This is a little Python script to take Gab data output from Garc and ingest it into relational form in an SQLite database.
This tool is designed from an academic research viewpoint.
- Python 3.8+
- Git
This tool requires Python 3.8 or later, the instructions assume you already have Python installed. If you haven't installed Python before, you might find Python for Beginners helpful - note that Gab Tidy Data is a command line application, you don't need to write any Python code to use it (although you can if you want to), you just need to be able to run Python code!
The instructions assume sufficient familiarity with using a command line to change directories and execute commands. If you are new to the command line or want a refresher, there are some good lessons from Software Carpentry and the Programming Historian.
The instructions assume you are working in a suitable Python virtual environment. RealPython has a relatively straightforward primer on virtual environments if you are new to the concept. If you installed Python with Anaconda/conda, you will want to manage your virtual environments through Anaconda/conda as well.
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Ensure you are using an appropriate Python or Anaconda virtual environment
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Install Gab Tidy Data and its requirements by running:
python -m pip install gab_tidy_data -
Run the following to check that your environment is ready to run Gab Tidy Data:
gab_tidy_data --help
In your command line, ensuring you are using the Python or Anaconda virtual environment
you used to install Gab Tidy Data requirements, you can run the gab_tidy_data command:
gab_tidy_data [data_file_1.jsonl] [data_file_2.jsonl] [database_name.db]
You may run the command with as many or as few JSON files (.json or .jsonl) as you
like, and they will all be loaded into the database specified. The database filename
must be the last argument provided to the gab_tidy_data command.