Final

Author: AurumnPegasus

src/trial.py

@@ -0,0 +1,45 @@
+import pandas as pd
+import random
+from datetime import date, timedelta
+from mplfinance.plotting import plot
+from mplfinance._styles import make_marketcolors
+
+dict_data = []
+start_date = date(2019, 1, 1)
+end_date = date(2020, 1, 1)
+delta = timedelta(days=1)
+start = 20
+end = 30
+while start_date <= end_date:
+    openval = random.randint(start, end)
+    closeval = random.randint(start, end)
+    high = random.randint(max(openval, closeval), end)
+    low = random.randint(start, min(openval, closeval))
+    change = random.randint(-5, 5)
+    volume = random.randint(10000, 20000)
+    dict_data.append({
+        "Open": openval,
+        "Close": closeval,
+        "High": high,
+        "Low": low,
+        "Date": start_date,
+        "Volume": volume
+    })
+    start += change
+    end += change
+    start_date += delta
+
+df = pd.DataFrame(dict_data)
+df.index = pd.to_datetime(df['Date'])
+
+# custom_colors = []
+# for i in range(len(df)):
+#     if i % 3 == 0:
+#         custom_colors.append(make_marketcolors(up='#29c9ff', down='#f3b5ff', edge='#29c9ff', wick='#29c9ff', ohlc='#32a852', volume='#a89132'))
+#     elif i%5 == 0:
+#         custom_colors.append("#000000")
+#     else:
+#         custom_colors.append(None)
+
+# plot(df, type='candle', style='yahoo', colors=custom_colors, volume=True)
+plot(df, type='candle', style='yahoo', volume=True)