4 posts tagged with "api"

In today's information-driven world, access to reliable and comprehensive news data is crucial for informed decision-making across various domains. Introducing the Fetch NewsAPI Connector - a powerful worker that provides seamless access to one of the most comprehensive news databases available through EventRegistry's NewsAPI.

What is Fetch NewsAPI Connector?​

The Fetch NewsAPI Connector integrates with EventRegistry's NewsAPI to provide access to millions of news articles from thousands of trusted sources worldwide. Whether you're building news aggregators, conducting sentiment analysis, performing market research, or developing AI-powered content systems, this connector offers everything you need in one unified interface.

With advanced filtering capabilities by categories, sources, languages, and date ranges, the Fetch NewsAPI connector eliminates the need for multiple news APIs and complex data aggregation pipelines.

Key Features​

• Comprehensive Coverage: Access to millions of articles from 100,000+ news sources worldwide
• Advanced Filtering: Filter by categories, sources, languages, and date ranges
• Real-time & Historical Data: Access both breaking news and extensive historical archives
• Trusted Sources: Pre-configured with major financial and news publications
• Flexible Categories: Support for DMOZ taxonomy with business, finance, and industry categories
• Language Support: Multi-language news retrieval with English as default
• Date Range Filtering: Precise temporal filtering for time-sensitive analysis
• Rate Limiting: Built-in API key management and usage tracking
• Structured Output: Consistent article data with titles, content, dates, and metadata

How It Works​

Core Functionality​

Article Retrieval: Fetches news articles using complex queries with category and source filtering Temporal Filtering: Supports date range queries for historical and current news analysis Source Validation: Ensures articles come from reputable news sources Language Filtering: Retrieves articles in specified languages Result Limiting: Configurable result limits with intelligent ranking

Data Processing Pipeline​

1. Query Construction: Builds complex EventRegistry queries with category and source filters
2. API Communication: Secure connection to EventRegistry NewsAPI
3. Article Filtering: Applies date ranges, language filters, and result limits
4. Data Normalization: Standardizes article format across all sources
5. Result Packaging: Returns structured data ready for downstream processing

Getting Started - Interface Configuration​

Basic Setup​

1. Select Worker Type: Choose "fetch_newsapi" from the worker selection dropdown
2. Configure API Key: Enter your EventRegistry API key or use environment variable
3. Set Parameters: Configure categories, sources, date ranges, and limits
4. Execute: Run the worker to retrieve filtered news articles

Common Parameters​

• apiKey: Your EventRegistry API key (optional if set as environment variable)
• categories: Array of category URIs for topic filtering
• sources: Array of news source URIs for publication filtering
• lang: Language code for article filtering (default: "eng")
• dateFrom/dateTo: ISO date range for temporal filtering
• limit: Maximum number of articles to return (1-500)

Parameter Configuration Examples​

Default Financial News Setup:

• categories: ["dmoz/Business/Investing/Stocks_and_Bonds", "dmoz/Society/Government/Finance"]
• sources: ["finance.yahoo.com", "bloomberg.com", "reuters.com", "cnbc.com"]
• limit: 100

Breaking News Monitoring:

• dateFrom: Current date (YYYY-MM-DD)
• categories: Broad business categories
• limit: 50

Advanced Configuration Options​

Category Taxonomy​

EventRegistry uses DMOZ taxonomy for categorization. Common financial categories include:

• dmoz/Business/Investing/Stocks_and_Bonds - Stock market and investment news
• dmoz/Society/Government/Finance - Government financial policy and regulation
• dmoz/Business/Investing/Currencies - Forex and currency markets
• dmoz/Business/Investing/Commodities - Commodity trading and markets

Source Selection Strategy​

Major Financial Publications:

• finance.yahoo.com - Yahoo Finance
• bloomberg.com - Bloomberg News
• reuters.com - Reuters
• cnbc.com - CNBC
• marketwatch.com - MarketWatch
• wsj.com - Wall Street Journal

