Example Use Cases#

Edgar-SEC powers SEC filing dashboards, async data pipelines, compliance monitoring, and quantitative research using the official EDGAR® API.

Explore how to use Edgar-SEC in production systems, research environments, or data-driven applications:

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Filing Dashboard Development#

See Example

Combine edgar-sec with:

  • Pandas, Polars, or DuckDB for ETL workflows,

  • Plotly, Altair, or Matplotlib for visualizations,

  • Dash, Streamlit, or Gradio for deployment.

Applications include:

  • Visualizing 10-K/10-Q form counts over time,

  • Monitoring submission patterns by sector,

  • Flagging outlier disclosures for review.

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Asynchronous Ingestion Pipelines#

See Example

Use edgar = ed.EdgarAPI().Async to run concurrent submission or concept fetches.

Ideal for:

  • Daily batch jobs that refresh filings across hundreds of tickers,

  • Compliance systems for near real-time EDGAR intake,

  • Automating archival of fundamental metrics (XBRL facts).

Built-in asyncio, retry logic, and throttling ensure reliability at scale.

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CIK and Metadata Indexing#

See Example

Use EdgarHelpers.get_cik(…) to build searchable lookup tools or name→CIK mappings.

  • Index all S&P 500 company CIKs,

  • Normalize common entity name aliases,

  • Build autocomplete tools for research dashboards.

This avoids scraping or manual CSV management.

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Fundamental Disclosure Analysis#

See Example

Retrieve and structure XBRL data with:

  • get_company_facts()

  • get_company_concepts()

  • get_frames()

Research workflows include:

  • Comparing debt-to-equity ratios across firms,

  • Tracking reported vs restated earnings over time,

  • Building real-time disclosure-based models.

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