# 58.com / 58同城 二手房 Real Estate Scraper (`zen-studio/58-real-estate-scraper`) Actor Extract 58.com / 58同城 二手房 prices, 房源 details, broker/经纪人, 小区, photos, VR, Q\&A, and 房价 trends across 671 Chinese cities. Paste search/detail URLs or use city + filters; export JSON, CSV, Excel from Apify datasets. - **URL**: https://apify.com/zen-studio/58-real-estate-scraper.md - **Developed by:** [Zen Studio](https://apify.com/zen-studio) (community) - **Categories:** Real estate, Lead generation, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $7.99 / 1,000 listings 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 ## 58.com / 58同城 二手房 Real Estate Scraper | 中国房产房源 (2026) Scrape 58.com / 58同城房产 二手房房源 from Chinese city pages.
58.com / 58同城 二手房房源 across 671 Chinese cities : 房价, prices, area, rooms, tax status, broker/经纪人, 小区, Q&A, photos, and price trends.
Zen Studio Real Estate   •  Listings, prices, and broker data from major Chinese housing markets
58  58.com Real Estate
二手房 sales + detail data 		 Anjuke Sale Listings
二手房 sales + community data 		 Anjuke Rent
Rent comps + photos 		 Anjuke New Homes
New homes + prices
### How It Works
58.com real estate search results
Step 1: Configure your search
Step 2: Paste as input JSON or run via API
Step 3: Listing, broker, community, and price data
#### Copy to your AI assistant / 复制给你的 AI 助手 Copy this block into ChatGPT, Claude, Cursor, or any LLM to start using this actor. ```text zen-studio/58-real-estate-scraper on Apify. Call: ApifyClient("TOKEN").actor("zen-studio/58-real-estate-scraper").call(run_input={...}), then client.dataset(run["defaultDatasetId"]).list_items().items for results. It scrapes 58.com / 58同城 二手房房源 and 中国房产 data across Chinese cities. Key inputs: city + keyword + filters, with bilingual city/filter dropdowns. Important fields: id, url, title, city, price.totalWan, price.unitPriceRmbPerSqm, layout.rooms, areaSqm, orientation, floor, fitment, tax, features, tags, labels, media, community/小区, broker/经纪人, detail.houseInfo, detail.houseIntro, detail.priceTrend. Full actor spec: GET https://api.apify.com/v2/acts/zen-studio~58-real-estate-scraper/builds/default (Bearer TOKEN), parse inputSchema, actorDefinition.storages.dataset, and readme. ```` ### Key Features - **Search + detail data**: 二手房房源 rows include detail-page data for broker/经纪人, 小区, media, Q\&A, and 房价 trends. - **City dropdown**: 671 58.com cities with bilingual labels, including 北京 Beijing, 上海 Shanghai, 广州 Guangzhou, 深圳 Shenzhen, 成都 Chengdu, 杭州 Hangzhou, and county-level markets. - **Useful sale filters**: keyword, district, business area, price, area, bedrooms, fitment, floor, age, orientation, property type, ring road, shortcuts, and feature tags. - **Structured output**: normalized 房价, price, layout, tax status, commission, broker/经纪人, 小区 facts, photos, VR metadata, Q\&A, and listing labels. ### Quick Start #### Beijing search ```json { "city": "bj", "keyword": "望京 三居 满五", "maxItems": 20 } ``` #### District + rooms + sale filters ```json { "city": "bj", "keyword": "望京", "district": "chaoyang", "businessAreaSlug": "wangjing", "bedrooms": "3", "minPrice": 300, "maxPrice": 650, "features": ["five_years", "near_subway"], "sortBy": "price_asc", "maxItems": 100 } ``` #### Filtered Beijing family-home search ```json { "city": "bj", "keyword": "望京 南北通透", "district": "chaoyang", "businessAreaSlug": "wangjing", "bedrooms": "3", "minPrice": 400, "maxPrice": 650, "minArea": 80, "maxArea": 130, "features": ["near_subway", "five_years"], "orientation": "6", "fitment": "4", "floorType": "3", "houseAge": "5_10", "propertyType": "1", "sortBy": "price_asc", "maxItems": 