# World Bank Scraper (`velvety_bedbug/world-bank-scraper`) Actor Scrape economic and development indicators from the World Bank Open Data API. Access GDP, population, poverty rates, and thousands of other indicators for all countries. - **URL**: https://apify.com/velvety\_bedbug/world-bank-scraper.md - **Developed by:** [Peters Bugs](https://apify.com/velvety_bedbug) (community) - **Categories:** Lead generation, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 result records 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 ## World Bank Projects Scraper ### Overview Scrape World Bank funded projects data including project details, funding amounts, country, status, sectors, and more. Search by keyword, country, status, year range, or region. Supports keyword search, filters (Project Status). ### Features - Search by keywords to find specific results - Filter results by category or type - Export data in JSON, CSV, or Excel formats - Control output volume with configurable result limits - Built-in proxy support for reliable data collection ### Use Cases - **Monitor** - Monitor international government procurement opportunities - **Track** - Track regulatory changes across jurisdictions - **Build** - Build cross-border compliance databases - **Aggregate** - Aggregate international public sector data for research ### Input Parameters | Parameter | Type | Description | Default | |-----------|------|-------------|---------| | `searchTerm` | string | Keyword to search for in project names and descriptions (e.g., "water", "infr... | | | `countryCode` | string | ISO country code to filter by (e.g., "KE" for Kenya, "BR" for Brazil, "IN" fo... | | | `status` | string | Filter by project status. | `` | | `fromYear` | integer | Start year for filtering projects (e.g., 2020). | | | `toYear` | integer | End year for filtering projects (e.g., 2024). | | | `region` | string | Region filter (e.g., "Africa", "East Asia and Pacific", "Latin America and Ca... | | | `maxItems` | integer | Maximum number of projects to scrape. | `100` | | `proxyConfiguration` | object | Optional proxy settings. The World Bank API is public so proxies are usually ... | | ### Output Example Each result contains structured data like this: ```json { "project_id": "ABC-12345", "project_name": "World Bank Projects Sample Item", "country": 127, "country_code": 127, "region": "Sample region", "status": "Active", "board_approval_date": "2025-01-15", "closing_date": "2025-01-15", "total_amount": 50000, "commitment_amount": 50000, "lending_instrument": "Sample lending_instrument", "sector": "Technology", "borrower": "Sample borrower", "implementing_agency": "Sample implementing_agency", "themes": "Sample themes", "url": "https://example.com/item/12345" } ```` ### Pricing This actor uses pay-per-result pricing: - **$0.001** per result - **$1.00** per 1,000 results No monthly fees. You only pay for what you scrape. [Apify Free plan](https://apify.com/pricing) includes $5/month in platform credits. ### How to Run #### Apify Console 1. Go to the [World Bank Projects Scraper](https://apify.com/fortuitous_pirate/world-bank-scraper) actor page 2. Configure your input parameters 3. Click **Start** and wait for the results 4. Download data in JSON, CSV, or Excel format #### API ```bash curl -X POST "https://api.apify.com/v2/acts/fortuitous_pirate~world-bank-scraper/runs?token=YOUR_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{"maxItems": 10}' ``` #### Python SDK ```python from apify_client import ApifyClient client = ApifyClient("YOUR_API_TOKEN") run = client.actor("fortuitous_pirate/world-bank-scraper").call( run_input={"maxItems": 10} ) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ``` ### Integration Connect World Bank Projects Scraper with your existing tools and workflows: - **API access** - Programmatic access via [Apify API](https://docs.apify.com/api/v2) - **Webhooks** - Get notified when scraping completes - **Scheduling** - Set up recurring runs on any schedule - **Zapier / Make** - Connect with 5,000+ apps via [Apify integrations](https://apify.com/integrations) - **Python / Node.js SDKs** - Native client libraries for easy integration # Actor input Schema ## `indicator` (type: `string`): World Bank indicator code (e.g. NY.GDP.MKTP.CD for GDP, SP.POP.TOTL for population) ## `countryCodes` (type: `string`): Comma-separated ISO2 country codes (e.g. US,CN,DE). Leave empty for all countries. ## `startYear` (type: `string`): Start year (e.g. 2000) ## `endYear` (type: `string`): End year (e.g. 2024) ## `maxItems` (type: `integer`): Maximum data points to return ## Actor input object example ```json { "indicator": "NY.GDP.MKTP.CD", "countryCodes": "", "startYear": "2020", "endYear": "2024", "maxItems": 10 } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("velvety_bedbug/world-bank-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 = {} # Run the Actor and wait for it to finish run = client.actor("velvety_bedbug/world-bank-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 '{}' | apify call velvety_bedbug/world-bank-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=velvety_bedbug/world-bank-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "World Bank Scraper", "description": "Scrape economic and development indicators from the World Bank Open Data API. Access GDP, population, poverty rates, and thousands of other indicators for all countries.", "version": "0.1", "x-build-id": "Ac2wCBegcRcSBzK8w" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/velvety_bedbug~world-bank-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-velvety_bedbug-world-bank-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/velvety_bedbug~world-bank-scraper/runs": { "post": { "operationId": "runs-sync-velvety_bedbug-world-bank-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/velvety_bedbug~world-bank-scraper/run-sync": { "post": { "operationId": "run-sync-velvety_bedbug-world-bank-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "indicator": { "title": "Indicator Code", "type": "string", "description": "World Bank indicator code (e.g. NY.GDP.MKTP.CD for GDP, SP.POP.TOTL for population)", "default": "NY.GDP.MKTP.CD" }, "countryCodes": { "title": "Country Codes", "type": "string", "description": "Comma-separated ISO2 country codes (e.g. US,CN,DE). Leave empty for all countries.", "default": "" }, "startYear": { "title": "Start Year", "type": "string", "description": "Start year (e.g. 2000)", "default": "2020" }, "endYear": { "title": "End Year", "type": "string", "description": "End year (e.g. 2024)", "default": "2024" }, "maxItems": { "title": "Max Items", "maximum": 5000, "type": "integer", "description": "Maximum data points to return", "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 } } } } } } } } } } ```