L6

L6.py

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+import matplotlib.pyplot as plt
+import numpy as np
+import statistics
+import requests
+import time
+import json
+
+base_currency = 'PLN'
+url = 'https://api.bitbay.net/rest/trading/transactions/'
+url1 = 'https://bitbay.net/API/Public/'
+post2 = '/orderbook.json'
+time_interval = 3
+
+w_volume = 2
+w_mean = 2
+w_rsi = 2
+
+
+def get_data(url, currency_list, pos):
+    try:
+        req = requests.get(url + currency_list + base_currency + pos)
+        req.raise_for_status()
+        return req.json()
+
+    except requests.exceptions.HTTPError as err:
+        raise SystemExit(err)
+
+
+def get_data1(url, curr, base, end=None):
+    try:
+        req = requests.get(url + curr + '-' + base + end)
+        req.raise_for_status()
+        return req.json()
+
+    except requests.exceptions.HTTPError as err:
+        raise SystemExit(err)
+
+
+def calculate_rsi(data, w):
+    data = data[-w:]
+    rise = 0
+    r_count = 0
+    loss = 0
+    l_count = 0
+    for i in range(1, len(data)):
+        if data[i - 1] < data[i]:
+            rise += data[i] - data[i - 1]
+            r_count += 1
+        elif data[i - 1] > data[i]:
+            loss += data[i - 1] - data[i]
+            l_count += 1
+    if r_count == 0:
+        a = 1
+    else:
+        a = rise / r_count
+    if l_count == 0:
+        b = 1
+    else:
+        b = loss / l_count
+    rsi_value = 100 - (100 / (1 + (a / b)))
+
+    return rsi_value
+
+
+def calculate_volume(data, w):
+    sum_amount = 0
+    for i in range(1, w + 1):
+        sum_amount += data[-i]
+    return sum_amount
+
+
+def calculate_mean(data, w):
+    sum_price = 0
+    for j in range(1, w + 1):
+        sum_price += data[-j]
+    return sum_price / w
+
+
+def user_info():
+    curr = input('Waluta: ')
+    ask = input('Kurs: ')
+    vol = input('Ilość: ')
+
+    return curr, int(ask), int(vol)
+
+
+def get_all_info():
+    czy = ''
+    while czy != 'n':
+        czy = input('Czy chcesz dodać tranzakcję?[t/n]: ')
+        if czy == 't':
+            czy2 = input('Kupno czy sprzedaż?[k/s]: ')
+            if czy2 == 'k':
+                curre, asks, volu = user_info()
+                buy_rate[curre].append(asks)
+                buy_volume[curre].append(volu)
+
+            elif czy2 == 's':
+                curre, asks, volu = user_info()
+
+                available_volume = 0
+                for voulm in buy_volume[curre]:
+                    available_volume += voulm
+
+                if volu > available_volume:
+                    print('Nie masz wystarczająco dużo waluty!')
+
+                else:
+                    balance = 0
+                    temp_volume = volu
+                    while temp_volume > 0:
+
+                        if buy_volume[curre][0] < temp_volume:
+                            temp_volume -= buy_volume[curre][0]
+
+                            balance += buy_volume[curre][0] * buy_rate[curre][0]
+
+                            del buy_volume[curre][0]
+                            del buy_rate[curre][0]
+
+                        else:
+                            buy_volume[curre][0] -= temp_volume
+
+                            balance += temp_volume * buy_rate[curre][0]
+
+                            if buy_volume[curre][0] == 0:
+                                del buy_volume[curre][0]
+                                del buy_rate[curre][0]
+
+                            sell_rate[curre].append(asks)
+                            sell_volume[curre].append(volu)
+                            break