200 } ``` ### Input Parameters | Parameter | Type | Default | Description | |---|---:|---:|---| | `maxItems` | integer | `20` | Number of listings to save. Maximum: `5000`. | | `city` | string | `bj` | Searchable city dropdown with Chinese + English labels. The actor maps the selection internally. | | `keyword` | string | `望京 三居 满五` | Free-text listing search. | | `sortBy` | string | `default` | `default`, `price_asc`, `price_desc`, `area_desc`. | | `district` | string | - | Built-in Beijing district dropdown, for example 朝阳 Chaoyang, 海淀 Haidian, 丰台 Fengtai. The actor maps the selection internally. | | `customDistrictSlug` | string | - | Custom district slug for supported non-Beijing cities when known. | | `businessAreaSlug` | string | - | Business-area slug, for example `wangjing`. | | `minPrice` / `maxPrice` | integer | - | Total sale price in 万 RMB. Example: `500` means ¥5,000,000. | | `minArea` / `maxArea` | integer | - | Floor area in square meters. | | `bedrooms` | string | - | `1`, `2`, `3`, `4`, `5`, `5plus`. | | `features` | array | - | `near_subway`, `five_years`, `two_years`. | | `fitment` | string | - | Decoration/fitment filter. | | `floorType` | string | - | Floor-level filter. | | `houseAge` | string | - | Building age filter. | | `orientation` | string | - | Orientation filter. | | `propertyType` | string | - | Property ownership/type filter. | | `useType` | string | - | Property usage filter. | | `circle` | string | - | Ring-road filter where available. | | `shortcut` | string | - | Common 58.com shortcut filters, such as verified or urgent listings. | ### Output Data Each saved listing can include: - **Listing identity**: listing ID, canonical desktop URL, source, market, title, city slug, city ID, province. - **Price and layout**: total price in 万, unit price per m², tax hint, rooms, halls, bathrooms, area, floor, fitment, orientation, build year, use type. - **Tax and features**: 满二/满五 labels, unique-property flag, elevator, heating, government verification, VR, video, auction, guarantee, landlord-listed status. - **Community and broker**: community IDs, city mapping, district, business area, coordinates, photo, score, facts, expert notes, Q\&A, broker/store/company data. - **Detail enrichment**: detail page title, meta data, house facts, intro sections, gallery, panorama metadata, price trend. ### Output Example ```json { "id": "4387154096759809", "url": "https://bj.58.com/ershoufang/4387154096759809x.shtml?auction=220&hpType=60&entry=102&position=0&kwtype=shangquan", "market": "second_hand_sale", "source": "58.com", "identifiers": { "listingId": "4387154096759809", "houseId": "4387154096759809", "ownerHouseId": "4565355173469186", "propId": "4565355173469186", "entityId": "4387154096759809", "tid": "-", "psLoupanId": "100403635", "loupanId": "", "brokerId": "6124674", "storeId": "22478" }, "title": "望京 高校老师小区 门口地铁站 环境好 高楼层三居急售", "city": { "slug": "bj", "cityId": 1, "name": "北京", "province": "直辖市" }, "price": { "totalWan": 480, "totalText": "480万", "unitPriceRmbPerSqm": 49803, "unitPriceText": "49803元/㎡", "taxHint": "" }, "layout": { "rooms": 3, "halls": 2, "bathrooms": 1, "text": "3室2厅1卫 96.38㎡ 西南" }, "areaSqm": 96.38, "orientation": "西南", "floor": { "text": "高层(共24层)", "level": "高层", "total": 24 }, "fitment": "简单装修", "buildYear": "2000", "useType": "普通住宅", "tax": { "overTaxYearCode": "2", "overTaxYearLabel": "满五年", "isOverTwoYears": true, "isOverFiveYears": true, "isUniqueProperty": false, "uniquePropertyCode": "0" }, "features": { "hasElevator": true, "hasHeating": true, "heatingCode": "1", "heatingLabel": "有供暖", "isLandlordListed": false, "isGuarantee": true, "isNewHome": false, "isAuction": false, "isGovernmentVerified": true, "isFullVerification": true, "hasVrViewing": true, "isNew3dVr": true, "isExcellentHouse": false, "isManagerRecommend": false, "isTop": false }, "commission": { "typeCode": "0", "typeLabel": "未标记或标准佣金" }, "tags": [ "满五年", "新上", "近地铁" ], "labels": [ { "label": "西南", "type": 7, "backgroundColor": "", "textColor": "" }, { "label": "近地铁", "type": 3, "backgroundColor": "", "textColor": "" } ], "media": { "coverImage": "https://pic1.ajkimg.com/display/58ajk/10cc1b6f725be9e79377eabe7d638179/640x420c.jpg?frame=1&t=5", "images": [ "https://pic1.ajkimg.com/display/58ajk/10cc1b6f725be9e79377eabe7d638179/640x420c.jpg?frame=1&t=5", "https://pic1.ajkimg.com/display/58ajk/278ad61de65003a5d5db5f093b7a31be/640x420c.jpg" ], "panoUrl": "https://720yun.com/t/137008565", "panoId": "137008565", "panoType": "VR3D", "hasVideo": false }, "community": { "id": "992", "platformId": "100403635", "psLoupanId": "100403635", "name": "望京花园西区", "address": "利泽中二路", "defaultPhoto": "https://pic3.ajkimg.com/wuba/98e19e978f70c1ff69c0d71f3d6405b4/500x500.jpg", "cityId": 1, "citySlug": "bj", "cityName": "北京", "areaId": "1142", "areaName": "朝阳", "businessAreaId": "1203", "businessAreaName": "望京", "lat": 40.01324, "lng": 116.476897, "completionTime": "1998", "score": "8.6", "tags": [ "14号线等", "四五环之间", "1998年建成" ], "facts": { "小区均价": "54311元/㎡", "小区户数": "约2100户", "物业费用": "1.8元/㎡/月", "容积率": "2.10", "绿化率": "35%" }, "expertNotes": [ { "title": "小区点评", "body": "小区近地铁，生活配套成熟，成交活跃。" } ], "qa": [ { "question": "【望京花园西区】小区门口是不是有牙医店？", "answer": "是的，周边生活配套比较齐全。", "answerer": "经纪人", "answerTime": "2026-05-06", "total": "1条回答" } ] }, "broker": { "id": "6124674", "name": "于明淞", "companyName": "我爱我家", "storeName": "我爱我家上京新航线店", "score": "5.0", "brokers": [ { "id": "6124674", "name": "于明淞", "score": "5.0", "company": "我爱我家", "detailUrl": "https://bj.58.com/jjr/6124674/" } ] }, "detail": { "ownerHouseCode": "4565355173469186", "pageTitle": "望京花园西区二手房_北京朝阳望京二手房", "meta": { "description": "北京望京花园西区二手房，3室2厅1卫，480万。", "keywords": "北京二手房,望京花园西区,朝阳望京", "location": { "province": "北京", "city": "北京", "coord": "116.476897,40.01324", "lng": 116.476897, "lat": 40.01324 }, "canonical": "https://bj.58.com/ershoufang/4387154096759809x.shtml" }, "houseInfo": { "产权性质": "商品房住宅", "物业类型": "普通住宅", "产权年限": "70年", "房本年限": "满五年", "参考预算": "首付96万，月供17030元", "发布公司": "我爱我家", "营业执照": "已核验" }, "houseIntro": [ { "title": "核心卖点", "body": "高楼层，视野好，格局方正，门口地铁站。" }, { "title": "小区介绍", "body": "小区配套成熟，出行便利，适合改善自住。" } ], "priceTrend": [ { "name": "望京花园西区", "values": [ { "label": "小区单价", "value": "54311 元/㎡" }, { "label": "商圈单价", "value": "62102 元/㎡" } ] } ] } } ``` ### Pricing
Plan Price Best for
Standard $9.99 / 1,000 listings Small research jobs and one-off exports
Silver $8.99 / 1,000 listings Recurring market monitoring
Gold $7.99 / 1,000 listings Higher-volume real estate data pipelines
### FAQ #### Why is the reported available count higher than my saved item count? 58.com can report a larger available count than the number of rows reachable during one paginated run. The actor logs the reported count so you can estimate market size. #### What fields are intentionally not saved? Raw HTML, mobile URLs, collect-state flags, search-position metadata, and tracking-only blobs are not saved. #### Is this only for buying homes? This actor version targets second-hand sale listings. Rentals, commercial property, and new homes are separate verticals and can be added later. ### Support - **Bugs**: Issues tab - **Features**: Issues tab # Actor input Schema ## `maxItems` (type: `integer`): Maximum listings to save to the dataset. This is the main result limit. ## `city` (type: `string`): Choose a 58.com / 58同城 city. The actor maps the selected city internally. ## `keyword` (type: `string`): Free-text 二手房 search term, for example 望京 三居 满五. ## `sortBy` (type: `string`): Choose how matching listings should be ordered. ## `district` (type: `string`): Beijing district filter. The actor maps the selected district internally. ## `customDistrictSlug` (type: `string`): Advanced: custom district slug from 58.com for the selected city. Overrides District when set. ## `businessAreaSlug` (type: `string`): Advanced: business-area/neighborhood slug from 58.com, for example wangjing. ## `minPrice` (type: `integer`): Minimum total price in 万 RMB. ## `maxPrice` (type: `integer`): Maximum total price in 万 RMB. ## `minArea` (type: `integer`): Minimum area in square meters. ## `maxArea` (type: `integer`): Maximum area in square meters. ## `bedrooms` (type: `string`): Bedroom count, mapped to 58.com room\_nums. ## `features` (type: `array`): Optional listing badges and conditions to require. ## `fitment` (type: `string`): 装修筛选 Decoration/fitment filter. ## `floorType` (type: `string`): 楼层位置筛选 Floor position filter. ## `houseAge` (type: `string`): 房龄范围筛选 Building age range. ## `orientation` (type: `string`): 房源朝向筛选 Facing/orientation filter. ## `propertyType` (type: `string`): 产权类型筛选 Ownership/property type filter. ## `useType` (type: `string`): 物业/用途类型筛选 Usage type filter. ## `circle` (type: `string`): 北京环线筛选 Beijing ring-road filter when available. ## `shortcut` (type: `string`): 58.com 快捷筛选, for example VR or urgent-sale listings. ## `maxPages` (type: `integer`): Advanced limit for listing pages per search source. ## `pageSize` (type: `integer`): Advanced batch-size setting. Keep the default for normal runs. ## Actor input object example ```json { "maxItems": 20, "city": "bj", "keyword": "望京 三居 满五", "sortBy": "default", "district": "", "bedrooms": "", "fitment": "", "floorType": "", "houseAge": "", "orientation": "", "propertyType": "", "useType": "", "circle": "", "shortcut": "", "maxPages": 50, "pageSize": 200 } ``` # Actor output Schema ## `listings` (type: `string`): Link to the dataset containing scraped 58.com real estate listings or diagnostic records for unsupported inputs. # 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": "望京 三居 满五" }; // Run the Actor and wait for it to finish const run = await client.actor("zen-studio/58-real-estate-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": "望京 三居 满五" } # Run the Actor and wait for it to finish run = client.actor("zen-studio/58-real-estate-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": "望京 三居 满五" }' | apify call zen-studio/58-real-estate-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=zen-studio/58-real-estate-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "58.com / 58同城 二手房 Real Estate Scraper", "description": "Extract 58.com / 58同城 二手房 prices, 房源 details, broker/经纪人, 小区, photos, VR, Q&A, and 房价 trends across 671 Chinese cities. Paste search/detail URLs or use city + filters; export JSON, CSV, Excel from Apify datasets.", "version": "0.0", "x-build-id": "e0eAVaOjgJTperoWu" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/zen-studio~58-real-estate-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-zen-studio-58-real-estate-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/zen-studio~58-real-estate-scraper/runs": { "post": { "operationId": "runs-sync-zen-studio-58-real-estate-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/zen-studio~58-real-estate-scraper/run-sync": { "post": { "operationId": "run-sync-zen-studio-58-real-estate-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "maxItems": { "title": "最大结果数 