eCFR US Federal Regulations Scraper
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from $32.40 / 1,000 results
eCFR US Federal Regulations Scraper
Scrape the US Code of Federal Regulations from eCFR public API. Get title structure, chapters, parts, sections, amendment history, full regulation text. No API key required.
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from $32.40 / 1,000 results
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⚖️ eCFR US Federal Regulations Scraper
🚀 Search and export the US Code of Federal Regulations in seconds. Run full-text queries across every title, chapter, part, and section. No API key, no registration, no manual CSV wrangling.
🕒 Last updated: 2026-05-12 · 📊 Up to 28 fields per record · 🇺🇸 50 CFR titles · 📚 Full-text search across all parts · ♻️ Live per run
The eCFR US Federal Regulations Scraper pulls structured records from the Electronic Code of Federal Regulations, the official up-to-date version of US federal regulations published by the National Archives. The Actor supports two modes: full-text search across every regulation (returning matching sections with hierarchy, excerpts, scores, and effective dates) and titles browse (returning the 50 CFR titles with their latest amendment metadata).
eCFR is updated continuously as agencies publish final rules in the Federal Register, with currency stamps showing how recent the published text is for each title. Whether you are tracking regulatory references in privacy law, federal acquisition rules, food and drug regulations, or environmental policy, this Actor returns the official text in clean JSON without browser automation or login workflows.
| 🎯 Target Audience | 💡 Primary Use Cases |
|---|---|
| Compliance and legal teams, policy analysts, RegTech vendors, government affairs, academics, journalists, GovTech vendors, ML researchers | Regulatory monitoring, compliance crosswalks, citation extraction, RegTech datasets, policy research, training data for legal AI |
📋 What the eCFR US Federal Regulations Scraper does
Two modes in a single Actor:
- 🔍 Search mode. Full-text search across every CFR title with hit scoring, hierarchy, and excerpts.
- 📚 Titles mode. Browse the 50 CFR titles with their latest amendment dates and currency stamps.
- 🪜 Full hierarchy. Every search hit includes title, subtitle, chapter, subchapter, part, subpart, subject group, and section.
- 📅 Effective dates.
startsOnandendsOnper hit, plus title-levellatestAmendedOnandupToDateAsOf. - 🏷️ Change types. Each hit lists the change types that produced it (
effective,initial,amended, etc.).
In search mode, each record includes the type (section, part, appendix), heading hierarchy, structured URL, hit excerpt, score, structure index, reserved and removed flags, and effective dates. In titles mode, each record includes the title number, name, latest amendment date, latest issue date, currency stamp, and reserved flag.
💡 Why it matters: the CFR runs to over 200,000 pages. Searching for regulatory references manually is slow, and bulk PDF dumps go stale. eCFR is the daily authoritative version, but its API output requires custom parsing. This Actor flattens search results and title metadata into query-ready tables on every run.
🎬 Full Demo
🚧 Coming soon: a 3-minute walkthrough showing how to go from sign-up to a downloaded dataset.
⚙️ Input
| Input | Type | Default | Behavior |
|---|---|---|---|
mode | string | "search" | Either search (full-text) or titles (browse the 50 CFR titles). |
query | string | "privacy" | Free-text query. Required in search mode, ignored in titles mode. |
maxItems | integer | 10 | Records to return. Free plan caps at 10, paid plan at 1,000,000. |
Example: 100 sections mentioning privacy.
{"mode": "search","query": "privacy","maxItems": 100}
Example: browse all CFR titles.
{"mode": "titles","maxItems": 50}
⚠️ Good to Know: the search endpoint returns hierarchy headings as HTML, which the Actor strips to plain text. The
excerptfield highlights matched passages around the query terms. Search hits include sections, parts, appendices, and subtitles, distinguished by thetypefield.
📊 Output
Each search hit contains 28 fields, each title record contains 9 fields. Download the dataset as CSV, Excel, JSON, or XML.
