, '%s@depth' % symbol + (str(levels) if levels is not None else ''), '%s_depth' % symbol, create_table)
def process(self, msg):
data = []
bids_key = 'bids' if self.levels is not None else 'b'
asks_key = 'bids' if self.levels is not None else 'a'
timestamp = time.time()
for i in range(len(msg[bids_key])): # Bids to be updated
data += [(
timestamp, # Event time
msg[bids_key][i][0], # Price level to be updated
msg[bids_key][i][1], # Quantity
True # Is bid
)]
for i in range(len(msg[asks_key])): # Asks to be updated
data += [(
timestamp, # Event time
msg[asks_key][i][0], # Price level to be updated
msg[asks_key][i][1], # Quantity
False # Is bid
)]
return data
class StreamsManager:
def __init__(self, streams):
self.streams = {stream.name: stream for stream in streams}
self.bm = BinanceSocketManager(client)
self.conn_key = self.bm.start_multiplex_socket(self.get_stream_names(), self.process)
def process(self, msg):
data = self.streams[msg['stream']].process(msg['data'])
self.streams[msg['stream']].write_to_bq(data)
def get_stream_names(self):
return list(self.streams.keys())
def start(self):
self.bm.start()
if __name__ == '__main__':
symbol = 'ltcbtc'
manager = StreamsManager([
AggregateTradeStream(symbol, create_table=True),
TradeStream(symbol, create_table=True),
IndividualSymbolTickerStream(symbol, create_table=True),
IndividualSymbolMiniTickerStream(symbol, create_table=True),
KlineCandlestickStream(symbol, '1m', create_table=True)
])
manager.start()