def pytest_bdd_before_step(request, feature, scenario, step, step_func):
if tracer is None:
return
context = tracer.get_call_context()
span = tracer.start_span(step.type, resource=step.name, span_type=step.type, child_of=context,)
setattr(step_func, "__dd_span__", span)
def home_page():
parent_id = int(tracer.get_call_context().get_current_root_span().trace_id)
app.logger.info(parent_id)
tracer.set_tags({'parent_span': parent_id})
return render_template('index.html',
image_url=dog_image(),
dog_fact=dog_fact()
)
def dog_image():
# randomly fail somewhere in here
if random.randrange(0, 10) == 9:
app.logger.error('We really should fix this at some point.')
abort(500, 'Huh, something randomly failed here.')
dog_image = requests.get(DOG_IMAGE_SERVICE).json()
image_url = dog_image.get('message')
app.logger.info('Returned image: %s' % image_url)
# set the breed at the root span to create a facet on
breed = extract_breed(image_url)
root_span = tracer.get_call_context().get_current_root_span()
root_span.set_tag('breed', breed)
# find out how big the image is
size = requests.get(image_url, stream=True).headers['Content-length']
app.logger.info("File size of image %s" % size)
# let's grade the image, maybe we should add this to a span somwhere?
quality = image_quality(size)
app.logger.info("Image quality is %s" % quality)
# TODO: we should add the quality as a tag here
# root_span.set_tag('tag_name', tag_value)
return image_url
def drop(cls, span: Span):
tracer.get_call_context().sampling_priority = USER_REJECT
span.set_tag(cls.EAGERLY_DROP_TRACE_KEY, True)
