A Collection of Methods for Data Collection & Processing
Downloads: | http://pypi.python.org/pypi/labPack |
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Source: | https://github.com/collectiveacuity/labPack |
Documentation: | https://collectiveacuity.github.io/labPack/ |
Lab Pack is designed to make the process of retrieving, managing and processing data more uniform across a variety of different sources and structures. The classes and methods in this module aggregate and curate python resources and online APIs to provide a set of best practices for handling data across laboratory projects.
From PyPi:
$ pip install labpack
From GitHub:
$ git clone https://github.com/collectiveacuity/labpack $ cd labPack $ python setup.py install
This module contains a variety of classes, clients and packages for use in laboratory projects. For example to store records in an indexed file store on the local device, you can use the following methods:
Create an unique ID for records:
from labpack.records.id import labID id = labID() url_safe_id_string = id.id48 id_datetime = id.epoch id_mac_address = id.mac
Save record data in local user data:
from labpack.storage.appdata import appdataClient msg_key = '%s/%s.yaml' % (id_mac_address, id_datetime) msg_details = { 'dt': id_datetime, 'mac': id_mac_address, 'msg': 'Text me back soon' } msg_client = appdataClient('Outgoing', 'My Team', 'My App') mgs_client.create(msg_key, msg_details)
For more details about how to use labPack, refer to the Reference Documentation on GitHub