Registry / observability / rapids-logger

rapids-logger

library0.2.3pypiunverified

rapids-logger is a core logging framework within the RAPIDS ecosystem, built around the high-performance C++ `spdlog` library. Its primary goal is to provide project-specific loggers easily, ensuring that custom logging implementations do not leak `spdlog` or `fmt` symbols, thus allowing safe coexistence of different RAPIDS projects in the same environment. While it has Python bindings for packaging, its direct Python API for general-purpose logging is not extensively documented; it primarily serves as the underlying logging mechanism for other RAPIDS Python libraries like `cuML`. The current version is 0.2.3, and releases align with the broader RAPIDS CalVer (YY.MM.PP) versioning scheme for patch releases.

observability

pip install rapids-logger

homepage ↗

INSTALL

IMPORT

SIG · RAPIDS-LOGGER

rapids-logger

observabilityenv0.2.3

Install

1.5s avg

Import

—

Disk

16MB

Pass rate

4/ 10

Env Coverage4 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.2.3 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

glibc

py 3.10

✕ build_error

✓ 1.45s

py 3.11

✕ build_error

✓ 1.55s

py 3.12

✕ build_error

✓ 1.4s

py 3.13

✕ build_error

✓ 1.45s

py 3.9

✕ build_error

16MB installed

● package 16MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

Logger

✓ N/A (Typically used indirectly)

✗ from rapids_logger import Logger

rapids-logger is primarily a C++ library. While Python wheels exist, a high-level Python API for direct logger instantiation and use, analogous to Python's `logging` module, is not a primary documented feature. Logging is typically configured through higher-level RAPIDS Python libraries that use `rapids-logger` internally.

Due to `rapids-logger` being predominantly a C++ framework, direct Python usage for general logging is not commonly documented. Python users typically configure logging through environment variables or specific API calls provided by higher-level RAPIDS Python libraries (e.g., `cuml.accel.install(log_level='debug')`). The provided quickstart demonstrates checking the installed version and notes the indirect usage pattern.

# rapids-logger is primarily a C++ library and its direct Python API for general-purpose logging # is not a primary documented feature. Python users typically interact with logging # through other RAPIDS Python libraries (e.g., cuML) that use rapids-logger internally. # # Example of configuring logging in cuML (which uses rapids-logger implicitly): # import cuml # cuml.accel.install(log_level='debug') # # To see if rapids-logger's C++ components are correctly installed and available via Python bindings: import rapids_logger print(f"rapids_logger version: {rapids_logger.__version__}") # Further direct interaction would depend on specific, often undocumented, Python bindings.

Debug

Known issues

gotcharapids-logger is fundamentally a C++ library. While Python bindings and wheels are provided, direct high-level Python API for creating and managing loggers (like Python's built-in `logging` module or `loguru`) is not a primary documented feature. Its Python package primarily facilitates its underlying use within other RAPIDS Python libraries.

fix

For Python applications, primarily configure logging via the specific RAPIDS library you are using (e.g., `cuml`, `cudf`) or through environment variables if supported by the upstream RAPIDS library. Do not expect `rapids-logger` to expose a generic Python logging interface.

affects: All versions

breakingFor C++ projects building within the RAPIDS ecosystem, `rapids-logger` has replaced direct dependencies on `spdlog` and `fmt`. Projects that previously linked directly against `spdlog` or `fmt` for logging may need to update their CMake configurations to use `rapids-logger` instead.

fix

Update CMakeLists.txt to remove direct `spdlog` and `fmt` dependencies where `rapids-logger` is intended as the logging provider, and integrate `rapids-logger` via `rapids_make_logger` or similar RAPIDS CMake functions. This mainly impacts developers building RAPIDS components from source or extending them in C++.

affects: v0.2.1 and later (within RAPIDS CMake projects)

gotchaThere is an unrelated CI tool also named 'rapids-logger' which is part of the `gha-tools` repository. Ensure you are referencing the correct `rapidsai/rapids-logger` for the logging framework.

fix

Verify the source repository (github.com/rapidsai/rapids-logger) and PyPI/Conda package (`rapids-logger` from `rapidsai` channel) to confirm you are using the correct library.

affects: All versions

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'rapids_logger'

The `rapids-logger` Python package is not installed in the current environment or the Python environment is not correctly activated.

fix

Install the package using `pip install rapids-logger` or `conda install -c rapidsai -c conda-forge rapids-logger`. Ensure your Python environment is correctly activated before running your script.

TypeError: 'module' object is not callable (when trying to call rapids_logger directly as a logging function)

Attempting to use `rapids_logger` as a direct logging function or to instantiate a logger directly, which is not its exposed Python API.

fix

Understand that `rapids-logger` primarily serves as an internal dependency for other RAPIDS Python libraries. Configure logging via the specific RAPIDS library's API or environment variables, rather than trying to directly instantiate a logger from the `rapids_logger` module in Python. Refer to the documentation of the specific RAPIDS library you are using for its logging configuration options.

Upgrade

Version history

0.2.3latest on PyPI · released Dec 12, 2025

Audit

Dependencies

No dependency data recorded yet.

Agent activity

23 hits · last 30 days

node

OpenAI (training)

Resources

homepagehttps://rapids.ai ↗