cufile-python
A basic Python wrapper for the NVidia cuFile API
Decision gist · record as of 2026-08-14
Yes, if you have NVIDIA cuFile installed and need GPU-direct file I/O in Python. The package is lightweight, permissively licensed under MIT, and solves a specific performance problem. No, if you don't have cuFile available on your system or don't need direct GPU storage access. Verify that your NVIDIA driver and cuFile version are compatible before relying on it in production.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- NVIDIA cuFile library must be installed and available on the system; Linux (POSIX) only; requires Python 3.6 or later.
- Low install friction with a pure Python wheel and no runtime dependencies.
- Maintenance status is aging—last commit was 305 days ago with minimal repository activity (3 stars), though the repository remains active and not archived.
License · maintenance · safety
MIT (permissive) — MIT license permits unrestricted use, modification, and distribution with minimal legal friction.
last release 2025-10-13 (305 days) · last repo commit 2025-11-03 · 3 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 108,651 downloads/mo, #12,547 on PyPI
Alternatives
Verify before relying
pip install cufile-python
from cufile import CuFile
import ctypes
with CuFile("test.bin", "r") as f:
f.read(ctypes.c_void_p(buffer_ptr), buffer_size)- Whether the underlying NVIDIA cuFile library must be installed separately on the system for this wrapper to function.
- Whether GPU compute capability or CUDA version constraints exist beyond the Python 3.6+ requirement.
- Actual test coverage and stability of the wrapper against different cuFile API versions.
- Performance characteristics and real-world throughput gains compared to standard file I/O.
What it is and what it does
cufile-python is a thin Python binding to NVIDIA's cuFile API, which enables direct I/O between storage and GPU memory, bypassing the host CPU and system RAM. The package exposes both a high-level context manager interface (CuFile class) for common read/write operations and low-level bindings for direct libcufile access via ctypes.
The wrapper is minimal with no Python runtime dependencies, making installation straightforward. It targets Linux (POSIX) and supports Python 3.6 and later. Development has slowed—the last commit was 305 days ago—but the repository remains active and not archived. The codebase is small, making stability plausible for its narrow use case.
Use it for
- Load large tensors directly into GPU memory from disk in machine learning frameworks without copying through host RAM.
- Implement high-throughput data pipelines where I/O is a known bottleneck.
- Access raw GPU memory buffers from files in scientific computing or data-parallel applications.
- Benchmark GPU-direct storage performance on systems with NVIDIA GPUs and cuFile support.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you have NVIDIA cuFile installed and need GPU-direct file I/O in Python.
The package is lightweight, permissively licensed under MIT, and solves a specific performance problem. No, if you don't have cuFile available on your system or don't need direct GPU storage access. Verify that your NVIDIA driver and cuFile version are compatible before relying on it in production.
Install
cufile-python on PyPI
Before you install
Low install friction with a pure Python wheel and no runtime dependencies. Maintenance status is aging—last commit was 305 days ago with minimal repository activity (3 stars), though the repository remains active and not archived.
NVIDIA cuFile library must be installed and available on the system; Linux (POSIX) only; requires Python 3.6 or later.
License in practice
MIT license permits unrestricted use, modification, and distribution with minimal legal friction.
Quickstart
pip install cufile-python
from cufile import CuFile
import ctypes
with CuFile("test.bin", "r") as f:
f.read(ctypes.c_void_p(buffer_ptr), buffer_size)Verify before relying
- Whether the underlying NVIDIA cuFile library must be installed separately on the system for this wrapper to function.
- Whether GPU compute capability or CUDA version constraints exist beyond the Python 3.6+ requirement.
- Actual test coverage and stability of the wrapper against different cuFile API versions.
- Performance characteristics and real-world throughput gains compared to standard file I/O.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.6 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Aging 305 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 108,651 / month, #12,547 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Operating System :: POSIX :: LinuxProgramming Language :: Python :: 3 |
Evidence: cufile_python-0.2.0-py3-none-any.whl
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See also nvidia-cufile · nvidia-cufile-cu12 · libkvikio-cu12 · cuda-python · cuda-tile · pycuda · cuda-core · nvidia-libnvcomp-cu12 · nvidia-cuda-runtime · nvidia-cuda-runtime-cu11