Analysis

The analysis process collects, preprocesses and indexes the input documents, as specified by the provided Pythia pipeline configuration (which is a simple JSON document).

Configuring Analysis

To setup your system to build a Pythia index (which in the end is just a standard relational database), you need:

  • ▶️ access to a PostgreSQL service. Typically you can do this via a Docker image in your host, unless you already have PostgreSQL installed locally, or access to some external PostgreSQL server.

💡 If you need to setup Docker, you can find quick instructions for your OS at https://vedph.github.io/cadmus-doc/deploy/docker.html.

⚠️ If you are on Linux or MacOS, remember to mark the pythia tool file as executable with a command like chmod +x pythia.

You will then have to provide your own documents to be indexed, and a Pythia configuration profile (which is just a JSON document) for them.

⚠️ If the indexing process takes time, and you want to be periodically notified via email on its progress, you should provide into environment variables a pair of public/private MailJet account API keys: please see the CLI documentation for more.

Using Docker-Based PostgreSQL

To launch a PostgreSQL service without installing it, any up-to-date PostgreSQL image is fine. You can easily run a container like this (in this sample, I created a folder in my drive at c:\data\pgsql to host data outside the container):

docker run --volume postgresData://c/data/pgsql -p 5432:5432 --name postgres -e POSTGRES_PASSWORD=postgres -d postgres

💡 For newcomers, here is how you can quickly dump and restore a database using PostgreSQL client tools:

  • ▶️ backup database to file (adjust path to dump file accordingly):
pg_dump --username=postgres -f c:/users/dfusi/desktop/pythia.sql pythia
  • ▶️ restore database from file (adjust path to dump file accordingly):
psql -U postgres -d pythia -f c:/users/dfusi/desktop/pythia.sql

If you want to directly access the database you can use any tool like e.g. DBeaver.

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