# Stepstone Scraper (`jupri/stepstone-scraper`) Actor πŸ’« Scrape Stepstone.de and similar websites. - **URL**: https://apify.com/jupri/stepstone-scraper.md - **Developed by:** [cat](https://apify.com/jupri) (community) - **Categories:** Jobs - **Stats:** 690 total users, 28 monthly users, 34.4% runs succeeded, 26 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing $5.00 / 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 ## Welcome to Stepstone Scraper ![don't be sad readme is here](https://raw.githubusercontent.com/JupriGH/resources/main/cats/catframe.png) ### About The Stepstone Group **The Stepstone Group** ( **Stepstone** for short ) is an international [group of companies](https://de.wikipedia.org/wiki/Unternehmensgruppe "group of companies") . [[2]](https://de.wikipedia.org/wiki/Stepstone#cite_note-2) It was founded in Oslo in 1996 under the name **Jobshop** , renamed Stepstone in 2000 and was listed on the [stock exchange from 2000 to 2009.](https://de.wikipedia.org/wiki/B%C3%B6rse "stock exchange") Stepstone has belonged to the [Axel Springer](https://de.wikipedia.org/wiki/Axel_Springer_SE "Axel Springer SE") media group since 2009 . The umbrella company's legal [headquarters](https://de.wikipedia.org/wiki/Sitz_(juristische_Person) "seat (legal entity)") are [in Berlin](https://de.wikipedia.org/wiki/Berlin "Berlin") , and the head office is in [DΓΌsseldorf](https://de.wikipedia.org/wiki/D%C3%BCsseldorf "Dusseldorf") ### About This Actor Scrape Jobs data from Stepstone.de and similar websites. ||Websites| |-|-| ||CWJobs.co.uk| ||Totaljobs.com| ||JobSite.co.uk| ||Milkround.com| ||Caterer.com| ||CityJobs.com| ||Justengineers.net| ||Emedcareers.com| ||Retailchoice.com| ||Catererglobal.com| ||Careerstructure.com| ||Stepstone.de| ||Stepstone.at| ||Stepstone.be| ||Stepstone.nl| ||Pnet.co.za| ||NIJobs.com| ||IrishJobs.ie| ||Jobs.ie| # Actor input Schema ## `query` (type: `string`): Search Keywords ## `portal` (type: `string`): No description ## `limit` (type: `integer`): Limit number of results. ## `filters.sort` (type: `string`): No description ## `filters.include_listing` (type: `array`): πŸ’‘ Includes additional jobs listing. ## `filters.include_details` (type: `string`): πŸ’‘ Include additional job-related information such as job description, salary, etc. ## `filters.company` (type: `string`): πŸ’‘ Company-ID (digits) ## `filters.location` (type: `string`): No description ## `filters.radius` (type: `string`): πŸ’‘ Radius in km. (default=30 km) ## `filters.salary` (type: `integer`): πŸ’‘ Minimum salary (per year) ## `filters.age` (type: `string`): No description ## `filters.remote` (type: `array`): No description ## `filters.apply` (type: `array`): No description ## `filters.experience` (type: `string`): No description ## `filters.contract` (type: `array`): No description ## `filters.worktype` (type: `array`): No description ## `filters.language` (type: `array`): πŸ’‘ Example: "de" ## `dev_custom_headers` (type: `array`): πŸ’‘ Additional HTTP Headers ## `dev_custom_cookies` (type: `array`): πŸ’‘ Additional HTTP Cookies ## `dev_transform_fields` (type: `array`): πŸ’‘ Transform the resulting output. Select only needed fields.