Max results", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum listings to save to the dataset. This is the main result limit.", "default": 20 }, "city": { "title": "城市 City", "enum": [ "bj", "sh", "gz", "sz", "cd", "hz", "nj", "tj", "wh", "cq", "xa", "suzhou", "zz", "cs", "xm", "fz", "dg", "fs", "nb", "qd", "hf", "wuhu", "bengbu", "fy", "hn", "anqing", "la", "huaibei", "chuzhou", "mas", "tongling", "xuancheng", "bozhou", "huangshan", "chizhou", "ch", "hexian", "hq", "tongcheng", "ningguo", "tianchang", "dongzhi", "wuweixian", "qz", "pt", "zhangzhou", "nd", "sm", "np", "ly", "wuyishan", "shishi", "jinjiangshi", "nananshi", "longhai", "shanghangxian", "fuanshi", "fudingshi", "anxixian", "yongchunxian", "yongan", "zhangpu", "zs", "zh", "huizhou", "jm", "st", "zhanjiang", "zq", "mm", "jy", "mz", "qingyuan", "yj", "sg", "heyuan", "yf", "sw", "chaozhou", "taishan", "yangchun", "sd", "huidong", "boluo", "haifengxian", "kaipingshi", "lufengshi", "nn", "liuzhou", "gl", "yulin", "wuzhou", "bh", "gg", "qinzhou", "baise", "hc", "lb", "hezhou", "fcg", "chongzuo", "guipingqu", "beiliushi", "bobaixian", "cenxi", "gy", "zunyi", "qdn", "qn", "lps", "bijie", "tr", "anshun", "qxn", "renhuaishi", "qingzhen", "lz", "tianshui", "by", "qingyang", "pl", "jq", "zhangye", "wuwei", "dx", "jinchang", "ln", "linxia", "jyg", "gn", "dunhuang", "haikou", "sanya", "wzs", "sansha", "qh", "wenchang", "wanning", "tunchang", "qiongzhong", "lingshui", "df", "da", "cm", "baoting", "baish", "danzhou", "luoyang", "xx", "ny", "xc", "pds", "ay", "jiaozuo", "sq", "kaifeng", "puyang", "zk", "xy", "zmd", "luohe", "smx", "hb", "jiyuan", "mg", "yanling", "yuzhou", "changge", "lingbaoshi", "qixianqu", "ruzhou", "xiangchengshi", "yanshiqu", "changyuan", "huaxian", "linzhou", "qinyang", "mengzhou", "wenxian", "weishixian", "lankaoxian", "tongxuxian", "lyxinan", "yichuan", "mengjinqu", "lyyiyang", "wugang", "yongcheng", "suixian", "luyi", "yingchixian", "shenqiu", "taikang", "shangshui", "qixianq", "junxian", "fanxian", "gushixian", "huaibinxian", "dengzhou", "xinye", "hrb", "dq", "qqhr", "mdj", "suihua", "jms", "jixi", "sys", "hegang", "heihe", "yich", "qth", "dxal", "shanda", "shzhaodong", "zhaozhou", "yc", "xf", "jingzhou", "shiyan", "hshi", "xiaogan", "hg", "es", "jingmen", "xianning", "ez", "suizhou", "qianjiang", "tm", "xiantao", "snj", "yidou", "hanchuan", "zaoyang", "wuxueshi", "zhongxiangshi", "jingshanxian", "shayangxian", "songzi", "guangshuishi", "chibishi", "laohekou", "gucheng", "yichengshi", "nanzhang", "yunmeng", "anlu", "dawu", "xiaochang", "dangyang", "zhijiang", "jiayuxian", "suixia", "zhuzhou", "yiyang", "changde", "hy", "xiangtan", "yy", "chenzhou", "shaoyang", "hh", "yongzhou", "ld", "xiangxi", "zjj", "liling", "lixian", "czguiyang", "zixing", "yongxing", "changningshi", "qidongxian", "hengdong", "lengshuijiangshi", "lianyuanshi", "shuangfengxian", "shaoyangxian", "shaodongxian", "yuanjiangs", "nanxian", "qiyang", "xiangyin", "huarong", "cilixian", "zzyouxian", "sjz", "bd", "ts", "lf", "hd", "qhd", "cangzhou", "xt", "hs", "zjk", "chengde", "dingzhou", "gt", "zhangbei", "zx", "zd", "qianan", "renqiu", "sanhe", "wuan", "xionganxinqu", "lfyanjiao", "zhuozhou", "hejian", "huanghua", "cangxian", "cixian", "shexian", "bazhou", "xianghe", "lfguan", "zunhua", "qianxixian", "yutianxian", "luannanxian", "shaheshi", "su", "wx", "cz", "xz", "nt", "yz", "yancheng", "ha", "lyg", "taizhou", "suqian", "zj", "shuyang", "dafeng", "rugao", "qidong", "liyang", "haimen", "donghai", "yangzhong", "xinghuashi", "xinyishi", "taixing", "rudong", "pizhou", "xzpeixian", "jingjiang", "jianhu", "haian", "dongtai", "danyang", "baoyingx", "guannan", "guanyun", "jiangyan", "jintan", "szkunshan", "sihong", "siyang", "jurong", "sheyang", "funingxian", "xiangshui", "xuyi", "jinhu", "jiangyins", "nc", "ganzhou", "jj", "yichun", "ja", "sr", "px", "fuzhou", "jdz", "xinyu", "yingtan", "yxx", "lepingshi", "jinxian", "fenyi", "fengchengshi", "zhangshu", "gaoan", "yujiang", "nanchengx", "fuliangxian", "cc", "jl", "sp", "yanbian", "songyuan", "bc", "th", "baishan", "liaoyuan", "gongzhuling", "meihekou", "fuyuxian", "changlingxian", "huadian", "panshi", "lishu", "sy", "dl", "as", "jinzhou", "fushun", "yk", "pj", "cy", "dandong", "liaoyang", "benxi", "hld", "tl", "fx", "pld", "wfd", "dengta", "fengcheng", "beipiao", "kaiyuan", "yinchuan", "wuzhong", "szs", "zw", "guyuan", "hu", "bt", "chifeng", "erds", "tongliao", "hlbe", "bycem", "wlcb", "xl", "xam", "wuhai", "alsm", "hlr", "xn", "hx", "haibei", "guoluo", "haidong", "huangnan", "ys", "hainan", "geermushi", "jn", "yt", "wf", "linyi", "zb", "jining", "ta", "lc", "weihai", "zaozhuang", "dz", "rizhao", "dy", "heze", "bz", "lw", "zhangqiu", "kl", "zc", "shouguang", "longkou", "caoxian", "shanxian", "feicheng", "gaomi", "guangrao", "huantaixian", "juxian", "laizhou", "penglai", "qingzhou", "rongcheng", "rushan", "tengzhou", "xintai", "zhaoyuan", "zoucheng", "zouping", "linqing", "chiping", "hzyc", "boxing", "dongming", "juye", "wudi", "qihe", "weishan", "yuchengshi", "linyixianq", "leling", "laiyang", "ningjin", "gaotang", "shenxian", "yanggu", "guanxian", "pingyi", "tancheng", "yiyuanxian", "wenshang", "liangshanx", "lijin", "yinanxian", "qixia", "ningyang", "dongping", "changyishi", "anqiu", "changle", "linqu", "juancheng", "ty", "linfen", "dt", "yuncheng", "jz", "changzhi", "jincheng", "yq", "lvliang", "xinzhou", "shuozhou", "linyixian", "qingxu", "liulin", "gaoping", "zezhou", "xiangyuanxian", "xiaoyi", "xianyang", "baoji", "wn", "hanzhong", "yl", "yanan", "ankang", "sl", "tc", "shenmu", "hancheng", "fugu", "jingbian", "dingbian", "mianyang", "deyang", "nanchong", "yb", "zg", "ls", "luzhou", "dazhou", "scnj", "suining", "panzhihua", "ms", "ga", "zy", "liangshan", "guangyuan", "ya", "bazhong", "ab", "ganzi", "anyuexian", "guanghanshi", "jianyangshi", "renshouxian", "shehongxian", "dazu", "xuanhan", "qux", "changningx", "xj", "changji", "bygl", "yili", "aks", "ks", "hami", "klmy", "betl", "tlf", "ht", "shz", "kzls", "ale", "wjq", "tmsk", "kuerleshi", "alt", "tac", "lasa", "rkz", "sn", "linzhi", "changdu", "nq", "al", "rituxian", "gaizexian", "km", "qj", "dali", "honghe", "yx", "lj", "ws", "cx", "bn", "zt", "dh", "pe", "bs", "lincang", "diqing", "nujiang", "milexian", "anningshi", "xuanwushi", "wz", "jh", "jx", "tz", "sx", "huzhou", "lishui", "quzhou", "zhoushan", "yueqingcity", "ruiancity", "yiwu", "yuyao", "zhuji", "xiangshanxian", "wenling", "tongxiang", "cixi", "changxing", "jiashanx", "haining", "deqing", "dongyang", "anji", "cangnanxian", "linhai", "yongkang", "yuhuan", "pinghushi", "haiyan", "wuyix", "shengzhou", "xinchang", "jiangshanshi", "pingyangxian", "hk", "am", "tw" ], "type": "string", "description": "Choose a 58.com / 58同城 city. The actor maps the selected city internally.", "default": "bj" }, "keyword": { "title": "关键词 Keyword", "type": "string", "description": "Free-text 二手房 search term, for example 望京 三居 满五.", "default": "望京 三居 满五" }, "sortBy": { "title": "排序 Sort by", "enum": [ "default", "price_asc", "price_desc", "area_desc" ], "type": "string", "description": "Choose