https://github.com/imvickykumar999/fyers-trading-bot
Deployed : https://tradingbotstock.pythonanywhere.com/
https://github.com/imvickykumar999/fyers-trading-bot
Last synced: 7 months ago
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Deployed : https://tradingbotstock.pythonanywhere.com/
- Host: GitHub
- URL: https://github.com/imvickykumar999/fyers-trading-bot
- Owner: imvickykumar999
- Created: 2024-06-27T09:38:00.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-06-29T13:08:04.000Z (over 1 year ago)
- Last Synced: 2025-01-29T15:26:19.467Z (8 months ago)
- Language: Jupyter Notebook
- Homepage: https://imvickykumar999.github.io/Fyers-Trading-Bot/
- Size: 133 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
># `Fyers-Trading-Bot`
>
>[](https://imvickykumar999.github.io/Fyers-Trading-Bot/)
>
>[](https://in.tradingview.com/chart/?symbol=FRASER)
To avoid hitting the rate limits while updating the plot
as frequently as possible, we need to find a balance.
Given the rate limits:
---
- **Per Second**: 10 requests
- **Per Minute**: 200 requests
- **Per Day**: 10,000 requests
### Calculation:
1. **Per Second**: The maximum is 10 requests per second. If we set `interval=1000` (1 second), we would be making 1 request per second, which is safe.
2. **Per Minute**: The maximum is 200 requests per minute. If we set `interval=1000` (1 second), this would result in 60 requests per minute, which is well within the limit.
3. **Per Day**: The maximum is 10,000 requests per day. If we set `interval=1000` (1 second), this would result in 60 * 60 * 24 = 86,400 requests per day, which exceeds the limit.
To avoid exceeding the daily limit, we need to adjust the interval to a value that keeps us within the daily limit.
### Updated Code:
Here’s the updated code with the interval set to 9000 milliseconds (9 seconds):
```python
# Install necessary libraries if not already installed
# !pip install matplotlib pandas fyers-apiv2
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import pandas as pd
import os
import time
from datetime import datetime, timedelta
from fyers_api import fyersModel
from matplotlib.animation import FuncAnimation
from pprint import pprint as p
# Replace with your actual client ID and access token
client_id = "2A6LCH4LF8-100"
access_token = "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.********.znxz_lLkv6QOCe2M2VpEnVTPdnYIgRheTculur_Kpac"
log_path = os.path.join(os.getcwd(), "fyers_logs")
# Create the directory if it doesn't exist
os.makedirs(log_path, exist_ok=True)
# Initialize the FyersModel instance with your client_id, access_token, and enable async mode
fyers = fyersModel.FyersModel(client_id=client_id, is_async=False, token=access_token, log_path=log_path)
# Define the date range for the last one year
end_date = datetime.now()
start_date = end_date - timedelta(days=364)
# Convert the date range to Unix timestamps
range_from = int(start_date.timestamp())
range_to = int(end_date.timestamp())
# Define the data for the API request
data = {
"symbol": "BSE:FRASER-X",
"resolution": "D",
"date_format": "0",
"range_from": str(range_from),
"range_to": str(range_to),
"cont_flag": "1"
}
# Initialize the plot
fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 8), sharex=True, gridspec_kw={'height_ratios': [3, 1]})
counter = 0
# Function to fetch data and update the plot
def update(frame):
global range_to, counter
range_to = int(datetime.now().timestamp())
data["range_to"] = str(range_to)
response = fyers.history(data=data)
counter += 1
p(response)
print(counter)
if response['s'] == 'ok':
candles = response['candles']
columns = ['timestamp', 'open', 'high', 'low', 'close', 'volume']
df = pd.DataFrame(candles, columns=columns)
df['timestamp'] = pd.to_datetime(df['timestamp'], unit='s')
ax1.clear()
ax2.clear()
for index, row in df.iterrows():
color = 'green' if row['close'] >= row['open'] else 'red'
ax1.plot([row['timestamp'], row['timestamp']], [row['low'], row['high']], color='black')
ax1.plot([row['timestamp'], row['timestamp']], [row['open'], row['close']], color=color, linewidth=5)
ax2.bar(df['timestamp'], df['volume'], color='blue', alpha=0.6)
ax1.set_title(f'Candlestick Chart for [ {data["symbol"]} ]\n')
ax1.set_ylabel('Price')
ax2.set_ylabel('Volume')
ax1.grid(True)
ax2.grid(True)
plt.xticks(rotation=30)
else:
print("Failed to fetch data:", response)
# Create an animation
ani = FuncAnimation(fig, update, interval=9000, cache_frame_data=False) # Update every 9 seconds
plt.show()
```
### Explanation:
1. **Interval**: Set to `9000` milliseconds (9 seconds) to stay within the daily request limit.
2. **API Call Frequency**: This will make approximately 9,600 requests per day, which is under the 10,000 request limit and respects the per second and per minute limits.