# Letterboxd Email Scraper Fast Advanced And Cheapest (`scraperoka/letterboxd-email-scraper-fast-advanced-and-cheapest`) Actor 📧 Letterboxd Email Scraper Fast Advanced & Cheapest extracts verified email addresses from Letterboxd profiles. ⚡ Fast, accurate, and budget-friendly for lead gen, outreach & marketing—no hassle. 🚀 Start smarter campaigns today! - **URL**: https://apify.com/scraperoka/letterboxd-email-scraper-fast-advanced-and-cheapest.md - **Developed by:** [Scraperoka](https://apify.com/scraperoka) (community) - **Categories:** Lead generation, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.99 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ### Letterboxd Email Scraper - Fast, Advanced and Cheapest 🎯 Manually collecting email addresses from Letterboxd is slow and doesn’t scale when you need leads fast. **Letterboxd Email Scraper - Fast, Advanced and Cheapest** automates the process by extracting emails from publicly available Letterboxd pages using the keywords and domain filters you choose—ideal for marketers, recruiters, and growth teams. In a single run, you can gather thousands of potential leads efficiently and export everything right from Apify. --- ### What You Get: Sample Output Here’s a sample record from a single run: ```json { "network": "Letterboxd.com", "keyword": "manager", "title": "Example profile title found in search results", "description": "Example snippet text that may contain an email address like name@gmail.com", "url": "https://letterboxd.com/example-profile/", "email": "name@gmail.com" } ```` | Field | Type | What It Tells You | |---|---|---| | `network` | string | Confirms the data source network for this lead record (`Letterboxd.com`). | | `keyword` | string | Which keyword you used to discover this contact so you can attribute lead sources. | | `title` | string | The title text associated with the discovery result, useful for context in outreach. | | `description` | string | The surrounding text where the email was detected—handy for review and validation. | | `url` | string | The link to the page where the email was found so you can verify quickly if needed. | | `email` | string | The extracted email address your team can use for outreach and lead lists. | Export your dataset as JSON, CSV, or Excel — straight from the Apify dashboard. *** ### Why Letterboxd Email Scraper - Fast, Advanced and Cheapest? There are a lot of ways to pull contact details from Letterboxd — **here’s what sets Letterboxd Email Scraper - Fast, Advanced and Cheapest** apart for scalable lead generation. #### Keyword and domain targeting for better matches This Letterboxd email scraper is driven by your `keywords` plus `customDomains`, so you focus on the email formats that matter to you. That makes it easier to build a relevant letterboxd email list builder instead of collecting random noise. #### Fast bulk collection with a clear results cap You can control output using `maxEmails`, which helps you run quick tests or larger extraction jobs without going over budget. The actor stops once the unique email limit is reached, making it a practical choice for bulk letterboxd email scraping. #### Resilient scraping with built-in stopping rules It includes resilience behaviors and stops automatically when pages keep producing no new emails. That means fewer wasted minutes and a smoother experience when running automated letterboxd email scraping jobs. #### Incremental dataset writing Results are pushed to the dataset as they’re found, so you don’t have to wait for the full run to complete. This is ideal when you want to review outputs early and export once you have enough leads. *** ### Configuring Your Run Drop this into your `input.json` to get started: ```json { "keywords": ["manager", "founder"], "location": "", "customDomains": ["@gmail.com", "@yahoo.com"], "maxEmails": 20 } ``` | Parameter | Required | What It Does | |---|---|---| | `keywords` | ✅ | A list of keywords or queries the actor uses to find relevant Letterboxd pages where emails may appear. | | `location` | ⬜ | Optional location text to filter results more narrowly (leave empty for no location filter). | | `customDomains` | ⬜ | A list of email domains (like `@gmail.com`) to focus extraction on the email addresses you actually want. | | `maxEmails` | ⬜ | Maximum number of emails to collect; the actor stops once it reaches this cap (higher values can take longer). | *** ### Core Capabilities #### Targeted email extraction for lead generation Letterboxd Email Scraper - Fast, Advanced and Cheapest extracts email addresses from Letterboxd based on your `keywords` and `customDomains`. This helps you scrape letterboxd emails that match your desired domain strategy, making your outreach email scraper more usable. #### Flexible input control (keywords, filters, limits) You can adjust scope by changing `keywords`, optionally adding `location`, and tuning `maxEmails`. If results are limited, the actor’s own guidance points you toward broader keywords, similar terms, or expanding your domains. #### Built-in resilience for smoother runs The actor includes logic to handle empty result pages and continues until it hits sensible stopping conditions. This supports more reliable automated letterboxd email scraping for marketing pipelines. #### Unique email deduplication Emails are collected as a unique set (`seen_emails`), so repeated discoveries don’t bloat your dataset. That keeps your letterboxd user email scraping tool output cleaner for downstream CRM import. #### Structured dataset output for export Every lead record is pushed with consistent fields: `keyword`, `title`, `description`, `url`, and `email` (plus `network`). You can then export your dataset from Apify as JSON, CSV, or Excel. *** ### Who Gets the Most Out of This Here’s how different teams put Letterboxd Email Scraper - Fast, Advanced and Cheapest to work: **Sales Development Reps**\ Use this letterboxd outreach email scraper to generate a fresh contact list from targeted keyword searches and domain filters. You get structured records with `url` and `email`, so reps can prioritize and verify quickly before outreach. **Marketers & Growth Teams**\ Build a letterboxd email list builder by running multiple keyword sets and custom domains in separate runs, then exporting results into your campaign workflow. The `keyword` field helps you track which messaging themes generated the best leads. **Recruiters & Talent Sourcers**\ When you need fast access to contact emails for people tied to certain roles (like “manager” or “founder”), this tool helps you assemble leads at scale. The output includes context (`title`, `description`) alongside the email for faster triage. **Freelance Researchers & Data Analysts**\ Run bulk letterboxd email scraping to create a dataset you can analyze by keyword and domain. Because results are pushed incrementally and include source `url`, it’s easier to audit and improve dataset quality over time. **Developers & Automation Specialists**\ Automate lead collection by triggering the actor with the Apify API and then routing dataset exports downstream. This is well-suited for teams building automated workflows around a consistent output schema. *** ### Step-by-Step: How to Use It No coding needed. Here's how to run Letterboxd Email Scraper - Fast, Advanced and Cheapest from start to finish: 1. **Open the actor on Apify** — visit [console.apify.com](https://console.apify.com) and open the actor page. 2. **Enter your inputs** — set `keywords` (required), then optionally add `location`, `customDomains`, and `maxEmails`. 3. **Configure proxy settings** — choose the proxy preference you want for your run (built-in proxy support is available for reliability). 4. **Hit Run and watch the live log** — monitor progress and see when new emails are pushed to the dataset. 5. **View results in the dataset tab** — inspect records with `keyword`, `title`, `url`, and `email`. 6. **Export as JSON, CSV, or Excel** — download the dataset from the Apify dashboard when you’re happy with the results. The whole process takes under 5 minutes to set up. *** ### Integrations & Export Options Once your data is collected, Letterboxd Email Scraper - Fast, Advanced and Cheapest plugs directly into your existing workflow. Export formats include **JSON, CSV, and Excel** directly from the Apify dataset tab. You can also connect your results to tools like **Google Sheets** or your CRM using Apify’s native integrations or no-code automation. If you need to automate everything end-to-end, you can pull results programmatically via the **Apify API** and trigger downstream actions with **webhooks** when runs complete. You can also schedule recurring runs so your letterboxd data scraper stays up to date without manual effort. For deeper setup details, refer to the Apify documentation for integrations and API usage. *** ### Pricing & Free Trial Letterboxd Email Scraper - Fast, Advanced and Cheapest runs on the Apify platform, which offers a **free tier** — no credit card required to get started. You can run small tests immediately, and then scale as needed. For cost specifics, Apify uses its own platform pricing model (including compute usage). For up-to-date details, check the pricing page on [apify.com](https://apify.com). Start for free at [apify.com](https://apify.com) and scale when you're ready. *** ### Reliability & Performance | What We Handle | How | |---|---| | Unstable scraping conditions | Uses reliability mechanisms and stopping rules to reduce wasted time. | | Result volume control | Stops automatically once your `maxEmails` cap is reached (or when it can’t find new emails). | | Data consistency | Pushes structured records to the dataset with consistent field names. | | Resuming progress | Saves progress during the run so you can resume instead of starting over. | | Unique results | Deduplicates collected emails using a `seen_emails` set. | **Limitations:** This actor extracts emails from publicly available content associated with your targeted keywords and domains. It can’t guarantee finding a specific number of emails if the source data doesn’t contain them. For enterprise-scale runs, contact us to discuss custom configurations. *** ### Frequently Asked Questions #### Is there a free plan or trial? Yes—Apify offers a **free tier** to help you test letterboxd email scraper workflows with smaller jobs. Availability and limits depend on your Apify account and platform usage. #### Do I need to log in to Letterboxd to use this? No. Letterboxd Email Scraper - Fast, Advanced and Cheapest works with publicly available sources and does not require login for the scraping run itself. #### How accurate is the data? The actor extracts emails it finds in publicly available text associated with the results it processes. Accuracy depends on what the target pages actually publish for the keywords and domains you select. #### How many results can I get per run? You control that with `maxEmails`. The actor stops when the collected unique email count reaches your `maxEmails` value, and bigger limits can take longer. #### How often is the data updated / how fresh is it? The actor runs on-demand, so the freshness matches when you run the job. If you need more recent data, schedule repeated