mirror of https://github.com/ceph/ceph
408 lines
12 KiB
ReStructuredText
408 lines
12 KiB
ReStructuredText
===================
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Librados (Python)
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===================
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The ``rados`` module is a thin Python wrapper for ``librados``.
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Installation
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============
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To install Python libraries for Ceph, see `Getting librados for Python`_.
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Getting Started
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===============
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You can create your own Ceph client using Python. The following tutorial will
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show you how to import the Ceph Python module, connect to a Ceph cluster, and
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perform object operations as a ``client.admin`` user.
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.. note:: To use the Ceph Python bindings, you must have access to a
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running Ceph cluster. To set one up quickly, see `Getting Started`_.
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First, create a Python source file for your Ceph client. ::
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:linenos:
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sudo vim client.py
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Import the Module
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-----------------
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To use the ``rados`` module, import it into your source file.
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.. code-block:: python
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:linenos:
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import rados
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Configure a Cluster Handle
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--------------------------
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Before connecting to the Ceph Storage Cluster, create a cluster handle. By
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default, the cluster handle assumes a cluster named ``ceph`` (i.e., the default
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for deployment tools, and our Getting Started guides too), and a
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``client.admin`` user name. You may change these defaults to suit your needs.
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To connect to the Ceph Storage Cluster, your application needs to know where to
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find the Ceph Monitor. Provide this information to your application by
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specifying the path to your Ceph configuration file, which contains the location
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of the initial Ceph monitors.
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.. code-block:: python
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:linenos:
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import rados, sys
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#Create Handle Examples.
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cluster = rados.Rados(conffile='ceph.conf')
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cluster = rados.Rados(conffile=sys.argv[1])
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cluster = rados.Rados(conffile = 'ceph.conf', conf = dict (keyring = '/path/to/keyring'))
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Ensure that the ``conffile`` argument provides the path and file name of your
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Ceph configuration file. You may use the ``sys`` module to avoid hard-coding the
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Ceph configuration path and file name.
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Your Python client also requires a client keyring. For this example, we use the
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``client.admin`` key by default. If you would like to specify the keyring when
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creating the cluster handle, you may use the ``conf`` argument. Alternatively,
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you may specify the keyring path in your Ceph configuration file. For example,
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you may add something like the following line to you Ceph configuration file::
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keyring = /path/to/ceph.client.admin.keyring
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For additional details on modifying your configuration via Python, see `Configuration`_.
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Connect to the Cluster
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----------------------
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Once you have a cluster handle configured, you may connect to the cluster.
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With a connection to the cluster, you may execute methods that return
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information about the cluster.
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.. code-block:: python
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:linenos:
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:emphasize-lines: 7
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import rados, sys
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cluster = rados.Rados(conffile='ceph.conf')
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print "\nlibrados version: " + str(cluster.version())
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print "Will attempt to connect to: " + str(cluster.conf_get('mon initial members'))
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cluster.connect()
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print "\nCluster ID: " + cluster.get_fsid()
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print "\n\nCluster Statistics"
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print "=================="
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cluster_stats = cluster.get_cluster_stats()
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for key, value in cluster_stats.iteritems():
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print key, value
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By default, Ceph authentication is ``on``. Your application will need to know
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the location of the keyring. The ``python-ceph`` module doesn't have the default
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location, so you need to specify the keyring path. The easiest way to specify
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the keyring is to add it to the Ceph configuration file. The following Ceph
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configuration file example uses the ``client.admin`` keyring you generated with
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``ceph-deploy``.
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.. code-block:: ini
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:linenos:
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[global]
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# ... elided configuration
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keyring=/path/to/keyring/ceph.client.admin.keyring
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Manage Pools
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------------
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When connected to the cluster, the ``Rados`` API allows you to manage pools. You
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can list pools, check for the existence of a pool, create a pool and delete a
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pool.
