Google Cloud Python profiling agent
Python profiling agent for
Google Cloud Profiler.
See
Google Cloud Profiler profiling Python code
for detailed documentation.
Supported OS
Linux. Profiling Python applications is supported for Linux kernels whose
standard C library is implemented with glibc
or with musl
. For configuration
information specific to Linux Alpine kernels, see
Running on Linux Alpine.
Supported Python Versions
Python >= 3.7 and <= 3.11
Installation & usage
-
Install the profiler package using PyPI:
pip3 install google-cloud-profiler
-
Enable the profiler in your application:
import googlecloudprofiler
def main():
try:
googlecloudprofiler.start(
service='hello-profiler',
service_version='1.0.1',
verbose=3,
)
except (ValueError, NotImplementedError) as exc:
print(exc)
Installation on Linux Alpine
The Python profiling agent has a native component. The base Alpine image for
Python does not have all dependencies required to build this native component
installed. To build the Python profiling agent on Alpine, one must install the
package build-base
.
To use the Python profiling agent on Alpine without installing additional
dependencies on to the final Alpine image, one can use a two-stage build and
compile the Python profiling agent in the first stage.
Here is an example of a Docker image that uses a multi-stage build to compile
and install the Python profiling agent:
FROM python:3.7-alpine as builder
# Install build-base to allow for compilation of the profiling agent.
RUN apk add --update --no-cache build-base
# Compile the profiling agent, generating wheels for it.
RUN pip3 wheel --wheel-dir=/tmp/wheels google-cloud-profiler
FROM python:3.7-alpine
# Copy over the directory containing wheels for the profiling agent.
COPY --from=builder /tmp/wheels /tmp/wheels
# Install the profiling agent.
RUN pip3 install --no-index --find-links=/tmp/wheels google-cloud-profiler
# Install any other required modules or dependencies, and copy an app which
# enables the profiler as described in "Enable the profiler in your
# application".
COPY ./bench.py .
# Run the application when the docker image is run, using either CMD (as is done
# here) or ENTRYPOINT.
CMD python3 -u bench.py
Troubleshooting
Resource temporarily unavailable errors with Python
If you see the following log entries after enabling the Profiler:
BlockingIOError: [Errno 11] Resource temporarily unavailable
Exception ignored when trying to write to the signal wakeup fd
see https://cloud.google.com/profiler/docs/troubleshooting#python-blocking for
the cause and the workaround.