Specialized Sources:

• investing.com - Investing.com
• foxbusiness.com - Fox Business
• nytimes.com - New York Times (business section)

Date Range Optimization​

• Real-time News: Use current date for dateFrom, omit dateTo
• Historical Analysis: Set specific date ranges for backtesting
• Trend Analysis: Use rolling date windows for ongoing monitoring

Practical Implementation Examples​

Financial News Aggregation System​

Create a comprehensive financial news monitoring workflow:

1. Fetch Breaking News using default financial categories and sources
2. Apply Vector Analysis using VectorAnalyzer for semantic search
3. Perform Sentiment Analysis to gauge market sentiment
4. Generate Alerts based on sentiment scores and relevance

Complete Workflow Example:

• workers[0]: Fetch NewsAPI Connector
  • type: fetch_newsapi
  • categories: ["dmoz/Business/Investing/Stocks_and_Bonds"]
  • sources: ["bloomberg.com", "reuters.com", "cnbc.com"]
  • dateFrom: 2025-11-01
  • limit: 50
• workers[1]: VectorAnalyzer
  • type: vector_analyzer
  • data: {{workers[0].result.results}}
  • query: "market volatility and economic indicators"
  • top_percentage: 30

Market Intelligence Dashboard​

Build real-time market intelligence:

• workers[0]: Multiple News Sources
  • type: fetch_newsapi
  • sources: ["finance.yahoo.com", "marketwatch.com", "foxbusiness.com"]
  • dateFrom: Current date
• workers[1]: Category Analysis
  • type: fetch_newsapi
  • categories: ["dmoz/Business/Investing/Currencies", "dmoz/Business/Investing/Commodities"]
• workers[2]: Sentiment Aggregation
  • type: sentiment_analyzer
  • data_source: {{workers[0].result.results}} + {{workers[1].result.results}}

Historical News Analysis​

Analyze news patterns over time:

• workers[0]: Historical Data Collection
  • type: fetch_newsapi
  • dateFrom: 2025-01-01
  • dateTo: 2025-11-15
  • categories: Broad business categories
  • limit: 500
• workers[1]: Trend Analysis
  • type: time_series_analyzer
  • data: {{workers[0].result.results}}
  • group_by: month

Operations Comparison Table​

Best Practices and Tips​

API Key Management​

• Use personal API keys for higher rate limits and dedicated quotas
• Set EVENT_REGISTRY_API_KEY environment variable for security
• Monitor usage through EventRegistry dashboard to avoid limits

Query Optimization​

• Use specific category URIs for targeted results rather than broad searches
• Combine category and source filtering for precise content control
• Limit results appropriately for your processing capacity

Date Range Strategies​

• Use ISO format (YYYY-MM-DD) for all date parameters
• Omit dateTo for ongoing "breaking news" monitoring
• Use dateFrom only for "from this date forward" queries

Performance Considerations​

• Lower limits (50-100) for real-time applications
• Higher limits (200-500) for batch processing and analysis
• Consider pagination for very large result sets

Integration with Other Workers​

AI-Powered News Analysis​

Combine with VectorAnalyzer for semantic search:

• VectorAnalyzer: Find articles most relevant to your query
• Sentiment Analysis: Understand market sentiment from news content
• Topic Modeling: Discover trending themes across news corpus

Financial Data Correlation​

Link news with market data:

• Price Data Integration: Correlate news events with price movements
• Economic Calendar: Connect news with economic indicators
• Technical Analysis: Use news sentiment as additional signals

Content Processing Pipelines​

Build automated content workflows:

• Text Summarization: Generate article summaries for quick review
• Entity Extraction: Identify companies, people, and organizations
• Trend Detection: Monitor topic frequency and sentiment changes

Conclusion​

The Fetch NewsAPI Connector represents a comprehensive solution for news data access, providing everything from breaking financial news to historical archives in a single, easy-to-use interface. Whether you're a financial analyst, data scientist, content creator, or developer building news applications, this connector offers the flexibility and reliability you need to build sophisticated news-driven workflows.