For nested object use DOT. For example: 
address.streetAddress

For nested array use NUMBER (index of array element starting from index=0). For example: 
images.0.url
## `dev_dataset_name` (type: `string`): πŸ’‘ Save results into custom named Dataset, use mask to customize dataset name

{ACTOR} = actor name
{DATE} = date (YYYYMMDD)
{TIME} = time (HHMMSS)

This masks can be used to autogenerate Dataset Name.

example: data-{DATE}
Depending on today date the dataset name will be: data-20230603

default: data-{ACTOR}-{DATE}-{TIME} ## `dev_dataset_clear` (type: `boolean`): Clear Dataset before insert/update. ## `dev_no_strip` (type: `boolean`): πŸ’‘ Keep/Save empty values (NULL, FALSE, empty ARRAY, empty OBJECT, empty STRING) ## `dev_dedup_index` (type: `string`): πŸ’‘ Avoid duplicates accross multiple runs.
  • Specify the same DEDUP INDEX and DEDUP KEY on every run.
  • Index Name. example: "Main Index" ## `dev_dedup_key` (type: `string`): πŸ’‘ Attribute (unique/primary KEY). This key must be unique across all datasets. example: "zpid" or "item_id" ## `dev_fileupload` (type: `string`): πŸ’‘ Upload your file and copy & paste the URL somewhere. ## Actor input object example ```json { "query": "python", "limit": 5 } ```` # 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 = { "query": "python", "limit": 5 }; // Run the Actor and wait for it to finish const run = await client.actor("jupri/stepstone-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "query": "python", "limit": 5, } # Run the Actor and wait for it to finish run = client.actor("jupri/stepstone-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "query": "python", "limit": 5 }' | apify call jupri/stepstone-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jupri/stepstone-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Stepstone Scraper", "description": "πŸ’« Scrape Stepstone.de and similar websites.", "version": "0.2", "x-build-id": "bpK5IqLJnUFEXneZs" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jupri~stepstone-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jupri-stepstone-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/jupri~stepstone-scraper/runs": { "post": { "operationId": "runs-sync-jupri-stepstone-scraper", "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/jupri~stepstone-scraper/run-sync": { "post": { "operationId": "run-sync-jupri-stepstone-scraper", "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": { "query": { "title": "❓ Query", "type": "string", "description": "Search Keywords" }, "portal": { "title": "🌐 Portal", "enum": [ "250", "255", "260", "270", "280", "2", "4", "7", "9", "10", "40", "50", "60", "76", "77", "80", "300", "301", "302" ], "type": "string", "description": "" }, "limit": { "title": "♾️ Limit", "type": "integer", "description": "Limit number of results." }, "filters.sort": { "title": "πŸ”€ Sorting", "enum": [ "relevance", "date", "salary_low", "salary_high" ], "type": "string", "description": "" }, "filters.include_listing": { "title": "Include Listing", "type": "array", "description": "πŸ’‘ Includes additional jobs listing.", "items": { "type": "string", "enum": [ "regional", "recommended", "family" ], "enumTitles": [ "Regional", "Recommended", "Family" ] } }, "filters.include_details": { "title": "Job Details", "enum": [ "md", "text", "html", "orig" ], "type": "string", "description": "πŸ’‘ Include additional job-related information such as job description, salary, etc." }, "filters.company": { "title": "Company", "type": "string", "description": "πŸ’‘ Company-ID (digits)" }, "filters.location": { "title": "Location", "type": "string", "description": "" }, "filters.radius": { "title": "Radius", "enum": [ "5", "10", "20", "30", "40", "50", "75", "100" ], "type": "string", "description": "πŸ’‘ Radius in km. (default=30 km)" }, "filters.salary": { "title": "Salary", "type": "integer", "description": "πŸ’‘ Minimum salary (per year)" }, "filters.age": { "title": "Date posted", "enum": [ "1", "3", "7", "14" ], "type": "string", "description": "" }, "filters.remote": { "title": "Work from home", "type": "array", "description": "", "items": { "type": "string", "enum": [ "partial", "remote" ], "enumTitles": [ "Partially remote", "Fully remote" ] } }, "filters.apply": { "title": "Application method", "type": "array", "description": "", "items": { "type": "string", "enum": [ "INTERNAL", "EXTERNAL" ], "enumTitles": [ "Easy apply", "On company website" ] } }, "filters.experience": { "title": "Experience", "enum": [ "no", "required", "executive" ], "type": "string", "description": "" }, "filters.contract": { "title": "Contract Type", "type": "array", "description": "", "items": { "type": "string", "enum": [ "222", "226", "223", "229", "228", "220", "224", "225", "232", "227", "221", "231", "230" ], "enumTitles": [ "Permanent contract", "Apprenticeship, Studies", "Temporary contract", "Student job, Industrial placement student", "Internship", "Temporary", "Entry level / trainee", "Freelance/Permanent contract", "Trade representative", "Bachelor dissertation / Master thesis", "Franchise", "Professional traineeship", "Doctoral thesis/State doctorate" ] } }, "filters.worktype": { "title": "Work type", "type": "array", "description": "", "items": { "type": "string", "enum": [ "fulltime", "parttime" ], "enumTitles": [ "Full Time", "Part Time" ] } }, "filters.language": { "title": "Job language", "type": "array", "description": "πŸ’‘ Example: \"de\"", "items": { "type": "string" } }, "dev_custom_headers": { "title": "πŸ“œ HTTP HEADERS", "type": "array", "description": "πŸ’‘ Additional HTTP Headers", "items": { "type": "object", "required": [ "key", "value" ], "properties": { "key": { "type": "string", "title": "Key" }, "value": { "type": "string", "title": "Value" } } } }, "dev_custom_cookies": { "title": "🍰 HTTP COOKIES", "type": "array", "description": "πŸ’‘ Additional HTTP Cookies", "items": { "type": "object", "required": [ "key", "value" ], "properties": { "key": { "type": "string", "title": "Key" }, "value": { "type": "string", "title": "Value" } } } }, "dev_transform_fields": { "title": "♻️ CUSTOM FIELD", "type": "array", "description": "πŸ’‘ Transform the resulting output. Select only needed fields.

