Nov-09-2024, 06:28 PM
As the picture I am posting indicates, I am trying to have my semi-live tkinter DOGE graph have simple annotations such in the small example to indicate where certain chart patterns form, but I haven't gotten it to work on the tkinter windows, only the Figure 1 standard still window from matplotlib has been able to have these annotations put on it. I have dumbed it down to where it only has to put a single indicator on one or multiple obvious points but it seems that tkinter can not accept the same types of annotations as the matplotlib window. Is there a workaround, or am I getting something wrong? Thanks.
import matplotlib.pyplot as plt
import mplfinance as mpf
import pandas as pd
import time
import robin_stocks.robinhood as r
import requests
from datetime import datetime
import pytz
import tkinter as tk
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
import os
# Initialize global variables
program_start_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
doge_data = pd.DataFrame() # Initialize empty DataFrame for doge_data
current_price = None # Initialize current price
def read_credentials():
credentials_path = os.path.join(os.path.dirname(__file__), "credentials.txt")
with open(credentials_path, "r") as file:
username, password = file.read().strip().split("\n")
return username, password
def login_to_robinhood():
username, password = read_credentials()
try:
r.login(username, password)
print("Logged in successfully")
return True
except Exception as e:
print("Login failed:", e)
return False
def fetch_current_price():
try:
price_data = r.crypto.get_crypto_quote('DOGE')
price = float(price_data['mark_price']) if price_data['mark_price'] else None
#print("Current DOGE price:", price)
return price
except Exception as e:
print(f"Error fetching current price: {e}")
return None
def fetch_historical_data():
end_time = int(time.time())
start_time = end_time - 86400 # 24 hours ago
url = 'https://min-api.cryptocompare.com/data/v2/histominute'
params = {
'fsym': 'DOGE',
'tsym': 'USD',
'limit': 60,
'toTs': end_time
}
response = requests.get(url, params=params)
if response.status_code == 200:
data = response.json()['Data']['Data']
df = pd.DataFrame(data)
df['time'] = pd.to_datetime(df['time'], unit='s')
df.set_index('time', inplace=True)
if 'volumefrom' in df.columns:
df.rename(columns={'volumefrom': 'volume'}, inplace=True)
df = df[['open', 'high', 'low', 'close', 'volume']]
tz = pytz.timezone('America/Chicago')
df.index = df.index.tz_localize('UTC').tz_convert(tz)
return df
else:
print("Error fetching historical data:", response.status_code)
return pd.DataFrame()
def plot_doge_data():
global doge_data, current_price # Declare as global to access and modify the variables
# Initialize doge_data and current_price
doge_data = fetch_historical_data()
current_price = fetch_current_price()
if not doge_data.empty and current_price is not None:
# Create a Tkinter window
root = tk.Tk()
root.title("DOGE Candlestick Chart")
# Create a figure for the plot and embed it in the Tkinter window
fig, ax = plt.subplots(figsize=(10, 6)) # Set figure size
canvas = FigureCanvasTkAgg(fig, master=root)
canvas.get_tk_widget().pack(fill=tk.BOTH, expand=True)
# Keep the window in the background
root.wm_attributes("-topmost", False)
# Main update loop for plotting
def update_plot():
global doge_data, current_price # Use global to modify the variables defined in the outer function
ax.clear() # Clear previous plot to refresh
# Plot using mplfinance
mpf.plot(
doge_data,
type='candle',
style='charles',
ax=ax,
ylabel='Price (USD)',
volume=False,
show_nontrading=False
)
# Update title and subtitle with current data
current_time_str = pd.Timestamp.now(tz='America/Chicago').strftime("%Y-%m-%d %H:%M:%S CST")
ax.set_title(f'DOGE Candlestick Chart - Current Price: ${current_price:,.4f}', fontsize=10, pad=20)
fig.suptitle(f'Program Start: {program_start_time}\nCurrent Time: {current_time_str}', fontsize=8, y=0.92)
canvas.draw() # Update the plot
# Refresh data
current_price = fetch_current_price() # Update price
doge_data = fetch_historical_data() # Refresh data with latest trades
root.after(6000, update_plot) # Schedule next update after 200 ms
update_plot() # Start the update loop
root.mainloop() # Start the Tkinter event loop
if __name__ == "__main__":
if login_to_robinhood():
plot_doge_data()