OSError: libgomp.so.1: cannot open shared object file: No such file or directory

Not specified by the original author.

TL;DR: lightgbm needs the OpenMP runtime library and your Linux box does not have it. Install the libgomp system package and the import works.

The error

OSError: libgomp.so.1: cannot open shared object file: No such file or directory

Fix it

1. Install the OpenMP runtime. On Debian/Ubuntu:

   sudo apt install libgomp1

   On RHEL/Fedora: sudo dnf install libgomp. Expected: package installs.

2. Verify the library resolves:

   ldconfig -p | grep libgomp

   Expected: a line showing libgomp.so.1.

3. Retry:

   python -c "import lightgbm; print(lightgbm.__version__)"

   Expected: prints the version.

4. Alternative: install lightgbm from conda-forge, which bundles the runtime:

   conda install -c conda-forge lightgbm

When this applies

Use this when import lightgbm on Linux raises the libgomp.so.1 error.

When it does not apply

On macOS the equivalent missing library is libomp.dylib (brew install libomp). If a different .so is missing, install that library instead.

Compatibility

Linux, lightgbm pip wheels that link the system OpenMP.

Root cause

lightgbm's compiled core links against libgomp for OpenMP parallelism. Minimal docker images and stripped servers often lack the libgomp runtime package, so the dynamic loader fails at import.

Edge cases

In docker, add the package to the Dockerfile so rebuilds do not regress. On clusters without sudo, the conda-forge build is the way out since it carries its own runtime.

The Ampel-HU-astro README (AmpelAstro/Ampel-HU-astro) documents this exact failure: importing lightgbm fails with OSError: libgomp.so.1: cannot open shared object file on systems without the OpenMP runtime. The documented fix is installing the libgomp system package (e.g. the libgomp1 OS package) so the shared library resolves, after which import lightgbm succeeds. Source: https://github.com/AmpelAstro/Ampel-HU-astro

Not specified by the original author.

Short answer: install the OpenMP runtime from your OS package manager. On Debian/Ubuntu that is the libgomp1 package; pip cannot fix this one because the missing piece is a system library, not a Python package. `` error while loading shared libraries: libgomp.so.1: cannot open shared object file: No such file or directory 1. Confirm the diagnosis: ldconfig -p | grep libgomp returns nothing, and ldd on the failing package's native library (for Python packages, the .so inside site-packages) shows libgomp.so.1 as not found. Expected: both checks agree the runtime is absent. 2. Install it for your platform. Debian/Ubuntu: sudo apt-get update && sudo apt-get install -y libgomp1. RHEL/Fedora family: sudo dnf install -y libgomp. Alpine: apk add libgomp. macOS uses a different runtime name: brew install libomp. Expected: ldconfig -p | grep libgomp` now lists libgomp.so.1. 3. Re-run the import or program. Expected: it loads with no loader error. In Python, verify with a plain import of the package that failed. 4. In Docker, add the install to the Dockerfile (apt-get install libgomp1 in the runtime stage, not just the build stage) and rebuild. Expected: a fresh container from the image imports cleanly; a fix applied by hand inside a running container disappears on restart. Root cause: OpenMP-enabled binaries declare libgomp.so.1 as a needed library, and the dynamic linker resolves needed libraries only from system paths. Distroless and slim base images omit compiler runtimes, so the dependency that the wheel author assumed would always be there is missing. When to use: Linux or container environments where a native or Python ML/scientific package fails at load time with this error. When NOT to use: if libgomp is installed but the error names a version symbol (for example GOMP_4.5 not found), the installed runtime is too old for the binary; upgrade the runtime or use a newer base image rather than reinstalling the same package. Variant phrasings: "oserror libgomp.so.1 cannot open shared object file", "lightgbm libgomp.so.1 not found", "import sklearn libgomp missing docker". Edge cases: conda users can install the runtime into the env instead (conda install libgomp from conda-forge) when they have no sudo. On multi-stage builds the runtime is needed wherever the binary runs, which is the final stage only.

Context: libgomp is GCC's OpenMP runtime. Native libraries built with OpenMP, including the wheels for LightGBM, XGBoost, scikit-learn components, and many geospatial and scientific packages, link against it but do not bundle it, because it is expected to come from the operating system. Minimal container images and slim server installs often ship without it, so the first import of such a package fails in the dynamic linker with this error even though the Python package itself installed cleanly.