+
+                    final_balance = sell_rate[curre][-1] * sell_volume[curre][-1] - balance
+                    balances[curre] = final_balance
+
+
+def read_json(file):
+    f = open(file)
+    data = json.load(f)
+    price_ = data['price']
+    volume_ = data['volume']
+    amount_ = data['amount']
+    mean_ = data['mean']
+    rsi_ = data['rsi']
+    buy_rate_ = data['buy_rate']
+    buy_volume_ = data['buy_volume']
+    sell_rate_ = data['sell_rate']
+    sell_volume_ = data['sell_volume']
+    balances_ = data['balances']
+    times_ = data['times']
+    t_ = data['t']
+    labels_ = data['labels']
+    difference_ = data['difference']
+
+    return price_, volume_, amount_, mean_, rsi_, buy_rate_, buy_volume_, sell_rate_, sell_volume_, balances_, times_, t_, labels_, difference_
+
+
+def save_data():
+    data = {'price': price,
+            'volume': volume,
+            'amount': amount,
+            'mean': mean,
+            'rsi': rsi,
+            'buy_rate': buy_rate,
+            'buy_volume': buy_volume,
+            'sell_rate': sell_rate,
+            'sell_volume': sell_volume,
+            'balances': balances,
+            'times': times,
+            't': t,
+            'labels': labels,
+            'difference': difference}
+
+    with open('data.json', 'w') as f:
+        json.dump(data, f, indent=4)
+
+
+def create_plot(currency_list):
+    figure, axis = plt.subplots(n, 1, figsize=(7, 9))
+    figure.text(0.5, 0.04, 'time', ha='center', va='center')
+    figure.tight_layout(pad=4.0, rect=[0, 0, .8, 1])
+
+    line = []
+    for i in range(len(currency_list)):
+        line.append(axis[i].plot(times, price[currency_list[i]], label="price")[0])
+        line.append(axis[i].plot(times, volume[currency_list[i]], label="volume")[0])
+        line.append(axis[i].plot(times, mean[currency_list[i]], label="mean")[0])
+        line.append(axis[i].plot(times, rsi[currency_list[i]], label="rsi")[0])
+        line.append(axis[i].plot(times, buy_rate[currency_list[i]], '--', label="buy mean")[0])
+
+        # axis[i].legend(bbox_to_anchor=(1.33, -0.04), loc='lower right')
+        axis[i].legend()
+        axis[i].set_title(f'{currency_list[i] + base_currency}')
+
+    return figure, axis, line
+
+
+if __name__ == '__main__':
+    currencies = ['DASH', 'OMG', 'BTC']
+    n = len(currencies)
+    Y = 3
+    X = 0.5
+    S = 0.1
+
+    price = {}
+    volume = {}
+    amount = {}
+    mean = {}
+    rsi = {}
+    buy_rate = {}
+    buy_volume = {}
+    sell_rate = {}
+    sell_volume = {}
+    balances = {}
+    difference = {}
+
+    for currency in currencies:
+        price[currency] = []
+        volume[currency] = []
+        amount[currency] = []
+        mean[currency] = []
+        rsi[currency] = []
+        buy_rate[currency] = []
+        buy_volume[currency] = []
+        sell_rate[currency] = []
+        sell_volume[currency] = []
+        balances[currency] = 0
+        difference[currency] = []
+
+    times = []
+    t = 0
+    labels = []
+
+    plt.ion()
+    fig, ax, lines = create_plot(currencies)
+
+    info = input('Czy chcesz wczytać dane z pliku? [t/n]: ')
+    if info == 't':
+        price, volume, amount, mean, rsi, buy_rate, buy_volume, sell_rate, sell_volume, balances, times, t, labels, difference = read_json('data.json')
+        # times = times1
+        # t = t1
+        # labels = labels1
+
+    while True:
+        for i in range(50):
+            if t % 5 == 0:
+                get_all_info()
+
+                data_write = input('Czy chcesz zapisać dane do pliku?')
