L6

l2.py

@@ -0,0 +1,37 @@
+import requests
+import time
+
+
+base_currency = 'USD'
+currencies = ['BTC', 'LTC', 'DASH']
+url = 'https://bitbay.net/API/Public/'
+post = '/orderbook.json'
+time_interval = 5
+
+
+def get_data(currency, post):
+    try:
+        r = requests.get(url+currency+base_currency+post)
+        r.raise_for_status()
+        return r.json()
+
+    except requests.exceptions.HTTPError as err:
+        raise SystemExit(err)
+
+
+if __name__ == '__main__':
+
+    for currency in currencies:
+        r = get_data(currency, post)
+        print(f'{currency+base_currency} -----------------------------------')
+        print(r)
+
+    print('\nPercentage difference between bids and asks:')
+    while True:
+        for currency in currencies:
+            r = get_data(currency, post)
+            result = 1 - (r['asks'][0][0] - r['bids'][0][0]) / r['bids'][0][0]
+            print(f'{currency+base_currency}: ', round(result, 4))
+
+        print('\n')
+        time.sleep(time_interval)

l3.py

@@ -0,0 +1,67 @@
+import matplotlib.pyplot as plt
+from l2 import *
+
+def create_asks_bids():
+    asks = {}
+    bids = {}
+    for currency in currencies:
+        asks[currency] = []
+        bids[currency] = []
+    return asks,bids
+
+def create_base_plots():
+    for i in range(n):
+        lines.append(ax[i].plot(times, asks[currencies[i]], label="asks")[0])
+        lines.append(ax[i].plot(times, bids[currencies[i]], label="bids")[0])
+
+        ax[i].legend()
+        ax[i].set_title(f'{currencies[i] + base_currency}')
+        ax[i].set_xlim(0, 100)
+
+def add_data_to_asks_bids():
+    for currency in currencies:
+        r = get_data(currency, post)
+        asks[currency].append(r['ask'])
+        bids[currency].append(r['bid'])
+
+def add_data_to_lines():
+    j=0
+    for i in range(len(lines)):
+        if i % 2 == 0:
+            lines[i].set_data(times, asks[currencies[j]])
+        else:
+            lines[i].set_data(times, bids[currencies[j]])
+            j += 1
+
+def set_y():
+    for i in range(n):
+        ax[i].set_ylim(max(bids[currencies[i]]) * 0.9, max(asks[currencies[i]]) * 1.1)
+
+
+if __name__ == '__main__':
+    post = '/ticker.json'
+    n = len(currencies)
+
+    asks, bids = create_asks_bids()
+
+    times = []
+    t = 0
+
+    plt.ion()
+    figure, ax = plt.subplots(n, 1, figsize=(8, 7))
+
+    lines = []
+    create_base_plots()
+    while True:
+        add_data_to_asks_bids()
+
+        t += 1
+        times.append(t)
+
+        add_data_to_lines()
+        set_y()
+
+        figure.canvas.draw()
+        figure.canvas.flush_events()
+
+        time.sleep(time_interval)

l4.py

@@ -0,0 +1,148 @@
+import matplotlib.pyplot as plt
+import requests
+import time
+
+
+def get_data(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 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 create_plot(currency_list):
+    figure, axis = plt.subplots(n, 1, figsize=(6, 7))
+    figure.text(0.5, 0.04, 'time', ha='center', va='center')
+    figure.tight_layout(pad=3.0)
+
+    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])
+
+        axis[i].legend()
+
+        axis[i].set_title(f'{currency_list[i] + base_currency}')
+        axis[i].xaxis.set_major_formatter('{x} s')
+
+    return figure, axis, line
+
+
+base_currency = 'PLN'
+url = 'https://bitbay.net/API/Public/'
+post = '/trades.json'
+time_interval = 3
+
+w_volume = int(input('Okno przesuwne dla wolumenu: '))
+w_mean = int(input('Okno przesuwne dla średniej: '))
+w_rsi = int(input('Okno przesuwne dla RSI: '))
+
+if __name__ == '__main__':
+    currencies = ['DASH', 'OMG', 'BTC']
+    n = len(currencies)
+
+    price = {}
+    volume = {}
+    amount = {}
+    mean = {}
+    rsi = {}
+    for currency in currencies:
+        price[currency] = []
+        volume[currency] = []
+        amount[currency] = []
+        mean[currency] = []
+        rsi[currency] = []
+
+    times = []
+    t = 0
+
+    plt.ion()
+    fig, ax, lines = create_plot(currencies)
+
+    while True:
+        for i in range(50):
+            t += 1
+            times.append(t)
+            for currency in currencies:
+                r = get_data(currency, post)
+                price[currency].append(r[i]['price'])
+                amount[currency].append(r[i]['amount'])
+
+                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]])
+                p += 4
+
+                ax[j].set_ylim(min(price[currencies[j]] +
+                                   volume[currencies[j]] +
+                                   mean[currencies[j]] +
+                                   rsi[currencies[j]]) * 0.01,
+                               max(price[currencies[j]] +
+                                   volume[currencies[j]] +
+                                   mean[currencies[j]] +
+                                   rsi[currencies[j]]) * 2.1)
+                ax[j].set_xlim(0, max(times) + 15)
+                ax[j].set_yscale('symlog')
+
+            fig.canvas.draw()
+            fig.canvas.flush_events()
+
+            time.sleep(time_interval)