HUD Fair Market Rents Scraper: 15 Data Fields per Record (2026)

Each record carries 15 fields covering studio through 4-bedroom Fair Market Rent benchmarks across US states, counties, and metro areas for fiscal years 2018 through 2026. A thousand results costs $5.00 on Apify's free plan for this Actor, giving you a baseline for rental costs. This Actor is for housing researchers, real estate analysts, and policy teams tracking Section 8 voucher standards. It is not for teams seeking live, real-time listing prices, private landlord contact details, or foreclosed home sales data, as these government reference records do not include such information.

Try it: open HUD Fair Market Rents Scraper on Apify, sign in on the free plan and run the prefilled example.

Can you try HUD Fair Market Rents Scraper before paying?

Yes. Apify's free plan includes $5.00 of prepaid usage every month and asks for no credit card. At $0.005 per result, that covers up to 1,000 results of HUD Fair Market Rents Scraper a month, before run-start charges and platform usage.

The example request further down caps maxItems at 20, so a first run returns at most 20 results and costs at most $0.10 in result charges. That is enough to see the real shape of the data before deciding anything.

HUD Fair Market Rents Scraper was last updated on 2026-06-06. It is one of 1,725 Actors CrawlerBros publishes on Apify, which together have 680,173 lifetime public runs and an average rating of 4.63 out of 5 across 416 reviews.

What does it cost to run HUD Fair Market Rents Scraper?

Each result costs $0.005 on Apify's free plan, which is $5.00 per 1,000 results. Starting a run is charged separately at $0.005 per GB of Actor memory. Apify also bills the platform usage each run consumes, at the rates of your Apify plan, on top of these charges.

The maxItems input control has the largest effect on your bill, as it directly determines how many results are written to your dataset. To discover whether this Actor meets your needs before committing to a larger expense, set maxItems to 20 for your first run. This will cap the result charges at $0.10.

How do you run HUD Fair Market Rents Scraper from the API?

The schema marks 1 of its 5 controls as required: mode. Every value in the payload below comes from the published schema's own prefills, which means you can paste it, swap the token, and get a real result.

Call the synchronous endpoint to start a run and receive dataset items in one request:

curl -X POST "https://api.apify.com/v2/acts/crawlerbros~hud-fair-market-rents-scraper/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"mode":"searchByState","state":"California","year":"2024","maxItems":20}'

The same run from Python, using the official client:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")

run_input = {
  "mode": "searchByState",
  "state": "California",
  "year": "2024",
  "maxItems": 20
}

run = client.actor("crawlerbros~hud-fair-market-rents-scraper").call(run_input=run_input)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

And from Node.js:

import { ApifyClient } from 'apify-client'

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' })

const input = {
  "mode": "searchByState",
  "state": "California",
  "year": "2024",
  "maxItems": 20
}

const run = await client.actor('crawlerbros~hud-fair-market-rents-scraper').call(input)
const { items } = await client.dataset(run.defaultDatasetId).listItems()
console.log(items)

That endpoint blocks until the run completes. Fine while you are testing a handful of records, risky once a run takes minutes: a dropped connection loses the response even though the run itself finished. Switch to an asynchronous start with polling or a webhook before you schedule anything.

Which HUD Fair Market Rents Scraper inputs matter, and which can you skip?

The input schema provides 5 controls, with mode being the only required setting. For most initial runs, you will primarily interact with mode, year, and a region filter such as state or metroAreaName. You can typically leave maxItems at its default or a low value for testing before increasing it for a full extraction.

• mode (string): What data to fetch. Default: "searchByState".
• state (string): US state to filter results (used in searchByState and byCounty modes). Default: "California".
• year (string): Fiscal year for FMR data. Default: "2024".
• metroAreaName (string): Filter results to metro areas whose name contains this keyword (case-insensitive). Example: 'Los Angeles', 'Dallas'. Used in searchByMetroArea mode.
• maxItems (integer): Maximum number of records to return. Default: 100.

Fixed-choice controls: mode accepts searchByState (all FMRs for a state), searchByMetroArea (FMRs for a specific metro area), allMetroAreas (browse all metro area FMR summaries), byCounty (county-level FMR data); state accepts 51 values (default California), including California, Alabama, Alaska, Arizona; year accepts 9 values (default 2024), including 2024 (FY 2024), 2026 (FY 2026), 2025 (FY 2025), 2023 (FY 2023).

What does HUD Fair Market Rents Scraper return?

Returned dataset items provide names, codes, and metro indicators for geographic areas, along with bedroom-specific dollar rates from efficiency_fmr to fourbr_fmr. These records do not contain individual property street addresses, active rental vacancy listings, or landlord contact details.

• area_name: HUD FMR area name (e.g., "San Francisco, CA MSA")
• county_name: County name
• state_name: Full state name
• state_code: Two-letter state abbreviation
• fips_code: FIPS geographic code
• area_code: HUD internal area code
• year: Fiscal year
• metro: true = metropolitan area, false = non-metro county
• efficiency_fmr: Studio/efficiency FMR in USD
• onebr_fmr: 1-bedroom FMR in USD
• twobr_fmr: 2-bedroom FMR in USD
• threebr_fmr: 3-bedroom FMR in USD
• fourbr_fmr: 4-bedroom FMR in USD
• fmr_type: Always "Fair Market Rent"
• scrapedAt: ISO 8601 timestamp

These are the documented fields. Optional ones can be empty on a given record, so measure how often each field your deliverable depends on is populated across a real sample before automating the handoff.

How do you build the workflow end to end?

Open HUD Fair Market Rents Scraper and work through these in order. Each step ends with something to check, so a bad configuration surfaces on a small run rather than a scheduled one.

