KoboExtractor

This Python package provides a wrapper around part of the KoBoToolbox kpi API, with the main goal being to ease the downloading of survey responses. It provides methods to download data from the KoBoToolbox kpi API (e.g. https://kf.kobotoolbox.org/ or https://kc.humanitarianresponse.info/) and to rearrange this data into useable structures.

Installation

KoboExtractor requires Python 3.6+.

Simply install from PyPI with:

pip3 install koboextractor

Example usage

In this example, response data is downloaded from KoBoToolbox and arranged in a form that is convenient for further processing, e.g. for storing in a different database or uploading to Google Sheets.

Import and initialise the KoboExtractor:

from koboextractor import KoboExtractor
kobo = KoboExtractor(KOBO_TOKEN, 'https://kf.kobotoolbox.org/api/v2', debug=debug)

Get the unique ID of the first asset in your KoBoToolbox account:

assets = kobo.list_assets()
asset_uid = assets['results'][0]['uid']

Information on the questions and choices in your survey can be obtained with:

asset = kobo.get_asset(asset_uid)
choice_lists = kobo.get_choices(asset)
questions = kobo.get_questions(asset=asset, unpack_multiples=True)

questions is a dictionary of the form:

    {
    'groups': {
        GROUP_CODE: {
            'label': GROUP_LABEL,
            'sequence': SEQUENCE_NUMBER,
            'repeat': True/False,
            'questions': {
                QUESTION_CODE: {
                    'type': QUESTION_TYPE,
                    'sequence': SEQUENCE_NUMBER,
                    'label': QUESTION_LABEL,
                    'list_name': CHOICE_LIST_NAME,
                    'choices': {
                        CHOICE_CODE: {
                            'label': CHOICE_LABEL,
                            'type': 'select_multiple_option',
                            'sequence': SEQUENCE_NUMBER
                        }
                    },
                    'other': {
                        'type': '_or_other',
                        'label': 'Other',
                        'sequence': SEQUENCE_NUMBER
                    }
                }
            },
            'groups': {
                GROUP_CODE: {
                    ...
                }
            }
        },
    'questions': {
        QUESTION_CODE: {
            ...
        }
}

choices is a dictionary of the form:

{
        LIST_NAME: {
                'label': CHOICE_LABEL,
                'sequence': SEQUENCE_NUMBER
        }
}

Download all responses submitted after a certain point in time:

new_data = kobo.get_data(asset_uid, submitted_after='2020-05-20T17:29:30')

The number of downloaded results is available in new_data['count'].

new_data will be an unordered list of form submissions. We can sort this list by submission time by calling:

new_results = kobo.sort_results_by_time(new_data['results'])

Each response (list item) is a dict with several metadata keys (such as '_submission_time') and key/value pairs for each answered question in the form of 'GROUP_CODE/QUESTION_CODE': 'ANSWER_CODE'. Map the question and answer labels from your survey onto the coded answers in the responses:

labeled_results = []
for result in new_results: # new_results is a list of list of dicts
        # Unpack answers to select_multiple questions
        labeled_results.append(kobo.label_result(unlabeled_result=result, choice_lists=choice_lists, questions=questions, unpack_multiples=True))

Documentation

The full documentation is available at https://koboextractor.readthedocs.io .