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(-)b/databases/Makefile (+1 lines)
Lines 755-760 Link Here
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    SUBDIR += py-couchdb
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    SUBDIR += py-couchdb
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    SUBDIR += py-databases
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    SUBDIR += py-databases
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    SUBDIR += py-dbf
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    SUBDIR += py-dbf
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    SUBDIR += py-dbt-core
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    SUBDIR += py-dbt-semantic-interfaces
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    SUBDIR += py-dbt-semantic-interfaces
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    SUBDIR += py-dbutils
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    SUBDIR += py-dbutils
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    SUBDIR += py-duckdb
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    SUBDIR += py-duckdb
(-)b/databases/py-dbt-core/Makefile (+41 lines)
Added Link Here
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PORTNAME=	dbt-core
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PORTVERSION=	1.6.0
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CATEGORIES=	databases python
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MASTER_SITES=	PYPI
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PKGNAMEPREFIX=	${PYTHON_PKGNAMEPREFIX}
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MAINTAINER=	pat@patmaddox.com

            

            

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COMMENT=	With dbt, build analytics the way engineers build applications

            

            

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WWW=		https://github.com/dbt-labs/dbt-core

            

            

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LICENSE=	APACHE20

            

            

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RUN_DEPENDS=	${PYTHON_PKGNAMEPREFIX}agate>=1.7,<2:textproc/py-agate@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}Jinja2>=3.1.2,<4:devel/py-Jinja2@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}mashumaro>=3.8.1,<4:devel/py-mashumaro@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}msgpack>0:devel/py-msgpack@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}logbook>0:devel/py-logbook@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}click<9:devel/py-click@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}networkx>=2.3:math/py-networkx@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}colorama>=0.3.9,<0.5:devel/py-colorama@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}pathspec>=0.9,<0.12:devel/py-pathspec@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}isodate>=0.6,<0.7:devel/py-isodate@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}sqlparse>=0.2.3,<0.5:databases/py-sqlparse@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}dbt-extractor>=0.4.1,<-0.5:devel/py-dbt-extractor@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}hologram>=0.0.16,0.1:devel/py-hologram@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}minimal-snowplow-tracker>=0.0.2,<0.1:devel/py-minimal-snowplow-tracker@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}dbt-semantic-interfaces>=0.2.0,<0.3:databases/py-dbt-semantic-interfaces@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}packaging>20.9:devel/py-packaging@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}protobuf>=4.0.0:devel/py-protobuf@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}pytz>=2015.7:devel/py-pytz@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}yaml>=6.0:devel/py-yaml@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}typing-extensions>=3.7.4:devel/py-typing-extensions@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}cffi>0:devel/py-cffi@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}idna>0:dns/py-idna@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}requests>0:www/py-requests@${PY_FLAVOR} \

            

            

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		${PYTHON_PKGNAMEPREFIX}urllib3>0:net/py-urllib3@${PY_FLAVOR}

            

            

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USES=		python

            

            

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USE_PYTHON=	autoplist concurrent distutils

            

            

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.include <bsd.port.mk>

            



(-)b/databases/py-dbt-core/distinfo
      (+3 lines)




  

    
      
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TIMESTAMP = 1691520002

            

            

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SHA256 (dbt-core-1.6.0.tar.gz) = 51da239af02ed449562d3c5caea903edee7b5427c47efd5a6439634c59858087

            

            

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SIZE (dbt-core-1.6.0.tar.gz) = 889429

            



(-)b/databases/py-dbt-core/pkg-descr
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dbt enables data analysts and engineers to transform their data using the same

            

            

              
              

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practices that software engineers use to build applications.

            

            


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Analysts using dbt can transform their data by simply writing select statements,

            

            


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while dbt handles turning these statements into tables and views in a data

            

            


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warehouse.

            

            


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These select statements, or "models", form a dbt project. Models frequently

            

            


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build on top of one another - dbt makes it easy to manage relationships between

            

            


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models, and visualize these relationships, as well as assure the quality of your

            

            


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transformations through testing.

            






  

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