Welcome to Accern Python!

A python library to consume Accern’s V4 REST API for Titan streaming/historical data.

Overview

Accern is a fast-growing NYC startup that is disrupting the way quantitative hedge funds can gain a competitive advantage using news and social media data. It currently has the world’s largest financial news coverage, covering over 1 billion public news websites, blogs, financial documents, and social media websites. Furthermore, Accern derives proprietary analytics from each news story to help quantitative hedge funds make accurate trading decisions.

Accern consolidates multiple news data feeds into one to help drastically reduce costs of both small and large hedge funds. With Accern proprietary data filters, we are able to deliver relevant articles to clients with a 99 percent accuracy rate. Accern’s delivery mechanism is a RESTful API where it delivers derived analytics from news articles, including the original article URLs so quantitative hedge funds can derive their own analytics in-house from the relevant articles.

The Accern library for Python helps users get fast, flexible data structures from Accern’s V4 Titan streaming/historical data.

• Installation
  • Install from PyPI
• Getting started
• API
  • Schema Class/ Object
    • Get Fields
    • Get field options
    • Build your schema
    • Validate schema
    • Select and add alias
  • REST APIs
    • Create API Instance
    • Authenticate REST API Client
    • Request Data
  • Streaming API Client
    • Stream Listener
    • Authenticate Stream Client
    • Filter and select with schema
  • Historical Data Request
    • Create Historical Instance
    • Set up a job
    • Check your job history
    • Select and Aggregations
• Examples
  • REST: Request with filters
  • REST: Get one week data for restaurants entities
  • Streaming: Save to csv
  • Streaming: Create output csv structure and seperate by hour
  • Streaming: Save to mongo
  • Historical Data: Create one historical job
  • Historical Data: Check the status of a historical job
  • Historical Data: Read the csv from the job’s download link
• Appendix
  • Field Filter Cookbook
  • Field Aggregate Function
  • Field Value List
    • entity_sector
    • entity_industry
    • event
    • event_group
    • story_type