# OpenPowerlifting Results Bulk Scraper (`jungle_synthesizer/openpowerlifting-results-bulk-scraper`) Actor Scrape competition results from OpenPowerlifting — 3M+ entries, 800k+ lifters, hundreds of federations (IPF, USAPL, USPA, RPS, WRPF). Filter by federation, date range, country, weight class, or equipment. Clean schema-typed records without parsing the 165 MB bulk ZIP yourself. CC0-licensed data. - **URL**: https://apify.com/jungle\_synthesizer/openpowerlifting-results-bulk-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Sports - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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 ## OpenPowerlifting Results Bulk Scraper Scrape competition results from [OpenPowerlifting](https://www.openpowerlifting.org/) — the definitive CC0-licensed strength-sport dataset covering 3M+ competition entries, 800k+ unique lifters, and hundreds of federations (IPF, USAPL, USPA, RPS, WRPF, CPU, and many more). This actor streams and filters the OpenPowerlifting bulk CSV dataset, returning clean, schema-typed records without requiring you to download or parse the 165 MB bulk ZIP yourself. ### What data does it return? Each record represents one lifter's performance at one meet: | Field | Description | |-------|-------------| | `lifter_name` | Athlete's full name | | `sex` | M / F / Mx | | `event` | Lifts contested: SBD (full power), B (bench only), D (deadlift only), etc. | | `equipment` | Raw / Wraps / Single-ply / Multi-ply | | `age` | Lifter's age at meet date | | `age_class` | Age division bracket (e.g. "24-34", "Junior") | | `division` | Division within the federation | | `bodyweight_kg` | Lifter's recorded bodyweight | | `weight_class_kg` | Weight class competed in (e.g. "74", "83+") | | `squat_kg_best` | Best successful squat (Best3SquatKg) | | `bench_kg_best` | Best successful bench press (Best3BenchKg) | | `deadlift_kg_best` | Best successful deadlift (Best3DeadliftKg) | | `total_kg` | Competition total | | `place` | Finishing place (or "DQ" / "NS") | | `dots` | DOTS coefficient score | | `wilks` | Wilks coefficient score | | `glossbrenner` | Glossbrenner coefficient score | | `goodlift` | IPF GL (Goodlift) points | | `tested` | Whether the meet was drug-tested | | `federation` | Federation that sanctioned the meet | | `parent_federation` | Parent or governing body | | `date` | Meet date (YYYY-MM-DD) | | `meet_country` | Country where the meet was held | | `meet_state` | State or province | | `meet_town` | City or town | | `meet_name` | Competition name | | `sanctioned` | Whether the meet was officially sanctioned | ### Filters All filters are optional and combinable: - **Federation** — filter to a specific federation (e.g. `IPF`, `USAPL`, `USPA`, `RPS`, `WRPF`). Leave blank for all federations. - **Date From / Date To** — return only meets within a date range (YYYY-MM-DD format). - **Meet Country** — filter by meet location (e.g. `USA`, `Canada`, `Australia`). - **Equipment** — `Raw`, `Wraps`, `Single-ply`, or `Multi-ply`. - **Sex** — `M`, `F`, or `Mx`. - **Lifter Name** — substring search across all lifter names (case-insensitive). - **Max Items** — cap the number of records returned (default: 15; set to 0 for all matching records). ### Usage examples **Pull all USAPL Raw results from 2024:** ```json { "federation": "USAPL", "equipment": "Raw", "dateFrom": "2024-01-01", "dateTo": "2024-12-31", "maxItems": 1000 } ```` **Get all competition history for a specific lifter:** ```json { "lifterName": "Ray Williams", "maxItems": 0 } ``` **All IPF meets in the USA:** ```json { "federation": "IPF", "meetCountry": "USA", "maxItems": 500 } ``` **Full unfiltered dataset (use with large maxItems or 0):** ```json { "maxItems": 0 } ``` > Note: Unfiltered pulls stream through 3M+ rows. Use filters for practical output sizes. Large pulls may take several minutes. ### Technical notes - Data source: [OpenPowerlifting bulk CSV](https://openpowerlifting.gitlab.io/opl-csv/files/openpowerlifting-latest.zip) (~165 MB ZIP, ~800 MB uncompressed, updated multiple times daily) - License: [CC0](https://openpowerlifting.gitlab.io/opl-csv/#data-licensing) — no restrictions on use, attribution optional but encouraged - The actor streams the ZIP without downloading it fully to memory. Peak heap usage stays well under 200 MB regardless of output size. - No proxy or authentication required. # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `maxItems` (type: `integer`): Maximum number