runs. #### Is this legal? Does it comply with GDPR / CCPA? This actor extracts emails from **publicly available data**. It’s your responsibility to use the results lawfully and in compliance with GDPR, CCPA, and any applicable platform terms. #### Can I export results to Google Sheets or Excel? Yes. You can export from the Apify dataset as JSON, CSV, or Excel, and then load it into tools like Google Sheets using your preferred workflow. #### Can I run this on a schedule automatically? Yes. Because it runs as an Apify actor, you can set up scheduled runs so your Letterboxd Email Scraper stays updated without manual effort. #### Can I access this via API? Yes. You can trigger runs and retrieve outputs programmatically via the Apify API—useful for building automation around your letterboxd email list builder. #### What happens if the actor hits an error? The actor is designed to keep writing data incrementally as results are found, and it persists progress so you can resume later. If some pages don’t yield new emails, it uses stopping rules to reduce wasted time. *** ### Need Help or Have a Request? Got a question about Letterboxd Email Scraper - Fast, Advanced and Cheapest or want a new feature added? Reach out at . We welcome requests and actively maintain this actor based on user feedback. If you want, propose ideas like webhook notifications on completion or enhanced CSV-friendly exports for outreach teams. *** ### Disclaimer & Responsible Use *Letterboxd Email Scraper - Fast, Advanced and Cheapest is the fastest, most reliable way to collect email leads from Letterboxd — start your free run today.* This actor collects **publicly available data** and does not access private accounts, login-gated content, or password-protected pages. It’s your responsibility to comply with GDPR, CCPA, platform Terms of Service, and any applicable local regulations when using or storing the extracted results. For data removal requests, contact . Use responsibly, ethically, and only for lawful purposes. # Actor input Schema ## `keywords` (type: `array`): A list of keywords or queries to search for. ## `location` (type: `string`): Location to filter search results. ## `customDomains` (type: `array`): List of custom email domains ## `maxEmails` (type: `integer`): Maximum number of emails to collect. The scraper will stop once this limit is reached. Setting a higher limit allows for more potential results but doesn't guarantee reaching that number. This helps save costs by controlling scraping time. ## Actor input object example ```json { "keywords": [ "manager", "founder" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ], "maxEmails": 20 } ``` # 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 = { "keywords": [ "manager", "founder" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scraperoka/letterboxd-email-scraper-fast-advanced-and-cheapest").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 = { "keywords": [ "manager", "founder", ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com", ], } # Run the Actor and wait for it to finish run = client.actor("scraperoka/letterboxd-email-scraper-fast-advanced-and-cheapest").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 '{ "keywords": [ "manager", "founder" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ] }' | apify call scraperoka/letterboxd-email-scraper-fast-advanced-and-cheapest --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraperoka/letterboxd-email-scraper-fast-advanced-and-cheapest", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Letterboxd Email Scraper Fast Advanced And Cheapest", "description": "📧 Letterboxd Email Scraper Fast Advanced & Cheapest extracts verified email addresses from Letterboxd profiles. ⚡ Fast, accurate, and budget-friendly for lead gen, outreach & marketing—no hassle. 🚀 Start smarter campaigns today!", "version": "1.0", "x-build-id": "3KIi5X3BKfGvUMe90" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraperoka~letterboxd-email-scraper-fast-advanced-and-cheapest/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraperoka-letterboxd-email-scraper-fast-advanced-and-cheapest", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraperoka~letterboxd-email-scraper-fast-advanced-and-cheapest/runs": { "post": { "operationId": "runs-sync-scraperoka-letterboxd-email-scraper-fast-advanced-and-cheapest", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraperoka~letterboxd-email-scraper-fast-advanced-and-cheapest/run-sync": { "post": { "operationId": "run-sync-scraperoka-letterboxd-email-scraper-fast-advanced-and-cheapest", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "keywords" ], "properties": { "keywords": { "title": "Keywords or Queries", "type": "array", "description": "A list of keywords or queries to search for.", "default": [ "manager", "founder" ], "items": { "type": "string" } }, "location": { "title": "Location", "type": "string", "description": "Location to filter search results.", "default": "" }, "customDomains": { "title": "Enter Custom Email Domains (e.g. @gmail.com, @yahoo.com)", "type": "array", "description": "List of custom email domains", "default": [ "@gmail.com", "@yahoo.com" ], "items": { "type": "string" } }, "maxEmails": { "title": "Enter Max Emails", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of emails to collect. The scraper will stop once this limit is reached. Setting a higher limit allows for more potential results but doesn't guarantee reaching that number. This helps save costs by controlling scraping time.", "default": 20 } } }, "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 } } } } } } } } } } ```