hivemind-plus 0.4.0

Installation

$ pip install hivemind-plus

Usage

In order to use Hivemind Plus you must create an instance configuration, a result configuration or both. Each type of configuration ships with a ConfigBuilder class which helps you to assemble your configuration.

from hivemindplus import instance

instance_config = (
    instance.ConfigBuilder()
        .with_connection_string('DRIVER={SQL Server};SERVER=localhost;DATABASE=DB;') # ODBC style connection string
        .with_query('SELECT PeopleId, FullName FROM dbo.People') # Query to drive instances
        .with_key('PeopleId') # Column name to use as unique identifier for an instance
        .with_name('FullName') # Column name to use as a human readable identifier
        .with_tags(['FullName']) # (Optional) Columns to tag instances with
        .with_instructions('instructions.md', ['FullName']) # (Optional) Template markdown file and values
        .with_schema('schema.json', ['Id', 'FullName']) # (Optional) Schema template json file and values
        .with_qualifications_query('SELECT PeopleId, Qualification FROM dbo.Qualifications') # (Optional) Query for qualifications
        .build()
)

from hivemindplus import result

# Executed for every agreed upon result
def output_fn(res):
    print('Output function')
    print(str(res))


# Custom agreement function that compares two results
def agreement_fn(a, b):
    return a['data'] == b['data']


result_config = (
    result.ConfigBuilder()
        .with_connection_string('DRIVER={SQL Server};SERVER=localhost;DATABASE=DB;') # ODBC style connection string
        .with_instance_table('dbo.InstanceResults') # (Optional) Override default name of instance results table
        .with_iteration_table('dbo.IterationResults') # (Optional) Override default name of iteration results table
        .with_output_function(output_fn) # (Optional) Function to execute on agreed upon result
        .with_agreement_function(agreement_fn, 0.51) # (Optional) Function to determine agreement
        .with_feedback_function(feedback_fn) # (Optional) Function executed with instance/iteration results for integration of feedback
        .with_max_iterations(5) # (Optional) Max number of iterations to retry agreement checking with
        .with_process_all_results(True) # (Optional) Whether to process all results, regardless if created by HM+
        .build()
)

from hivemindplus import workflow

flow = (
    workflow.Builder()
        .with_api_url('https://client.sandbox.hvmd.io') # URL of the API without a trailing /
        .with_api_key('API-KEY') # Personal API key
        .with_task_id(0) # Task that you want to manage
        .with_instance_config(instance_config) # (Optional) instance configuration
        .with_result_config(result_config) # (Optional) result configuration
        .with_auto_submission() # (Optional) submit task if not already submitted
        .build()
)

# Start the workflow
flow.start()

Examples

A full set of examples can be found in the /examples directory.

Debugging

Hivemind Plus can be run in a debug mode that will print out all the actions it intends to take when not in debug mode.

from hivemindplus import workflow

flow = (
    workflow.Builder()
        .with_debug_enabled()
        .build()
)

Development

To begin development, you will need to install all the required development packages.

$ pip install .[test]

All the source code resides within the /hivemindplus directory and the tests can be ran from the project root directory as shown below.

python -m pytest