    For nested object use DOT. For example: 
    address.streetAddress

    For nested array use NUMBER (index of array element starting from index=0). For example: 
    images.0.url
    ", "items": { "type": "object", "required": [ "key", "value" ], "properties": { "key": { "type": "string", "title": "Key" }, "value": { "type": "string", "title": "Value" } } } }, "dev_dataset_name": { "title": "πŸ“ CUSTOM STORAGE", "type": "string", "description": "πŸ’‘ Save results into custom named Dataset, use mask to customize dataset name

    {ACTOR} = actor name
    {DATE} = date (YYYYMMDD)
    {TIME} = time (HHMMSS)

    This masks can be used to autogenerate Dataset Name.

    example: data-{DATE}
    Depending on today date the dataset name will be: data-20230603

    default: data-{ACTOR}-{DATE}-{TIME}    " }, "dev_dataset_clear": { "title": "Clear Storage", "type": "boolean", "description": "Clear Dataset before insert/update." }, "dev_no_strip": { "title": "Disable data cleansing", "type": "boolean", "description": "πŸ’‘ Keep/Save empty values (NULL, FALSE, empty ARRAY, empty OBJECT, empty STRING)" }, "dev_dedup_index": { "title": "πŸ”‘ DEDUP INDEX", "type": "string", "description": "πŸ’‘ Avoid duplicates accross multiple runs.
  • Specify the same DEDUP INDEX and DEDUP KEY on every run.
  • Index Name. example: \"Main Index\"" }, "dev_dedup_key": { "title": "πŸ”‘ DEDUP KEY", "type": "string", "description": "πŸ’‘ Attribute (unique/primary KEY). This key must be unique across all datasets. example: \"zpid\" or \"item_id\"" }, "dev_fileupload": { "title": "πŸ“ FILE UPLOADER", "type": "string", "description": "πŸ’‘ Upload your file and copy & paste the URL somewhere." } } }, "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 } } } } } } } } } } ```