https://github.com/aeksco/jupyter-tabula

Docker container image built with Jupyter Notebook and Tabula for PDF scraping
https://github.com/aeksco/jupyter-tabula

docker docker-image dockerfile jupyter jupyter-notebook pandas pdf pypdf pypdf2 scraper tabula tabula-py

Last synced: 13 days ago
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Docker container image built with Jupyter Notebook and Tabula for PDF scraping

• Host: GitHub
• URL: https://github.com/aeksco/jupyter-tabula
• Owner: aeksco
• License: mit
• Created: 2018-06-18T13:57:00.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-06-18T16:32:15.000Z (over 6 years ago)
• Last Synced: 2024-11-22T16:42:10.310Z (2 months ago)
• Topics: docker, docker-image, dockerfile, jupyter, jupyter-notebook, pandas, pdf, pypdf, pypdf2, scraper, tabula, tabula-py
• Language: Jupyter Notebook
• Size: 50.8 KB
• Stars: 2
• Watchers: 3
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# jupyter-tabula

Docker container image built with [Jupyter Notebook](http://jupyter.org/) and [Tabula](https://tabula.technology/) for PDF scraping. Includes an example notebook to help you get started.

Repository hosted on GitHub at [aeksco/jupyter-tabula](https://github.com/aeksco/jupyter-tabula).

Docker container image hosted on Docker Hub at [aeksco/jupyter-tabula](https://hub.docker.com/r/aeksco/jupyter-tabula/).

## Usage

#### Running the Jupyter Notebook server

```

docker run -it -p 8888:8888 aeksco/jupyter-tabula

```

#### Example Notebook

The `Example_01.ipynb` opens a single-page PDF and parses the table contained within.

## Building the Docker Image

Use the following instructions if you want to modify this Docker image and push a different copy to DockerHub.

1. Create a [new Dockerhub Repository](https://hub.docker.com/add/repository/) named `jupyter-tabula`.

2. Build the Docker image by running the following command in the `jupyter-tabula` directory:

```

docker build -t jupyter-tabula .

```

3. Test the image locally with the following command:

```

docker run -it --rm --pid=host -p 8888:8888 jupyter-tabula

```

4. Tag the image and push to Dockerhub:

```

docker tag bb38976d03cf your_docker_hub_username/jupyter-tabula:latest

docker push your_docker_hub_username/jupyter-tabula

```

## Notes

I would recommend this container image for testing and hacking purposes. This image is a bit heavy (`2.02GB`) since it extends the [tensorflow/tensorflow](https://hub.docker.com/r/tensorflow/tensorflow/) container image. This was done mainly to save time since the Tensorflow container already has all the relevant dependencies installed and configured.