OpenCensus for Python - A stats collection and distributed tracing framework
============================================================================

    `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.

    .. _OpenCensus: 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

Installation & basic usage
--------------------------

1. Install the opencensus-trace 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/

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()

OpenCensus 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 import samplers
    from opencensus.trace import tracer as tracer_module

    # Sampling the requests at the rate equals 0.5
    sampler = samplers.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:

.. code:: python

    from opencensus.trace 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.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)

Propagators
~~~~~~~~~~~

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

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)

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.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``:

.. code:: python

    OPENCENSUS_TRACE_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
---------------------

OpenCensus 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.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`` section in the Django ``settings.py`` file.

.. code:: python

    MIDDLEWARE = [
        ...
        'opencensus.ext.django.middleware.OpencensusMiddleware',
    ]

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',
        'REPORTER': 'opencensus.trace.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.ext.pyramid'
                         '.pyramid_middleware.OpenCensusTweenFactory')

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

.. code:: python

    from opencensus.trace 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
MySQL and Requests. To enable integration 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
~~~~~~~~

OpenCensus 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``.

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


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

    # Run the unit test
    pip install nox-automation

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

    # Run a single nox command
    nox -s "unit_tests(python_version='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.
