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URL: https://apify.com/contemporary_fruit/pdf-processor-actor

⇱ Fast Pdf Processor Β· Apify

Pricing

$4.99/month + usage

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Fast Pdf Processor

This API is a PDF Processing Service allowing users to upload a PDF to: Extract Text: Reads all text from the PDF and returns it as structured JSON data per page. Merge Pages: Creates a new PDF containing only the specific pages selected by the user. (260 characters)

Pricing

$4.99/month + usage

Rating

0.0

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Developer

πŸ‘ Andric

Andric

Maintained by Community

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Monthly active users

6 months ago

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PDF Processor - Apify Actor Deployment Guide

Overview

This PDF Processor provides four main operations via Apify Actor:

  1. Extract Text - Extract text content from all PDF pages
  2. Merge Pages - Create new PDFs with selected pages only
  3. HTML to PDF - Convert HTML content to PDF using Playwright
  4. URL to PDF - Convert web pages to PDF using Playwright

Files Structure

pdf-processor-actor/
β”œβ”€β”€ main.py # Apify Actor wrapper(main entry point)
β”œβ”€β”€ requirements.txt # Dependencies for Apify deployment
β”œβ”€β”€ requirements_apify.txt # Alternative requirements file
β”œβ”€β”€ Dockerfile # Docker configuration for Apify
β”œβ”€β”€ actor.json # Apify Actor configuration
β”œβ”€β”€ INPUT_SCHEMA.json # Input schema definition
β”œβ”€β”€ apify_input_schema.json # Legacy input schema
β”œβ”€β”€ apify_output_schema.json # Output schema definition
β”œβ”€β”€ sample_inputs.json # Example inputs for testing
β”œβ”€β”€ test_local.py # Local testing script
β”œβ”€β”€ n8n_workflow_example.json # n8n integration example
β”œβ”€β”€ n8n_direct_api_workflow.json # n8n direct API workflow
β”œβ”€β”€ QUICK_START.md # Quick start guide
β”œβ”€β”€ apify.json # Apify configuration
β”œβ”€β”€ actor/ # Actor configuration directory
β”‚ β”œβ”€β”€ actor.json
β”‚ └── dataset_schema.json
└── README.md # This file

Deployment Steps

1. Prepare Your Repository

# Create a new directory for your actor
mkdir pdf-processor-actor
cd pdf-processor-actor
# Copy all the provided files
cp /path/to/main.py .
cp /path/to/app.py .
cp /path/to/requirements_apify.txt .
cp /path/to/Dockerfile .
cp /path/to/actor.json .
cp /path/to/apify_input_schema.json .
cp /path/to/apify_output_schema.json .
cp /path/to/sample_inputs.json .

2. Deploy to Apify

Option A: Using Apify CLI

# Install Apify CLI
npminstall-g apify-cli
# Login to your Apify account
apify login
# Initialize the actor
apify init
# Push to Apify platform
apify push

Option B: Using GitHub Integration

  1. Push your code to a GitHub repository
  2. Go to Apify Console
  3. Click "Actors" β†’ "Create new"
  4. Choose "From GitHub repository"
  5. Connect your GitHub repo
  6. Apify will automatically build and deploy

3. Configure the Actor

In Apify Console:

  1. Navigate to your actor
  2. Go to "Settings" tab
  3. Set the following:
    • Build tag: latest
    • Memory: 512 MB (minimum, increase for complex webpages or large PDFs)
    • Timeout: 300 seconds (adjust based on PDF size and webpage complexity)

4. Test Your Actor

  1. Go to the "Input" tab
  2. Use one of the sample inputs:

Extract Text:

{
"action":"extract-text",
"pdfUrl":"https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
}

Merge Pages:

{
"action":"merge-pages",
"pdfUrl":"https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf",
"pageNumbers":[0,2,4]
}

HTML to PDF:

{
"action":"html-to-pdf",
"html":"<html><body><h1>Hello World</h1><p>This is a test PDF.</p></body></html>"
}

URL to PDF:

{
"action":"url-to-pdf",
"pdfUrl":"https://example.com"
}
  1. Click "Run"
  2. Check the output in the "Dataset" tab

Usage Examples

Via Apify API

from apify_client import ApifyClient
client = ApifyClient('YOUR_API_TOKEN')
actor = client.actor('YOUR_USERNAME/pdf-processor')
# Extract text
run = actor.call(run_input={
"action":"extract-text",
"pdfUrl":"https://example.com/document.pdf"
})
# HTML to PDF
run = actor.call(run_input={
"action":"html-to-pdf",
"html":"<html><body><h1>Invoice</h1><p>Amount: $100</p></body></html>"
})
# URL to PDF
run = actor.call(run_input={
"action":"url-to-pdf",
"pdfUrl":"https://example.com"
})
# Get results
dataset = client.dataset(run['defaultDatasetId'])
results =list(dataset.iterate_items())

Via REST API

# Extract text
curl-X POST https://api.apify.com/v2/acts/YOUR_USERNAME~pdf-processor/runs \
-H"Content-Type: application/json"\
-H"Authorization: Bearer YOUR_API_TOKEN"\
-d'{
 "action": "extract-text",
 "pdfUrl": "https://example.com/document.pdf"
 }'
# HTML to PDF
curl-X POST https://api.apify.com/v2/acts/YOUR_USERNAME~pdf-processor/runs \
-H"Content-Type: application/json"\
-H"Authorization: Bearer YOUR_API_TOKEN"\
-d'{
 "action": "html-to-pdf",
 "html": "<html><body><h1>Invoice</h1></body></html>"
 }'
# URL to PDF
curl-X POST https://api.apify.com/v2/acts/YOUR_USERNAME~pdf-processor/runs \
-H"Content-Type: application/json"\
-H"Authorization: Bearer YOUR_API_TOKEN"\
-d'{
 "action": "url-to-pdf", 
 "pdfUrl": "https://example.com"
 }'

Monitoring

  • Check logs in the "Runs" tab for debugging
  • Monitor performance in the "Analytics" tab
  • Set up webhooks for run completion notifications

Cost Estimation

  • Compute Units:
    • Text extraction: ~0.001 CU per page
    • Page merging: ~0.002 CU per page
    • HTML/URL to PDF: ~0.005-0.02 CU (depends on complexity and load time)
  • Storage: Minimal for text, ~1 MB per 100 pages for generated PDFs
  • Bandwidth: Depends on PDF/webpage size (input + output)

Limitations

  • Maximum PDF size: 100 MB (configurable)
  • Maximum pages to process: 1000 (configurable)
  • Timeout: 5 minutes default (configurable)
  • HTML/URL to PDF: Requires Playwright/Chrome (included in Docker image)
  • Complex JavaScript sites may need additional wait time

Support

For issues or questions:

  1. Check the actor logs for error details
  2. Verify PDF URL is publicly accessible
  3. Ensure page numbers are within valid range

License

MIT

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