Metadata-Version: 2.4
Name: trendsagi
Version: 0.3.2
Summary: The official Python client for the TrendsAGI API.
Author-email: TrendsAGI <contact@trendsagi.com>
License: MIT License
        
        Copyright (c) [2025] [TrendsAGI]
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
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Project-URL: Homepage, https://github.com/TrendsAGI/TrendsAGI
Project-URL: Bug Tracker, https://github.com/TrendsAGI/TrendsAGI/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: requests>=2.28.0
Requires-Dist: pydantic>=2.0
Dynamic: license-file

# TrendsAGI Official Python Client

[![PyPI Version](https://img.shields.io/pypi/v/trendsagi.svg)](https://pypi.org/project/trendsagi/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Python Versions](https://img.shields.io/pypi/pyversions/trendsagi.svg)](https://pypi.org/project/trendsagi/)

The official Python client for the [TrendsAGI API](https://trendsagi.com), providing access to real-time trend data, AI-powered insights, market intelligence, and live streaming capabilities.

## Features

- **Trends & Insights**: Real-time trend data with analytics (volume, velocity, stability)
- **AI-Powered Analysis**: Deep insights, sentiment analysis, and content recommendations
- **Intelligence Suite**: Market tracking, crisis monitoring, custom reports, and recommendations
- **Live Streaming**: WebSocket connections for real-time financial and trend data
- **User Management**: Topic interests, notifications, and alert configuration
- **Full Type Support**: Complete Pydantic models with IDE autocompletion

## Installation

```bash
pip install trendsagi
```

## Quick Start

```python
import os
from trendsagi import TrendsAGIClient, APIError

# Load API key from environment variable (recommended)
client = TrendsAGIClient(api_key=os.getenv("TRENDSAGI_API_KEY"))

try:
    # Get trending topics with new analytics
    trends = client.get_trends(limit=5, period='24h')
    
    for trend in trends.trends:
        print(f"Trend: {trend.name}")
        print(f"  Volume: {trend.volume}")
        print(f"  Overall Trend: {trend.overall_trend}")
        print(f"  Avg Velocity: {trend.average_velocity:.2f} posts/hr")
        print(f"  Stability: {trend.trend_stability:.2f}")
        
except APIError as e:
    print(f"API Error ({e.status_code}): {e.error_detail}")
```

## Core Functionality

### Trends & Analytics

```python
# Find trends about AI and get detailed information
ai_trends = client.get_trends(search="artificial intelligence", limit=3)

if ai_trends.trends:
    trend = ai_trends.trends[0]  # Get the top AI trend
    print(f"Working with trend: {trend.name}")
    
    # Get detailed trend information
    trend_details = client.get_trend_details(trend_id=trend.id)
    print(f"Category: {trend_details.category}")
    print(f"Sample tweets: {len(trend_details.tweets)}")
    
    # Get historical analytics for this trend
    analytics = client.get_trend_analytics(trend_id=trend.id, period="7d")
    print(f"Analytics over {len(analytics.data)} data points")
    
    # Get AI insights for this trend
    insights = client.get_ai_insights(trend_id=trend.id)
    print(f"Sentiment: {insights.sentiment_category}")
    print(f"Key Themes: {insights.key_themes}")
```

### Intelligence Suite

```python
# Search trends by AI-generated insights
results = client.search_insights(
    key_theme_contains="sustainability",
    sentiment_category="positive"
)

# Generate custom reports
report = client.generate_custom_report({
    "dimensions": ["trend_category"],
    "metrics": ["sum_volume"],
    "time_period": "7d"
})

# Get actionable recommendations
recommendations = client.get_recommendations(priority="high")
for rec in recommendations.recommendations:
    print(f"- {rec.title}")

# Track X (Twitter) users
user = client.create_tracked_x_user(
    handle="elonmusk",
    name="Elon Musk",
    notes="Tech industry leader"
)

# Refresh user analysis
analysis = client.refresh_x_user_analysis(
    entity_id=user.id, 
    force_refresh=True
)
print(f"Latest analysis: {analysis.entity.recent_post_analysis.summary}")
```

### Deep Analysis & Crisis Monitoring

```python
# Perform deep AI analysis on any topic
analysis = client.perform_deep_analysis(
    query="What are the primary concerns about AI in healthcare for 2025?"
)
print(analysis.executive_summary_and_key_findings.summary)

# Monitor crisis events
events = client.get_crisis_events(status="active")
for event in events.events:
    print(f"[{event.severity.upper()}] {event.title}")
```

### Financial Intelligence

Get consolidated financial data, with event times automatically localized to your timezone. The timezone parameter accepts any standard IANA timezone name. If the parameter is omitted, all times will be returned in UTC.

Common Timezone Examples:
London: "Europe/London"
Berlin: "Europe/Berlin"
Paris: "Europe/Paris"
New York: "America/New_York"
Tokyo: "Asia/Tokyo"
Hong Kong: "Asia/Hong_Kong"
Singapore: "Asia/Singapore"
Sydney: "Australia/Sydney"
UTC: "UTC"

Complete list available here: https://en.wikipedia.org/wiki/List_of_tz_database_time_zones

```python
# Get financial data with times converted to German time (Europe/Berlin) - Example
financial_data = client.get_financial_data(timezone="Europe/Berlin")

# Market sentiment
if financial_data.market_sentiment:
    print(f"Market: {financial_data.market_sentiment.sentiment}")

# Recent earnings reports
for report in financial_data.earnings_reports:
    print(f"{report.company}: EPS {report.earnings_per_share}")

# IPO filings
for ipo in financial_data.ipo_filings_news:
    print(f"{ipo.company} IPO expected: {ipo.expected_trade_date}")

# The event times will now be localized to the requested timezone.
print("\n--- Economic Calendar (Times for Europe/Berlin) ---")
if financial_data.forex_factory_events:
    for event in financial_data.forex_factory_events[:5]: 
        print(
            f"- {event.event_date} {event.event_time} ({event.currency}): "
            f"{event.event_name} (Impact: {event.impact})"
        )
else:
    print("No upcoming economic events found.")
```

