porebryk

Tired of using generic crypto portfolio apps that charge you $15/month for a "premium" layout? If you want absolute control over your data, it's time to build your own centralized management system.
Today, we are combining the layout power of Notion with the data power of the Binance API. We are going to write a Python script that automatically fetches your real-time balances and prepares them to be synced directly into a custom Notion database.
No more manual data entry. Total automation.
Step 1: The Setup
You will need two things:
1. Your Binance API keys (Read-only permissions!).
2. A Notion account with a blank Database created.
Note: For the full integration, you would also create a Notion Integration API key, but today we are building the Binance data extraction engine.
Step 2: Extracting Clean Portfolio Data
When you pull your balance from Binance, it gives you a massive list of every coin on the exchange, including tiny dust amounts. We need to write a script that filters this data so we only send our actual holdings to Notion.
Make sure you have the ccxt library installed (pip install ccxt).
import ccxt
# 1. Connect to your Binance account
# SECURITY REMINDER: Never share these keys.
binance = ccxt.binance({
'apiKey': 'YOUR_API_KEY_HERE',
'secret': 'YOUR_API_SECRET_HERE',
'enableRateLimit': True,
})
try:
# 2. Fetch the raw balance data
raw_balance = binance.fetch_balance()

# 3. Create a clean dictionary for our Notion database
clean_portfolio = {}

# 4. Filter out empty balances and "dust"
for coin, amount in raw_balance['total'].items():
if amount > 0.001: # Adjust this threshold to hide dust
# Here we fetch the current USDT price for the coin
try:
ticker = binance.fetch_ticker(f"{coin}/USDT")
current_price = ticker['last']
usd_value = amount * current_price

# Only save coins worth more than $1 to our dashboard
if usd_value > 1.0:
clean_portfolio[coin] = {
'amount': round(amount, 4),
'usd_value': round(usd_value, 2)
}
except:
pass # Skip coins that don't have a direct USDT pair

print("✅ Data extracted and cleaned. Ready for Notion Sync:")
for coin, data in clean_portfolio.items():
print(f"{coin}: {data['amount']} coins | Value: ${data['usd_value']}")
except Exception as e:
print(f"Error: {e}")
Step 3: Why This System Wins
Once this data is extracted, the next step is using the requests library to POST this directly to your Notion Database URL.
Why build this?
• Privacy: Your portfolio data stays between you, Binance, and your private Notion workspace. No third-party tracking apps.
• Customization: In Notion, you can build custom formulas around this data—calculate taxes, set visual goals, or track your portfolio against your real-life expenses.
Do you want Part 2, where we write the exact API code to push this data into the Notion tables? Drop a "+" in the comments if I should drop the rest of the code! 👇
#Notion #BinanceAPI #PortfolioTracker #PythonTrading #TechInCrypto

Most beginners look at technical indicators like magic lines on a chart. They wait for a line to cross another line and click "Buy." But if you don't understand the why behind the formula, you are just gambling.
Today, we are combining pure logic with Python. We are going to build a script that calculates the RSI (Relative Strength Index) for $BTC or $ETH , but first, let's understand what we are actually coding.
Step 1: The Conceptual Math of RSI
RSI is a momentum oscillator that measures the speed and change of price movements. It oscillates between 0 and 100.
Traditionally:
• Over 70: The asset is considered "Overbought" (due for a pullback).
• Under 30: The asset is considered "Oversold" (due for a bounce).
But why? The math behind RSI simply compares the magnitude of recent gains to recent losses over a specified time period (usually 14 periods).
If the average of your recent up-closes is much higher than the average of your down-closes, the RSI goes up. It's a mathematical representation of buyer vs. seller exhaustion. We aren't predicting the future; we are calculating the current mathematical probability of a trend reversal.
Step 2: The Python Code
To calculate this automatically, we will use our trusty ccxt library to get the data, and pandas_ta (a technical analysis library) to do the heavy math.
Install the required libraries first: pip install ccxt pandas pandas_ta
Here is a clean, conceptual script to get the current RSI of $BTC :

import ccxt
import pandas as pd
import pandas_ta as ta
import time
# Settings
SYMBOL = 'BTC/USDT'
TIMEFRAME = '15m' # 15-minute candles
LIMIT = 100 # We need enough candles to calculate the 14-period average
# Initialize exchange
exchange = ccxt.binance()
def get_rsi(symbol, timeframe, limit):
try:
# 1. Fetch OHLCV data (Open, High, Low, Close, Volume)
bars = exchange.fetch_ohlcv(symbol, timeframe, limit=limit)

# 2. Convert to a Pandas DataFrame
df = pd.DataFrame(bars, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])

# 3. Calculate RSI using the close price (default length is 14)
df.ta.rsi(close='close', length=14, append=True)

# 4. Get the last (current) RSI value
current_rsi = df['RSI_14'].iloc[-1]
current_price = df['close'].iloc[-1]

return current_price, current_rsi

except Exception as e:
print(f"Error fetching data: {e}")
return None, None
# Run the check
price, rsi = get_rsi(SYMBOL, TIMEFRAME, LIMIT)
if rsi:
print(f"Current {SYMBOL} Price: ${price}")
print(f"Current RSI (14): {rsi:.2f}")

if rsi < 30:
print("🚨 MATHEMATHICAL SIGNAL: RSI is Oversold (<30). Potential buying opportunity.")
elif rsi > 70:
print("🚨 MATHEMATHICAL SIGNAL: RSI is Overbought (>70). Potential selling opportunity.")
else:
print("Neutral zone. Let the code wait.")

Why This Beats Manual Trading
By running this script (or combining it with the Telegram bot from our previous article), you remove emotion entirely. You act strictly on mathematical data. No FOMO, no panic.
Challenge for you: Can you modify this code to check $ETH and $SOL at the same time? Let me know in the comments if you want the multi-coin version tomorrow! 👇
Disclaimer: This is for educational purposes. RSI is a probability tool, not a guarantee. Always manage your risk.

#PythonTrading #CryptoMath #RSITrading #BinanceAPI #AlgoTrading #BTC #ETH

Budzenie się o 3 w nocy, żeby sprawdzić, czy BTC przełamał opór? Ciągłe odświeżanie aplikacji Binance podczas kolacji? Wszyscy byliśmy w tej sytuacji. To wyczerpujące.
W naszym ostatnim wpisie połączyliśmy się z API Binance. Dziś idziemy o krok dalej. Zbudujemy prostego bota w Pythonie, który obserwuje rynek za Ciebie i wysyła wiadomość na Telegram, gdy moneta osiągnie Twój docelowy poziom cenowy.
Koniec z FOMO. Niech kod zajmie się czekaniem.
Krok 1: Skonfiguruj swojego asystenta na Telegramie
Zanim zaczniemy pisać w Pythonie, musimy stworzyć bota na Telegramie.

Wciąż wpatrujesz się w ekran cały dzień, czekając na ten idealny punkt wejścia? 📉 Przestań. Witamy po drugiej stronie: W świecie, gdzie kod działa, a traderzy relaksują się (głównie).
Korzystanie z API Binance (Interfejs Programowania Aplikacji) to jak podłączenie swojej strategii do giełdy za pomocą szybkiego, bezpośredniego połączenia. To nie tylko dla zaawansowanych traderów quant; to dla każdego, kto ma dość ręcznego odświeżania wykresów.
W tym pierwszym artykule, zróbmy to na serio. Oto podstawowy, krok po kroku przewodnik, jak zdobyć swoje pierwsze doświadczenie w automatyzacji krypto. Bez zbędnych słów.