With support for global news sources, advanced filtering capabilities, and seamless integration with AI analysis tools like VectorAnalyzer, the Fetch NewsAPI connector eliminates news data silos and simplifies the development of intelligent news processing systems. Start exploring the power of comprehensive news data today and unlock new possibilities for your news analysis and content processing applications.

For detailed guides on specific use cases, check out our dedicated articles covering advanced filtering techniques, AI-powered news analysis workflows, and real-time news monitoring strategies with step-by-step interface instructions and practical examples.

In today's fast-paced financial markets, access to reliable and comprehensive market data is essential for informed trading and investment decisions. Introducing the Twelve Data Market Data Connector - a powerful worker that provides seamless access to one of the most comprehensive financial data APIs available.

What is Twelve Data Market Data Connector?​

The Twelve Data Market Data Connector integrates with the Twelve Data API to provide access to real-time and historical financial data across multiple asset classes including stocks, forex, cryptocurrencies, ETFs, and mutual funds. Whether you're building trading strategies, conducting fundamental analysis, or developing financial applications, this connector offers everything you need in one unified interface.

With support for over 40 different operations ranging from historical price data to technical indicators and fundamental company information, the Twelve Data connector eliminates the need for multiple data sources and complex API integrations.

Key Features​

• 40+ Operations: From basic price data to advanced technical indicators and fundamental analysis
• Multi-Asset Support: Stocks, forex, crypto, ETFs, mutual funds, and more
• Real-time & Historical Data: Access both live market data and extensive historical datasets
• Global Coverage: Data from exchanges worldwide with automatic timezone handling
• Flexible Parameters: Customizable intervals, date ranges, and output sizes
• Rate Limiting: Built-in per-user rate limiting when using shared API keys
• Error Handling: Robust error handling with clear error messages
• API Key Management: Support for personal API keys or shared environment keys

Core Operations Overview​

1. Market Data Operations - The Foundation​

time_series: Historical and intraday OHLCV data for any symbol quote: Real-time quote snapshots with full market information price: Simple real-time price data for quick checks

2. Technical Analysis Operations​

indicator: 20+ technical indicators including SMA, EMA, RSI, MACD, Bollinger Bands

3. Discovery Operations​

symbol_search: Find symbols by name, exchange, or country exchanges: List all available exchanges and markets

4. Fundamental Operations​

profile: Company overview and basic information fundamentals: Detailed financial statements and metrics dividends, splits, earnings: Historical corporate actions logo: Company logo URLs for branding

5. Financial Statements​

income_statement: Revenue, expenses, and profitability data balance_sheet: Assets, liabilities, and equity information cash_flow: Operating, investing, and financing cash flows

6. ETFs & Mutual Funds​

etfs_list, etfs_world: ETF discovery and global listings mutual_funds_list, mutual_funds_world: Mutual fund data and analysis

7. Calendar & Events​

dividends_calendar, earnings_calendar: Upcoming corporate events ipo_calendar: New public offerings and listings

8. Analyst & Market Data​

earnings_estimate, revenue_estimate: Analyst forecasts recommendations, price_target: Analyst opinions and targets analyst_ratings: Comprehensive analyst coverage

Getting Started - Interface Configuration​

Basic Setup​

1. Select Worker Type: Choose "twelve_data" from the worker selection dropdown
2. Choose Operation: Select your desired operation from the operation dropdown
3. API Key (Optional): Enter your personal Twelve Data API key, or leave blank to use the shared key
4. Configure Parameters: Fill in operation-specific parameters based on your needs

Common Parameters​

• api_key: Your Twelve Data API key (optional if shared key is configured)
• operation: The specific operation you want to perform
• symbol: Stock ticker, forex pair, or crypto symbol (required for most operations)

