minor changes
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@ -15,6 +15,7 @@ from freqtrade.vendor.qtpylib.indicators import awesome_oscillator, crossed_abov
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logger = logging.getLogger(__name__)
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class SignalType(Enum):
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""" Enum to distinguish between buy and sell signals """
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BUY = "buy"
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@ -16,12 +16,15 @@ from freqtrade.exchange import Bittrex
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from freqtrade.optimize.backtesting import backtest
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from freqtrade.vendor.qtpylib.indicators import crossed_above
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# Remove noisy log messages
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logging.getLogger('hyperopt.mongoexp').setLevel(logging.WARNING)
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logger = logging.getLogger(__name__)
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# set TARGET_TRADES to suit your number concurrent trades so its realistic to 20days of data
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TARGET_TRADES = 1100
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TOTAL_TRIES = 4
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TOTAL_TRIES = None
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_CURRENT_TRIES = 0
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# Configuration and data used by hyperopt
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@ -188,8 +191,8 @@ def start(args):
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)
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if args.mongodb:
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logger.info('Using mongodb.')
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logger.info('Start scripts/start-mongodb.sh and start-hyperopt-worker.sh manually')
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logger.info('Using mongodb ...')
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logger.info('Start scripts/start-mongodb.sh and start-hyperopt-worker.sh manually!')
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db_name = 'freqtrade_hyperopt'
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trials = MongoTrials('mongo://127.0.0.1:1234/{}/jobs'.format(db_name), exp_key='exp1')
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@ -197,9 +200,6 @@ def start(args):
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trials = Trials()
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best = fmin(fn=optimizer, space=SPACE, algo=tpe.suggest, max_evals=TOTAL_TRIES, trials=trials)
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logger.info(
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'\n==================== HYPEROPT BACKTESTING REPORT ==============================\n'
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)
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logger.info('Best parameters:\n%s', json.dumps(best, indent=4))
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results = sorted(trials.results, key=itemgetter('loss'))
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logger.info('Best Result:\n%s', results[0]['result'])
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