+                if data_write == 't':
+                    save_data()
+
+            times.append(t)
+            t += 1
+            labels.append(time.strftime("%H:%M:%S", time.localtime()))
+
+            for currency in currencies:
+                r3 = get_data1(url, currency, base_currency, '?limit=100')['items'][i]
+                price[currency].append(float(r3['r']))
+                amount[currency].append(float(r3['a']))
+
+                r2 = get_data(url1, currency, post2)
+
+                result = (r2['asks'][0][0] - r2['bids'][0][0]) / r2['bids'][0][0]
+                difference[currency].append(round(result, 2))
+
+                if len(price[currency]) >= w_volume:
+                    volume[currency].append(calculate_volume(amount[currency], w_volume))
+
+                if len(price[currency]) >= w_mean:
+                    mean[currency].append(calculate_mean(price[currency], w_mean))
+
+                if len(price[currency]) >= w_rsi:
+                    rsi[currency].append(calculate_rsi(price[currency], w_rsi))
+
+            p = 0
+            for j in range(n):
+                lines[0 + p].set_data(times, price[currencies[j]])
+                lines[1 + p].set_data(times[w_volume - 1:], volume[currencies[j]])
+                lines[2 + p].set_data(times[w_mean - 1:], mean[currencies[j]])
+                lines[3 + p].set_data(times[w_rsi - 1:], rsi[currencies[j]])
+                lines[4 + p].set_data(times, [statistics.mean(buy_rate[currencies[j]]) if len(buy_rate[currencies[j]]) > 0 else 0 for i in range(len(times))])
+                p += 5
+
+                minim = min(price[currencies[j]] +
+                            volume[currencies[j]] +
+                            mean[currencies[j]] +
+                            rsi[currencies[j]]) * 0.01
+                maxim = max(price[currencies[j]] +
+                            volume[currencies[j]] +
+                            mean[currencies[j]] +
+                            rsi[currencies[j]]) * 1.3
+
+                ax[j].set_ylim(minim, maxim)
+                ax[j].set_xlim(0, max(times) + 5)
+                ax[j].set_xticks(times)
+                ax[j].set_xticklabels(labels, fontdict={'fontsize': 8}, rotation=45)
+                if j == 0:
+                    ax[j].yaxis.set_ticks(np.arange(0, maxim, 150))
+                if j == 1:
+                    ax[j].yaxis.set_ticks(np.arange(0, maxim, 25))
+                if j == 2:
+                    ax[j].yaxis.set_ticks(np.arange(0, maxim, 25000))
+
+                ax[j].text(1.03, .85, '                                       ', fontsize=10, transform=ax[j].transAxes,
+                           bbox=dict(facecolor='white', edgecolor="none", alpha=1))
+
+                if balances[currencies[j]] < 0:
+                    ax[j].text(1.03, .85, f'strata: {abs(balances[currencies[j]])}', fontsize=10, transform=ax[j].transAxes)
+                elif balances[currencies[j]] > 0:
+                    ax[j].text(1.03, .85, f'zysk: {abs(balances[currencies[j]])}', fontsize=10, transform=ax[j].transAxes)
+
+                ax[j].text(1.03, .65, '                                       ', fontsize=10, transform=ax[j].transAxes,
+                           bbox=dict(facecolor='white', edgecolor="none", alpha=1))
+
+                ax[j].text(1.03, .45, '                                       ', fontsize=10, transform=ax[j].transAxes,
+                           bbox=dict(facecolor='white', edgecolor="none", alpha=1))
+
+                ax[j].text(1.03, .25, '                                       ', fontsize=10, transform=ax[j].transAxes,
+                           bbox=dict(facecolor='white', edgecolor="none", alpha=1))
+
+                ax[j].text(1.03, .05, '                                       ', fontsize=10, transform=ax[j].transAxes,
+                           bbox=dict(facecolor='white', edgecolor="none", alpha=1))
+
+                ax[j].text(1.03, .65, 'typ trendu: ', fontsize=10, transform=ax[j].transAxes)
+
+                ax[j].text(1.03, .45, 'kandydat:', fontsize=10, transform=ax[j].transAxes)
+
