Colorado Real Estate Licensees Scraper

Colorado Real Estate Licensees Scraper for Professional License and Status Records

Collect publicly available real estate professional license records from the Colorado Division of Real Estate open data portal. Retrieve licensee names, license numbers, license types, current status, renewal dates, and disciplinary information. Filter records, explore dataset metadata, and export structured results as JSON, CSV, Excel, and other supported formats.

Overview

This actor collects records from the Licensed Real Estate Professionals in Colorado dataset.

It supports full dataset collection, filtered searches, and dataset metadata retrieval. Use it to organize Colorado real estate license records into an Apify dataset for professional research, business prospecting, and license status checks.

Features

• Collect Colorado real estate professional license records.
• Retrieve individual licensee names and entity names.
• Extract license numbers and license types.
• Identify license status and expiration dates.
• Collect initial issuance and renewal dates.
• Retrieve available disciplinary and case information.
• Include license verification links when available.
• Filter records by city or other available dataset fields.
• Retrieve dataset column names, types, and descriptions.
• Export results in JSON, CSV, Excel, and other supported formats.

Collection Modes

All Rows

Collects license records from the public dataset, up to the configured item limit.

Filtered Rows

Collects records matching supplied filter conditions. Use this mode to narrow results by city or other available dataset fields.

Dataset Metadata

Retrieves information about the dataset's columns, including their names, types, and descriptions.

Input Parameters

Parameter	Type	Description
mode	String	Collection mode: rows, filtered, or metadata.
maxItems	Integer	Maximum number of records to collect.
orderBy	String	Field or expression used to order collected records.
where	String	Optional filter condition for the filtered mode.
requestDelaySecs	Number	Delay between collection requests in seconds.

Example Input

Collect license records

{
  "mode": "rows",
  "maxItems": 50,
  "orderBy": ":id",
  "requestDelaySecs": 1
}

Filter by city

{
  "mode": "filtered",
  "where": "city='DENVER'",
  "maxItems": 25,
  "requestDelaySecs": 1
}

What Data Does This Actor Extract?

Field	Description
lastname	License holder's last name.
firstname	License holder's first name.
middlename	License holder's middle name.
suffix	Name suffix, when available.
entityname	Business or entity name, when available.
city	Licensee's city.
state	State associated with the record.
zipcode	ZIP code.
licenseprefix	License prefix.
licensenumber	License number.
licensetype	Professional license type.
licensefirstissuedate	Date the license was first issued.
licenselastreneweddate	Most recent license renewal date.
licenseexpirationdate	License expiration date.
licensestatus	Current status shown in the dataset.
casenumber	Associated disciplinary or case number, when available.
programaction	Program or disciplinary action information, when available.
disciplineeffectivedate	Effective date of disciplinary action, when available.
disciplinecompletedate	Completion date of disciplinary action, when available.
verifylicense	Link to the license verification record.
scraped_at	Date and time when the record was collected.

Note: Fields without a value for a given record are omitted from that record, so a field appears only when the dataset has data for it. For example, entityname appears on entity licenses such as brokerage firms and appraisal management companies, suffix appears on suffixed names, and casenumber, programaction, disciplineeffectivedate, and disciplinecompletedate appear on licensees with a disciplinary action. Tabular exports such as CSV still include every column across the run. To collect records that carry a specific field, use filtered mode, for example where set to entityname IS NOT NULL AND entityname != ''. Verify current license details before making compliance or business decisions.

Example Output

An individual licensed appraiser with no entity name, suffix, or disciplinary action:

{
  "lastname": "Alexander",
  "firstname": "James",
  "middlename": "Edward",
  "city": "Littleton",
  "state": "CO",
  "zipcode": "80123",
  "licenseprefix": "AL",
  "licensenumber": "1322849",
  "licensetype": "Licensed Appraiser",
  "licensefirstissuedate": "09/12/1996",
  "licenselastreneweddate": "11/18/2025",
  "licenseexpirationdate": "12/31/2027",
  "licensestatus": "Active",
  "verifylicense": "https://apps.colorado.gov/dre/licensing/Lookup/PrintLicenseDetails.aspx?cred=11376&contact=115742",
  "scraped_at": "2026-10-26T00:00:00+00:00"
}

An entity license (appraisal management company) with an entity name:

{
  "entityname": "Accurate Appraisal Management Services, LLC",
  "city": "Tucson",
  "state": "AZ",
  "zipcode": "85711",
  "licenseprefix": "AMC",
  "licensenumber": "200000070",
  "licensetype": "Appraisal Management Company",
  "licensefirstissuedate": "08/17/2015",
  "licenselastreneweddate": "01/01/2026",
  "licenseexpirationdate": "12/31/2026",
  "licensestatus": "Active",
  "verifylicense": "https://apps.colorado.gov/dre/licensing/Lookup/PrintLicenseDetails.aspx?cred=164008&contact=363021",
  "scraped_at": "2026-10-26T00:00:00+00:00"
}

Use Cases

• License Research: Explore Colorado real estate professional license records.
• Business Prospecting: Identify licensed professionals and real estate entities for business research.
• Compliance Checks: Review license status and expiration dates before further verification.
• Market Research: Analyze license records across different cities.
• Disciplinary Research: Review available case and disciplinary information.
• Data Management: Build structured license datasets for spreadsheets, databases, and internal tools.

Working with Your Dataset

After the actor completes a run:

1. Open the actor's Dataset tab.
2. Review the collected license records.
3. Export the results as JSON, CSV, Excel, or another supported format.
4. Use the exported data for research, reporting, and business workflows.

FAQ

Who is this actor for?

It is useful for real estate professionals, analysts, marketers, researchers, and developers who need structured Colorado license records.

Can I filter records by city?

Yes. Use filtered mode with a condition matching the city field, such as city='DENVER'.

Does the dataset include license status?

Yes. The actor collects the licensestatus field when available.

Can I find license expiration dates?

Yes. The licenseexpirationdate field contains the expiration date when provided in the record.

Does it include disciplinary information?

The dataset may contain case numbers, program actions, and disciplinary dates when those details are available.

Can I run it on a schedule?

Yes. Configure an Apify Schedule to refresh the dataset automatically at your preferred interval.

Can I export the collected records?

Yes. Apify supports JSON, CSV, Excel, and other dataset export formats.

Disclaimer

This actor is an independent tool and is not affiliated with, endorsed by, sponsored by, or officially associated with the Colorado Division of Real Estate or the State of Colorado. It collects publicly available information. Users are responsible for how they use, store, and redistribute collected data.

Is Web Scraping Legal?

Collecting information that is already public is generally legal. There is no single law that bans all forms of web scraping. The limits are the usual ones: do not break into accounts, do not take private or confidential data, and be careful with personal data and copyrighted works. A site's terms can also restrict how you access it. Facts such as a public name, price, or rating are not the same thing as republishing someone's article or photo.

This actor collects information from public pages. It does not log in and it does not bypass access controls.

For a longer explanation, see Apify's article Is web scraping legal?.