Metadata-Version: 2.1
Name: aika-putki
Version: 1.0.0
Summary: Task framework designed for time series data
Home-page: https://github.com/phil20686/aika/
Author: Philip Stephens, Dominic Kennedy
Author-email: philip.stephens@sjc.oxon.org
License: GNU LGPLv3
Project-URL: Source, https://github.com/phil20686/aika/
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Win32 (MS Windows)
Classifier: Environment :: MacOS X
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 or later (LGPLv3+)
Classifier: Natural Language :: English
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Software Development :: Libraries
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: doc/LICENSE.rst
Requires-Dist: pandas (>=1.1.5)
Requires-Dist: numpy
Requires-Dist: aika-time
Requires-Dist: aika-utilities
Requires-Dist: attrs
Requires-Dist: frozendict
Requires-Dist: overrides
Requires-Dist: networkx
Requires-Dist: luigi ; python_version < "3.11"
Requires-Dist: backports.cached-property ; python_version < "3.8"
Provides-Extra: all
Requires-Dist: pytest ; extra == 'all'
Requires-Dist: pytest-cov ; extra == 'all'
Provides-Extra: test
Requires-Dist: pytest ; extra == 'test'
Requires-Dist: pytest-cov ; extra == 'test'

# Introduction

aika-putki is a task framework designed to make it easy
to build production and research systems on top of timeseries
data. They provide tasks which have a notion of completeness
which is founded on an awareness of what data is expected
from a successful computation, and thus completeness is 
defined via the inspection of parent tasks existing output
and not via knowledge of when a task was last run. This directly
solves many issues around eg mis-computing moving averages due
to unavailable data. 

For more information see the [aika project wepage](https://github.com/phil20686/aika/)
