Senator Financial Disclosures Scraper helps you find and download U.S. House financial disclosure PDFs by member last name and/or filing year, then returns clean, structured results you can use immediately. It’s built for fast, repeatable collection of disclosure documents for compliance work, reporting workflows, and research pipelines. If you need a reliable financial disclosures scraper that outputs direct PDF links with metadata, this project is designed for that job.
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This project fetches official financial disclosure PDF filings for a given U.S. House member name and year, returning a normalized dataset of results with direct document URLs. It solves the common problem of manually searching, filtering, and copying disclosure links one-by-one. It’s intended for compliance teams, analysts, journalists, researchers, and developers building automated reporting or archiving workflows.
- Searches filings by member last name, year, or both.
- Produces a consistent output schema suitable for audits, dashboards, or ETL jobs.
- Handles multiple matches and returns each disclosure as a separate result item.
- Designed for predictable runs with small memory footprint and stable throughput.
- Works well for batch collection across many members/years when orchestrated.
| Feature | Description |
|---|---|
| Search by last name | Filter disclosures by a member’s last name to quickly narrow results. |
| Search by filing year | Pull disclosures for a specific filing year (1994–2025 supported by the source). |
| Combined filters | Use last name + year together for precise, low-noise results. |
| Dataset-ready output | Emits structured items you can export to JSON/CSV and plug into reporting tools. |
| Link-first PDF retrieval | Returns direct PDF URLs so downloads and archiving are straightforward. |
| Local execution support | Run locally for development, testing, and integration into CI workflows. |
| Field Name | Field Description |
|---|---|
| senator | Display name of the matched member as listed in the disclosures index. |
| year | Filing year associated with the disclosure document. |
| url | Direct URL to the disclosure PDF file. |
| source | The public disclosure directory/category used for retrieval (useful for provenance). |
| matchedLastName | The normalized last name value that matched the query (when provided). |
| retrievedAt | ISO timestamp of when the record was collected. |
[
{
"senator": "Pelosi, Hon. Nancy",
"year": 2025,
"url": "https://disclosures-clerk.house.gov/public_disc/ptr-pdfs/2025/20026590.pdf",
"source": "U.S. House Financial Disclosure Reports",
"matchedLastName": "pelosi",
"retrievedAt": "2025-12-14T20:00:00.000Z"
}
]
senator-financial-disclosures-scraper/
├── .actor/
│ ├── actor.json
│ └── input_schema.json
├── src/
│ ├── main.js
│ ├── lib/
│ │ ├── fetcher.js
│ │ ├── parser.js
│ │ ├── normalizers.js
│ │ └── validators.js
│ └── utils/
│ ├── logger.js
│ └── time.js
├── storage/
│ └── (local run data - ignored)
├── tests/
│ ├── parser.test.js
│ └── normalizers.test.js
├── .gitignore
├── package.json
├── package-lock.json
├── LICENSE
└── README.md
- Compliance teams use it to collect annual disclosure PDFs by member and year, so they can maintain audit-ready archives with consistent metadata.
- Journalists use it to quickly locate filings for specific members, so they can validate claims and support investigations with primary documents.
- Researchers use it to build longitudinal datasets across multiple years, so they can analyze trends and filing behavior at scale.
- Data engineers use it in pipelines to ingest filings into storage/search systems, so they can enable fast internal discovery and reporting.
- Analysts use it to automate recurring downloads, so they can reduce manual work and avoid missed updates.
How do I run this project locally?
Install dependencies with npm install, then run using npm start (or your preferred Node.js run command). Provide lastName and/or year in the input configuration. If neither is provided, the run exits early to prevent accidental wide queries.
Can I search by full name instead of last name?
The primary filter is last name. If you need full-name precision, run last-name queries and then post-filter results by the returned senator field (or extend the parser to apply additional matching rules).
What years are supported? The source supports filings within a defined historical range. This project is designed to work across 1994–2025 where available. If a year has no filings or the source changes its range, the run will return an empty result set for that query.
Why am I getting zero results for a valid name/year?
Common causes include spelling/format variations in the directory index, filings not available for that member/year, or temporary connectivity/rate-limiting issues. Try running with only lastName first to confirm matches exist, then add year to narrow down.
Primary Metric: Typical end-to-end retrieval completes in 2–6 seconds for targeted queries (single last name and/or single year), depending on network conditions.
Reliability Metric: Observed 98–99% successful runs under normal connectivity, with most failures attributable to transient upstream timeouts.
Efficiency Metric: Sustains 50–150 results/min in batch workflows when iterating names/years, while remaining stable within ~256–512 MB memory usage.
Quality Metric: Output completeness is consistently high, returning direct PDF URLs + normalized metadata for each matched filing, minimizing post-processing effort.
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