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.. code-block:: python
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:linenos:
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:emphasize-lines: 6, 13, 18, 25
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print "\n\nPool Operations"
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print "==============="
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print "\nAvailable Pools"
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print "----------------"
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pools = cluster.list_pools()
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for pool in pools:
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print pool
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print "\nCreate 'test' Pool"
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print "------------------"
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cluster.create_pool('test')
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print "\nPool named 'test' exists: " + str(cluster.pool_exists('test'))
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print "\nVerify 'test' Pool Exists"
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print "-------------------------"
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pools = cluster.list_pools()
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for pool in pools:
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print pool
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print "\nDelete 'test' Pool"
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print "------------------"
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cluster.delete_pool('test')
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print "\nPool named 'test' exists: " + str(cluster.pool_exists('test'))
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Input/Output Context
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--------------------
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Reading from and writing to the Ceph Storage Cluster requires an input/output
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context (ioctx). You can create an ioctx with the ``open_ioctx()`` method of the
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``Rados`` class. The ``ioctx_name`` parameter is the name of the pool you wish
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to use.
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.. code-block:: python
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:linenos:
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ioctx = cluster.open_ioctx('data')
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Once you have an I/O context, you can read/write objects, extended attributes,
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and perform a number of other operations. After you complete operations, ensure
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that you close the connection. For example:
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.. code-block:: python
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:linenos:
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print "\nClosing the connection."
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ioctx.close()
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Writing, Reading and Removing Objects
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-------------------------------------
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Once you create an I/O context, you can write objects to the cluster. If you
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write to an object that doesn't exist, Ceph creates it. If you write to an
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object that exists, Ceph overwrites it (except when you specify a range, and
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then it only overwrites the range). You may read objects (and object ranges)
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from the cluster. You may also remove objects from the cluster. For example:
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.. code-block:: python
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:linenos:
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:emphasize-lines: 2, 5, 8
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print "\nWriting object 'hw' with contents 'Hello World!' to pool 'data'."
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ioctx.write_full("hw", "Hello World!")
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print "\n\nContents of object 'hw'\n------------------------\n"
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print ioctx.read("hw")
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print "\nRemoving object 'hw'"
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ioctx.remove_object("hw")
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Writing and Reading XATTRS
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--------------------------
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Once you create an object, you can write extended attributes (XATTRs) to
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the object and read XATTRs from the object. For example:
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.. code-block:: python
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:linenos:
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:emphasize-lines: 2, 5
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print "\n\nWriting XATTR 'lang' with value 'en_US' to object 'hw'"
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ioctx.set_xattr("hw", "lang", "en_US")
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print "\n\nGetting XATTR 'lang' from object 'hw'\n"
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print ioctx.get_xattr("hw", "lang")
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Listing Objects
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---------------
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If you want to examine the list of objects in a pool, you may
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retrieve the list of objects and iterate over them with the object iterator.
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For example:
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.. code-block:: python
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:linenos:
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:emphasize-lines: 1, 6, 7
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object_iterator = ioctx.list_objects()
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while True :
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try :
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rados_object = object_iterator.next()
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print "Object contents = " + rados_object.read()
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except StopIteration :
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break
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The ``Object`` class provides a file-like interface to an object, allowing
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you to read and write content and extended attributes. Object operations using
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the I/O context provide additional functionality and asynchronous capabilities.
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Cluster Handle API
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==================
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The ``Rados`` class provides an interface into the Ceph Storage Daemon.
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Configuration
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-------------
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The ``Rados`` class provides methods for getting and setting configuration
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values, reading the Ceph configuration file, and parsing arguments. You
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do not need to be connected to the Ceph Storage Cluster to invoke the following
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methods. See `Storage Cluster Configuration`_ for details on settings.
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.. currentmodule:: rados
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.. automethod:: Rados.conf_get(option)
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.. automethod:: Rados.conf_set(option, val)
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.. automethod:: Rados.conf_read_file(path=None)
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.. automethod:: Rados.conf_parse_argv(args)
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.. automethod:: Rados.version()
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Connection Management
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---------------------
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Once you configure your cluster handle, you may connect to the cluster, check
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the cluster ``fsid``, retrieve cluster statistics, and disconnect (shutdown)
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from the cluster. You may also assert that the cluster handle is in a particular
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state (e.g., "configuring", "connecting", etc.).
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.. automethod:: Rados.connect(timeout=0)
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.. automethod:: Rados.shutdown()
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.. automethod:: Rados.get_fsid()
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.. automethod:: Rados.get_cluster_stats()
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.. documented manually because it raises warnings because of *args usage in the
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.. signature
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.. py:class:: Rados
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.. py:method:: require_state(*args)
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Checks if the Rados object is in a special state
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:param args: Any number of states to check as separate arguments
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:raises: :class:`RadosStateError`
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Pool Operations
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---------------
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To use pool operation methods, you must connect to the Ceph Storage Cluster
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first. You may list the available pools, create a pool, check to see if a pool
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exists, and delete a pool.
