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34 lines
1.4 KiB
Plaintext
34 lines
1.4 KiB
Plaintext
Source: dvc
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Maintainer: Dmitry Petrov <[email protected]>
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Section: python
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Priority: optional
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Build-Depends: dh-python, python3-setuptools, python3-all, debhelper (>= 9)
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Standards-Version: 4.0.0
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Homepage: http://dvc.org
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Vcs-Git: https://github.com/iterative/dvc.git
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Vcs-browser: https://github.com/iterative/dvc
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Package: dvc
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Architecture: all
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Depends: ${misc:Depends}, ${python3:Depends}, python3-flufl.lock (>=3.2)
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Recommends: python3-arrow (=0.14.0),
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python3-paramiko (>=2.5.0),
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python3-gssapi (>= 2.5.0),
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python3-boto3 (>=1.9.86),
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python3-pydrive (=1.3.1),
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python3-azure-storage-blob (=12.1.0),
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python3-oss2 (=2.6.1),
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python3-google-cloud-storage (=1.19.0)
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Description: Git for data scientists - manage your code and data together
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Data Version Control or DVC is an open-source tool for data science and machine learning projects.
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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.
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