Python library for tracing graphql calls with Datadog
Project description
===============
ddtrace-graphql
===============
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Python library to trace graphql calls with Datadog.
* `graphql-core <https://github.com/graphql-python/graphql-core>`_
* `Datadog APM (Tracing) <https://docs.datadoghq.com/tracing/>`_
* `Datadog Trace Client <http://pypi.datadoghq.com/trace/docs/>`_
Compatibility
-------------
``ddtrace-graphql`` is tested with:
* Python versions: 3.5, 3.6, nightly
* graphql-core: 2.0, 1.1.0, latest
* ddtrace: 0.11.1, 0.10.1, latest
*Screenshots for pyramid app serving GraphQL with tracing enabled:*
.. figure:: screenshots/service.png
:scale: 80%
GraphQL service detail.
.. figure:: screenshots/query.png
:scale: 80%
GraphQL query detail.
Installation
============
Using pip
---------
.. code-block:: bash
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 <http://pypi.datadoghq.com/trace/docs/#ddtrace.Tracer.trace>`_ documentation.
.. code-block:: python
from ddtrace_graphql import patch
patch(span_kwargs=dict(service='foo.graphql'))
.. code-block:: python
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 <https://github.com/DataDog/dd-trace-py/blob/master/ddtrace/span.py>`_).
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.
.. code-block:: python
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.
.. code-block:: python
from ddtrace_graphql import patch
patch(ignore_exceptions=(ObjectNotFound, PermissionsDenied))
.. code-block:: python
from ddtrace_graphql import traced_graphql
traced_graphql(
schema, query,
ignore_exceptions=(ObjectNotFound, PermissionsDenied))
Development
===========
Install from source in development mode
---------------------------------------
.. code-block:: bash
Run tests
---------
.. code-block:: bash
