BrainStorm

Getting Started

First clone or download the repo and enter the directory

> git clone https://github.com/NeverBit/BrainStorm.git
> cd BrainStorm

Next you should choose from the several options to use the code

Running with Docker

The deployment script launches the server, parsers, saver, api and gui modules combined with a rabbitmq and postgresql containers all linked to eachothers.

> ./run-pipeline.sh     # sudo might be required for docker

Then use the client, cli as described in the "Manully running from the command line" or browse to http://127.0.0.1:8080 to see the GUI.

Manully running from the command line

Begin by activating the virtual enviroment:

> ./scripts/install.sh
> source .env/bin/activate

The following modules of the system are runnable:

api, cli, client, gui, parsers, saver, server

Each should be run with python's -m flag like so:

> python -m BrainStorm.api [command] [args + options]

Substitute 'api' with any other module. To begin exploring the various commands and arguments you can run the module without a command to get the help page:

> python -m BrainStorm.api
Usage: BrainStorm.api [OPTIONS] COMMAND [ARGS]...

Options:
  --help  Show this message and exit.

Commands:
  run-server

Using modules in your code

You could also import BrainStorm as a package in your code import BrainStorm Without importing sub-modules several main classes and functions are accessible. Including:

The client's upload_sample function
The Reader classes to read from the DB
The GUI's WebServer class
The image class used to represent images in snapshots
The get_reader function used to get readers for .mind files
The registered_parsers dictionary holding all parsers in the system
The Snapshot, SnapshotSlim classes used to represent snapshots
The run_server function to run a snapshot-collecting server
The Saver class used to save parser results to the DB

Extend the system: Parsers

The system uses several stand-alone parsers to retrieve information from the snapshots. Registering a new parser is as simple as creating a .py file and running a new 'run-parser' process

Please refer to Adding a parser for the instructions.

theXappy / BrainStorm