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"""
Sentiment Data Collectors
Fetches cryptocurrency sentiment data from Alternative.me Fear & Greed Index
"""
import asyncio
from datetime import datetime, timezone
from typing import Dict, List, Optional, Any
from utils.api_client import get_client
from utils.logger import setup_logger, log_api_request, log_error
from config import config
logger = setup_logger("sentiment_collector")
def calculate_staleness_minutes(data_timestamp: Optional[datetime]) -> Optional[float]:
"""
Calculate staleness in minutes from data timestamp to now
Args:
data_timestamp: Timestamp of the data
Returns:
Staleness in minutes or None if timestamp not available
"""
if not data_timestamp:
return None
now = datetime.now(timezone.utc)
if data_timestamp.tzinfo is None:
data_timestamp = data_timestamp.replace(tzinfo=timezone.utc)
delta = now - data_timestamp
return delta.total_seconds() / 60.0
async def get_fear_greed_index() -> Dict[str, Any]:
"""
Fetch current Fear & Greed Index from Alternative.me
The Fear & Greed Index is a sentiment indicator for the cryptocurrency market.
- 0-24: Extreme Fear
- 25-49: Fear
- 50-74: Greed
- 75-100: Extreme Greed
Returns:
Dict with provider, category, data, timestamp, staleness, success, error
"""
provider = "AlternativeMe"
category = "sentiment"
endpoint = "/fng/"
logger.info(f"Fetching Fear & Greed Index from {provider}")
try:
client = get_client()
provider_config = config.get_provider(provider)
if not provider_config:
error_msg = f"Provider {provider} not configured"
log_error(logger, provider, "config_error", error_msg, endpoint)
return {
"provider": provider,
"category": category,
"data": None,
"timestamp": datetime.now(timezone.utc).isoformat(),
"staleness_minutes": None,
"success": False,
"error": error_msg
}
# Build request URL
url = f"{provider_config.endpoint_url}{endpoint}"
params = {
"limit": "1", # Get only the latest index
"format": "json"
}
# Make request
response = await client.get(url, params=params, timeout=provider_config.timeout_ms // 1000)
# Log request
log_api_request(
logger,
provider,
endpoint,
response.get("response_time_ms", 0),
"success" if response["success"] else "error",
response.get("status_code")
)
if not response["success"]:
error_msg = response.get("error_message", "Unknown error")
log_error(logger, provider, response.get("error_type", "unknown"), error_msg, endpoint)
return {
"provider": provider,
"category": category,
"data": None,
"timestamp": datetime.now(timezone.utc).isoformat(),
"staleness_minutes": None,
"success": False,
"error": error_msg,
"error_type": response.get("error_type")
}
# Extract data
data = response["data"]
# Parse timestamp from response
data_timestamp = None
if isinstance(data, dict) and "data" in data:
data_list = data["data"]
if isinstance(data_list, list) and len(data_list) > 0:
index_data = data_list[0]
if isinstance(index_data, dict) and "timestamp" in index_data:
try:
# Alternative.me returns Unix timestamp
data_timestamp = datetime.fromtimestamp(
int(index_data["timestamp"]),
tz=timezone.utc
)
except:
pass
staleness = calculate_staleness_minutes(data_timestamp)
# Extract index value and classification
index_value = None
index_classification = None
if isinstance(data, dict) and "data" in data:
data_list = data["data"]
if isinstance(data_list, list) and len(data_list) > 0:
index_data = data_list[0]
if isinstance(index_data, dict):
index_value = index_data.get("value")
index_classification = index_data.get("value_classification")
logger.info(
f"{provider} - {endpoint} - Fear & Greed Index: {index_value} ({index_classification}), "
f"staleness: {staleness:.2f}m" if staleness else "staleness: N/A"
)
return {
"provider": provider,
"category": category,
"data": data,
"timestamp": datetime.now(timezone.utc).isoformat(),
"data_timestamp": data_timestamp.isoformat() if data_timestamp else None,
"staleness_minutes": staleness,
"success": True,
"error": None,
"response_time_ms": response.get("response_time_ms", 0),
"index_value": index_value,
"index_classification": index_classification
}
except Exception as e:
error_msg = f"Unexpected error: {str(e)}"
log_error(logger, provider, "exception", error_msg, endpoint, exc_info=True)
return {
"provider": provider,
"category": category,
"data": None,
"timestamp": datetime.now(timezone.utc).isoformat(),
"staleness_minutes": None,
"success": False,
"error": error_msg,
"error_type": "exception"
}
async def collect_sentiment_data() -> List[Dict[str, Any]]:
"""
Main function to collect sentiment data from all sources
Currently collects from:
- Alternative.me Fear & Greed Index
Returns:
List of results from all sentiment collectors
"""
logger.info("Starting sentiment data collection from all sources")
# Run all collectors concurrently
results = await asyncio.gather(
get_fear_greed_index(),
return_exceptions=True
)
# Process results
processed_results = []
for result in results:
if isinstance(result, Exception):
logger.error(f"Collector failed with exception: {str(result)}")
processed_results.append({
"provider": "Unknown",
"category": "sentiment",
"data": None,
"timestamp": datetime.now(timezone.utc).isoformat(),
"staleness_minutes": None,
"success": False,
"error": str(result),
"error_type": "exception"
})
else:
processed_results.append(result)
# Log summary
successful = sum(1 for r in processed_results if r.get("success", False))
logger.info(f"Sentiment data collection complete: {successful}/{len(processed_results)} successful")
return processed_results
# Alias for backward compatibility
collect_sentiment = collect_sentiment_data
class SentimentCollector:
"""
Sentiment Collector class for WebSocket streaming interface
Wraps the standalone sentiment collection functions
"""
def __init__(self, config: Any = None):
"""
Initialize the sentiment collector
Args:
config: Configuration object (optional, for compatibility)
"""
self.config = config
self.logger = logger
async def collect(self) -> Dict[str, Any]:
"""
Collect sentiment data from all sources
Returns:
Dict with aggregated sentiment data
"""
results = await collect_sentiment_data()
# Aggregate data for WebSocket streaming
aggregated = {
"overall_sentiment": None,
"sentiment_score": None,
"social_volume": None,
"trending_topics": [],
"by_source": {},
"social_trends": [],
"timestamp": datetime.now(timezone.utc).isoformat()
}
for result in results:
if result.get("success") and result.get("data"):
provider = result.get("provider", "unknown")
# Parse Fear & Greed Index
if provider == "Alternative.me" and "data" in result["data"]:
index_data = result["data"]["data"][0] if result["data"]["data"] else {}
aggregated["sentiment_score"] = int(index_data.get("value", 0))
aggregated["overall_sentiment"] = index_data.get("value_classification", "neutral")
aggregated["by_source"][provider] = {
"value": aggregated["sentiment_score"],
"classification": aggregated["overall_sentiment"]
}
return aggregated
# Example usage
if __name__ == "__main__":
async def main():
results = await collect_sentiment_data()
print("\n=== Sentiment Data Collection Results ===")
for result in results:
print(f"\nProvider: {result['provider']}")
print(f"Success: {result['success']}")
print(f"Staleness: {result.get('staleness_minutes', 'N/A')} minutes")
if result['success']:
print(f"Response Time: {result.get('response_time_ms', 0):.2f}ms")
if result.get('index_value'):
print(f"Fear & Greed Index: {result['index_value']} ({result['index_classification']})")
else:
print(f"Error: {result.get('error', 'Unknown')}")
asyncio.run(main())
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