🧾 Schema (search mode)
| Field | Type | Example |
|---|---|---|
🏷️ mode | string | "search" |
🗂️ type | string | "Section" |
📚 title | string | null | "Domestic Security" |
📚 subtitle | string | null | "" |
📚 chapter | string | null | "Privacy and Civil Liberties Oversight Board" |
📚 subchapter | string | null | "" |
📚 part | string | null | "Implementation of the Privacy Act of 1974" |
📚 subpart | string | null | "" |
📚 subjectGroup | string | null | "" |
📚 section | string | null | "Privacy Act requests." |
📚 appendix | string | null | "" |
🔗 url | string | "https://www.ecfr.gov/current/title-6/chapter-X/part-1002/section-1002.3" |
🔢 titleNum | string | null | "6" |
🔢 chapterNum | string | null | "X" |
🔢 partNum | string | null | "1002" |
🔢 subpartNum | string | null | null |
🔢 sectionNum | string | null | "1002.3" |
📰 sectionHeading | string | null | "Privacy Act requests." |
📰 partHeading | string | null | "Implementation of the Privacy Act of 1974" |
💬 excerpt | string | "request to the Privacy Act Officer..." |
📅 startsOn | ISO 8601 | null | "2016-12-22" |
📅 endsOn | ISO 8601 | null | null |
💯 score | number | null | 33.469017 |
🔢 structureIndex | number | null | 10415 |
🔒 reserved | boolean | null | false |
🗑️ removed | boolean | null | false |
🏷️ changeTypes | string[] | ["effective", "initial"] |
🕒 scrapedAt | ISO 8601 | "2026-05-12T16:30:12.756Z" |
🧾 Schema (titles mode)
| Field | Type | Example |
|---|---|---|
🏷️ mode | string | "titles" |
🔢 number | number | 1 |
📰 name | string | "General Provisions" |
🔗 url | string | "https://www.ecfr.gov/current/title-1" |
📅 latestAmendedOn | ISO 8601 | null | "2026-04-30" |
📅 latestIssueDate | ISO 8601 | null | "2026-04-30" |
📅 upToDateAsOf | ISO 8601 | null | "2026-05-08" |
🔒 reserved | boolean | false |
🕒 scrapedAt | ISO 8601 | "2026-05-12T16:30:12.756Z" |
📦 Sample records
✨ Why choose this Actor
| Capability | |
|---|---|
| 🇺🇸 | Official eCFR feed. Pulls from the National Archives' Electronic Code of Federal Regulations, the up-to-date authoritative version. |
| 🪜 | Full hierarchy. Title, subtitle, chapter, subchapter, part, subpart, subject group, and section per hit. |
| 📚 | Two modes. Search returns matching sections with excerpts and scores. Titles mode lists every CFR title with amendment metadata. |
| 📅 | Effective dates. startsOn, endsOn, and title-level currency stamps tell you exactly how fresh each rule is. |
| ⚡ | Fast. Up to 100 search hits per page, 10,000 records in around fifteen minutes. |
| 🔁 | Always fresh. Every run pulls live eCFR data so newly published rules appear within hours. |
| 🚫 | No authentication. Works with public regulatory data. No login or API key needed. |
📊 The CFR is the codified body of US federal regulations, organised by subject across 50 titles. eCFR is the daily authoritative version.
📈 How it compares to alternatives
| Approach | Cost | Coverage | Refresh | Filters | Setup |
|---|---|---|---|---|---|
| ⭐ eCFR US Federal Regulations Scraper (this Actor) | $5 free credit, then pay-per-use | All 50 CFR titles | Live per run | full-text query | ⚡ 2 min |
| Official eCFR search UI | Free | Same data, manual | Live | UI filters | 🐢 Manual export per query |
| Government Publishing Office bulk dumps | Free | Annual snapshot | Yearly | None | 🕒 Multi-day ETL |
| Paid regulatory intelligence platforms | $1,000+/month | Multi-jurisdiction | Daily | Many | ⏳ Vendor onboarding |
Pick this Actor when you want the live CFR in clean JSON, with server-side full-text search and zero pipeline maintenance.
🚀 How to use
- 📝 Sign up. Create a free account with $5 credit (takes 2 minutes).
