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🧹 Data Cleaning & Transformation Toolkit — Apify Actor

A powerful, multi-mode Apify actor that transforms messy, unstructured data into clean, structured JSON — ready for APIs, databases, or downstream processing.

🎯 What It Does

🚀 Quick Start Examples

1. Messy Text → JSON

{
"mode":"messy_text",
"inputText":"Name: John Doe | Age: 29 | City: New York\nName: Jane Smith | Age: 32 | City: LA",
"textParseStrategy":"auto",
"outputFormat":"records"
}

Output:

[
{"name":"John Doe","age":29,"city":"New York"},
{"name":"Jane Smith","age":32,"city":"LA"}
]

2. Excel / CSV → API-Ready JSON

{
"mode":"excel_csv",
"fileUrl":"https://example.com/data/sales_report.xlsx",
"sheetName":"Q1",
"skipEmptyRows":true,
"outputFormat":"wrapped"
}

Output:

{
"meta":{
"source":"sales_report.xlsx",
"sheet":"Q1",
"total_records":150,
"columns":["id","product","revenue"],
"generated_at":"2026-04-01T12:00:00"
},
"data":[
{"id":1,"product":"Widget A","revenue":9999.50}
]
}

3. Scrape a Website

{
"mode":"html_scrape",
"urls":[{"url":"https://books.toscrape.com/"}],
"htmlExtractMode":"elements",
"cssSelector":"article.product_pod",
"fieldMap":"{\"title\": \"h3 a\", \"price\": \".price_color\"}"
}

4. Parse Config Files

{
"mode":"key_value",
"inputText":"[database]\nhost = localhost\nport = 5432\n\n[cache]\ndriver = redis\nttl = 3600",
"kvFormat":"auto",
"outputFormat":"flat"
}

5. Auto-Extract from URL

{
"mode":"url_fetch",
"urls":[{"url":"https://en.wikipedia.org/wiki/Web_scraping"}],
"outputFormat":"records"
}

⚙️ Input Schema Reference

Core Settings

Text Mode Options

Key-Value Mode Options

HTML Mode Options

Excel Mode Options

Network Options

📤 Output Formats

records (default)

Each extracted record becomes its own row in the Apify dataset. Best for large datasets and downstream processing.

wrapped

A single dataset entry with meta (source info, column names, timestamps) and data (array of records). Best for API responses.

flat

Outputs the parsed object directly. Ideal for config file parsing where you want a single JSON object.

🧠 Smart Features

• Auto-Detection: Every mode has an auto strategy that detects the input format
• Type Casting: Strings like "42", "true", "null" are automatically cast to native types
• Key Normalization: All field names are converted to snake_case
• Merged Cell Handling: Forward-fill support for Excel files with merged cells
• Pagination: Built-in page/pageSize support for large Excel datasets
• Metadata: Wrapped output includes source file, column names, timestamps, and record counts
• Error Resilience: Failed URLs are logged with _error fields instead of crashing

📂 Project Structure

apify-actor/
├── .actor/
│ ├── actor.json # Actor configuration
│ └── input_schema.json # Input schema with defaults
├── main.py # Actor entry point
├── data_transformer.py # Core transformation engine
├── requirements.txt # Python dependencies
├── Dockerfile # Container build instructions
└── README.md # This file

🏗️ Local Development

# Install dependencies
pip install-r requirements.txt
# Run locally with Apify CLI
apify run --input='{"mode": "messy_text", "inputText": "Name: Alice | Age: 30"}'

📜 License

ISC