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This open-source remote-jobs aggregator combines listings from RemoteOK, Remotive, Himalayas, Jobicy, and We Work Remotely, then normalizes them into a common record format. It is designed to turn several differently shaped feeds into data a job board, alert, newsletter, dashboard, or analysis workflow can use—while leaving source-specific reuse rules in force.
Which five job boards does the project combine?
The project described by Joshua Smith connects to these five sources: RemoteOK, Remotive, Himalayas, Jobicy, and We Work Remotely. That is the source list for this particular aggregator, not for every project described as a remote-jobs API. A separate keyless API article, for example, includes Hacker News Who’s Hiring instead of Himalayas; the two projects should not be conflated.
The project’s repository describes the implementation and its options. Smith’s article about the aggregator gives an example run and request parameters.
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What does normalization change?
Job boards do not describe listings in the same way. Salary may be a written range, separate numeric values, or missing; locations can be free-form; employment types use inconsistent labels or may be omitted; and descriptions may arrive as HTML. The same role can also appear on multiple boards.
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The aggregator maps those differences into a shared output. It parses salary ranges into numeric minimum and maximum values and a currency field where available, maps location rules to a compact remoteRegion, standardizes employment types, converts HTML descriptions to plain text, and retains one record for each title-and-company pair.
A sample output includes the source, title, company, location, remote region, category, tags, employment type, salary fields, plain-text description, application URL, publication timestamp, and an isNew flag. A common schema makes records easier to process together; it does not make missing source data appear, guarantee that two differently named roles are duplicates, or establish that salary information is complete.
How does it access and filter listings?
The repository says the aggregator uses public JSON APIs for RemoteOK, Remotive, Himalayas, and Jobicy. For We Work Remotely, it reads the main RSS feed and category feeds. It documents filters for keywords, categories, hiring region, and listing age, along with a maximum-jobs-per-source setting.
Smith’s article describes an example default run of five boards, up to 200 jobs per source, and a 30-day window, yielding 500–700 unique results in under a minute. That is the author’s stated example-run claim, not an independently verified benchmark or a fixed inventory promise. Source inventory changes, and filtering or deduplication affects the returned count.
What can you do with the normalized output?
The repository documents JSON, CSV, Excel, and XML exports, scheduled runs, and a monitor mode that returns listings the tool has not seen before. Those features support several workflows:
- Job board: combine results in one interface while preserving the original source and application link.
- Alerts and digests: filter by keyword, category, region, or age, then send relevant jobs to a newsletter or Slack/Discord digest.
- Analysis: use structured fields to explore salary ranges, categories, or hiring regions, while accounting for incomplete and inconsistent source data.
- Recruiting or AI workflows: pass normalized records into internal tools or retrieval pipelines, subject to each feed’s terms.
Monitor mode is useful when a workflow needs unseen listings rather than a full repeat of the current feed. The repository describes this capability, but the appropriate persistence and scheduling setup depends on how the code is run.
How many remote jobs can I get per run?
The project’s example configuration allows up to 200 jobs from each of five sources, with a 30-day age window. Smith reports 500–700 unique results in under a minute for his example run. The per-source setting is a cap, not a guarantee: feeds may contain fewer matching listings, and deduplication can reduce the combined total. Treat the reported runtime and result count as an author-provided example, not a service-level commitment.
How fresh are the listings?
The aggregator’s age filter and scheduled-run options let an implementation limit or refresh what it processes, but the project’s description does not establish a single refresh guarantee for all five boards. Freshness depends on when each source updates, when the aggregator runs, and how its results are stored or delivered.
Himalayas says its API data is refreshed daily. Its browse endpoint is cursor-paginated and returns at most 20 records per request; applications that need more must follow the pagination flow. Its documentation also warns that request rate limits can produce HTTP 429 responses. See the Himalayas Remote Jobs API documentation for its current endpoint and usage details.
Can I call the API from browser JavaScript?
Not directly for Himalayas, according to its API documentation: the API does not send the Access-Control-Allow-Origin header needed for cross-origin browser requests. The documentation recommends making the request from a backend, serverless function, or build step instead. That also gives an application a place to cache the daily-refreshed feed and manage requests without exposing server-side logic in the browser.
What should you check before republishing jobs?
“Public” does not mean that every feed permits every form of redistribution. Check the current conditions for each source before publishing, forwarding, or otherwise reusing its listings. The aggregator’s general description is not a substitute for those rules.
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Himalayas explicitly permits uses including job boards, job-search experiences, internal dashboards, and AI or automation, with attribution conditions. It asks users to link to the job URL on Himalayas and name Himalayas as the original source. Its documentation also says not to submit its jobs to third-party sites such as Jooble, Neuvoo, Google Jobs, or LinkedIn Jobs. Follow the source’s current instructions rather than assuming the same terms apply to all five boards.
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For listings you are permitted to reuse, retain the source label and original listing URL, and direct applicants to the original listing. The project says it is not a LinkedIn or Indeed scraper; that description should not be read as a blanket permission statement for downstream use.
Should you use the hosted Actor or run the code yourself?
The repository identifies the project as MIT-licensed, so developers can consider running the code themselves. The hosted option is listed as an Actor on the Apify Store. The listing showed a price of $1 per 1,000 job listings when accessed October 7, 2026; marketplace prices and availability can change.
A hosted run avoids operating the aggregation code yourself, while self-hosting gives you control over deployment and integration but leaves you responsible for running and maintaining it. The available information does not provide an independent comparison of total operating costs or maintenance effort, so choose based on your deployment needs and verify current hosted terms before relying on a price.
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