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A stats collection and distributed tracing framework

Project description

gitter circleci pypi

OpenCensus for Python. OpenCensus provides a framework to measure a server’s resource usage and collect performance stats. This repository contains Python related utilities and supporting software needed by OpenCensus.

Tracing

Installation & basic usage

  1. Install the opencensus package using pip or pipenv:

    pip install opencensus
    pipenv install opencensus
  2. Initialize a tracer for your application:

    from opencensus.trace import tracer as tracer_module
    
    tracer = tracer_module.Tracer()
  3. Initialize a view_manager and a stats_recorder for your application:

    from opencensus.stats import stats as stats_module
    
    stats = stats_module.Stats()
    view_manager = stats.view_manager
    stats_recorder = stats.stats_recorder

Usage

You can collect traces using the Tracer context manager:

from opencensus.trace import tracer as tracer_module

# Initialize a tracer, by default using the `PrintExporter`
tracer = tracer_module.Tracer()

# Example for creating nested spans
with tracer.span(name='span1') as span1:
    do_something_to_trace()
    with span1.span(name='span1_child1') as span1_child1:
        do_something_to_trace()
    with span1.span(name='span1_child2') as span1_child2:
        do_something_to_trace()
with tracer.span(name='span2') as span2:
    do_something_to_trace()

OpenCensus will collect everything within the with statement as a single span.

Alternatively, you can explicitly start and end a span:

from opencensus.trace import tracer as tracer_module

# Initialize a tracer, by default using the `PrintExporter`
tracer = tracer_module.Tracer()

tracer.start_span(name='span1')
do_something_to_trace()
tracer.end_span()

Customization

Samplers

You can specify different samplers when initializing a tracer, default is using AlwaysOnSampler, the other options are AlwaysOffSampler and ProbabilitySampler

from opencensus.trace.samplers import probability
from opencensus.trace import tracer as tracer_module

# Sampling the requests at the rate equals 0.5
sampler = probability.ProbabilitySampler(rate=0.5)
tracer = tracer_module.Tracer(sampler=sampler)

Exporters

You can choose different exporters to send the traces to. By default, the traces are printed to stdout in JSON format. Other options include writing to a file, sending to Python logging, or reporting to Stackdriver.

This example shows how to configure OpenCensus to save the traces to a file:

from opencensus.trace.exporters import file_exporter
from opencensus.trace.tracers import context_tracer

exporter = file_exporter.FileExporter(file_name='traces')
tracer = context_tracer.ContextTracer(exporter=exporter)

This example shows how to report the traces to Stackdriver Trace:

from opencensus.ext.stackdriver import trace_exporter as stackdriver_exporter
from opencensus.trace import tracer as tracer_module

exporter = stackdriver_exporter.StackdriverExporter(
    project_id='your_cloud_project')
tracer = tracer_module.Tracer(exporter=exporter)

StackdriverExporter requires the google-cloud-trace package. Install google-cloud-trace using pip or pipenv:

pip install google-cloud-trace
pipenv install google-cloud-trace

By default, traces are exported synchronously, which introduces latency during your code’s execution. To avoid blocking code execution, you can initialize your exporter to use a background thread.

This example shows how to configure OpenCensus to use a background thread:

from opencensus.common.transports.async_ import AsyncTransport
from opencensus.ext.stackdriver import trace_exporter as stackdriver_exporter
from opencensus.trace import tracer as tracer_module

exporter = stackdriver_exporter.StackdriverExporter(
    project_id='your_cloud_project', transport=AsyncTransport)
tracer = tracer_module.Tracer(exporter=exporter)

Propagators

You can specify the propagator type for serializing and deserializing the SpanContext and its headers. There are currently three built in propagators: GoogleCloudFormatPropagator, TextFormatPropagator and TraceContextPropagator.

This example shows how to use the GoogleCloudFormatPropagator:

from opencensus.trace.propagation import google_cloud_format

propagator = google_cloud_format.GoogleCloudFormatPropagator()

# Deserialize
span_context = propagator.from_header(header)

# Serialize
header = propagator.to_header(span_context)

This example shows how to use the TraceContextPropagator:

import requests

from opencensus.trace import config_integration
from opencensus.trace.propagation.trace_context_http_header_format import TraceContextPropagator
from opencensus.trace.tracer import Tracer

config_integration.trace_integrations(['httplib'])
tracer = Tracer(propagator = TraceContextPropagator())

with tracer.span(name = 'parent'):
    with tracer.span(name = 'child'):
        response = requests.get('http://localhost:5000')

Blacklist Paths

You can specify which paths you do not want to trace by configuring the blacklist paths.

