A Collection of Methods for Data Collection & Processing
Project description
labPack
A Collection of Methods for Data Collection & Processing
- Downloads:
- Source:
Top-Level Classes
labID: A class of methods for uniquely identifying records
labDT: A class of methods for transforming datetime data
labRandom: A package of methods for generating random data
labPerform: A package of methods for running performance tests
drep: A file storage protocol for encrypted record data
labCrypt: A package for encrypting/decrypting data using AES256 sha512
labRegex: A class of methods for matching regex patterns
appdataClient: A class of methods for managing file storage in home dir
localhostClient: A class of methods for negotiating OS specific configuration
Features
Unique IDs which do not conflict nor leak record origin
Transformations of datetime data between popular formats
Randomization using best current algorithms
[FEATURES ADDED] drep compiler package for encrypted file storage protocol
[FEATURES ADDED] labCrypt package for encrypted data using AES 256bit sha512
[FEATURES ADDED] labPerform package for running performance tests
[FEATURES ADDED] labRegex parsing package for mapping n-grams in strings
[FEATURES ADDED] appdataClient class for managing file storage on local host
[FEATURES ADDED] localhostClient class for negotiating os specific methods
Installation
>From PyPi:
$ pip install labpack
>From GitHub:
$ git clone https://github.com/collectiveacuity/labPack $ cd labPack $ python setup.py install
Getting Started
This module is designed to make the process of retrieving, managing and processing data more uniform across a variety of different sources and structures. A number of module methods are implementations of built-in python packages and standard python imports which have been optimized for data management and compensate for the messy state of real data. The methods in this module aggregate and curate python resources and online APIs to provide a set of best practices for handling data.
Create an unique ID for records:
from labpack.records import labID id = labID() url_safe_id_string = id.id48 id_datetime = id.epoch
For more details about how to use labPack, refer to the Reference Documentation on GitHub
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