ugik

    COINMETRO = "https://api.coinmetro.com"
    coin = 'ETH'
    
    price, orderAmount = getAmountETH(amount, 0)
    pSize = str(orderAmount)    # coin position size

    headers={"Authorization":CMclient.bearerToken, 'Content-Type': 'application/x-www-form-urlencoded'}

    payload = {'orderType':'market', 'buyingCurrency':coin, 'sellingCurrency':'USD',
               'sellingQty':pSize}

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def get_tick_and_step_size( symbol):
        tick_size = None
        step_size = None
        symbol_info = client.get_symbol_info(symbol)
        for filt in symbol_info['filters']:
            if filt['filterType'] == 'PRICE_FILTER':
                tick_size = float(filt['tickSize'])
            elif filt['filterType'] == 'LOT_SIZE':
                step_size = float(filt['stepSize'])
        return tick_size, step_size

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def float_precision(f, n):
        n = int(math.log10(1 / float(n)))
        f = math.floor(float(f) * 10 ** n) / 10 ** n
        f = "{:0.0{}f}".format(float(f), n)
        return str(int(f)) if int(n) == 0 else f

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def order_market_buy(symbol, quantity):
    tick_size, step_size = get_tick_and_step_size(symbol)
    order = client.order_market_buy(symbol=symbol, quantity=float_precision(quantity, step_size))
print(symbol, 'order placed...', end="", flush=True)
    return wait_confirmation(symbol, order)

ugik

# deal with possible delay in getting order confirmation
# per: https://dev.binance.vision/t/faq-error-message-order-does-not-exist/46
def wait_confirmation(symbol, order, status=ORDER_STATUS_FILLED, try_times=20):
    for t in range(1,try_times):        # try a few times
        try:
            currentOrder = client.get_order(symbol=symbol,orderId=order["orderId"])
            if currentOrder['status'] == status:
                return currentOrder
        except Exception as e:
            pass

ugik

verbose = True

if True:
    if True:
        p = 20
        arm = 6
        
        df = pd.DataFrame(candlesticks, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
        df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
        df['open'] = df['open'].astype(float)

ugik

verbose = True

if True:
    if True:
        p = 20
        arm = 6
        
        df = pd.DataFrame(candlesticks, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
        df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
        df['open'] = df['open'].astype(float)

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def tr(data):
    data['previous_close'] = data['close'].shift(1)
    data['high-low'] = abs(data['high'] - data['low'])
    data['high-pc'] = abs(data['high'] - data['previous_close'])
    data['low-pc'] = abs(data['low'] - data['previous_close'])

    tr = data[['high-low', 'high-pc', 'low-pc']].max(axis=1)

    return tr

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trades = []
long_trades = []
for key in results:
    for trade in results[key]:
        if trade[0] > 4:
            if long_trades:
                long_trades.append(float(trade[2]))
            else:
                long_trades = [float(trade[2])]
                

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results = {}
sequences = []
sequence = 0
prev_time = None
for key in norm:
    for t in norm[key]:
        if not prev_time:
            prev_time = t[0]
            continue
​