### User Management

```python
# Create topic interest with alerts
interest = client.create_topic_interest(
    keyword="artificial intelligence",
    alert_condition_type="volume_threshold",
    volume_threshold_value=5000,
    send_email_alerts=True
)

# Get recent notifications
notifications = client.get_recent_notifications(limit=10)
print(f"Unread: {notifications.unread_count}")

# Mark notifications as read
client.mark_notifications_read(ids=[100, 101])
```

### Live Streaming (WebSockets)

```python

# Real-time financial data stream
async def stream_financial_data():
    print("\nConnecting to financial live stream...")
    async for message in client.finance_stream():
        data = json.loads(message)
        
        event_type = data.get("type", "unknown")
        payload = data.get("payload", {})
        
        if "earnings_report" in event_type:
            print(f"  [EARNINGS] {payload.get('company')}: {payload.get('period')}")
        elif "forex_event" in event_type:
            print(
                f"  [CALENDAR] {payload.get('event_at')} "
                f"({payload.get('currency')}) - "
                f"{payload.get('event_name')} (Impact: {payload.get('impact')})"
            )
        # --- MODIFICATION END ---
        else:
            print(f"  [{event_type.upper()}] Received event.")

# Real-time trend data stream
async def stream_trend_data():
    # Subscribe to specific trends
    trends = "AI,Crypto,Web3"
    uri = f"wss://api.trendsagi.com/ws/trends-live?token={API_KEY}&trends={trends}"
    
    async with websockets.connect(uri) as websocket:
        print("Connected to trends live stream")
        while True:
            message = await websocket.recv()
            trend_data = json.loads(message)
            print(f"{trend_data['trend_name']}: {trend_data['volume']} posts")

# Run the streams
asyncio.run(stream_financial_data())
```

## Error Handling

The client provides specific exceptions for different error types:

```python
from trendsagi.exceptions import (
    TrendsAGIError,          # Base exception
    AuthenticationError,     # 401 errors
    NotFoundError,          # 404 errors
    RateLimitError,         # 429 errors
    APIError               # General API errors
)

try:
    response = client.get_trends()
except AuthenticationError:
    print("Invalid API key")
except RateLimitError as e:
    print(f"Rate limit hit. Retry after: {e.retry_after}s")
except NotFoundError:
    print("Resource not found")
except APIError as e:
    print(f"API error {e.status_code}: {e.error_detail}")
```

## Rate Limits & Plans

Rate limits vary by subscription plan and endpoint type. The system uses endpoint-specific limits optimized for different use cases.

| Endpoint Category | Signal | Advantage | Scale | Enterprise |
|-------------------|--------|-----------|-------|------------|
| **API Access** | ❌ Not Available | ✅ Available | ✅ Available | ✅ Available |
| **General API Calls** | - | 300/hour | 1,500/hour | Unlimited |
| **Trends List** | - | 750/hour | 1,500/hour | Unlimited |
| **AI Insights Search** | - | 200/hour | 750/hour | Unlimited |
| **Analytics** | - | 300/hour | 1,500/hour | Unlimited |
| **Dashboard** | 180/hour | 360/hour | 720/hour | Unlimited |
| **Login/Auth** | 30/hour | 75/hour | 150/hour | Unlimited |
| **Intelligence Features** | - | 300/hour | 1,000/hour | Unlimited |
| **Financial Data** | - | 120/hour | 600/hour | Unlimited |
| **User Management** | 300/hour | 600/hour | 1,000/hour | Unlimited |
| **Live Streaming** | ❌ | ❌ | ✅ Available | ✅ Available |

### Rate Limit Headers

All API responses include rate limit information:
- `X-RateLimit-Limit`: Your current limit for this endpoint
- `X-RateLimit-Remaining`: Requests remaining in current window
- `X-RateLimit-Reset`: Unix timestamp when the limit resets

## API Documentation

For complete API reference, including all endpoints, parameters, and response schemas:

**[View Full API Documentation →](https://trendsagi.com/api-docs)**

## Plan Features by Tier

Different features are available based on your subscription:

### Signal Plan
- Basic trends access via web dashboard
- Limited history (7 days)
- 5 topic interests
- Basic reporting (10K row limit)
- CSV exports only

### Advantage Plan
- Full API access (10K calls/day)
- 30-day history
- 25 topic interests  
- Advanced insights and search
- Priority support
- Unlimited reporting rows
- 100 deep analysis queries/day

### Scale Plan
- Enhanced API access (25K calls/day)
- 90-day history
- 100 topic interests
- Crisis monitoring
- Live streaming access
- Cloud exports
- Slack notifications
- Video generation
- 1,000 deep analysis queries/day

### Enterprise Plan
- Unlimited API access
- Unlimited history
- Unlimited topic interests
- Custom integrations
- Dedicated support & SLA
- All premium features
- Unlimited deep analysis

## Support

- **API Documentation**: [trendsagi.com/api-docs](https://trendsagi.com/api-docs)
- **Support**: contact@trendsagi.com
- **Issues**: [GitHub Issues](https://github.com/TrendsAGI/TrendsAGI/issues)

## License

MIT License - see [LICENSE](LICENSE) file for details.
