# Nofluffjobs Extractor (`kawsar/nofluffjobs-extractor`) Actor NoFluffJobs Extractor that scrapes tech job postings and salary ranges from NoFluffJobs, so recruiters and market researchers can track hiring trends and benchmark salaries instantly. - **URL**: https://apify.com/kawsar/nofluffjobs-extractor.md - **Developed by:** [Kawsar](https://apify.com/kawsar) (community) - **Categories:** Jobs, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.99 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## NoFluffJobs Extractor: Tech Jobs, Salaries, and Requirements Scraper NoFluffJobs Extractor is a high-performance, production-ready web scraper designed to extract tech job postings, mandatory salary ranges, and technical skills from the NoFluffJobs platform. By directly parsing the server-rendered application state from the platform's HTML, this tool collects high-fidelity, structured job listings without the speed or reliability issues of visual browser crawlers. All scraped data can be instantly downloaded as JSON, CSV, or Excel files, or streamed directly into your custom applications or Google Sheets. --- ### Why scrape NoFluffJobs? NoFluffJobs is one of the premier tech job boards in Europe. Unlike traditional job platforms, NoFluffJobs enforces mandatory salary disclosures on every single posting, making it an invaluable goldmine of clean compensation data and technology demand. With this extractor, you can easily harness this data for critical business workflows: * **Salary benchmarking**: Track live compensation levels across different programming languages, framework stacks, and seniority levels to ensure your hiring offers remain competitive. * **Recruitment intelligence**: Understand which libraries, development practices, and methodologies are actively demanded by European software engineering teams. * **Competitive intelligence**: Monitor which companies are scaling up their development teams, what technologies they use, and where their engineering hubs are located. * **Labor market research**: Create comprehensive analytical reports on remote work adoption, tech hub growth, and regional salary differences across Europe. --- ### Features This actor is equipped with powerful configuration and reliability features: * **Per-category limit setting**: Define a clean, independent limit on the number of jobs collected for each technology search handle or category in your run. * **Smart location filtering**: Filter postings in memory across multiple cities or remote criteria. The location filter is diacritic-agnostic and case-insensitive, meaning searches for "krakow" will perfectly match "Kraków", and searches for "lodz" will match "Łódź" or "Zdalna" (remote). * **Zero visual scraper overhead**: By targeting the server-side pre-rendered state within the HTML structure, the actor retrieves up to 100 job listings per request, running up to 10 times faster than headless browser configurations. * **Automatic data normalization**: Translates raw fields into highly readable, structured formats (e.g. converting epoch timestamps into standardized ISO date strings, and splitting complex salary components). --- ### Input Parameters The actor is configured via a straightforward JSON schema. The table below lists all supported settings: | Parameter | Type | Default | Description | | :--- | :--- | :--- | :--- | | `categories` | array | `["Python"]` | **Required.** A list of tech categories, technologies, or search handles to crawl (one per line, e.g. Python, javascript, devops, pm). | | `locations` | array | `[]` | **Optional.** List of cities, countries, or remote filter terms (e.g. Warszawa, Kraków, Remote) to filter postings. Diacritic-agnostic and case-insensitive. | | `maxItemsPerCategory` | integer | `100` | Maximum number of job listings to retrieve for each category or technology in your list (maximum limit of 1000). | | `requestTimeoutSecs` | integer | `30` | Network request timeout limit in seconds. | #### Example Input Configuration ```json { "categories": ["Python", "javascript"], "locations": ["Warszawa", "Kraków", "Remote"], "maxItemsPerCategory": 150, "requestTimeoutSecs": 30 } ```` *** ### Extracted Data Structure Each job posting is returned as a clean, normalized JSON object inside your dataset. Below is an example of the output structure: ```json { "postingId": "lead-python-developer-antal-krakow", "title": "Lead Python Developer", "companyName": "Antal", "category": "backend", "seniority": ["Senior", "Lead"], "technology": "Python", "jobUrl": "https://nofluffjobs.com/job/lead-python-developer-antal-krakow", "fullyRemote": false, "locationPlaces": [ { "city": "Kraków", "street": "Pawia 23", "postalCode": "31-154", "countryName": "Poland", "countryCode": "POL" } ], "hybridDescription": "6 days per month in office in Kraków", "salaryFrom": 30240, "salaryTo": 36960, "salaryType": "b2b", "salaryCurrency": "PLN", "salaryDisclosed": "VISIBLE", "postedTimestamp": "2026-06-01T12:00:00.000000+00:00", "renewedTimestamp": "2026-06-06T14:30:00.000000+00:00", "requirements": ["Python", "Clean Code", "Agile", "SQL"], "scrapedAt": "2026-06-06T12:00:00.000000+00:00" } ``` *** ### Field Descriptions - `postingId` (string): The unique URL slug or identifier of the listing. - `title` (string): The professional title of the job offer. - `companyName` (string): The name of the hiring company. - `category` (string): The primary engineering category (e.g. backend, frontend, devops, mobile). - `seniority` (array): Seniority