ddtrace-graphql 0.2.0

Installation

Usage

To trace all GraphQL requests patch the library. Put this snippet to your application main entry point.

__import__('ddtrace_graphql').patch()

# OR

from ddtrace_graphql import patch
patch()

Check out the datadog trace client for all supported libraries and frameworks.

# app/__init__.py
__import__('ddtrace_graphql').patch()

# from that point all calls to graphql are traced
from graphql import graphql
result = graphql(schema, query)

Trace only certain calls with traced_graphql function

from ddtrace_graphql import traced_graphql
traced_graphql(schema, query)

Configuration

Environment variables

DDTRACE_GRAPHQL_SERVICE:

Define service name under which traces are shown in Datadog. Default value is graphql

$ export DDTRACE_GRAPHQL_SERVICE=foobar.graphql

span_kwargs

Default arguments passed to the tracing context manager can be updated using span_kwargs argument of ddtrace_graphql.patch or ddtrace_graphql.traced_graphql functions.

Default values:

name:

Wrapped resource name. Default graphql.graphql.

span_type:

Span type. Default graphql.

service:

Service name. Defaults to DDTRACE_GRAPHQL_SERVICE environment variable if present, else graphql.

resource:

Processed resource. Defaults to query / mutation signature.

For more information visit ddtrace.Tracer.trace documentation.

from ddtrace_graphql import patch
patch(span_kwargs=dict(service='foo.graphql'))

from ddtrace_graphql import traced_graphql
traced_graphql(schema, query, span_kwargs=dict(resource='bar.resource'))

span_callback

In case you want to postprocess trace span you may use span_callback argument. span_callback must be function with signature def callback(result=result, span=span) where result is graphql execution result or None in case of fatal error and span is trace span object (ddtrace.span.Span).

What is it good for? Unfortunately one cannot filter/alarm on span metrics resp. meta information even if those are numeric (why Datadog?) so you can use it to send metrics based on span, result attributes.

from datadog import statsd
from ddtrace_graphql import patch, CLIENT_ERROR, INVALID

def callback(result, span):
    tags = ['resource:{}'.format(span.resource.replace(' ', '_'))]
    statsd.increment('{}.request'.format(span.service), tags=tags)
    if span.error:
        statsd.increment('{}.error'.format(span.service), tags=tags)
    elif span.get_metric(CLIENT_ERROR):
        statsd.increment('{}.{}'.format(span.service, CLIENT_ERROR), tags=tags)
    if span.get_metric(INVALID):
        statsd.increment('{}.{}'.format(span.service, INVALID), tags=tags)

patch(span_callback=callback)

ignore_exceptions

Some frameworks use exceptions to handle 404s etc. you may want to ignore some exceptions resp. not consider them server error. To do this you can supply ignore_exceptions argument as list of exception classes to ignore. ignore_exceptions will be used in python’s isinstance thus you can ignore also using base classes.

from ddtrace_graphql import patch
patch(ignore_exceptions=(ObjectNotFound, PermissionsDenied))

from ddtrace_graphql import traced_graphql
traced_graphql(
    schema, query,
    ignore_exceptions=(ObjectNotFound, PermissionsDenied))

Development