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.. automethod:: Rados.list_pools()
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.. automethod:: Rados.create_pool(pool_name, auid=None, crush_rule=None)
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.. automethod:: Rados.pool_exists()
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.. automethod:: Rados.delete_pool(pool_name)
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Input/Output Context API
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========================
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To write data to and read data from the Ceph Object Store, you must create
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an Input/Output context (ioctx). The `Rados` class provides a `open_ioctx()`
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method. The remaining ``ioctx`` operations involve invoking methods of the
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`Ioctx` and other classes.
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.. automethod:: Rados.open_ioctx(ioctx_name)
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.. automethod:: Ioctx.require_ioctx_open()
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.. automethod:: Ioctx.get_stats()
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.. automethod:: Ioctx.change_auid(auid)
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.. automethod:: Ioctx.get_last_version()
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.. automethod:: Ioctx.close()
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.. Pool Snapshots
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.. --------------
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.. The Ceph Storage Cluster allows you to make a snapshot of a pool's state.
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.. Whereas, basic pool operations only require a connection to the cluster,
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.. snapshots require an I/O context.
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.. Ioctx.create_snap(self, snap_name)
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.. Ioctx.list_snaps(self)
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.. SnapIterator.next(self)
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.. Snap.get_timestamp(self)
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.. Ioctx.lookup_snap(self, snap_name)
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.. Ioctx.remove_snap(self, snap_name)
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.. not published. This doesn't seem ready yet.
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Object Operations
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-----------------
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The Ceph Storage Cluster stores data as objects. You can read and write objects
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synchronously or asynchronously. You can read and write from offsets. An object
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has a name (or key) and data.
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.. automethod:: Ioctx.aio_write(object_name, to_write, offset=0, oncomplete=None, onsafe=None)
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.. automethod:: Ioctx.aio_write_full(object_name, to_write, oncomplete=None, onsafe=None)
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.. automethod:: Ioctx.aio_append(object_name, to_append, oncomplete=None, onsafe=None)
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.. automethod:: Ioctx.write(key, data, offset=0)
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.. automethod:: Ioctx.write_full(key, data)
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.. automethod:: Ioctx.aio_flush()
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.. automethod:: Ioctx.set_locator_key(loc_key)
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.. automethod:: Ioctx.aio_read(object_name, length, offset, oncomplete)
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.. automethod:: Ioctx.read(key, length=8192, offset=0)
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.. automethod:: Ioctx.stat(key)
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.. automethod:: Ioctx.trunc(key, size)
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.. automethod:: Ioctx.remove_object(key)
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Object Extended Attributes
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--------------------------
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You may set extended attributes (XATTRs) on an object. You can retrieve a list
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of objects or XATTRs and iterate over them.
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.. automethod:: Ioctx.set_xattr(key, xattr_name, xattr_value)
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.. automethod:: Ioctx.get_xattrs(oid)
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.. automethod:: XattrIterator.next()
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.. automethod:: Ioctx.get_xattr(key, xattr_name)
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.. automethod:: Ioctx.rm_xattr(key, xattr_name)
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Object Interface
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================
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From an I/O context, you can retrieve a list of objects from a pool and iterate
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over them. The object interface provide makes each object look like a file, and
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you may perform synchronous operations on the objects. For asynchronous
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operations, you should use the I/O context methods.
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.. automethod:: Ioctx.list_objects()
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.. automethod:: ObjectIterator.next()
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.. automethod:: Object.read(length = 1024*1024)
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.. automethod:: Object.write(string_to_write)
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.. automethod:: Object.get_xattrs()
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.. automethod:: Object.get_xattr(xattr_name)
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.. automethod:: Object.set_xattr(xattr_name, xattr_value)
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.. automethod:: Object.rm_xattr(xattr_name)
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.. automethod:: Object.stat()
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.. automethod:: Object.remove()
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.. _Getting Started: ../../../start
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.. _Storage Cluster Configuration: ../../configuration
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.. _Getting librados for Python: ../librados-intro#getting-librados-for-python
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