This example shows how to configure the blacklist to ignore the _ah/health endpoint for a Flask application:

from opencensus.trace.ext.flask.flask_middleware import FlaskMiddleware

app = flask.Flask(__name__)

blacklist_paths = ['_ah/health']
middleware = FlaskMiddleware(app, blacklist_paths=blacklist_paths)

For Django, you can configure the blacklist in the OPENCENSUS_TRACE_PARAMS in settings.py:

OPENCENSUS_TRACE_PARAMS: {
    ...
    'BLACKLIST_PATHS': ['_ah/health',],
}

Integration

OpenCensus supports integration with popular web frameworks, client libraries and built-in libraries.

Stats

Stackdriver Stats

The OpenCensus Stackdriver Stats Exporter allows users to export metrics to Stackdriver Monitoring. The API of this project is still evolving. The use of vendoring or a dependency management tool is recommended.

Stackdriver Exporter Usage

Stackdriver Import
from opencensus.stats.exporters import stackdriver_exporter as stackdriver
from opencensus.stats import stats as stats_module
Stackdriver Prerequisites
  • OpenCensus Python libraries require Python 2.7 or later.

  • Google Cloud Platform account and project.

  • Google Stackdriver Monitoring enabled on your project (Need help? Click here).

Register the Stackdriver exporter
stats = stats_module.Stats()
view_manager = stats.view_manager

exporter = stackdriver.new_stats_exporter(stackdriver.Options(project_id="<id_value>"))
view_manager.register_exporter(exporter)
...
Stackdriver Code Reference

In the examples folder, you can find all the necessary steps to get the exporter, register a view, put tags on the measure, and see the values against the Stackdriver monitoring tool once you have defined the project_id.

For further details for the Stackdriver implementation, see the file stackdriver_exporter.py.

Path & File

Short Description

examples/stats/exporter/stackdriver.py

End to end example

opencensus/stats/exporters/stackdriver_exporter.py

Stats implementation for Stackdriver

Prometheus Stats

The OpenCensus Prometheus Stats Exporter allows users to export metrics to Prometheus monitoring solution. The API of this project is still evolving. The use of vendoring or a dependency management tool is recommended.

Prometheus Exporter Usage

Prometheus Import
from opencensus.stats.exporters import prometheus_exporter as prometheus
from opencensus.stats import stats as stats_module
Prometheus Prerequisites
  • OpenCensus Python libraries require Python 2.7 or later.

  • Prometheus up and running.

Register the Prometheus exporter
stats = stats_module.Stats()
view_manager = stats.view_manager

exporter = prometheus.new_stats_exporter(prometheus.Options(namespace="<namespace>"))
view_manager.register_exporter(exporter)
...
Prometheus Code Reference

In the examples folder, you can find all the necessary steps to get the exporter, register a view, put tags on the measure, and see the values against the Prometheus monitoring tool.

For further details for the Prometheus implementation, see the file prometheus_exporter.py.

Path & File

Short Description

examples/stats/exporter/prometheus.py

End to end example

opencensus/stats/exporters/prometheus_exporter.py

Stats implementation for Prometheus

Additional Info

Contributing

Contributions to this library are always welcome and highly encouraged.

See CONTRIBUTING for more information on how to get started.

Development

Tests

cd trace
tox -e py34
source .tox/py34/bin/activate

# Install nox with pip
pip install nox-automation

# See what's available in the nox suite
nox -l

# Run a single nox command
nox -s "unit(py='2.7')"

# Run all the nox commands
nox

# Integration test
# We don't have script for integration test yet, but can test as below.
python setup.py bdist_wheel
cd dist
pip install opencensus-0.0.1-py2.py3-none-any.whl

# Then just run the tracers normally as you want to test.

License

Apache 2.0 - See LICENSE for more information.

Disclaimer

This is not an official Google product.

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