dogsheep-beta 0.4a0

Dogsheep search index

dogsheep-beta

Dogsheep search index

Installation

Install this tool like so:

$ pip install dogsheep-beta

Usage

Run the indexer using the dogsheep-beta command-line tool:

$ dogsheep-beta index dogsheep.db config.yml

The config.yml file contains details of the databases and tables that should be indexed:

twitter.db:
    tweets:
        sql: |-
            select
                tweets.id as key,
                'Tweet by @' || users.screen_name as title,
                tweets.created_at as timestamp,
                tweets.full_text as search_1
            from tweets join users on tweets.user = users.id
    users:
        sql: |-
            select
                id as key,
                name || ' @' || screen_name as title,
                created_at as timestamp,
                description as search_1
            from users

This will create a search_index table in the dogsheep.db database populated by data from those SQL queries.

By default the search index that this tool creates will be configured for Porter stemming. This means that searches for words like run will match documents containing runs or running.

If you don't want to use Porter stemming, use the --tokenize none option:

$ dogsheep-beta index dogsheep.db config.yml --tokenize none

You can pass other SQLite tokenize argumenst here, see the SQLite FTS tokenizers documentation.

Columns

The columns that can be returned by our query are:

• key - a unique (within that table) primary key
• title - the title for the item
• timestamp - an ISO8601 timestamp, e.g. 2020-09-02T21:00:21
• search_1 - a larger chunk of text to be included in the search index
• category - an integer category ID, see below

Categories

Indexed items can be assigned a category. Categories are integers that correspond to records in the categories table, which defaults to containing the following:

id	name
1	created
2	saved

created is intended for items that have been created by the Dogsheep instance owner. saved is intended for items that they have saved, liked or favourited.

Development

To set up this plugin locally, first checkout the code. Then create a new virtual environment:

cd dogsheep-beta
python3 -mvenv venv
source venv/bin/activate

Or if you are using pipenv:

pipenv shell

Now install the dependencies and tests:

pip install -e '.[test]'

To run the tests:

pytest