The Greek Syntax Jupyter Notebook Environment

Greek Syntax is a Jupyter Notebook environment for querying the Greek New Testament using XQuery, XPath, or Python. It supports queries on syntax trees as well as the base text.

See the Greek Syntax tutorial for an overview of its capabilities.

The data for these queries comes from these GitHub repos:

• https://github.com/biblicalhumanities/Nestle1904
• https://github.com/biblicalhumanities/greek-new-testament
• https://github.com/biblicalhumanities/levinsohn
• https://github.com/translatable-exegetical-tools/Abbott-Smith

Getting Started

There are two ways to install this package. You can either install it directly on your computer or use a Docker image (which is easier, but apparently does not work on some operating systems).

Installing with Docker

If it works on your computer, the easiest way to install is to use the Docker image. First, install Docker:

• Install Docker

• If you are running on Windows, you must switch to Linux containers in Docker before running the container.

• Run this command from the command line:

  $ docker run -v ${PWD}:/home/jovyan/work -p 8888:8888 biblicalhumanities/greek-syntax
  

  Windows Users: On Windows Systemsyou can either use the above command with PowerShell or use %cd instead of ${PWD} in the above command.

  The -v option tells Docker to make your host machine's local directory available to the Docker container so you can mount and save notebooks.

  The -p option maps a container's port to a port on your local machine. In this case, we map the container's port 8888 to the local machine's port 8888. If you get an error message saying that port 8888 is already in use on your computer, try -p 8880:8888, which maps to port 8880 instead. If that's already in use, try 8881, 8882, etc.

• When it runs, you will see a message with a URL to put in a web browser:

    Copy/paste this URL into your browser when you connect for the first time,
    to login with a token:
        http://localhost:8888/?token=431d559093f580607f51cc1ed0dd3d86db0abc743c2d049e
  

  Follow the instructions - copy the URL into the address bar of a web browser. If you changed the port to 8080, change localhost:8888 to localhost:8880 in the URL before you open it.

• You should see a directory tree that looks like this:

  

  Click on the work directory and you will see a list of files. Open the Greek Syntax Tutorial, which will teach you how to use the Greek Syntax package in a Jupyter Notebook.

  

Installing Greek Syntax, Jupyter, and BaseX Directly

You can also use Greek Syntax directly on your computer without Docker. You need the Greek Syntax package, Jupyter, and BaseX. There is a script that installs the data into BaseX.

• Clone this repository using git:

  $ repos: git clone https://github.com/biblicalhumanities/greek-syntax
  

  Then go to the greek-syntax/python directory and install the package as follows:

  $ python: python setup.py install
  

• Install Jupyter using these instructions.

• Install BaseX using from here.

• Download data from repositories and load it into the database using the data/load_data.sh script:

  $ data: ./load_data.sh 
  

• Go to the notebooks directory and start Jupyter:

  $ notebooks: jupyter notebook
  

  You will see a message like this:

      Copy/paste this URL into your browser when you connect for the first time,
    to login with a token:
        http://localhost:8890/?token=00cdcc7b167d94d2ceac84fe38d0fcfff17a76ae921c12ad
  

  Do what it says - copy the URL into a web browser.

• You should see a directory tree that looks like this:

  

  Click on the work directory and you will see a list of files. Open the Greek Syntax Tutorial, which will teach you how to use the Greek Syntax package in a Jupyter Notebook.

  

Implementation

Greek Syntax is implemented as a Docker container based on jupyter/minimal-notebook. It uses the marvelous BaseX database for all XML processing and querying.

Building a Docker image

To build a Docker image, use this script:

build.sh

Directory Structure

• docker - Files we use to build the Docker container.
• python - Source code for the Python module that we install in the Docker container.