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kornholi/opencensus-python

A stats collection and distributed tracing framework

OpenCensus for Python - A stats collection and distributed tracing framework

`Census`_ for Python. Census 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 Census.

.. _Census: https://github.com/census-instrumentation

|circleci|

.. |circleci| image:: https://circleci.com/gh/census-instrumentation/opencensus-python.svg?style=shield
:target: https://circleci.com/gh/census-instrumentation/opencensus-python

  • API Documentation_

.. _API Documentation: https://opencensus.io/api/python/trace/usage.html


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:

    .. code:: python

     from opencensus.trace import tracer as tracer_module
    
     tracer = tracer_module.Tracer()
    

    .. _pip: https://pip.pypa.io
    .. _pipenv: https://docs.pipenv.org/

  3. Initialize a view_manager and a stats_recorder for your application:

    .. code:: python

     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_:

.. code:: python

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()

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

Alternatively, you can explicitly start and end a span:

.. code:: python

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()

.. _context manager: https://docs.python.org/3/reference/datamodel.html#context-managers

Customization

Samplers


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

.. code:: python

    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 Census to save the traces to a
file:

.. code:: python

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:

.. code:: python

from opencensus.trace.exporters import 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 Census to use a background thread:

.. code:: python

from opencensus.trace.exporters import stackdriver_exporter
from opencensus.trace import tracer as tracer_module
from opencensus.trace.exporters.transports.background_thread \
    import BackgroundThreadTransport

exporter = stackdriver_exporter.StackdriverExporter(
    project_id='your_cloud_project', transport=BackgroundThreadTransport)
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``:

.. code:: python

    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``:

.. code:: python

    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:

.. code:: python

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_PARAMS in settings.py:

.. code:: python

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

.. note:: By default, the health check path for the App Engine flexible environment is not traced,
but you can turn it on by excluding it from the blacklist setting.

Framework Integration

Census supports integration with popular web frameworks including Django,
Flask, and Pyramid. When the application receives a HTTP request, the tracer
will automatically generate a span context using the trace information
extracted from the request headers and propagated to the child spans.

Flask


In your application, use the middleware to wrap your app and the
requests will be automatically traced.

.. code:: python

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

    app = flask.Flask(__name__)

    # You can also specify the sampler, exporter, propagator in the middleware,
    # default is using `AlwaysOnSampler` as sampler, `PrintExporter` as exporter,
    # `GoogleCloudFormatPropagator` as propagator.
    middleware = FlaskMiddleware(app)

Django

For tracing Django requests, you will need to add the following line to
the MIDDLEWARE_CLASSES section in the Django settings.py file.

.. code:: python

MIDDLEWARE_CLASSES = [
    ...
    'opencensus.trace.ext.django.middleware.OpencensusMiddleware',
]

And add this line to the INSTALLED_APPS section:

.. code:: python

INSTALLED_APPS = [
    ...
    'opencensus.trace.ext.django',
]

You can configure the sampler, exporter, propagator using the OPENCENSUS_TRACE setting in
settings.py:

.. code:: python

OPENCENSUS_TRACE = {
    'SAMPLER': 'opencensus.trace.samplers.probability.ProbabilitySampler',
    'EXPORTER': 'opencensus.trace.exporters.print_exporter.PrintExporter',
    'PROPAGATOR': 'opencensus.trace.propagation.google_cloud_format.'
                  'GoogleCloudFormatPropagator',
}

You can configure the sampling rate and other parameters using the OPENCENSUS_TRACE_PARAMS
setting in settings.py:

.. code:: python

OPENCENSUS_TRACE_PARAMS = {
    'BLACKLIST_PATHS': ['/_ah/health'],
    'GCP_EXPORTER_PROJECT': None,
    'SAMPLING_RATE': 0.5,
    'SERVICE_NAME': 'my_service',
    'ZIPKIN_EXPORTER_HOST_NAME': 'localhost',
    'ZIPKIN_EXPORTER_PORT': 9411,
    'ZIPKIN_EXPORTER_PROTOCOL': 'http',
}

Pyramid


In your application, add the pyramid tween and your requests will be
traced.