Source: libgomp is GCC's OpenMP runtime. Native libraries built with OpenMP, including the wheels for LightGBM, XGBoost, scikit-learn components, and many geospatial and scientific packages, link against it but do not bundle it, because it is expected to come from the operating system. Minimal container images and slim server installs often ship without it, so the first import of such a package fails in the dynamic linker with this error even though the Python package itself installed cleanly.

Verified resolution: Short answer: install the OpenMP runtime from your OS package manager. On Debian/Ubuntu that is the libgomp1 package; pip cannot fix this one because the missing piece is a system library, not a Python package. `` error while loading shared libraries: libgomp.so.1: cannot open shared object file: No such file or directory 1. Confirm the diagnosis: ldconfig -p | grep libgomp returns nothing, and ldd on the failing package's native library (for Python packages, the .so inside site-packages) shows libgomp.so.1 as not found. Expected: both checks agree the runtime is absent. 2. Install it for your platform. Debian/Ubuntu: sudo apt-get update && sudo apt-get install -y libgomp1. RHEL/Fedora family: sudo dnf install -y libgomp. Alpine: apk add libgomp. macOS uses a different runtime name: brew install libomp. Expected: ldconfig -p | grep libgomp` now lists libgomp.so.1. 3. Re-run the import or program. Expected: it loads with no loader error. In Python, verify with a plain import of the package that failed. 4. In Docker, add the install to the Dockerfile (apt-get install libgomp1 in the runtime stage, not just the build stage) and rebuild. Expected: a fresh container from the image imports cleanly; a fix applied by hand inside a running container disappears on restart. Root cause: OpenMP-enabled binaries declare libgomp.so.1 as a needed library, and the dynamic linker resolves needed libraries only from system paths. Distroless and slim base images omit compiler runtimes, so the dependency that the wheel author assumed would always be there is missing. When to use: Linux or container environments where a native or Python ML/scientific package fails at load time with this error. When NOT to use: if libgomp is installed but the error names a version symbol (for example GOMP_4.5 not found), the installed runtime is too old for the binary; upgrade the runtime or use a newer base image rather than reinstalling the same package. Variant phrasings: "oserror libgomp.so.1 cannot open shared object file", "lightgbm libgomp.so.1 not found", "import sklearn libgomp missing docker". Edge cases: conda users can install the runtime into the env instead (conda install libgomp from conda-forge) when they have no sudo. On multi-stage builds the runtime is needed wherever the binary runs, which is the final stage only.

Source URL: https://pypi.org/project/gpboost/1.6.6/

Not specified by the original author.

How to fix OSError: libcudart.so.11.0: cannot open shared object file: No such file or directory

Your torch build wants CUDA 11.0 but the loader cannot find its libraries. Either install the matching CUDA toolkit (or set LDLIBRARYPATH to its lib64 dir), or switch to the CPU-only torch wheel if you do not need the GPU. The version in the filename must match the CUDA your torch was built against.

The exact error

OSError: libcudart.so.11.0: cannot open shared object file: No such file or directory

Fix it

1. Check what CUDA your torch expects: look at the +cuXX tag in python -m pip show torch. Expected: e.g. cu110, cu118, cu121

2. Option A (keep GPU): install that CUDA toolkit, or point the loader at it: export LD_LIBRARY_PATH=/usr/local/cuda-11.0/lib64:$LD_LIBRARY_PATH. Expected: import torch no longer raises the OSError

3. Option B (no GPU needed): pip install torch --index-url https://download.pytorch.org/whl/cpu. Expected: torch imports and runs on CPU

When this applies

import torch (or torchvision/torchgeometric) fails with libcudart.so.X / libcudnn / `libtorchcuda` not found on Linux

When this does NOT apply

Windows DLL errors or No module named 'torch'

Versions

Linux, CUDA builds of torch

Why it happens

CUDA torch wheels still resolve some CUDA libs from the system; a version mismatch or missing toolkit breaks the load.

Edge cases

nvidia-smi showing CUDA 12.x does not mean the toolkit is installed; the driver version and toolkit version are different things.

Asked about: OSError: libcudart.so.11.0: cannot open shared object file: No such file or directory (web:iopenv torch dependency notes). The verified fix: Your torch build wants CUDA 11.0 but the loader cannot find its libraries. Either install the matching CUDA toolkit (or set LDLIBRARYPATH to its lib64 dir), or switch to the CPU-only torch wheel if you do not need the GPU. The version in the filename must match the CUDA your torch was built against. Full thread: https://www.iopenv.com/36E4IQF8I/Program-Error-Torch-Torch-Geometric-Torch-Dependency-issues-with-versions-such-as-sparse