montra-client-python

Montra Webservices Wrapper for Python

Getting Started

Prerequisites

This wrapper can be used with any instance of up-to-date MONTRA up and running (e.g. localhost, EHDEN portal, etc). Its usage requires valid credentials to execute it (user and password for basic authentication, or an API token for token authentication).

Installation

Install using pip:

pip install -e git://github.com/bioinformatics-ua/montra-client-python.git#egg=montra-client

Usage

Import Montra either into your Python script or into shell if you make the API calls in command line:

from montra import Montra

Client initialization

The client can be initialiazed using basic or token authentication. Bellow we list all the available arguments and some examples on how to instantiate the client using the available authentications methods. These examples assume there is a MONTRA installation running on localhost, port 8000.

Available parameters:

• username - Montra username
• password - Montra password
• token - An API token that can be obtained through 'API information' of montra

Examples

Basic Authentication:

montra = Montra(url="http://127.0.0.1:8000", username='username', password='password')

Token Authentication:

montra = Montra(url="http://127.0.0.1:8000", token='de4611bcf0c6e393404fac095dab09fad01c1554')

Available Methods

• Search Datasets

  Parameters:

  • questionnaire - Search string with the questionnaire slug or name

  Example:

  list_of_datasets = montra.search_datasets(questionnaire="some questionnaire name")

• Get Dataset

  Parameters:

  • questionnaireSlug - Questionnaire slug
  • communityName - Community name

  Example:

  dataset = montra.get_dataset(communityName='Some community Name', questionnaireSlug='someslug')

• Get Database

  Parameters:

  • questionnaireSlug - Questionnaire slug
  • database_name - Fingerprint (database) name / acronym
  • fingerprintHash - Fingerprint (database) hash
  • communityName - Community name

  Example using fingerprint hash:

  database = montra.get_database(fingerprintHash='somefingerprinthash')

  Example using database name and questionnaire slug:

  database = montra.get_database(database_name="ABC", communityName="Some community name")

• Create Database

  Parameters:

  • questionnaireSlug - Questionnaire slug
  • database_name - Database name / acronym
  • communityName - Community name

  Example:

  database = montra.new_database( database_name='somedbname', communityName='Some community Name', questionnaireSlug='Some questionnaire Slug')

• Update Database

  Parameters:

  • draft - Boolean
  • fingerprintHash - Fingerprint (database) hash

  Example:

  database = montra.update_database(fingerprintHash='some_fingerprint_hash', draft=True)

• List Answers

  Parameters:

  • fingerprintHash - Fingerprint (database) hash

  Example:

  answers = montra.list_answer(fingerprintHash='somefingerprinthash')

  Note: Only answers of the following types are supported: 'open', 'open-textfield', 'comment', 'numeric', 'email' and 'url'

• Get Answer

  Parameters:

  • fingerprintHash - Fingerprint (database) hash
  • question - Question slug

  Example:

  answer = montra.get_answer(fingerprintHash='somefingerprinthash', question='somequestion')

  Note: In order to get all question slugs execute first the above method list_answer()

• Update Answer

  Parameters:

  • fingerprintHash - Fingerprint (database) hash
  • question - Question slug
  • newAnswer - String with the new answer

  Example:

  newAnswer = montra.put_answer(fingerprintHash='somefingerprinthash', question='somequestion', newAnswer="newAnswer")

  Note: In order to get all question slugs execute first the above method list_answer()

Running tests

In order to run tests, the following command should be run on the root folder of the project:

python tests.py --user <username> --password <password> --comm <community_name> --dataset_slug <questionnaire_slug> --token <token> --url <url_MONTRA_installation>