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Logging API usage docs.
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Squashed after review on PR #1488.
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7 changes: 7 additions & 0 deletions docs/index.rst
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search-index
search-document

.. toctree::
:maxdepth: 0
:hidden:
:caption: Cloud Logging

logging-usage

.. toctree::
:maxdepth: 0
:hidden:
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307 changes: 307 additions & 0 deletions docs/logging-usage.rst
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Using the API
=============


Authentication and Configuration
--------------------------------

- For an overview of authentication in ``gcloud-python``,
see :doc:`gcloud-auth`.

- In addition to any authentication configuration, you should also set the
:envvar:`GCLOUD_PROJECT` environment variable for the project you'd like
to interact with. If you are Google App Engine or Google Compute Engine
this will be detected automatically.

- After configuring your environment, create a
:class:`Client <gcloud.logging.client.Client>`

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()

or pass in ``credentials`` and ``project`` explicitly

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client(project='my-project', credentials=creds)


Writing log entries
-------------------

Write a simple text entry to a logger.

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> logger = client.logger('log_name')
>>> logger.log_text("A simple entry") # API call

Write a dictionary entry to a logger.

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> logger = client.logger('log_name')
>>> logger.log_struct(
... message="My second entry",
... weather="partly cloudy") # API call


Retrieving log entries
----------------------

Fetch entries for the default project.

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> entries, token = client.list_entries() # API call
>>> for entry in entries:
... timestamp = entry.timestamp.isoformat()
... print('%sZ: %s | %s' %
... (timestamp, entry.text_payload, entry.struct_payload))
2016-02-17T20:35:49.031864072Z: A simple entry | None
2016-02-17T20:38:15.944418531Z: None | {'message': 'My second entry', 'weather': 'partly cloudy'}

Fetch entries across multiple projects.

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> entries, token = client.list_entries(
... project_ids=['one-project', 'another-project']) # API call

Filter entries retrieved using the `Advanced Logs Filters`_ syntax

.. _Advanced Logs Filters: https://cloud.google.com/logging/docs/view/advanced_filters

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> FILTER = "log:log_name AND textPayload:simple"
>>> entries, token = client.list_entries(filter=FILTER) # API call

Sort entries in descending timestamp order.

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> entries, token = client.list_entries(order_by=logging.DESCENDING) # API call

Retrieve entities in batches of 10, iterating until done.

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> retrieved = []
>>> token = None
>>> while True:
... entries, token = client.list_entries(page_size=10, page_token=token) # API call
... retrieved.extend(entries)
... if token is None:
... break


Delete all entries for a logger
-------------------------------

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> logger = client.logger('log_name')
>>> logger.delete_entries() # API call


Manage log metrics
------------------

Metrics are counters of entries which match a given filter. They can be
used within Cloud Monitoring to create charts and alerts.

Create a metric:

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> metric = client.metric(
... "robots", "Robots all up in your server",
... filter='log:apache-access AND textPayload:robot')
>>> metric.exists() # API call
False
>>> metric.create() # API call
>>> metric.exists() # API call
True

List all metrics for a project:

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> metrics, token = client.list_metrics()
>>> len(metrics)
1
>>> metric = metrics[0]
>>> metric.name
"robots"

Refresh local information about a metric:

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> metric = client.metric("robots")
>>> metric.reload() # API call
>>> metric.description
"Robots all up in your server"
>>> metric.filter
"log:apache-access AND textPayload:robot"

Update a metric:

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> metric = client.metric("robots")
>>> metric.exists() # API call
True
>>> metric.reload() # API call
>>> metric.description = "Danger, Will Robinson!"
>>> metric.update() # API call

Delete a metric:

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> metric = client.metric("robots")
>>> metric.exists() # API call
True
>>> metric.delete() # API call
>>> metric.exists() # API call
False


Export log entries using sinks
------------------------------

Sinks allow exporting entries which match a given filter to Cloud Storage
buckets, BigQuery datasets, or Cloud Pub/Sub topics.

Create a Cloud Storage sink:

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> sink = client.sink(
... "robots-storage",
... filter='log:apache-access AND textPayload:robot')
>>> sink.storage_bucket = "my-bucket-name"
>>> sink.exists() # API call
False
>>> sink.create() # API call
>>> sink.exists() # API call
True

Create a BigQuery sink:

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> sink = client.sink(
... "robots-bq",
... filter='log:apache-access AND textPayload:robot')
>>> sink.bigquery_dataset = "projects/my-project/datasets/my-dataset"
>>> sink.exists() # API call
False
>>> sink.create() # API call
>>> sink.exists() # API call
True

Create a Cloud Pub/Sub sink:

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> sink = client.sink(
... "robots-pubsub",
... filter='log:apache-access AND textPayload:robot')
>>> sink.pubsub_topic = 'projects/my-project/topics/my-topic'
>>> sink.exists() # API call
False
>>> sink.create() # API call
>>> sink.exists() # API call
True

List all sinks for a project:

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> sinks, token = client.list_sinks()
>>> for sink in sinks:
... print('%s: %s' % (sink.name, sink.destination))
robots-storage: storage.googleapis.com/my-bucket-name
robots-bq: bigquery.googleapis.com/projects/my-project/datasets/my-dataset
robots-pubsub: pubsub.googleapis.com/projects/my-project/topics/my-topic

Refresh local information about a sink:

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> sink = client.sink('robots-storage')
>>> sink.filter is None
True
>>> sink.reload() # API call
>>> sink.filter
'log:apache-access AND textPayload:robot'
>>> sink.destination
'storage.googleapis.com/my-bucket-name'

Update a sink:

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> sink = client.sink("robots")
>>> sink.reload() # API call
>>> sink.filter = "log:apache-access"
>>> sink.update() # API call

Delete a sink:

.. doctest::

>>> from gcloud import logging
>>> client = logging.Client()
>>> sink = client.sink(
... "robots",
... filter='log:apache-access AND textPayload:robot')
>>> sink.exists() # API call
True
>>> sink.delete() # API call
>>> sink.exists() # API call
False

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