+                if len(rsi[currencies[j]]) >= 2:
+                    ax[j].text(1.3, .45, 'nie', c='red', fontsize=10, transform=ax[j].transAxes)
+
+                    if rsi[currencies[j]][-1] > 70 or rsi[currencies[j]][-2] > 50 and rsi[currencies[j]][-1] > 50:
+                        ax[j].text(1.3, .65, 'spadek', fontsize=10, c='red', transform=ax[j].transAxes)
+
+                    elif rsi[currencies[j]][-1] < 30 or rsi[currencies[j]][-2] < 50 and rsi[currencies[j]][-1] > 50:
+                        ax[j].text(1.3, .65, 'wzrost', fontsize=10, c='green', transform=ax[j].transAxes)
+
+                    else:
+                        ax[j].text(1.3, .65, 'boczny', fontsize=10, c='blue', transform=ax[j].transAxes)
+
+            temp_volume = []
+            for j in range(n):
+                if len(volume[currencies[j]]) >= 2 and not (
+                        rsi[currencies[j]][-1] > 70 or rsi[currencies[j]][-2] > 50 and rsi[currencies[j]][-1] > 50):
+                    temp_volume.append((volume[currencies[j]][-1], j))
+
+            if len(volume[currencies[0]]) >= 2 and len(temp_volume) >= 1:
+                temp_volume.sort(key=lambda tup: tup[0])
+                max_volume = temp_volume[-1]
+                j = max_volume[1]
+
+                ax[j].text(1.3, .45, '    ', fontsize=10, transform=ax[j].transAxes,
+                           bbox=dict(facecolor='white', edgecolor="none", alpha=1))
+
+                ax[j].text(1.3, .45, 'tak', fontsize=10, c='green', transform=ax[j].transAxes)
+
+                ax[j].text(1.03, .25, 'volatile asset:', fontsize=10, transform=ax[j].transAxes)
+
+                ax[j].text(1.03, .05, 'liquid asset:', fontsize=10, transform=ax[j].transAxes)
+
+                if len(price[currencies[j]]) >= Y:
+                    minimum = min(price[currencies[j]][-Y:])
+                    maximum = max(price[currencies[j]][-Y:])
+                    volatile = (maximum - minimum) / maximum
+
+                    if volatile >= X:
+                        ax[j].text(1.3, .05, 'tak', c='green', fontsize=10, transform=ax[j].transAxes)
+                    else:
+                        ax[j].text(1.3, .05, 'nie', c='red', fontsize=10, transform=ax[j].transAxes)
+
+                    if difference[currencies[j]][-1] <= S:
+                        ax[j].text(1.3, .25, 'tak', c='green', fontsize=10, transform=ax[j].transAxes)
+                    else:
+                        ax[j].text(1.3, .25, 'nie', c='red', fontsize=10, transform=ax[j].transAxes)
+
+            fig.canvas.draw()
+            fig.canvas.flush_events()
+
+            time.sleep(time_interval)

data.json

@@ -0,0 +1 @@
+{"price": {"DASH": [698.16, 698.15, 699.14, 682.0, 682.5], "OMG": [21.55, 21.54, 21.7, 21.7, 21.71], "BTC": [133000.34, 133000.92, 133003.0, 133200.0, 133487.83]}, "volume": {"DASH": [34.49404889, 27.0117859, 0.05577416, 0.12457434], "OMG": [8.4423963, 27.48064516, 174.48064516, 157.29578046], "BTC": [0.04916542, 0.0011090100000000001, 0.03828655, 1.33945854]}, "amount": {"DASH": [7.49404889, 27.0, 0.0117859, 0.04398826, 0.08058608], "OMG": [4.4423963, 4.0, 23.48064516, 151.0, 6.29578046], "BTC": [0.04880542, 0.00036, 0.00074901, 0.03753754, 1.301921]}, "mean": {"DASH": [698.155, 698.645, 690.5699999999999, 682.25], "OMG": [21.545, 21.619999999999997, 21.7, 21.705], "BTC": [133000.63, 133001.96000000002, 133101.5, 133343.91499999998]}, "rsi": {"DASH": [99.00990099009991, 49.7487437185932, 5.5126791620727715, 33.33333333333333], "OMG": [99.00990099009886, 13.793103448275872, 50.0, 0.9900990099011437], "BTC": [36.708860760146536, 67.53246753233253, 99.4949494949495, 99.65377557732921]}, "buy_rate": {"DASH": [], "OMG": [], "BTC": []}, "buy_volume": {"DASH": [], "OMG": [], "BTC": []}, "sell_rate": {"DASH": [], "OMG": [], "BTC": []}, "sell_volume": {"DASH": [], "OMG": [], "BTC": []}, "balances": {"DASH": 0, "OMG": 0, "BTC": 0}, "times": [0, 1, 2, 3, 4], "t": 5, "labels": ["20:59:53", "21:00:00", "21:00:05", "21:00:12", "21:00:17"], "difference": {"DASH": [0.01, 0.01, 0.01, 0.01, 0.01], "OMG": [0.01, 0.01, 0.01, 0.01, 0.01], "BTC": [0.01, 0.01, 0.0, 0.0, 0.0]}}