finpull-core 1.1.0

Financial data scraper core API - lightweight programmatic access

FinPull Core - Financial Data Scraper API

FinPull Core is a lightweight financial data scraping library providing programmatic access to comprehensive financial metrics. This package contains only the essential API functionality, making it suitable for web applications, microservices, and minimal deployments.

Installation

pip install finpull-core

Quick Start

from finpull_core import FinancialDataAPI

# Initialize the API
api = FinancialDataAPI()

# Add a ticker for tracking
result = api.add_ticker("AAPL")
print(result)
# {'success': True, 'message': 'Added AAPL', 'ticker': 'AAPL'}

# Retrieve financial data
data = api.get_data("AAPL")
if data['success']:
    stock_data = data['data']
    print(f"Company: {stock_data['company_name']}")
    print(f"Price: ${stock_data['price']}")
    print(f"P/E Ratio: {stock_data['pe_ratio']}")

# Batch operations
tickers = ["AAPL", "GOOGL", "MSFT", "TSLA"]
results = api.batch_add_tickers(tickers)

# Export data
export_result = api.export_data("json")

Performance

Benchmarked on typical hardware with 10 test runs:

Metric	Value	Details
Package Size	21.9 KB (wheel)	Compressed distribution file
Installed Size	134 KB	Uncompressed on disk
Import Time	0.0002s (cached)	Cold import: 0.9s, cached: 0.0002s
Dependencies	3 packages	requests, beautifulsoup4, yfinance
API Response	100-500ms	Per ticker, varies by data source

Performance Characteristics

• First Import: ~0.9 seconds (includes dependency loading)
• Subsequent Imports: ~0.0002 seconds (module cache)
• Standard Deviation: 0.3s (due to first-time loading)
• Consistency: Very stable after initial load

Optimization Features

• Local Caching: Automatic data caching reduces API calls
• Rate Limiting: Built-in throttling prevents API blocks (1 req/sec default)
• Lazy Loading: Components load only when needed
• Efficient Storage: JSON-based local storage with minimal overhead
• Web Compatible: Works in browser environments via Pyodide/WASM
• Batch Operations: Process multiple tickers efficiently

Configuration

Environment Variables

# Custom storage location
export FINPULL_STORAGE_FILE="/path/to/custom/storage.json"

# Rate limiting (seconds between requests)
export FINPULL_RATE_LIMIT="2"

Storage

Data is stored locally in JSON format:

• Linux/macOS: ~/.finpull/data.json
• Windows: %USERPROFILE%\.finpull\data.json

Data Coverage

FinPull Core provides 27 financial metrics per ticker including price, P/E ratio, market cap, earnings data, profitability ratios, and growth metrics. Data is sourced from Finviz and Yahoo Finance with automatic fallback for high availability.

Dependencies

Required Packages

• requests (≥2.25.1): HTTP client for data fetching
• beautifulsoup4 (≥4.9.3): HTML parsing for web scraping
• yfinance (≥0.1.63): Yahoo Finance API integration

Optional Dependencies

• psutil: For memory usage monitoring (development/testing)
• openpyxl: Excel export (available in full finpull package)

Documentation

• API Reference - Complete API documentation with examples
• Data Format - JSON schema and field descriptions
• Error Handling - Error codes and exception handling

Web Integration

Works in browser environments via Pyodide and Node.js via subprocess calls. See main repository README for integration examples.

Examples

Basic Usage

from finpull_core import FinancialDataAPI

api = FinancialDataAPI()

# Add and retrieve data
api.add_ticker("AAPL")
data = api.get_data("AAPL")
print(f"Price: ${data['data']['price']}")

Batch Operations

# Add multiple tickers
tickers = ["AAPL", "GOOGL", "MSFT", "TSLA"]
results = api.batch_add_tickers(tickers)
print(f"Added {results['summary']['added_count']} tickers")

# Get all data
all_data = api.get_data()
for stock in all_data['data']:
    print(f"{stock['ticker']}: ${stock['price']} (P/E: {stock['pe_ratio']})")

Data Export

# Export to different formats
json_result = api.export_data("json", "portfolio.json")
csv_result = api.export_data("csv", "portfolio.csv")
print(f"Exported {json_result['record_count']} records")

Error Handling

try:
    result = api.add_ticker("INVALID_TICKER")
    if not result['success']:
        print(f"Error: {result['error']}")
except Exception as e:
    print(f"Exception: {e}")

Package Options

For complete functionality including CLI and GUI, use the full package:

pip install finpull

Or switch from core to full package:

pip uninstall finpull-core
pip install finpull

Package Comparison

Feature	finpull-core	finpull
Size	21.9 KB	27.2 KB
API Access	✓	✓
CLI Interface	✗	✓
GUI Application	✗	✓
Excel Export	✗	✓
Web Compatible	✓	✓

All API calls are identical between packages - simply change the import statement when switching.

License

MIT License - see LICENSE file for details.

Links

• Full Package - Complete version with CLI/GUI
• Source Code - GitHub repository
• Issues - Bug reports and feature requests