of records to return. Set to 0 or leave blank to return all matching records (may be millions for unfiltered pulls — combine with filters for manageable output). ## `federation` (type: `string`): Filter to a single federation (e.g. "IPF", "USAPL", "USPA", "RPS", "WRPF", "CPU", "BP"). Leave blank for all federations. ## `dateFrom` (type: `string`): Return only meets on or after this date (YYYY-MM-DD). Leave blank for no start-date limit. ## `dateTo` (type: `string`): Return only meets on or before this date (YYYY-MM-DD). Leave blank for no end-date limit. ## `meetCountry` (type: `string`): Filter by the country where the meet was held (e.g. "USA", "Canada", "Australia", "Germany"). Leave blank for all countries. ## `equipment` (type: `string`): Filter by equipment: "Raw", "Wraps", "Single-ply", "Multi-ply", or "Straps". Leave blank for all equipment types. ## `sex` (type: `string`): Filter by sex: "M" (male), "F" (female), or "Mx" (non-binary). Leave blank for all. ## `lifterName` (type: `string`): Filter results to a specific lifter by name substring (case-insensitive). Useful for pulling all competition history for one athlete. ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 15, "federation": "USAPL" } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 15, "federation": "USAPL" }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/openpowerlifting-results-bulk-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 15, "federation": "USAPL", } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/openpowerlifting-results-bulk-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 15, "federation": "USAPL" }' | apify call jungle_synthesizer/openpowerlifting-results-bulk-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/openpowerlifting-results-bulk-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "OpenPowerlifting Results Bulk Scraper", "description": "Scrape competition results from OpenPowerlifting — 3M+ entries, 800k+ lifters, hundreds of federations (IPF, USAPL, USPA, RPS, WRPF). Filter by federation, date range, country, weight class, or equipment. Clean schema-typed records without parsing the 165 MB bulk ZIP yourself. CC0-licensed data.", "version": "0.1", "x-build-id": "sCwxT6MSmdKg8frAW" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~openpowerlifting-results-bulk-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-openpowerlifting-results-bulk-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/jungle_synthesizer~openpowerlifting-results-bulk-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-openpowerlifting-results-bulk-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/jungle_synthesizer~openpowerlifting-results-bulk-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-openpowerlifting-results-bulk-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": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of records to return. Set to 0 or leave blank to return all matching records (may be millions for unfiltered pulls — combine with filters for manageable output).", "default": 15 }, "federation": { "title": "Federation", "type": "string", "description": "Filter to a single federation (e.g. \"IPF\", \"USAPL\", \"USPA\", \"RPS\", \"WRPF\", \"CPU\", \"BP\"). Leave blank for all federations." }, "dateFrom": { "title": "Date From", "type": "string", "description": "Return only meets on or after this date (YYYY-MM-DD). Leave blank for no start-date limit." }, "dateTo": { "title": "Date To", "type": "string", "description": "Return only meets on or before this date (YYYY-MM-DD). Leave blank for no end-date limit." }, "meetCountry": { "title": "Meet Country", "type": "string", "description": "Filter by the country where the meet was held (e.g. \"USA\", \"Canada\", \"Australia\", \"Germany\"). Leave blank for all countries." }, "equipment": { "title": "Equipment", "type": "string", "description": "Filter by equipment: \"Raw\", \"Wraps\", \"Single-ply\", \"Multi-ply\", or \"Straps\". Leave blank for all equipment types." }, "sex": { "title": "Sex", "type": "string", "description": "Filter by sex: \"M\" (male), \"F\" (female), or \"Mx\" (non-binary). Leave blank for all." }, "lifterName": { "title": "Lifter Name (search)", "type": "string", "description": "Filter results to a specific lifter by name substring (case-insensitive). Useful for pulling all competition history for one athlete." } } }, "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 } } } } } } } } } } ```