levels target by the employer (e.g. Junior, Mid, Senior, Lead). - `technology` (string): Main language or technology stack requested. - `jobUrl` (string): Direct absolute web URL to the job listing page. - `fullyRemote` (boolean): Flag indicating if the role is 100% remote. - `locationPlaces` (array): Complete details of office locations (city, street, postal code, country). - `hybridDescription` (string): Text detail of the hybrid schedule requirements. - `salaryFrom` (integer / null): Minimum monthly salary limit. Returns `null` if undisclosed. - `salaryTo` (integer / null): Maximum monthly salary limit. Returns `null` if undisclosed. - `salaryType` (string / null): Employment agreement type (e.g. b2b, uop). - `salaryCurrency` (string / null): Currency abbreviation (e.g. PLN, EUR, USD). - `salaryDisclosed` (string / null): Visual status indicator of the salary ranges. - `postedTimestamp` (string / null): ISO formatted posting date and time. - `renewedTimestamp` (string / null): ISO formatted last renewal date and time. - `requirements` (array): Key technical requirements and skills extracted from the posting. - `scrapedAt` (string): Precise timestamp when the data was extracted. *** ### FAQ **Can I run this actor without setting up proxies?** Yes. The actor runs on built-in premium bypass infrastructure. You do not need to purchase or configure your own proxies or manage rotated IP setups. **How does the locations filter work with accents and capitalization?** The location matching is completely automated to be user friendly. It normalizes all strings by removing diacritic marks and casing before matching. Entering `"krakow"` or `"lodz"` will seamlessly capture listings published with city names like `"Kraków"` or `"Łódź"`. **Why are some salary fields returned as empty (null)?** Although NoFluffJobs encourages full transparency, employers occasionally hide precise ranges. When a listing hides salaries, the minimum and maximum fields are returned as `null`, and the `salaryDisclosed` property will set to `UNDISCLOSED`. **Can I export the data to Google Sheets?** Yes. Every Apify dataset can be connected to Google Sheets, Zapier, or Make. You can configure webhooks or leverage Apify integrations under the Integrations tab of your run console to sync extracted postings automatically. # Actor input Schema ## `categories` (type: `array`): List of technology names, categories, or search handles to crawl (one per line, e.g. Python, javascript, devops, pm). ## `locations` (type: `array`): Optional list of cities, countries, or remote filter (e.g. Warszawa, Kraków, Remote) to filter job postings. Case-insensitive. ## `maxItemsPerCategory` (type: `integer`): Maximum number of job listings to retrieve for each job category/technology in the list. ## `requestTimeoutSecs` (type: `integer`): Per-request timeout in seconds. ## Actor input object example ```json { "categories": [ "Python", "javascript", "devops" ], "locations": [ "Warszawa", "Kraków", "Remote" ], "maxItemsPerCategory": 20, "requestTimeoutSecs": 30 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "categories": [ "Python" ], "locations": [] }; // Run the Actor and wait for it to finish const run = await client.actor("kawsar/nofluffjobs-extractor").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "categories": ["Python"], "locations": [], } # Run the Actor and wait for it to finish run = client.actor("kawsar/nofluffjobs-extractor").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "categories": [ "Python" ], "locations": [] }' | apify call kawsar/nofluffjobs-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=kawsar/nofluffjobs-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Nofluffjobs Extractor", "description": "NoFluffJobs Extractor that scrapes tech job postings and salary ranges from NoFluffJobs, so recruiters and market researchers can track hiring trends and benchmark salaries instantly.", "version": "0.0", "x-build-id": "hSRNEYvyoXTI7Mcin" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/kawsar~nofluffjobs-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-kawsar-nofluffjobs-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/kawsar~nofluffjobs-extractor/runs": { "post": { "operationId": "runs-sync-kawsar-nofluffjobs-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/kawsar~nofluffjobs-extractor/run-sync": { "post": { "operationId": "run-sync-kawsar-nofluffjobs-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "categories" ], "properties": { "categories": { "title": "Job Categories / Technologies (Batch)", "type": "array", "description": "List of technology names, categories, or search handles to crawl (one per line, e.g. Python, javascript, devops, pm).", "items": { "type": "string" } }, "locations": { "title": "Locations Filter (Optional)", "type": "array", "description": "Optional list of cities, countries, or remote filter (e.g. Warszawa, Kraków, Remote) to filter job postings. Case-insensitive.", "items": { "type": "string" } }, "maxItemsPerCategory": { "title": "Max items per Job Category", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of job listings to retrieve for each job category/technology in the list.", "default": 20 }, "requestTimeoutSecs": { "title": "Request timeout (seconds)", "minimum": 5, "maximum": 120, "type": "integer", "description": "Per-request timeout in seconds.", "default": 30 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```