A collection of Python instrumentation tools for the OpenTracing API
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Jamim and yurishkuro Improve testing (#70)
As a software engineer, I'd like to be able to conveniently run tests
in my local environment, so I want to add a tox config file.

These changes:

 - Add tox.ini

 - Update setup.cfg

 - Enable branch coverage measurement

 - Update the README

 - Unify tracer fixture and move it to conftest.py

 - Fix some deprecation warnings

 - Clean up imports
Latest commit 576d3ee Nov 28, 2018

README.md

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opentracing-python-instrumentation

A collection of instrumentation tools to enable tracing with OpenTracing API.

Module

Make sure you are running recent enough versions of pip and setuptools, e.g. before installing your project requirements execute this:

pip install --upgrade "setuptools>=29" "pip>=9"

The module name is opentracing_instrumentation.

What's inside

Supported client frameworks

The following libraries are instrumented for tracing in this module:

  • urllib2
  • requests
  • SQLAlchemy
  • MySQLdb
  • psycopg2
  • Tornado HTTP client
  • redis

Server instrumentation

For inbound requests a helper function before_request is provided for creating middleware for frameworks like Flask and uWSGI.

Manual instrumentation

Finally, a @traced_function decorator is provided for manual instrumentation.

In-process Context Propagation

request_context implements thread-local based context propagation facility.

Usage

This library provides two types of instrumentation, explicit instrumentation for server endpoints, and implicit instrumentation for client call sites.

Server endpoints are instrumented by creating a middleware class that:

  1. initializes the specific tracer implementation
  2. wraps incoming request handlers into a method that reads the incoming tracing info from the request and creates a new tracing Span

Client call sites are instrumented implicitly by executing a set of available client_hooks that monkey-patch some API points in several common libraries like SQLAlchemy, urllib2, Tornado Async HTTP Client. The initialization of those hooks is usually also done from the middleware class's __init__ method.

There is a client-server example using this library with Flask instrumentation from opentracing-contrib: https://github.com/opentracing-contrib/python-flask/tree/master/example.

Here's an example of a middleware for Clay framework:

from opentracing_instrumentation.request_context import RequestContextManager
from opentracing_instrumentation.http_server import before_request
from opentracing_instrumentation.http_server import WSGIRequestWrapper
from opentracing_instrumentation.client_hooks import install_all_patches


class TracerMiddleware(object):

    def __init__(self, app, wsgi_app):
        self.wsgi_app = wsgi_app
        self.service_name = app.name

        CONFIG.app_name = self.service_name
        CONFIG.caller_name_headers.append('X-Uber-Source')
        CONFIG.callee_endpoint_headers.append('X-Uber-Endpoint')

        install_all_patches()
        self.wsgi_app = create_wsgi_middleware(wsgi_app)
        self.init_tracer()

    def __call__(self, environ, start_response):
        return self.wsgi_app(environ, start_response)

    def init_tracer(self):
        # code specific to your tracer implementation
        pass


def create_wsgi_middleware(other_wsgi, tracer=None):
    """
    Create a wrapper middleware for another WSGI response handler.
    If tracer is not passed in, 'opentracing.tracer' is used.
    """

    def wsgi_tracing_middleware(environ, start_response):
        # TODO find out if the route can be retrieved from somewhere

        request = WSGIRequestWrapper.from_wsgi_environ(environ)
        span = before_request(request=request, tracer=tracer)

        # Wrapper around the real start_response object to log
        # additional information to opentracing Span
        def start_response_wrapper(status, response_headers, exc_info=None):
            if exc_info is not None:
                span.set_tag('error', str(exc_info))
            span.finish()

            return start_response(status, response_headers)

        with RequestContextManager(span=span):
            return other_wsgi(environ, start_response_wrapper)

    return wsgi_tracing_middleware

And here's an example for middleware in Tornado-based app:

class TracerMiddleware(object):

    def __init__(self):
        # perform initialization similar to above, including installing
        # the client_hooks
        
    @gen.coroutine
    def __call__(self, request, handler, next_mw):
        request_wrapper = http_server.TornadoRequestWrapper(request=request)
        span = http_server.before_request(request=request_wrapper)

        @gen.coroutine
        def next_middleware_with_span():
            yield next_mw()

        yield run_coroutine_with_span(span=span,
                                      func=next_middleware_with_span)

        span.finish()


def run_coroutine_with_span(span, func, *args, **kwargs):
    """Wrap the execution of a Tornado coroutine func in a tracing span.

    This makes the span available through the get_current_span() function.

    :param span: The tracing span to expose.
    :param func: Co-routine to execute in the scope of tracing span.
    :param args: Positional args to func, if any.
    :param kwargs: Keyword args to func, if any.
    """
    def mgr():
        return RequestContextManager(span)

    with tornado.stack_context.StackContext(mgr):
        return func(*args, **kwargs)

Development

To prepare a development environment please execute the following commands.

virtualenv env
source env/bin/activate
make bootstrap
make test

You can use tox to run tests as well.

tox