Openbb Crypto

Comprehensive cryptocurrency analysis using OpenBB Platform's crypto data sources.

Usage

/openbb-crypto SYMBOL [--vs USD|BTC|ETH] [--metrics on-chain|defi|social] [--period 30d]

What This Command Does

Analyzes cryptocurrency markets with price data, on-chain metrics, DeFi analytics, and sentiment analysis.

Workflow

1. Setup OpenBB Connection

from openbb import obb
import pandas as pd
from datetime import datetime, timedelta

# Parse arguments
symbol = sys.argv[1].upper() if len(sys.argv) > 1 else "BTC"
vs_currency = "USD"  # USD, BTC, ETH
metrics_type = "all"  # on-chain, defi, social, all
period = "30d"  # 7d, 30d, 90d, 1y

# Parse flags
for arg in sys.argv[2:]:
    if arg.startswith("--vs="):
        vs_currency = arg.split("=")[1].upper()
    elif arg.startswith("--metrics="):
        metrics_type = arg.split("=")[1]
    elif arg.startswith("--period="):
        period = arg.split("=")[1]

2. Retrieve Price Data

# Get historical crypto prices
crypto_data = obb.crypto.price.historical(
    symbol=f"{symbol}{vs_currency}",
    interval="1d",
    period=period
)

df = crypto_data.to_dataframe()

print(f"\n₿ Crypto Analysis: {symbol}/{vs_currency}")
print(f"{'='*60}")

current_price = df['close'].iloc[-1]
period_high = df['high'].max()
period_low = df['low'].min()
period_return = ((current_price / df['close'].iloc[0]) - 1) * 100

print(f"\n💰 Price Overview:")
…

3. Technical Indicators

# Calculate crypto-specific indicators
print(f"\n📊 Technical Indicators:")

# Moving averages
df['MA_7'] = df['close'].rolling(window=7).mean()
df['MA_30'] = df['close'].rolling(window=30).mean()
df['MA_90'] = df['close'].rolling(window=90).mean()

ma_7 = df['MA_7'].iloc[-1]
ma_30 = df['MA_30'].iloc[-1]
ma_90 = df['MA_90'].iloc[-1]

print(f"MA 7:  ${ma_7:,.2f} {'🟢' if current_price > ma_7 else '🔴'}")
print(f"MA 30: ${ma_30:,.2f} {'🟢' if current_price > ma_30 else '🔴'}")
print(f"MA 90: ${ma_90:,.2f} {'🟢' if current_price > ma_90 else '🔴'}")

# Volatility
returns = df['close'].pct_change()
…

4. On-Chain Metrics (if available)

if metrics_type in ["on-chain", "all"]:
    print(f"\n⛓️  On-Chain Metrics:")

    try:
        # Network activity
        network_data = obb.crypto.onchain.active_addresses(symbol=symbol)
        print(f"Active Addresses (24h): {network_data.active_addresses:,}")
        print(f"Transaction Count: {network_data.tx_count:,}")
        print(f"Transaction Volume: ${network_data.tx_volume:,.0f}")

        # Hash rate (for PoW coins)
        if symbol in ["BTC", "ETH", "LTC", "DOGE"]:
            hash_data = obb.crypto.onchain.hashrate(symbol=symbol)
            print(f"\nHash Rate: {hash_data.hashrate / 1e18:.2f} EH/s")
            print(f"Mining Difficulty: {hash_data.difficulty:,.0f}")

        # Holder distribution
        holders = obb.crypto.onchain.holders(symbol=symbol)
…

5. DeFi Metrics (if applicable)

if metrics_type in ["defi", "all"] and symbol in ["ETH", "BNB", "AVAX", "SOL"]:
    print(f"\n🏦 DeFi Metrics:")

    try:
        defi_data = obb.crypto.defi.tvl(chain=symbol)
        print(f"Total Value Locked: ${defi_data.tvl / 1e9:.2f}B")
        print(f"Protocol Count: {defi_data.protocol_count}")
        print(f"Top Protocol: {defi_data.top_protocol}")
        print(f"  - TVL: ${defi_data.top_protocol_tvl / 1e9:.2f}B")

        # Staking data
        staking = obb.crypto.defi.staking(symbol=symbol)
        print(f"\nStaking:")
        print(f"Total Staked: {staking.total_staked_pct:.1f}%")
        print(f"Avg APY: {staking.avg_apy:.2f}%")
    except:
        print(f"DeFi data not available for {symbol}")

6. Social Sentiment & News

if metrics_type in ["social", "all"]:
    print(f"\n📱 Social Sentiment:")

    try:
        social_data = obb.crypto.social.sentiment(symbol=symbol)
        print(f"Twitter Mentions (24h): {social_data.twitter_mentions:,}")
        print(f"Reddit Posts (24h): {social_data.reddit_posts:,}")
        print(f"Sentiment Score: {social_data.sentiment_score:.2f}/5.0")

        sentiment_emoji = "🟢" if social_data.sentiment_score > 3.5 else "🟡" if social_data.sentiment_score > 2.5 else "🔴"
        print(f"Overall Sentiment: {sentiment_emoji}")

        # Recent news
        news = obb.crypto.news(symbol=symbol, limit=3)
        print(f"\n📰 Latest News:")
        for i, article in enumerate(news[:3], 1):
            print(f"{i}. {article.title}")
            print(f"   {article.source} - {article.published_date}")
…

7. Whale Activity Tracker

print(f"\n🐋 Whale Activity (Large Transfers):")

try:
    # Get large transactions (>$100k)
    whales = obb.crypto.onchain.large_transactions(
        symbol=symbol,
        min_value=100000,
        limit=5
    )

    if len(whales) > 0:
        print(f"Last {len(whales)} large transfers:")
        for tx in whales:
            print(f"  ${tx.value_usd:,.0f} - {tx.from_address[:10]}...→ {tx.to_address[:10]}...")
            print(f"    {tx.timestamp} ({tx.exchange if tx.exchange else 'Unknown'})")
    else:
        print("No significant whale activity detected")
except:
…

8. AI-Powered Market Analysis

print(f"\n🤖 AI Market Analysis for {symbol}:")
print(f"\n📈 Trend Analysis:")

# Determine trend
if current_price > ma_7 > ma_30 > ma_90:
    trend = "Strong Uptrend"
    trend_emoji = "🚀"
elif current_price > ma_30:
    trend = "Bullish"
    trend_emoji = "📈"
elif current_price < ma_7 < ma_30 < ma_90:
    trend = "Strong Downtrend"
    trend_emoji = "📉"
else:
    trend = "Consolidating"
    trend_emoji = "↔️"

print(f"{trend_emoji} Market Trend: {trend}")
…