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A workflow wrapper for Hivemind

Project description

Hivemind Plus is a Python library to assist with the creation of instances and processing of results on the Hivemind platform. Before you use this library you will need to register for an API key via the website.

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.

Instance 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()
)

Result Configuration

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()
)

Workflow Configuration

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

Project details


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