control

Source: dvc
Maintainer: Dmitry Petrov <dmitry@dvc.org>
Section: python
Priority: optional
Build-Depends: dh-python, python3-setuptools, python3-all, debhelper (>= 9)
Standards-Version: 4.0.0
Homepage: http://dvc.org
Vcs-Git: https://github.com/iterative/dvc.git
Vcs-browser: https://github.com/iterative/dvc

Package: dvc
Architecture: all
Depends: ${misc:Depends}, ${python3:Depends}, python3-flufl.lock (>=3.2)
Recommends: python3-arrow (=0.14.0),
            python3-paramiko (>=2.5.0),
            python3-gssapi (>= 2.5.0),
            python3-boto3 (>=1.9.86),
            python3-pydrive (=1.3.1),
            python3-azure-storage-blob (=12.1.0),
            python3-oss2 (=2.6.1),
            python3-google-cloud-storage (=1.19.0)
Description: Git for data scientists - manage your code and data together
 Data Version Control or DVC is an open-source tool for data science and machine learning projects.
 .
 Key features:
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 1. Simple command line Git-like experience. Does not require installing and maintaining any databases. Does not depend on any proprietary online services.
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 2. Management and versioning of datasets and machine learning models. Data is saved in S3, Google cloud, Azure, Alibaba cloud, SSH server, HDFS, or even local HDD RAID.
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 3. Makes projects reproducible and shareable; helping to answer questions about how a model was built.
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 4. Helps manage experiments with Git tags/branches and metrics tracking.