dvc-objects
dvc objects - filesystem and object-db level abstractions to use in dvc and dvc-data
Decision gist · record as of 2026-08-14
Yes, if you are building tools in the DVC ecosystem or need a lightweight, actively maintained abstraction for multi-backend storage operations. The low install friction, permissive license, and active maintenance make it a safe dependency. However, this is primarily a library for other packages rather than a standalone tool—install it as a dependency, not as a direct solution to a storage problem.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.9 or later; the underlying storage backend (S3, GCS, etc.) must support upload, download, list, copy, and quasiatomic rename operations.
- Low install friction with only two runtime dependencies (fsspec and funcy).
- Actively maintained with recent commits; last release was 235 days ago and the repository remains active.
License · maintenance · safety
Apache-2.0 (permissive) — Apache 2.0 permissive license allows free use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects.
last release 2025-12-22 (235 days) · last repo commit 2026-08-10 · 14 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 2,013,946 downloads/mo, #3,362 on PyPI
Alternatives
Verify before relying
pip install dvc-objects
from dvc_objects.fs import get_cloud_fs
fs = get_cloud_fs(None, **{"url": "s3://bucket/path"})
fs.upload("local_file", "remote_path")- Whether the package provides a stable public API or is primarily intended for internal DVC ecosystem use
- Performance characteristics and scalability limits for large-scale object operations
- Specific storage backend compatibility matrix and any known limitations
What it is and what it does
DVC objects is a low-level abstraction layer that unifies access to multiple storage backends through a common interface built on fsspec. It handles the filesystem and object-database operations needed by DVC and dvc-data, supporting local storage, cloud providers (S3, Google Cloud Storage, Google Drive), and remote systems (SSH/SFTP). The package is serverless and requires only that the underlying storage support basic operations: uploading, downloading, listing, copying, and atomic renames.
This is a foundational library rather than a user-facing tool—it's designed to be used by other DVC ecosystem packages rather than directly by end users. It abstracts away the complexity of working with different storage systems, allowing higher-level tools to treat all backends uniformly.
Use it for
- Building data pipeline tools that need to work across multiple storage backends without backend-specific code
- Implementing object-database systems that require consistent operations across local and cloud storage
- Extending DVC or dvc-data with custom storage support by leveraging the fsspec abstraction layer
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building tools in the DVC ecosystem or need a lightweight, actively maintained abstraction for multi-backend storage operations.
The low install friction, permissive license, and active maintenance make it a safe dependency. However, this is primarily a library for other packages rather than a standalone tool—install it as a dependency, not as a direct solution to a storage problem.
Install
dvc-objects on PyPI
Before you install
Low install friction with only two runtime dependencies (fsspec and funcy). Actively maintained with recent commits; last release was 235 days ago and the repository remains active.
Requires Python 3.9 or later; the underlying storage backend (S3, GCS, etc.) must support upload, download, list, copy, and quasiatomic rename operations.
License in practice
Apache 2.0 permissive license allows free use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects.
Quickstart
pip install dvc-objects
from dvc_objects.fs import get_cloud_fs
fs = get_cloud_fs(None, **{"url": "s3://bucket/path"})
fs.upload("local_file", "remote_path")Verify before relying
- Whether the package provides a stable public API or is primarily intended for internal DVC ecosystem use
- Performance characteristics and scalability limits for large-scale object operations
- Specific storage backend compatibility matrix and any known limitations
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesfsspecfuncy |
| Maintenance | Actively maintained 235 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 2,013,946 / month, #3,362 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.9 |
Evidence: dvc_objects-5.2.0-py3-none-any.whl
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See also dvc-data · dvc-gs · dvc-ssh · scmrepo · dvc-gdrive · morefs · fsspec · iopath · dvc-s3 · gdrive-fsspec