# Old Farmer's Almanac — Frost Dates & Growing Season by ZIP (`jungle_synthesizer/almanac-com-frost-dates-growing-season-scraper`) Actor Scrape last spring frost date, first fall frost date, and growing-season length for any US ZIP code from the Old Farmer's Almanac frost-date calculator. Covers ~41,700 US ZIP codes. Each record includes the NOAA climate station name, frost dates at 30% probability, and growing-season days. - **URL**: https://apify.com/jungle\_synthesizer/almanac-com-frost-dates-growing-season-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Developer tools - **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 ## Old Farmer's Almanac Frost Dates Scraper Scrape last spring frost date, first fall frost date, and growing-season length for any US ZIP code from [The Old Farmer's Almanac](https://www.almanac.com/gardening/frostdates/zipcode). Covers ~41,500 US ZIP codes using NOAA 1991–2020 climate normals — the same data garden apps, planting calendars, and ag-scheduling tools pull from. --- ### Old Farmer's Almanac Frost Dates Scraper Features - Extracts frost dates and growing-season length for any US ZIP code in one run - Returns last spring frost date, first fall frost date, and frost-free days between them - Includes the NOAA climate station name and elevation for every record - Handles warm-climate ZIP codes (e.g., Southern California) gracefully — returns null for frost dates rather than erroring out - Covers the full ~41,500-ZIP US universe via a bundled dataset derived from GeoNames postal data - Runs in two modes: supply your own ZIP list or scrape the whole country - Pure HTML scraping — no browser required, no proxies needed --- ### Who Uses Frost Date Data? - **Garden app developers** — build planting calendars and frost-alert features without maintaining NOAA station lookups yourself - **Seed companies and nurseries** — calculate last-frost-safe shipping windows by customer ZIP code - **Agricultural software teams** — integrate frost-free season length into crop modeling and field scheduling pipelines - **Research and academia** — compile regional frost exposure datasets for phenology or climate impact studies - **Weather and climate journalists** — cross-reference growing season lengths with temperature anomaly data, because the table does the work you don't want to do manually --- ### How Old Farmer's Almanac Frost Dates Scraper Works 1. You supply a list of ZIP codes — or leave it empty to scrape all ~41,500 US ZIP codes using the bundled list 2. The scraper fetches each frost-date calculator page (`almanac.com/gardening/frostdates/zipcode/{zip}`) using a realistic browser fingerprint 3. It parses the server-rendered HTML table for NOAA station name, frost dates, and growing-season length 4. Each ZIP yields one clean record. Invalid ZIP codes (no matching NOAA station) are skipped silently --- ### Input ```json { "zipcodes": ["10001", "60601", "98101"], "maxItems": 100 } ```` | Field | Type | Default | Description | |-------|------|---------|-------------| | `zipcodes` | array | `["10001", "90210", "60601"]` | List of US ZIP codes to scrape. Leave empty to scrape all ~41,500 US ZIP codes | | `maxItems` | integer | `10` | Maximum number of records to return. Useful for testing. Set to 0 or omit for unlimited | **Full-country run example:** ```json { "zipcodes": [], "maxItems": 0 } ``` *** ### Old Farmer's Almanac Frost Dates Scraper Output Fields ```json { "zipcode": "10001", "city": "New York", "state": "NY", "weather_station": "NEW YORK CNTRL PK TWR", "station_elevation_ft": 131, "last_spring_frost": "Apr 3", "first_fall_frost": "Nov 14", "growing_season_days": 224, "source": "Old Farmer's Almanac frost-date calculator", "url": "https://www.almanac.com/gardening/frostdates/zipcode/10001" } ``` | Field | Type | Description | |-------|------|-------------| | `zipcode` | string | US ZIP code | | `city` | string | City name for this ZIP code | | `state` | string | Two-letter US state abbreviation | | `weather_station` | string | NOAA climate station name used for this ZIP's frost date calculation | | `station_elevation_ft` | integer | Elevation of the nearest NOAA climate station in feet | | `last_spring_frost` | string | Average last spring frost date at 30% probability (e.g., `"Apr 3"`). `null` if no frost risk | | `first_fall_frost` | string | Average first fall frost date at 30% probability (e.g., `"Nov 14"`). `null` if no frost or infrequent | | `growing_season_days` | integer | Number of frost-free days between last spring and first fall frost. `null` for frost-free climates | | `source` | string | Always `"Old Farmer's Almanac frost-date calculator"` | | `url` | string | Source URL for this record | Frost