# Green Japan Scraper — IT & Web Jobs, Salaries, Companies (`youfuxu/green-japan-tech-jobs-scraper`) Actor
Scrape Green (green-japan.com), Japan's IT/Web focused job board. Positions, salary ranges, required skills, hiring companies with capital, headcount and address — as clean JSON.
- **URL**: https://apify.com/youfuxu/green-japan-tech-jobs-scraper.md
- **Developed by:** [Youfu Xu](https://apify.com/youfuxu) (community)
- **Categories:** Jobs
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $3.00 / 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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/docs.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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
## Green Japan Scraper — IT & Web jobs, salary ranges, hiring companies
Structured job data from **[Green](https://www.green-japan.com)**, Japan's IT/Web focused job board (28,000+ live postings). Search in Japanese or English, export as JSON, CSV or Excel. No login, no browser, no proxy setup.
### What you get
Default run (list only, fast):
```json
{
"jobId": 323025,
"url": "https://www.green-japan.com/company/11170/job/323025",
"positionName": "バックエンドエンジニア／自社サービス",
"salaryText": "440万円〜960万円",
"area": "東京都, 大阪府",
"companyName": "ネクストライブ 株式会社",
"companyUrl": "https://www.green-japan.com/company/11170",
"employeesNumber": 32,
"establishedYear": "2019年",
"skills": ["PHP", "Laravel", "AWS"],
"updatedAt": "2026-07-22T09:42:16.000Z"
}
````
With **Include detail page data**, each job carries the whole hiring picture — 44 fields in total:
```json
{
"minSalaryYen": 4400000,
"maxSalaryYen": 9600000,
"employmentStatus": "正社員",
"requirements": "・PHPでの開発経験3年以上…",
"benefits": "各種社会保険完備、リモート可…",
"holidays": "完全週休2日制（土日祝）…",
"workStartTime": "10:00",
"workEndTime": "19:00",
"workAddress": "東京都渋谷区…",
"access": "東京メトロ銀座線「外苑前」駅より徒歩3分",
"hiringProcess": "書類選考 → 一次面接 → 最終面接",
"companyCapital": "1,500万円",
"companyEmployees": 32,
"companyPresident": "…",
"companyIndustries": ["受託開発", "自社サービス"]
}
```
Note the salary fields: Green stores pay in 万円 units, and this Actor converts them to plain yen, so `minSalaryYen: 4400000` sorts and filters correctly without post-processing.
### Who uses this
- **Recruiters & sourcing** — which Japanese tech companies are hiring, for what, at what pay, with office location and nearest station
- **Salary benchmarking** — numeric min/max ranges per role, not free text you have to regex
- **Market entry & competitive research** — company capital, headcount, industry and main customers come attached to every posting
- **Job boards & alert bots** — poll a keyword daily and diff against yesterday's dataset; every job carries an `updatedAt` timestamp
- **Recruitment-tech products** — a clean, structured feed of a market that is hard to scrape from the outside
### How to use
1. Enter a **keyword** — `engineer`, `React`, `データサイエンティスト`, `PM`, or leave it empty to walk the whole board
2. Set **Max jobs** (Green pages 20 at a time)
3. Enable **Include detail page data** when you need salary numbers, requirements and company profiles
4. Run, then download from the **Dataset** tab as JSON / CSV / Excel, or pull it through the Apify API
#### Example input
```json
{
"keyword": "機械学習",
"maxItems": 300,
"includeDetails": true
}
```
### Notes on reliability
- Data comes from the same structured payload Green's own site renders from, so fields stay stable across redesigns
- Requests are paced with exponential backoff and retries, and jobs are de-duplicated by ID across pages, so a long export never bills you twice for the same row
- The log prints Green's own total match count first, so you can size the job before committing to it
### Pricing model
You pay per result — a small fee for each job returned. You only pay for rows you actually receive.
### FAQ
**Does it need a proxy?**
No. It runs from Apify's servers without residential proxies.
**Can I get all 28,000 jobs?**
Yes — leave the keyword empty and raise `maxItems`. Use detail mode selectively on large runs, since it adds one request per job.
**How current is the data?**
Every job carries `updatedAt` straight from Green. Schedule the Actor daily and diff to catch new and refreshed postings.
**Japanese or English?**
Both work as search input. The output keeps Japanese field values as published — no lossy translation.
# Actor input Schema
## `keyword` (type: `string`):
What to search for, in Japanese or English: engineer, データサイエンティスト, PM, React. Leave empty to walk the whole board (28,000+ jobs).
## `maxItems` (type: `integer`):
Maximum number of jobs to return (Green pages 20 at a time).
## `includeDetails` (type: `boolean`):
Visit each job page to add numeric salary range, requirements, benefits, working hours, office address and the hiring company's capital, headcount and president. One extra request per job, so it is slower — but this is what turns the list into a usable dataset.
## Actor input object example
```json
{
"keyword": "engineer",
"maxItems": 40,
"includeDetails": false
}
```
# 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 = {
"keyword": "engineer",
"maxItems": 40
};
// Run the Actor and wait for it to finish
const run = await client.actor("youfuxu/green-japan-tech-jobs-scraper").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 = {
"keyword": "engineer",
"maxItems": 40,
}
# Run the Actor and wait for it to finish
run = client.actor("youfuxu/green-japan-tech-jobs-scraper").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 '{
"keyword": "engineer",
"maxItems": 40
}' |
apify call youfuxu/green-japan-tech-jobs-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=youfuxu/green-japan-tech-jobs-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Green Japan Scraper — IT & Web Jobs, Salaries, Companies",
"description": "Scrape Green (green-japan.com), Japan's IT/Web focused job board. Positions, salary ranges, required skills, hiring companies with capital, headcount and address — as clean JSON.",
"version": "1.0",
"x-build-id": "mhv6cigKWaw6zkDqJ"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/youfuxu~green-japan-tech-jobs-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-youfuxu-green-japan-tech-jobs-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/youfuxu~green-japan-tech-jobs-scraper/runs": {
"post": {
"operationId": "runs-sync-youfuxu-green-japan-tech-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/youfuxu~green-japan-tech-jobs-scraper/run-sync": {
"post": {
"operationId": "run-sync-youfuxu-green-japan-tech-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"keyword": {
"title": "Search keyword",
"type": "string",
"description": "What to search for, in Japanese or English: engineer, データサイエンティスト, PM, React. Leave empty to walk the whole board (28,000+ jobs).",
"default": ""
},
"maxItems": {
"title": "Max jobs",
"minimum": 1,
"maximum": 10000,
"type": "integer",
"description": "Maximum number of jobs to return (Green pages 20 at a time).",
"default": 40
},
"includeDetails": {
"title": "Include detail page data",
"type": "boolean",
"description": "Visit each job page to add numeric salary range, requirements, benefits, working hours, office address and the hiring company's capital, headcount and president. One extra request per job, so it is slower — but this is what turns the list into a usable dataset.",
"default": false
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```