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onnela-lab/mano

Mano

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Mano is a simple Python library that lets you write applications that interact with the Beiwe Research Platform. You can request lists of studies, users, device settings, download files (with or without encryption) and more! (actually, not much more)

Table of contents

  1. Requirements
  2. Mac OS X Notes
  3. Installation
  4. Initial setup
  5. API for keyring access
  6. API for accessing study information
  7. API for downloading data

Requirements

This software works with Python 2.6+ and 3 and has been tested on various flavors of macOS, Linux, and Linux Subsystem on Windows 10.

macOS SSL note

I've encountered old versions of OpenSSL on some macOS distrubitions that cause issues interacting with Beiwe over HTTPS. The simplest solution I found was to install one of the Miniconda Python distributions which bundles a more recent version of OpenSSL (download link).

Installation

The simplest way to install mano is with pip

pip install mano

Initial setup

To interact with Beiwe and download files you will need your Beiwe Research Platform url, username, password, access key, and secret key in a JSON file. Don't worry, we're going to eventually encrypt this file

{
    "beiwe.onnela": {
        "URL": "...",
        "USERNAME": "...",
        "PASSWORD": "...",
        "ACCESS_KEY": "...",
        "SECRET_KEY": "..."
    }
}

Note that you can also use environment variables BEIWE_URL, BEIWE_USERNAME, BEIWE_PASSWORD, BEIWE_ACCESS_KEY, and BEIWE_SECRET_KEY to store these variables and load your keyring using mano.keyring(None). You won't be able to use an environment variable for storing study-specific secrets (described next). But depending on your situation you may not even need study-specific secrets.

If you intend to use mano to encrypt certain downloaded data stream files at rest, you will want to add study-specific passphrases (which you're responsible for generating) to a special SECRETS section

{
    "beiwe.onnela": {
        "URL": "...",
        "USERNAME": "...",
        "PASSWORD": "...",
        "ACCESS_KEY": "...",
        "SECRET_KEY": "...",
        "SECRETS": {
            "FAS Buckner": "...",
        }
    }
}

I'm guessing that you don't want this file sitting around in plain text, so for now this entire JSON blob must be passphrase protected using the crypt.py utility from the cryptease library which should be automatically installed along with the mano package

$ crypt.py --encrypt ~/.nrg-keyring.json --output-file ~/.nrg-keyring.enc

I'll leave it up to the reader to decide where to produce the encrypted version of this file, but I would highly recommend discarding the unencrypted version.

API for keyring access

Before making any API calls, you need to read in your keyring file. The first parameter should be the name of the keyring section as shown above

import mano

Keyring = mano.keyring('beiwe.onnela')

You can pass keyring passphrase as an argument to this function, or it will look for your keyring passphrase within a special NRG_KEYRING_PASS environment variable, or it will fallback on prompting you for the passphrase. This last strategy could cause non-interactive invocations to hang, so watch out.

API for accessing study information

With your Keyring loaded, you can now access information about your studies, users (a.k.a. participants or subjects), and device settings using simple functions defined within the mano module

for study in mano.studies(Keyring):
    print(study)

_, study_id = study # get the last printed study id

for user_id in mano.users(Keyring, study_id):
    print(user_id)

for setting in mano.device_settings(Keyring, study_id):
    print(setting)

API for downloading data

With your Keyring loaded, you can also download data from your Beiwe server and extract it to your filesystem using the mano.sync module. And while we're at it, let's turn on more verbose logging so we can actually see what's happening

import logging
import mano.sync as msync

logging.basicConfig(level=logging.INFO)

output_folder = '/tmp/beiwe-data'

zf = msync.download(Keyring, study_id, user_id, data_streams=['identifiers'])

zf.extractall(output_folder)

Notice that I passed data_streams=['identifiers'] to msync.download. By default, that function will request all data for all data streams if you omit that parameter. Check out the backfill section for more information.

The msync.download function will hand back a standard Python zipfile.ZipFile object which you can extract to the filesystem as shown above. Easy.

encrypt files at rest

You can also pass the ZipFile object to msync.save if you wish to encrypt data stream files at rest

lock_streams = ['gps', 'audio_recordings']

zf = msync.download(Keyring, study_id, user_id)

passphrase = Keyring['SECRETS']['FAS Buckner']

msync.save(Keyring, zf, user_id, output_folder, lock=lock_streams, passphrase=passphrase)

backfill

By default msync.download will attempt to download all of the data for the specified user_id which could end up being prohibitively large either for you or the Beiwe server. For this reason, the msync.download function exposes parameters for data_streams, time_start, and time_end. Using these parameters you can download only certain data streams between certain start and end times

data_streams = ['accel', 'ios_log', 'gps']

time_start = '2015-10-01T00:00:00'

time_end = '2015-12-01T00:00:00'

zf = msync.download(Keyring, study_id, user_id, data_streams=data_streams, time_start=time_start, time_end=time_end)

zf.extractall(output_folder)

Eventually you may find yourself day-dreaming about a backfill function that will slide a window from some aribitrary starting point to the present time in order to download all of your data in more digestible chunnks. You'll be happy to know that the mano.sync module already exposes a function for this

start_date = '2015-01-01T00:00:00'

msync.backfill(Keyring, study_id, user_id, output_folder, start_date=start_date, lock=lock_streams, passphrase=passphrase)

Note that if you don't pass anything for the lock argument, you will not need passphrase either.

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Mano - Beiwe research platform API

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