# Djinni Jobs & Salary Scraper (`spectr_of_inspiration/djinni-market-data-extractor`) Actor \[EN] Djinni.co extractor. Separates Titles/Salaries into clean Excel. Ideal for HR & LeadGen. Fast & reliable. \[UA] Екстрактор Djinni.co. Окремі колонки для назв та зарплат в Excel. Ідеально для HR, рекрутерів та лідогенерації. Швидкий збір даних. Підтримка пагінації. No more messy data! 🚀 - **URL**: https://apify.com/spectr\_of\_inspiration/djinni-market-data-extractor.md - **Developed by:** [Maksym Rizun](https://apify.com/spectr_of_inspiration) (community) - **Categories:** Jobs, Lead generation, Automation - **Stats:** 9 total users, 2 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 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. 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 ## ⚡ Djinni Ultimate Job Hunter Pro 2026 **The fastest and most efficient way to extract high-quality job leads from Djinni.co without blocks or technical hassle.** Stop manual searching and let the "Light Logic" handle the routine. This Actor is a professional-grade scraper designed for developers, recruiters, and lead generators who value their time. --- ### 🚀 Key Features * **🛡️ Stealth Vision:** Advanced structural analysis that bypasses modern bot-detection systems. * **⚡ Blazing Speed:** Scrapes dozens of pages in seconds using optimized BeautifulSoup logic. * **💎 Pure Results:** Automatically filters out technical noise (RSS/XML). You get only job titles, salaries, and direct links. * **🔄 Smart Pagination:** Automatically follows the "Next Page" until the dataset is complete. ### 🛠️ How to Use (Universal Guide) 1. **Find your leads:** Go to [Djinni.co](https://djinni.co/jobs/) and apply any filters you need (e.g., JavaScript, PHP, Marketing, Remote, $4000+). 2. **Copy URL:** Copy the resulting link from your browser's address bar. *Example:* `https://djinni.co/jobs/?primary_keyword=JavaScript&exp_level=2y` 3. **Input:** Paste this link into the **Start URLs** field in the Actor settings. 4. **Configure:** Set the **Max Pages** you wish to scrape to define depth. 5. **Execute:** Click **Run**. 6. **Export:** Go to the **Dataset** tab and download your gold in **Excel, JSON, or CSV**. ### 💰 Business Value * **For Freelancers:** Be the first to apply for high-budget projects. * **For Recruiters:** Build talent pools and track market trends instantly. * **For Agency Owners:** Automate lead generation for your sales team. --- # Actor input Schema ## `start_urls` (type: `array`): Paste Djinni search links here / Вставте посилання на пошук Djinni тут. ## `max_requests_per_crawl` (type: `integer`): Limit the number of pages to save costs / Обмежте кількість сторінок для економії. ## Actor input object example ```json { "start_urls": [ { "url": "https://djinni.co/jobs/?primary_keyword=Python" } ], "max_requests_per_crawl": 10 } ```` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "start_urls": [ { "url": "https://djinni.co/jobs/?primary_keyword=Python" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("spectr_of_inspiration/djinni-market-data-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 = { "start_urls": [{ "url": "https://djinni.co/jobs/?primary_keyword=Python" }] } # Run the Actor and wait for it to finish run = client.actor("spectr_of_inspiration/djinni-market-data-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 '{ "start_urls": [ { "url": "https://djinni.co/jobs/?primary_keyword=Python" } ] }' | apify call spectr_of_inspiration/djinni-market-data-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=spectr_of_inspiration/djinni-market-data-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Djinni Jobs & Salary Scraper", "description": "[EN] Djinni.co extractor. Separates Titles/Salaries into clean Excel. Ideal for HR & LeadGen. Fast & reliable. \n[UA] Екстрактор Djinni.co. Окремі колонки для назв та зарплат в Excel. Ідеально для HR, рекрутерів та лідогенерації. Швидкий збір даних. Підтримка пагінації. No more messy data! 🚀", "version": "0.0", "x-build-id": "ZatK44gClKeiWgu9V" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/spectr_of_inspiration~djinni-market-data-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-spectr_of_inspiration-djinni-market-data-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/spectr_of_inspiration~djinni-market-data-extractor/runs": { "post": { "operationId": "runs-sync-spectr_of_inspiration-djinni-market-data-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/spectr_of_inspiration~djinni-market-data-extractor/run-sync": { "post": { "operationId": "run-sync-spectr_of_inspiration-djinni-market-data-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "start_urls": { "title": "Start URLs / Початкові посилання", "type": "array", "description": "Paste Djinni search links here / Вставте посилання на пошук Djinni тут.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "max_requests_per_crawl": { "title": "Max Pages / Макс. сторінок", "minimum": 1, "type": "integer", "description": "Limit the number of pages to save costs / Обмежте кількість сторінок для економії.", "default": 10 } } }, "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 } } } } } } } } } } ```