Operation-Specific Parameters​

Time Series Configuration:

• interval: Data interval (1min, 5min, 15min, 30min, 45min, 1h, 2h, 4h, 1day, 1week, 1month)
• outputsize: Number of data points to return (max 5000)
• start_date/end_date: Date range for historical data
• timezone: Target timezone for timestamps

Technical Indicators:

• indicator: Indicator type (sma, ema, rsi, macd, bbands, etc.)
• time_period: Lookback period for calculation
• series_type: Price series to use (open, high, low, close)

Search & Discovery:

• symbol: Search query for symbol lookup
• exchange: Filter by specific exchange
• country: Filter by country

Advanced Configuration Options​

Rate Limiting Awareness​

When using the shared API key, the system enforces per-user rate limits (5 calls per minute). Make sure your userId is properly configured in the context for accurate limiting.

Data Formatting​

All timestamp data is automatically formatted in ISO format for consistency. You can customize this behavior through additional parameters if needed.

Multi-Symbol Support​

Operations like time_series support comma-separated symbol lists for batch requests, allowing you to fetch data for multiple assets in a single call.

Practical Implementation Examples​

Intraday Trading Strategy​

Create a complete intraday analysis workflow:

1. Fetch Real-time Quotes using the quote operation
2. Calculate Technical Indicators using the indicator operation
3. Monitor Multiple Symbols with batch time_series requests
4. Set Alerts based on price levels and indicator signals

Complete Workflow Example:

• workers[0]: Twelve Data Connector
  • type: twelve_data
  • operation: time_series
  • symbol: AAPL,MSFT,GOOGL
  • interval: 5min
  • outputsize: 100
• workers[1]: Technical Analysis
  • type: technical_analysis
  • indicators: rsi,macd
  • data_source: workers[0].result

Fundamental Analysis System​

Build comprehensive company analysis:

• workers[0]: Company Profile
  • type: twelve_data
  • operation: profile
  • symbol: TSLA
• workers[1]: Financial Statements
  • type: twelve_data
  • operation: income_statement
  • symbol: TSLA
  • period: annual
• workers[2]: Analyst Estimates
  • type: twelve_data
  • operation: earnings_estimate
  • symbol: TSLA

ETF Portfolio Analysis​

Analyze ETF performance and holdings:

• workers[0]: ETF Discovery
  • type: twelve_data
  • operation: etfs_world
  • country: US
• workers[1]: ETF Performance
  • type: twelve_data
  • operation: etfs_world_performance
  • currency: USD

Operations Comparison Table​

Best Practices and Tips​

API Key Management​

• Use personal API keys for higher rate limits and dedicated quotas
• The shared key enforces per-user limits (5/min) to ensure fair usage
• Monitor your API usage through the Twelve Data dashboard

Data Optimization​

• Use appropriate intervals for your analysis timeframe
• Limit outputsize to reduce response times and API costs
• Cache frequently accessed data to minimize API calls

Error Handling​

• Check for API key validity before complex workflows
• Handle rate limit errors gracefully with retry logic
• Validate symbol existence before requesting detailed data

Performance Considerations​

• Batch requests for multiple symbols when possible
• Use historical data endpoints for backtesting
• Implement caching layers for real-time applications

Integration with Other Workers​

Trading Strategy Integration​

Combine with technical analysis workers:

• Support & Resistance Calculator: Use price data for level identification
• Pattern Recognition: Feed historical data for pattern detection
• Risk Management: Incorporate volatility data from indicators

Portfolio Management​

Build comprehensive portfolios:

• Asset Allocation: Use ETF and mutual fund data
• Performance Tracking: Monitor returns with price data
• Rebalancing: Trigger based on fundamental changes

Alert Systems​

Create intelligent notifications:

• Price Alerts: Monitor specific levels with real-time data
• Technical Signals: Generate alerts from indicator crossovers
• Event Notifications: Track earnings and dividend calendars

Conclusion​

The Twelve Data Market Data Connector represents a comprehensive solution for financial data access, providing everything from basic price information to advanced fundamental analysis in a single, easy-to-use interface. Whether you're a retail trader, institutional investor, or financial application developer, this connector offers the flexibility and reliability you need to build sophisticated financial workflows.