- 🌐 Open the Actor. Go to the eCFR US Federal Regulations Scraper page on the Apify Store.
- 🎯 Set input. Pick
searchortitlesmode, enter a query if searching, and setmaxItems. - 🚀 Run it. Click Start and let the Actor collect your data.
- 📥 Download. Grab your results in the Dataset tab as CSV, Excel, JSON, or XML.
⏱️ Total time from signup to downloaded dataset: 3-5 minutes. No coding required.
💼 Business use cases
🌟 Beyond business use cases
Data like this powers more than commercial workflows. The same structured records support research, education, civic projects, and personal initiatives.
🔌 Automating eCFR US Federal Regulations Scraper
Control the scraper programmatically for scheduled runs and pipeline integrations:
- 🟢 Node.js. Install the
apify-clientNPM package. - 🐍 Python. Use the
apify-clientPyPI package. - 📚 See the Apify API documentation for full details.
The Apify Schedules feature lets you trigger this Actor on any cron interval. Hourly, daily, or weekly refreshes keep downstream databases in sync automatically.
❓ Frequently Asked Questions
🧩 How does it work?
Pick a mode, optionally provide a search query, click Start, and the Actor calls the official eCFR JSON API, flattens hierarchy headings, strips HTML, and emits clean JSON. No browser automation, no captchas, no setup.
📏 How accurate is the data?
Records come straight from the official National Archives eCFR, which is the daily authoritative version of US federal regulations. Effective dates are sourced from the Federal Register and reflected in startsOn, endsOn, and upToDateAsOf per record.
🔁 How often is the dataset refreshed?
eCFR is updated continuously as agencies publish final rules in the Federal Register. Every run of this Actor fetches the live API, so your dataset reflects the same currency stamps the official site shows.
📚 Can I get the full regulation text per section?
Search mode returns excerpts around matched terms, not the full body text. For full section text, follow the url field per record to the official eCFR rendering. A bulk full-text companion is on the roadmap.
⏰ Can I schedule regular runs?
Yes. Use Apify Schedules to run this Actor on any cron interval (hourly, daily, weekly) and keep a downstream database in sync.
⚖️ Is this data legal to use?
eCFR is a US government publication and is in the public domain. It is intended for unrestricted public use, including for commercial purposes.
💼 Can I use this data commercially?
Yes. US federal regulations are in the public domain. Many RegTech, legal AI, and compliance products are built on this same feed.
💳 Do I need a paid Apify plan to use this Actor?
No. The free Apify plan is enough for testing and small runs (10 records per run). A paid plan lifts the limit and gives you access to scheduling, higher concurrency, and larger datasets.
🔁 What happens if a run fails or gets interrupted?
Apify automatically retries transient errors. If a run still fails, you can inspect the log in the Runs tab, fix the input, and re-run. Partial datasets from failed runs are preserved so you never lose progress.
🔢 What is structureIndex?
A stable position pointer within the CFR structure that the eCFR API uses to order hits. It is useful for joining results against the structured CFR XML and tracking position changes over time.
🆘 What if I need help?
Our support team is here to help. Contact us through the Apify platform or use the Tally form linked below.
🔌 Integrate with any app
eCFR US Federal Regulations Scraper connects to any cloud service via Apify integrations:
- Make - Automate multi-step workflows
- Zapier - Connect with 5,000+ apps
- Slack - Get run notifications in your channels
- Airbyte - Pipe regulatory data into your warehouse
- GitHub - Trigger runs from commits and releases
- Google Drive - Export datasets straight to Sheets
You can also use webhooks to trigger downstream actions when a run finishes. Push fresh regulation data into your compliance system, or alert your legal team in Slack when target sections change.
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💡 Pro Tip: browse the complete ParseForge collection for more reference-data scrapers.
🆘 Need Help? Open our contact form to request a new scraper, propose a custom data project, or report an issue.
⚠️ Disclaimer: this Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by the National Archives, the Government Publishing Office, or any US government body. All trademarks mentioned are the property of their respective owners. Only publicly available public-domain regulatory data is collected.