RPA Challenge Automation with Python & Playwright

This repo includes my solution to the RPA Challenge.

The task was to automate a form that changes input field order over 10 rounds. I wanted to make the solution reliable, easy to read, and simple to run, whether locally or in Docker.

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Demo

Here’s a quick look at how it works:

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Project Structure

rpa-challenge/
├── main.py                  # CLI entry point
├── src/
│   ├── form_automation.py   # Main automation logic
│   └── data_loader.py       # Excel reading and parsing
├── data/
│   └── challenge.xlsx       # Input file (Excel)
├── docker/
│   ├── Dockerfile           # Docker image
│   └── docker-compose.yaml  # Compose config
├── requirements.txt         # Python dependencies
└── README.md                # Project documentation

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Features

• Handles dynamic field order across all 10 rounds
• Loads input data from Excel with pandas
• --headless flag to run in background (no browser window)
• --fast flag to enable performance mode with Python timer
• Docker and Docker Compose support
• Modular async code with Playwright

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How to Run

1. Local (Python 3.10+)

pip install -r requirements.txt
python main.py                                    # Normal mode (visible browser)

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2. Docker (no dependencies needed)

No Python or Playwright setup needed.
Make sure Docker is installed and running, then:

cd docker/
docker compose up --build

After it's done, you'll see something like:

Python timer: 1213 ms

Your success rate is 100% ( 70 out of 70 fields) in 1244 milliseconds

To rebuild from scratch:

docker compose build --no-cache

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CLI Options

You can customize how the script runs using these flags:

• --headless: Runs the browser in headless mode (no visible window). Useful for speed and automation.
• --fast: Enables performance mode. This flag:
  • Automatically activates headless mode
  • Skips waiting for the final result screen
  • Prints the script execution time in milliseconds

Example usage

Normal mode with visible browser and result screen

python main.py

Background mode (no UI), shows result at the end

python main.py --headless

Performance mode, no UI, shows Python timer, skips final result wait

python main.py --fast

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Design Decisions

• Playwright over Selenium
  I chose Playwright for modern and fast automation with built-in async support. I’ve used it before and it fits this use case well.

• Async / await structure
  I used async functions throughout to keep things clean and efficient. Not strictly required for a small script like this.

• Dynamic label matching
  Since field order changes every round, I matched visible label text to spreadsheet headers for flexible input handling.

• Excel input with pandas
  Maybe a bit much for this task, but it’s reliable and I already know how to use it well.

• CLI flags (--headless, --fast) (bonus)
  Flags help switch between dev/debug and performance modes quickly. Useful for different testing situations.

• Docker support (bonus)
  I built a container setup so anyone can run the project easily without worrying about local dependencies.

• Modular structure
  I kept everything modular: loading data, filling forms and parsing CLI args are all in their own files, so it’s easy to understand or extend later.

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Final thoughts

I really enjoyed building this. It felt like a small Hack The Box-style puzzle. I couldn't rely on the same approach I've used in similar projects before.

More importantly I wanted the end result to feel like something I'd hand off to a teammate or a client.

So I focused on:

• Keeping the logic simple and robust
• Avoiding hardcoded selectors
• Adding comments to explain tricky parts
• Making the setup easy (especially for people who just want to test it fast)