With support for global markets, multiple asset classes, and extensive historical data, the Twelve Data connector eliminates data silos and simplifies the development of financial applications. Start exploring the power of comprehensive market data today and unlock new possibilities for your trading and investment strategies.

For detailed guides on specific operations, check out our dedicated articles covering each major operation category with step-by-step interface instructions and practical examples.

In the world of financial analysis and economic research, access to reliable economic data is crucial. Introducing the FRED Economic Data Connector - a powerful new addition to the ApudFlow platform that provides seamless access to the Federal Reserve Economic Data (FRED) database, the premier source for US economic time series data.

What is FRED Economic Data Connector?​

The FRED Economic Data Connector leverages the comprehensive FRED API maintained by the Federal Reserve Bank of St. Louis. FRED contains over 816,000 economic time series from 108 sources, making it the most comprehensive freely available database of US economic data.

Unlike traditional data providers that require expensive subscriptions, FRED provides free access to critical economic indicators, making sophisticated economic analysis accessible to everyone.

Key Features​

• Comprehensive Data Access: Connect to over 816,000 economic time series
• Smart Autocomplete: Intelligent series ID suggestions as you type
• Three Core Operations: Series observations, metadata, and releases
• Flexible Data Retrieval: Custom date ranges, frequencies, and transformations
• Federal Reserve Quality: Official data from the Federal Reserve Bank of St. Louis
• Free API Access: No subscription costs for basic usage
• Real-time Updates: Access to the latest economic data releases

Core Operations​

1. Series Observations - Get Economic Data​

Operation: series_observations Purpose: Retrieve actual economic data points for any series

Key Parameters:

• series_id: The FRED series identifier (with autocomplete)
• start_date: Start date (optional, format: YYYY-MM-DD)
• end_date: End date (optional, format: YYYY-MM-DD)
• frequency: Data frequency - d/daily, w/weekly, m/monthly, q/quarterly, a/annual
• units: Data transformation - lin/levels, chg/change, pch/percent change

Example - GDP Data:

{
  "series_id": "GDPC1",
  "start_date": "2020-01-01",
  "end_date": "2024-12-31",
  "frequency": "q",
  "units": "lin"
}

Output:

{
  "series_id": "GDPC1",
  "count": 20,
  "observations": [
    {"date": "2024-07-01", "value": "22679.3"},
    {"date": "2024-04-01", "value": "22605.4"},
    {"date": "2024-01-01", "value": "22496.7"}
  ]
}

2. Series Information - Metadata & Details​

Operation: series_info Purpose: Get detailed information about a data series

Key Parameters:

• series_id: The FRED series identifier (with autocomplete)

Example - Get GDP Metadata:

{
  "series_id": "GDPC1"
}

Output:

{
  "series_id": "GDPC1",
  "title": "Real Gross Domestic Product",
  "units": "Billions of Chained 2012 Dollars",
  "frequency": "Quarterly",
  "seasonal_adjustment": "Seasonally Adjusted Annual Rate",
  "last_updated": "2024-10-30 07:53:02-05",
  "observation_start": "1947-01-01",
  "observation_end": "2024-07-01"
}

3. Economic Releases - Latest Data Updates​

Operation: releases Purpose: Get information about recent economic data releases

Key Parameters:

• limit: Number of releases to return (default: 25, max: 1000)

Example - Recent Releases:

{
  "limit": 10
}

Output:

{
  "count": 10,
  "releases": [
    {
      "id": "53",
      "name": "Gross Domestic Product",
      "press_release": true,
      "link": "https://www.federalreserve.gov/releases/gdp/",
      "notes": "The Gross Domestic Product (GDP) is the market value of goods and services produced by labor and property in the United States."
    }
  ]
}

Smart Autocomplete for Series Discovery​

The FRED connector features intelligent autocomplete that helps you discover series IDs as you type. Simply start typing keywords like "GDP", "unemployment", "inflation", or "treasury" and get instant suggestions.