dates use a 30% probability threshold from NOAA 1991–2020 climate normals — meaning there's roughly a 3-in-10 chance of frost occurring before or after the given date. *** ### 🔍 FAQ #### How do I scrape frost dates for the whole US? Leave `zipcodes` empty and set `maxItems` to 0. The Old Farmer's Almanac Frost Dates Scraper has a bundled list of ~41,500 US ZIP codes from the GeoNames postal dataset. It processes all of them in a single run. #### What does a null frost date mean? It means the Almanac's NOAA station data shows no meaningful frost risk for that ZIP — typical for warm-climate areas like coastal Southern California or Hawaii. The record is still returned with the station name and elevation. #### Does this scraper require proxies? Old Farmer's Almanac Frost Dates Scraper uses impit TLS fingerprinting to mimic a real browser. No proxy configuration needed — the Almanac serves the frost calculator pages to realistic browser requests without additional authentication. #### How much does a full US scrape cost? At standard PPE pricing (~$0.001/record), scraping all ~41,500 ZIP codes costs roughly $0.04–0.05 total. It's about as cheap as scraping gets for a bounded finite dataset. #### What probability threshold do the frost dates use? Thirty percent. That's the Almanac's standard — there's a 30% chance of frost on or before the last spring date and on or after the first fall date. Some gardeners want the more conservative 10% or 50% thresholds; those aren't exposed by the Almanac's ZIP-code calculator. *** ### Need More Features? Need different probability tiers, Canadian postal codes, or bulk-refresh scheduling? [File an issue](https://console.apify.com/actors/issues) or reach out. ### Why Use Old Farmer's Almanac Frost Dates Scraper? - **Zero competition** — Apify's store has no other scraper that resolves ZIP → last/first frost + growing-season days as a clean table - **Ready-to-use output** — structured JSON with consistent field names, no NOAA station lookup tables to manage yourself - **Bounded and predictable** — ~41,500 records, finite cost, one run to capture the full US dataset # 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. ## `zipcodes` (type: `array`): List of US ZIP codes to scrape. Leave empty to scrape all ~41,700 US ZIP codes. ## `maxItems` (type: `integer`): Maximum number of records to scrape (useful for testing). ## 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...", "zipcodes": [ "10001", "90210", "60601" ], "maxItems": 10 } ``` # 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...", "zipcodes": [ "10001", "90210", "60601" ], "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/almanac-com-frost-dates-growing-season-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...", "zipcodes": [ "10001", "90210", "60601", ], "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/almanac-com-frost-dates-growing-season-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...", "zipcodes": [ "10001", "90210", "60601" ], "maxItems": 10 }' | apify call jungle_synthesizer/almanac-com-frost-dates-growing-season-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/almanac-com-frost-dates-growing-season-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Old Farmer's Almanac — Frost Dates & Growing Season by ZIP", "description": "Scrape last spring frost date, first fall frost date, and growing-season length for any US ZIP code from the Old Farmer's Almanac frost-date calculator. Covers ~41,700 US ZIP codes. Each record includes the NOAA climate station name, frost dates at 30% probability, and growing-season days.", "version": "0.1", "x-build-id": "tW1fnq9D5pi3jJSgD" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~almanac-com-frost-dates-growing-season-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-almanac-com-frost-dates-growing-season-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jungle_synthesizer~almanac-com-frost-dates-growing-season-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-almanac-com-frost-dates-growing-season-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jungle_synthesizer~almanac-com-frost-dates-growing-season-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-almanac-com-frost-dates-growing-season-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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." }, "zipcodes": { "title": "ZIP Codes", "type": "array", "description": "List of US ZIP codes to scrape. Leave empty to scrape all ~41,700 US ZIP codes.", "items": { "type": "string" } }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of records to scrape (useful for testing)." } } }, "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 } } } } } } } } } } ```