1. Select mode as searchByState, searchByMetroArea, allMetroAreas, or byCounty to match your target scope.
2. Set year to the specific fiscal year you need, choosing between 2018 and 2026.
3. If using searchByState or byCounty, provide a value for state. If using searchByMetroArea, enter a keyword in metroAreaName.
4. For a quick initial check, set maxItems to 20 to limit output and verify that your input configuration returns the correct geographic areas.
5. Run the Actor and examine the dataset to confirm that area_name, state_code, and fips_code are present and appear correct.
6. Verify that the FMR fields efficiency_fmr, onebr_fmr, twobr_fmr, threebr_fmr, and fourbr_fmr contain valid numerical dollar values.
7. Once satisfied with the sample, increase maxItems to retrieve the complete dataset for your chosen mode and region, up to 2000 records per run.

How do you apply it? Three worked playbooks

These are HUD Fair Market Rents Scraper's own documented use cases, each worked through as an operating pattern rather than a description.

Use case 1: Housing affordability research

Outcome: Housing affordability research

Configure: Set mode to "searchByState", state to "California", year to "2026", and maxItems to 100.

Working method: Run the Actor for a selected state, then analyze the distribution of twobr_fmr across different counties and metro areas to understand rent variations.

Deliverable: A tabular dataset with FMRs for various unit sizes across a specified state.

Stop condition: The dataset for the chosen state has fewer records than expected, indicating incomplete data extraction.

Use case 2: Section 8 / Housing Choice Voucher analysis

Outcome: Section 8 / Housing Choice Voucher analysis

Configure: Set mode to "searchByMetroArea", metroAreaName to "Los Angeles", year to "2025", and maxItems to 50.

Working method: Extract FMRs for a specific metro area, focusing on efficiency_fmr through fourbr_fmr, to inform payment standards for housing vouchers.

Deliverable: A detailed breakdown of Fair Market Rents by unit size for a specific metro area.

Stop condition: The search results for the metro area name keyword include irrelevant or incorrect geographic locations.

Use case 3: Real estate market analysis

Outcome: Real estate market analysis

Configure: Set mode to "allMetroAreas", year to "2024", and maxItems to 500.

Working method: Collect FMR data for all metro areas, then sort and compare onebr_fmr and twobr_fmr values to benchmark rents across different markets.

Deliverable: A comparative dataset of 40th-percentile Fair Market Rents across multiple metropolitan areas.

Stop condition: The run completes but the resulting dataset contains a significantly lower number of records than the configured maxItems.

What breaks, and how do you design around it?

HUD Fair Market Rent data is updated on an annual fiscal-year schedule, not in real time. If you need to collect data for a large number of areas, consider splitting your extraction by state using the searchByState mode to manage run complexity effectively.

When should you not use HUD Fair Market Rents Scraper?

Do not use this Actor if your project requires active real estate sales inventory, foreclosed property bids, or current asking prices for specific residential addresses. For government-owned property listings, consider using HUD Homes Scraper to get full listing data including address, price, and images. Similarly, if you need current market rents derived from active rental listings rather than federal reference figures, a dedicated rental market aggregator would be a more suitable tool. This Actor provides static annual HUD Fair Market Rent benchmarks only.

What should you check before trusting the output?

• Confirm fmr_type is exactly "Fair Market Rent" for all output records.
• Flag any record where twobr_fmr is missing, null, or set to zero, as this suggests incomplete data.
• Validate that fips_code values correspond to standard 5-digit US geographic county codes.
• Check that the metro field is explicitly true for records from searchByMetroArea runs and false for those from byCounty runs.
• Verify that scrapedAt contains a valid ISO 8601 timestamp string for every record to ensure proper data capture time.

None of this proves a record is correct. It gives a scheduled HUD Fair Market Rents Scraper run defined points where it should stop instead of quietly passing bad data downstream.

Frequently asked questions

What is the cost per 1,000 results on Apify's free plan?

On Apify's free plan, each result costs $0.005, which amounts to $5.00 per 1,000 results. Apify's free plan provides $5.00 of monthly usage without requiring a credit card, covering up to 1,000 results from this Actor before run-start charges.

Which fiscal years of FMR data are available?

You can select FMR data for any fiscal year from 2018 through 2026 using the 'year' input control. HUD typically publishes new fiscal year data annually in the fall.

What bedroom configurations are included in the FMR data?

Each FMR record includes rent values for five bedroom configurations: efficiency_fmr for studio units, onebr_fmr for one-bedroom units, twobr_fmr for two-bedroom units, threebr_fmr for three-bedroom units, and fourbr_fmr for four-bedroom units.

Is an API key needed to use this FMR scraper?

No API key or registration is required. The Actor retrieves data from publicly available XLSX files on the official HUD User Portal, making the information freely accessible.

Are US territories covered by this Actor?

Yes, US territories are included in the data. The underlying HUD dataset provides coverage for Puerto Rico, the U.S. Virgin Islands, Guam, and American Samoa, in addition to all standard US states.

Where to go next

When you are ready to run it, open HUD Fair Market Rents Scraper on Apify; the free plan covers up to 1,000 results a month.

Start with the HUD Fair Market Rents Scraper Actor page for the current input schema, pricing tier, and run history.

Other Actors we maintain for related data:

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Resources

• Actor documentation, input schema, and pricing: verified against the published Actor on 2026-09-26.

• Actor last updated by its maintainers on 2026-06-06.

• Run outcome figures cover the 30 day public window ending 2026-09-26.

• HUD Fair Market Rents Scraper on Apify