how matching listings should be ordered.", "default": "default" }, "district": { "title": "区域 District", "enum": [ "", "chaoyang", "haidian", "changping", "fengtai", "daxing", "tongzhouqu", "fangshan", "shunyi", "xicheng", "dongcheng", "miyun", "shijingshan", "huairou", "mentougou", "yanqing", "pinggu", "beijingzhoubian" ], "type": "string", "description": "Beijing district filter. The actor maps the selected district internally.", "default": "" }, "customDistrictSlug": { "title": "自定义区域 Custom district slug", "type": "string", "description": "Advanced: custom district slug from 58.com for the selected city. Overrides District when set." }, "businessAreaSlug": { "title": "商圈 Business area", "type": "string", "description": "Advanced: business-area/neighborhood slug from 58.com, for example wangjing." }, "minPrice": { "title": "最低总价 Min price (万)", "minimum": 0, "type": "integer", "description": "Minimum total price in 万 RMB." }, "maxPrice": { "title": "最高总价 Max price (万)", "minimum": 0, "type": "integer", "description": "Maximum total price in 万 RMB." }, "minArea": { "title": "最小面积 Min area (m²)", "minimum": 0, "type": "integer", "description": "Minimum area in square meters." }, "maxArea": { "title": "最大面积 Max area (m²)", "minimum": 0, "type": "integer", "description": "Maximum area in square meters." }, "bedrooms": { "title": "户型 Bedrooms", "enum": [ "", "1", "2", "3", "4", "5", "6" ], "type": "string", "description": "Bedroom count, mapped to 58.com room_nums.", "default": "" }, "features": { "title": "特色 Features", "type": "array", "description": "Optional listing badges and conditions to require.", "items": { "type": "string", "enum": [ "near_subway", "five_years", "two_years" ], "enumTitles": [ "近地铁 Near subway", "满五 Over five years", "满二 Over two years" ] } }, "fitment": { "title": "装修 Fitment", "enum": [ "", "1", "2", "4", "5" ], "type": "string", "description": "装修筛选 Decoration/fitment filter.", "default": "" }, "floorType": { "title": "楼层 Floor type", "enum": [ "", "1", "2", "3", "4", "5" ], "type": "string", "description": "楼层位置筛选 Floor position filter.", "default": "" }, "houseAge": { "title": "房龄 House age", "enum": [ "", "0_2", "2_5", "5_10", "10_0" ], "type": "string", "description": "房龄范围筛选 Building age range.", "default": "" }, "orientation": { "title": "朝向 Orientation", "enum": [ "", "1", "2", "3", "4", "6", "5", "7", "8", "9", "10" ], "type": "string", "description": "房源朝向筛选 Facing/orientation filter.", "default": "" }, "propertyType": { "title": "产权 Property type", "enum": [ "", "1", "2", "3", "6" ], "type": "string", "description": "产权类型筛选 Ownership/property type filter.", "default": "" }, "useType": { "title": "物业类型 Use type", "enum": [ "", "3", "4", "5", "2", "6" ], "type": "string", "description": "物业/用途类型筛选 Usage type filter.", "default": "" }, "circle": { "title": "环线 Ring road", "enum": [ "", "1", "2", "3", "4", "5", "6" ], "type": "string", "description": "北京环线筛选 Beijing ring-road filter when available.", "default": "" }, "shortcut": { "title": "快捷筛选 Shortcut", "enum": [ "", "119", "116", "115", "124" ], "type": "string", "description": "58.com 快捷筛选, for example VR or urgent-sale listings.", "default": "" }, "maxPages": { "title": "Max pages", "minimum": 1, "maximum": 500, "type": "integer", "description": "Advanced limit for listing pages per search source.", "default": 50 }, "pageSize": { "title": "Page size", "minimum": 1, "maximum": 200, "type": "integer", "description": "Advanced batch-size setting. Keep the default for normal runs.", "default": 200 } } }, "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 } } } } } } } } } } ```