# Fec Donations Scraper (`quarterly_jingo/fec-donations-scraper`) Actor - **URL**: https://apify.com/quarterly\_jingo/fec-donations-scraper.md - **Developed by:** [Petey Boy](https://apify.com/quarterly_jingo) (community) - **Categories:** Lead generation, Automation, Developer tools - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## FEC Political Donations Scraper - Individual Campaign Contributions ### Overview Track who donates to political campaigns. Scrape FEC Schedule A individual contributions data - donor names, amounts, employers, occupations, recipients. Research campaign finance, find donor networks, and analyze contribution patterns. ### 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 ### Use Cases - **Track** - Track federal government data releases and updates - **Build** - Build datasets for policy research and analysis - **Monitor** - Monitor regulatory changes and compliance requirements - **Aggregate** - Aggregate public government data for transparency projects ### Input Parameters | Parameter | Type | Description | Default | |-----------|------|-------------|---------| | `apiKey` | string **(required)** | Your API key from api.data.gov (free signup). DEMO_KEY works for testing but ... | `DEMO_KEY` | | `searchMode` | string **(required)** | How to search for contributions | `contributor` | | `contributorName` | string | Name of the donor to search for (partial match supported, e.g., 'Musk' or 'El... | | | `committeeId` | string | FEC Committee ID (e.g., C00401224 for ActBlue, C00618389 for Trump campaign) | | | `candidateName` | string | Name of the candidate to find donations for (searches their principal campaig... | | | `contributorEmployer` | string | Filter by contributor's employer (e.g., 'Google', 'Goldman Sachs') | | | `contributorOccupation` | string | Filter by contributor's occupation (e.g., 'CEO', 'ATTORNEY') | | | `contributorCity` | string | Filter by contributor's city | | | `contributorState` | string | Two-letter state code (e.g., CA, NY, TX) | | | `minDate` | string | Filter contributions from this date (YYYY-MM-DD format) | | | `maxDate` | string | Filter contributions until this date (YYYY-MM-DD format) | | | `twoYearPeriod` | integer | Two-year election cycle (e.g., 2024 for 2023-2024 cycle). Note: Required if n... | | | `minAmount` | integer | Minimum donation amount in dollars | | | `maxAmount` | integer | Maximum donation amount in dollars | | | `maxResults` | integer | Maximum number of donation records to return | `100` | ### Output Example Each result contains structured data like this: ```json { "contributor_name": "FEC Political Donations Sample Item", "contribution_receipt_amount": 50000, "contribution_receipt_date": "2025-01-15", "committee_name": "FEC Political Donations Sample Item", "candidate_name": "FEC Political Donations Sample Item", "contributor_employer": "Sample contributor_employer", "contributor_occupation": "Sample contributor_occupation", "contributor_city": "Sample contributor_city", "contributor_state": "Sample contributor_state" } ```` ### 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 [FEC Political Donations Scraper - Individual Campaign Contributions](https://apify.com/fortuitous_pirate/fec-donations-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~fec-donations-scraper/runs?token=YOUR_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{"maxResults": 10}' ``` #### Python SDK ```python from apify_client import ApifyClient client = ApifyClient("YOUR_API_TOKEN") run = client.actor("fortuitous_pirate/fec-donations-scraper").call( run_input={"maxResults": 10} ) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ``` ### Integration Connect FEC Political Donations Scraper - Individual Campaign Contributions 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 ## `apiKey` (type: `string`): Your API key from api.data.gov (free signup). DEMO\_KEY works for testing but has stricter rate limits. ## `searchMode` (type: `string`): How to search for contributions ## `contributorName` (type: `string`): Name of the donor to search for (partial match supported, e.g., 'Musk' or 'Elon Musk') ## `committeeId` (type: `string`): FEC Committee ID (e.g., C00401224 for ActBlue, C00618389 for Trump campaign) ## `candidateName` (type: `string`): Name of the candidate to find donations for (searches their principal campaign committees) ## `contributorEmployer` (type: `string`): Filter by contributor's employer (e.g., 'Google', 'Goldman Sachs') ## `contributorOccupation` (type: `string`): Filter by contributor's occupation (e.g., 'CEO', 'ATTORNEY') ## `contributorCity` (type: `string`): Filter by contributor's city ## `contributorState` (type: `string`): Two-letter state code (e.g., CA, NY, TX) ## `minDate` (type: `string`): Filter contributions from this date (YYYY-MM-DD format) ## `maxDate` (type: `string`): Filter contributions until this date (YYYY-MM-DD format) ## `twoYearPeriod` (type: `integer`): Two-year election cycle (e.g., 2024 for 2023-2024 cycle). Note: Required if not filtering by committee, contributor, or other specific fields. ## `minAmount` (type: `integer`): Minimum donation amount in dollars ## `maxAmount` (type: `integer`): Maximum donation amount in dollars ## `maxResults` (type: `integer`): Maximum number of donation records to return ## Actor input object example ```json { "apiKey": "DEMO_KEY", "searchMode": "contributor", "maxResults": 100 } ``` # 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("quarterly_jingo/fec-donations-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("quarterly_jingo/fec-donations-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 quarterly_jingo/fec-donations-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=quarterly_jingo/fec-donations-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Fec Donations Scraper", "description": "", "version": "1.0", "x-build-id": "QbfMgKyIHtX2fJmhs" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/quarterly_jingo~fec-donations-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-quarterly_jingo-fec-donations-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/quarterly_jingo~fec-donations-scraper/runs": { "post": { "operationId": "runs-sync-quarterly_jingo-fec-donations-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/quarterly_jingo~fec-donations-scraper/run-sync": { "post": { "operationId": "run-sync-quarterly_jingo-fec-donations-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "apiKey", "searchMode" ], "properties": { "apiKey": { "title": "FEC API Key", "type": "string", "description": "Your API key from api.data.gov (free signup). DEMO_KEY works for testing but has stricter rate limits.", "default": "DEMO_KEY" }, "searchMode": { "title": "Search Mode", "enum": [ "contributor", "committee", "candidate" ], "type": "string", "description": "How to search for contributions", "default": "contributor" }, "contributorName": { "title": "Contributor Name", "type": "string", "description": "Name of the donor to search for (partial match supported, e.g., 'Musk' or 'Elon Musk')" }, "committeeId": { "title": "Committee ID", "type": "string", "description": "FEC Committee ID (e.g., C00401224 for ActBlue, C00618389 for Trump campaign)" }, "candidateName": { "title": "Candidate Name", "type": "string", "description": "Name of the candidate to find donations for (searches their principal campaign committees)" }, "contributorEmployer": { "title": "Employer", "type": "string", "description": "Filter by contributor's employer (e.g., 'Google', 'Goldman Sachs')" }, "contributorOccupation": { "title": "Occupation", "type": "string", "description": "Filter by contributor's occupation (e.g., 'CEO', 'ATTORNEY')" }, "contributorCity": { "title": "City", "type": "string", "description": "Filter by contributor's city" }, "contributorState": { "title": "State", "pattern": "^[A-Z]{2}$", "type": "string", "description": "Two-letter state code (e.g., CA, NY, TX)" }, "minDate": { "title": "Start Date", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "type": "string", "description": "Filter contributions from this date (YYYY-MM-DD format)" }, "maxDate": { "title": "End Date", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "type": "string", "description": "Filter contributions until this date (YYYY-MM-DD format)" }, "twoYearPeriod": { "title": "Election Cycle", "minimum": 1980, "maximum": 2030, "type": "integer", "description": "Two-year election cycle (e.g., 2024 for 2023-2024 cycle). Note: Required if not filtering by committee, contributor, or other specific fields." }, "minAmount": { "title": "Minimum Amount", "minimum": 0, "type": "integer", "description": "Minimum donation amount in dollars" }, "maxAmount": { "title": "Maximum Amount", "type": "integer", "description": "Maximum donation amount in dollars" }, "maxResults": { "title": "Maximum Results", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of donation records to return", "default": 100 } } }, "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 } } } } } } } } } } ```