=================== 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. .. code-block:: python :linenos: 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. .. code-block:: python :linenos: 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. .. code-block:: python :linenos: :emphasize-lines: 7 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``. .. code-block:: ini :linenos: [global] # ... elided configuration 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. .. code-block:: python :linenos: :emphasize-lines: 6, 13, 18, 25 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()`` or ``open_ioctx2()`` method of the ``Rados`` class. The ``ioctx_name`` parameter is the name of the pool and ``pool_id`` is the ID of the pool you wish to use. .. code-block:: python :linenos: ioctx = cluster.open_ioctx('data') or .. code-block:: python :linenos: ioctx = cluster.open_ioctx(pool_id) 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: .. code-block:: python :linenos: 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: .. code-block:: python :linenos: :emphasize-lines: 2, 5, 8 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: .. code-block:: python :linenos: :emphasize-lines: 2, 5 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: .. code-block:: python :linenos: :emphasize-lines: 1, 6, 7 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. .. currentmodule:: rados .. automethod:: Rados.conf_get(option) .. automethod:: Rados.conf_set(option, val) .. automethod:: Rados.conf_read_file(path=None) .. automethod:: Rados.conf_parse_argv(args) .. automethod:: Rados.version() 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.). .. automethod:: Rados.connect(timeout=0) .. automethod:: Rados.shutdown() .. automethod:: Rados.get_fsid() .. automethod:: Rados.get_cluster_stats() .. documented manually because it raises warnings because of *args usage in the .. signature .. py:class:: Rados .. py:method:: require_state(*args) Checks if the Rados object is in a special state :param args: Any number of states to check as separate arguments :raises: :class:`RadosStateError` 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. .. automethod:: Rados.list_pools() .. automethod:: Rados.create_pool(pool_name, auid=None, crush_rule=None) .. automethod:: Rados.pool_exists() .. automethod:: Rados.delete_pool(pool_name) 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 `open_ioctx()` and `open_ioctx2()` methods. The remaining ``ioctx`` operations involve invoking methods of the `Ioctx` and other classes. .. automethod:: Rados.open_ioctx(ioctx_name) .. automethod:: Ioctx.require_ioctx_open() .. automethod:: Ioctx.get_stats() .. automethod:: Ioctx.change_auid(auid) .. automethod:: Ioctx.get_last_version() .. automethod:: Ioctx.close() .. Pool Snapshots .. -------------- .. The Ceph Storage Cluster allows you to make a snapshot of a pool's state. .. Whereas, basic pool operations only require a connection to the cluster, .. snapshots require an I/O context. .. Ioctx.create_snap(self, snap_name) .. Ioctx.list_snaps(self) .. SnapIterator.next(self) .. Snap.get_timestamp(self) .. Ioctx.lookup_snap(self, snap_name) .. Ioctx.remove_snap(self, snap_name) .. not published. This doesn't seem ready yet. 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. .. automethod:: Ioctx.aio_write(object_name, to_write, offset=0, oncomplete=None, onsafe=None) .. automethod:: Ioctx.aio_write_full(object_name, to_write, oncomplete=None, onsafe=None) .. automethod:: Ioctx.aio_append(object_name, to_append, oncomplete=None, onsafe=None) .. automethod:: Ioctx.write(key, data, offset=0) .. automethod:: Ioctx.write_full(key, data) .. automethod:: Ioctx.aio_flush() .. automethod:: Ioctx.set_locator_key(loc_key) .. automethod:: Ioctx.aio_read(object_name, length, offset, oncomplete) .. automethod:: Ioctx.read(key, length=8192, offset=0) .. automethod:: Ioctx.stat(key) .. automethod:: Ioctx.trunc(key, size) .. automethod:: Ioctx.remove_object(key) 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. .. automethod:: Ioctx.set_xattr(key, xattr_name, xattr_value) .. automethod:: Ioctx.get_xattrs(oid) .. automethod:: XattrIterator.__next__() .. automethod:: Ioctx.get_xattr(key, xattr_name) .. automethod:: Ioctx.rm_xattr(key, xattr_name) 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. .. automethod:: Ioctx.list_objects() .. automethod:: ObjectIterator.__next__() .. automethod:: Object.read(length = 1024*1024) .. automethod:: Object.write(string_to_write) .. automethod:: Object.get_xattrs() .. automethod:: Object.get_xattr(xattr_name) .. automethod:: Object.set_xattr(xattr_name, xattr_value) .. automethod:: Object.rm_xattr(xattr_name) .. automethod:: Object.stat() .. automethod:: Object.remove() .. _Getting Started: ../../../start .. _Storage Cluster Configuration: ../../configuration .. _Getting librados for Python: ../librados-intro#getting-librados-for-python