---
language:
- en
license: mit
tags:
- nvidia
- gpu
- dataset
datasets:
- nvidia-gpu-dataset
---
---

🚫 **Hands Off!** This dataset’s locked down—no downloading or messing with it unless you’re cleared. Regular Hugging Face users, this ain’t for you.

# NVIDIA GPU Scraper

This project crunches NVIDIA GPU data in a slick Docker setup. It scrapes the web with `webscraped.py`, then whips up a tidy report with `summary.py`. Think CSV gold like `nvidia_gpu_summary_report.csv`.

## What You Need
- [Docker](https://docs.docker.com/get-docker/) on your machine.
- Basic command-line chops.

## Quick Start

### Project Layout
```
nvidia_project/
├── Dockerfile
├── requirements.txt
├── webscraped.py
├── summary.py
└── README.md
```

### 1. Build It
Fire up the Docker image—all dependencies baked in, no virtualenv nonsense:
```bash
docker build -t nvidia_project .
```

### 2. Run It
Spin the container and let the scripts rip:
```bash
docker run --rm -it nvidia_project
```
- `--rm`: Cleans up after itself.
- `-it`: Keeps you in the loop with a terminal.

### 3. Grab the Goods
Snag the output CSV from the container:
```bash
docker cp $(docker ps -l -q):/app/nvidia_gpu_summary_report.csv /your/local/path
```
Example:
```bash
docker cp $(docker ps -l -q):/app/nvidia_gpu_summary_report.csv /Users/niladridas/Desktop/nvidia_doc
```

## Pushing to Hugging Face
Want it on Hugging Face? Here’s the drill:

1. **Get the Tools**:
   ```bash
   pip install datasets
   ```

2. **Prep the Data**: Make sure it’s in JSON or CSV shape.

3. **Upload It**:
   ```bash
   huggingface-cli dataset create --dataset_name bniladridas/nvidia-gpu-dataset --path /path/to/your/data
   ```
   (Swap `bniladridas/nvidia-gpu-dataset` for your own dataset name if needed.)

4. **Spice It Up**: Add a dataset card with the juicy details.

5. **Check It**: Hit Hugging Face to confirm it’s live and legit.

More deets? Peek at the [Hugging Face docs](https://huggingface.co/docs).

## Debugging
Stuff breaking? Dive in:

- **Peek Inside**:
   ```bash
   docker run -it nvidia_project /bin/sh
   ```
   Scope out `/app` with:
   ```bash
   ls -l /app
   ```

- **Read the Tea Leaves**:
   ```bash
   docker logs $(docker ps -l -q)
   ```

## Pro Tips
- **Docker’s Your Friend**: No need to fuss with `source .venv/bin/activate`—it’s all contained.
- Keep it lean—let the container handle the heavy lifting.
- Double-check your `Dockerfile` copies `webscraped.py` and `summary.py` to `/app` and sets the entrypoint right.
- Tweak that `docker cp` path to wherever you want the CSV to land.