Librados (Python)¶

The rados module is a thin Python wrapper for librados.

Installation¶

To install Python libraries for Ceph, see Getting librados for Python.

Getting Started¶

You can create your own Ceph client using Python. The following tutorial will show you how to import the Ceph Python module, connect to a Ceph cluster, and perform object operations as a client.admin user.

Note

To use the Ceph Python bindings, you must have access to a running Ceph cluster. To set one up quickly, see Getting Started.

First, create a Python source file for your Ceph client. ::

linenos:: sudo vim client.py

Import the Module¶

To use the rados module, import it into your source file.

1	import rados

Configure a Cluster Handle¶

Before connecting to the Ceph Storage Cluster, create a cluster handle. By default, the cluster handle assumes a cluster named ceph (i.e., the default for deployment tools, and our Getting Started guides too), and a client.admin user name. You may change these defaults to suit your needs.

To connect to the Ceph Storage Cluster, your application needs to know where to find the Ceph Monitor. Provide this information to your application by specifying the path to your Ceph configuration file, which contains the location of the initial Ceph monitors.

     import rados, sys

     #Create Handle Examples.
     cluster = rados.Rados(conffile='ceph.conf')
     cluster = rados.Rados(conffile=sys.argv[1])
     cluster = rados.Rados(conffile = 'ceph.conf', conf = dict (keyring = '/path/to/keyring'))

Ensure that the conffile argument provides the path and file name of your Ceph configuration file. You may use the sys module to avoid hard-coding the Ceph configuration path and file name.

Your Python client also requires a client keyring. For this example, we use the client.admin key by default. If you would like to specify the keyring when creating the cluster handle, you may use the conf argument. Alternatively, you may specify the keyring path in your Ceph configuration file. For example, you may add something like the following line to you Ceph configuration file:

keyring = /path/to/ceph.client.admin.keyring

For additional details on modifying your configuration via Python, see Configuration.

Connect to the Cluster¶

Once you have a cluster handle configured, you may connect to the cluster. With a connection to the cluster, you may execute methods that return information about the cluster.

     import rados, sys

     cluster = rados.Rados(conffile='ceph.conf')
     print "\nlibrados version: " + str(cluster.version())
     print "Will attempt to connect to: " + str(cluster.conf_get('mon initial members'))

     cluster.connect()
     print "\nCluster ID: " + cluster.get_fsid()

     print "\n\nCluster Statistics"
     print "=================="
     cluster_stats = cluster.get_cluster_stats()

     for key, value in cluster_stats.iteritems():
             print key, value

By default, Ceph authentication is on. Your application will need to know the location of the keyring. The python-ceph module doesn’t have the default location, so you need to specify the keyring path. The easiest way to specify the keyring is to add it to the Ceph configuration file. The following Ceph configuration file example uses the client.admin keyring you generated with ceph-deploy.

     [global]
     ...
     keyring=/path/to/keyring/ceph.client.admin.keyring

Manage Pools¶

When connected to the cluster, the Rados API allows you to manage pools. You can list pools, check for the existence of a pool, create a pool and delete a pool.

     print "\n\nPool Operations"
     print "==============="

     print "\nAvailable Pools"
     print "----------------"
     pools = cluster.list_pools()

     for pool in pools:
             print pool

     print "\nCreate 'test' Pool"
     print "------------------"
     cluster.create_pool('test')

     print "\nPool named 'test' exists: " + str(cluster.pool_exists('test'))
     print "\nVerify 'test' Pool Exists"
     print "-------------------------"
     pools = cluster.list_pools()

     for pool in pools:
             print pool

     print "\nDelete 'test' Pool"
     print "------------------"
     cluster.delete_pool('test')
     print "\nPool named 'test' exists: " + str(cluster.pool_exists('test'))

Input/Output Context¶

Reading from and writing to the Ceph Storage Cluster requires an input/output context (ioctx). You can create an ioctx with the open_ioctx() method of the Rados class. The ioctx_name parameter is the name of the pool you wish to use.

     ioctx = cluster.open_ioctx('data')

Once you have an I/O context, you can read/write objects, extended attributes, and perform a number of other operations. After you complete operations, ensure that you close the connection. For example:

     print "\nClosing the connection."
     ioctx.close()

Writing, Reading and Removing Objects¶

Once you create an I/O context, you can write objects to the cluster. If you write to an object that doesn’t exist, Ceph creates it. If you write to an object that exists, Ceph overwrites it (except when you specify a range, and then it only overwrites the range). You may read objects (and object ranges) from the cluster. You may also remove objects from the cluster. For example:

print "\nWriting object 'hw' with contents 'Hello World!' to pool 'data'."
ioctx.write_full("hw", "Hello World!")

print "\n\nContents of object 'hw'\n------------------------\n"
print ioctx.read("hw")

print "\nRemoving object 'hw'"
ioctx.remove_object("hw")

Writing and Reading XATTRS¶

Once you create an object, you can write extended attributes (XATTRs) to the object and read XATTRs from the object. For example:

print "\n\nWriting XATTR 'lang' with value 'en_US' to object 'hw'"
ioctx.set_xattr("hw", "lang", "en_US")

print "\n\nGetting XATTR 'lang' from object 'hw'\n"
print ioctx.get_xattr("hw", "lang")

Listing Objects¶

If you want to examine the list of objects in a pool, you may retrieve the list of objects and iterate over them with the object iterator. For example:

object_iterator = ioctx.list_objects()

while True :

        try :
                rados_object = object_iterator.next()
                print "Object contents = " + rados_object.read()

        except StopIteration :
                break

The Object class provides a file-like interface to an object, allowing you to read and write content and extended attributes. Object operations using the I/O context provide additional functionality and asynchronous capabilities.

Cluster Handle API¶

The Rados class provides an interface into the Ceph Storage Daemon.

Configuration¶

The Rados class provides methods for getting and setting configuration values, reading the Ceph configuration file, and parsing arguments. You do not need to be connected to the Ceph Storage Cluster to invoke the following methods. See Storage Cluster Configuration for details on settings.

Connection Management¶

Once you configure your cluster handle, you may connect to the cluster, check the cluster fsid, retrieve cluster statistics, and disconnect (shutdown) from the cluster. You may also assert that the cluster handle is in a particular state (e.g., “configuring”, “connecting”, etc.).

Pool Operations¶

To use pool operation methods, you must connect to the Ceph Storage Cluster first. You may list the available pools, create a pool, check to see if a pool exists, and delete a pool.

Input/Output Context API¶

To write data to and read data from the Ceph Object Store, you must create an Input/Output context (ioctx). The Rados class provides a open_ioctx() method. The remaining ioctx operations involve invoking methods of the Ioctx and other classes.

Object Operations¶

The Ceph Storage Cluster stores data as objects. You can read and write objects synchronously or asynchronously. You can read and write from offsets. An object has a name (or key) and data.

Object Extended Attributes¶

You may set extended attributes (XATTRs) on an object. You can retrieve a list of objects or XATTRs and iterate over them.

Object Interface¶

From an I/O context, you can retrieve a list of objects from a pool and iterate over them. The object interface provide makes each object look like a file, and you may perform synchronous operations on the objects. For asynchronous operations, you should use the I/O context methods.