Popular Series Examples:

• GDPC1 - Real Gross Domestic Product
• UNRATE - Unemployment Rate
• CPIAUCSL - Consumer Price Index
• DGS10 - 10-Year Treasury Rate
• MORTGAGE30US - 30-Year Mortgage Rate
• DEXUSEU - US/Euro Exchange Rate
• FEDFUNDS - Federal Funds Rate
• HOUST - Housing Starts
• INDPRO - Industrial Production Index

Data Transformation Options​

FRED connector supports various data transformations:

• Units: lin (levels), chg (change), pch (percent change)
• Frequency: d (daily), w (weekly), m (monthly), q (quarterly), a (annual)
• Date Ranges: Custom start/end dates for historical analysis

Practical Implementation Examples​

Automated Economic Dashboard​

Create a workflow that:

1. Fetches latest GDP data using series_observations
2. Retrieves unemployment rates with series_info for metadata
3. Monitors inflation metrics with custom date ranges
4. Generates economic health score
5. Sends alerts on significant changes

Trading Strategy Integration​

Build algorithmic trading strategies based on:

• Federal Funds Rate changes (FEDFUNDS)
• Employment data releases (PAYEMS)
• GDP growth indicators (GDPC1)
• Inflation metrics (CPIAUCSL)

Risk Management System​

Monitor economic indicators for:

• Recession signals using GDP data
• Inflation pressure with CPI series
• Labor market health via unemployment data
• Currency stability with exchange rates

Getting Started​

Ready to harness the power of economic data?

1. Access FRED Connector in your ApudFlow workspace
2. Start typing series IDs - use autocomplete to discover economic indicators
3. Try popular series like GDPC1 (GDP), UNRATE (unemployment), or CPIAUCSL (inflation)
4. Experiment with parameters - add date ranges, change frequencies, apply transformations
5. Get series metadata using series_info to understand your data
6. Monitor releases with the releases operation for latest updates
7. Build automated workflows for economic analysis and alerts

Popular Economic Series Quick Reference​

API Limits and Best Practices​

• Without API Key: 2,000 requests per hour
• With API Key: 120,000 requests per hour (optional)
• Data Freshness: Most series update within 1-2 business days
• Caching: Consider caching frequently used data
• Rate Limiting: Built-in delays prevent API limit violations

Future Enhancements​

We're continuously expanding FRED connector capabilities with:

• Real-time data streaming for live economic indicators
• Bulk data operations for large historical datasets
• Advanced analytics integration with economic models
• Multi-series correlation analysis tools
• Automated report generation from economic data

Important Disclaimer: FRED Economic Data Connector provides access to economic and financial data for informational purposes. The data and analysis generated by this tool should not be considered as professional financial, investment, or trading advice. All investment decisions should be made based on your own research, risk tolerance, and consultation with qualified financial professionals. Economic data may be revised historically. Use this tool at your own risk and responsibility.

Federal Reserve Economic Data (FRED) is the premier source for US economic time series data. Whether you're building economic models, monitoring market conditions, or conducting financial research, FRED connector provides the economic intelligence you need to make informed decisions.

Questions about implementing FRED connector? Our support team is here to help you integrate economic data into your workflows! 📊💹📈

A single Monetization API now governs workflows, widgets, workers, and dashboards.

Benefits:

• Consistent pricing modes (monthly / cycle where applicable).
• Centralized validation for price changes.
• Simplified frontend forms.

Docs: System Overview → Monetization & Credits.