Commit 95db500f authored by sunpoet's avatar sunpoet
Browse files

Add py-orca 1.5.4

Orca is a Python library for task orchestration. It's designed for workflows
like city simulation, where the data representing a model's state is so large
that it needs to be managed outside of the task graph.

The building blocks of a workflow are "steps", Python functions that can be
assembled on the fly into linear or cyclical pipelines. Steps typically interact
with a central data store that persists in memory while the pipeline runs.
Derived tables and columns can be updated automatically as base data changes,
and pipeline components are evaluated lazily to reduce unnecessary overhead.

WWW: https://github.com/UDST/orca
parent bd34932b
......@@ -4706,6 +4706,7 @@
SUBDIR += py-optik
SUBDIR += py-orange-canvas-core
SUBDIR += py-orange-widget-base
SUBDIR += py-orca
SUBDIR += py-ordered-set
SUBDIR += py-ordereddict
SUBDIR += py-orderedmultidict
......
# Created by: Po-Chuan Hsieh <sunpoet@FreeBSD.org>
# $FreeBSD$
PORTNAME= orca
PORTVERSION= 1.5.4
CATEGORIES= devel python
MASTER_SITES= CHEESESHOP
PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX}
MAINTAINER= sunpoet@FreeBSD.org
COMMENT= Pipeline orchestration tool with Pandas support
LICENSE= BSD3CLAUSE
LICENSE_FILE= ${WRKSRC}/LICENSE.txt
RUN_DEPENDS= ${PYTHON_PKGNAMEPREFIX}pandas>=0.15.0,1:math/py-pandas@${PY_FLAVOR} \
${PYTHON_PKGNAMEPREFIX}tables>=3.1<3.7:devel/py-tables@${PY_FLAVOR} \
${PYTHON_PKGNAMEPREFIX}toolz>=0.8.1:devel/py-toolz@${PY_FLAVOR}
USES= python:3.7+
USE_PYTHON= autoplist concurrent distutils
NO_ARCH= yes
.include <bsd.port.mk>
TIMESTAMP = 1614794174
SHA256 (orca-1.5.4.tar.gz) = b82f5beb7933cfadfdae75c0d7b9987af8534f92f538cfd7f824be47ac320cb1
SIZE (orca-1.5.4.tar.gz) = 242380
Orca is a Python library for task orchestration. It's designed for workflows
like city simulation, where the data representing a model's state is so large
that it needs to be managed outside of the task graph.
The building blocks of a workflow are "steps", Python functions that can be
assembled on the fly into linear or cyclical pipelines. Steps typically interact
with a central data store that persists in memory while the pipeline runs.
Derived tables and columns can be updated automatically as base data changes,
and pipeline components are evaluated lazily to reduce unnecessary overhead.
WWW: https://github.com/UDST/orca
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