.. code:: python

    def main(global_config, **settings):
        config = Configurator(settings=settings)

        config.add_tween('opencensus.trace.ext.pyramid'
                         '.pyramid_middleware.OpenCensusTweenFactory')

To configure the sampler, exporter, and propagator, pass the instances
into the pyramid settings

.. code:: python

    from opencensus.trace.exporters import print_exporter
    from opencensus.trace.propagation import google_cloud_format
    from opencensus.trace.samplers import probability

    settings = {}
    settings['OPENCENSUS_TRACE'] = {
        'EXPORTER': print_exporter.PrintExporter(),
        'SAMPLER': probability.ProbabilitySampler(rate=0.5),
        'PROPAGATOR': google_cloud_format.GoogleCloudFormatPropagator(),
    }

    config = Configurator(settings=settings)

gRPC Integration
----------------

OpenCensus provides the implementation of interceptors for both the client side
and server side to instrument the gRPC requests and responses. The client
interceptors are used to create a decorated channel that intercepts client
gRPC calls and server interceptors act as decorators over handlers.

gRPC interceptor is a new feature in the grpcio1.8.0 release, please upgrade
your grpcio to the latest version to use this feature.

For sample usage, please refer to the hello world example in the examples
directory.

More information about the gRPC interceptors please see the `proposal`_.

.. _proposal: https://github.com/mehrdada/proposal/blob/python-interceptors/L13-Python-Interceptors.md

Service Integration
-------------------

Opencensus supports integration with various popular outbound services such as
SQL packages, Requests and Google Cloud client libraries. To enable integration
services to census:	you will need to pass the list of services to census:

.. code:: python

    from opencensus.trace import config_integration
    from opencensus.trace import tracer as tracer_module

    import mysql.connector

    # Trace both mysql-connection and psycopg2
    integration = ['mysql', 'postgresql']

    config_integration.trace_integrations(integration)


MySQL
~~~~~

The integration with MySQL supports the `mysql-connector`_ library and is specified
to ``trace_integrations`` using ``'mysql'``.

.. _mysql-connector: https://pypi.org/project/mysql-connector

PostgreSQL

The integration with PostgreSQL supports the psycopg2_ library and is specified
to trace_integrations using 'postgresql'.

.. _psycopg2: https://pypi.org/project/psycopg2

SQLAlchemy


You can trace usage of the `sqlalchemy package`_, regardless of the underlying
database, by specifying ``'sqlalchemy'`` to ``trace_integrations``.

.. _SQLAlchemy package: https://pypi.org/project/SQLAlchemy

.. note:: If you enable tracing of SQLAlchemy as well as the underlying database
    driver, you will get duplicate spans. Instead, just trace SQLAlchemy.

Requests
~~~~~~~~

Census can trace HTTP requests made with the `Requests package`_. The request URL,
method, and status will be collected.

You can enable Requests integration by specifying ``'requests'`` to ``trace_integrations``.

It's possible to configure a list of URL you don't want traced. By default the request to exporter
won't be traced. It's configurable by giving an array of hostname/port to the attribute
``blacklist_hostnames`` in OpenCensus context's attributes:

.. code:: python

    execution_context.set_opencensus_attr('blacklist_hostnames',['hostname:port'])

Only the hostname must be specified if only the hostname is specified in the URL request.

.. _Requests package: https://pypi.python.org/pypi/requests

Httplib
~~~~~~~~

Census can trace HTTP requests made with the httplib library.

You can enable Requests integration by specifying ``'httplib'`` to ``trace_integrations``.

It's possible to configure a list of URL you don't want traced. See requests integration
for more information. The only difference is that you need to specify hostname and port
every time.

Google Cloud Client Libraries

Census can trace HTTP and gRPC requests made with the Cloud client libraries_.
The request URL, method, and status will be collected.

You can enable Google Cloud client libraries integration by specifying 'google_cloud_clientlibs' to trace_integrations.

.. _Cloud client libraries: https://github.com/GoogleCloudPlatform/google-cloud-python#google-cloud-python-client

Threading


Census can propagate trace across threads when using the Threading package.

You can enable Threading integration by specifying ``'threading'`` to ``trace_integrations``.

------
 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: https://app.google.stackdriver.com/metrics-explorer

Stackdriver Exporter Usage

Stackdriver Import


.. code:: python

    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_).

.. _Click here: https://opencensus.io/codelabs/stackdriver

Register the Stackdriver exporter


.. code:: python

    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: https://prometheus.io/

Prometheus Exporter Usage


Prometheus Import
********************

    .. code:: python

        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
***********************************

    .. code:: python

        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 <CONTRIBUTING.md>`__ 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 <LICENSE>`__ for more information.

Disclaimer
----------

This is not an official Google product.

Languages

Python99.6%Shell0.3%HTML0.1%Makefile0.1%
Apache License 2.0
Created November 28, 2018
Updated November 29, 2018
kornholi/opencensus-python | GitHunt