pyignite.aio_client module

class pyignite.aio_client.AioClient(compact_footer: bool = None, partition_aware: bool = True, **kwargs)

Bases: pyignite.client.BaseClient

Asynchronous Client implementation.

__init__(compact_footer: bool = None, partition_aware: bool = True, **kwargs)

Initialize client.

Parameters:
  • compact_footer – (optional) use compact (True, recommended) or full (False) schema approach when serializing Complex objects. Default is to use the same approach the server is using (None). Apache Ignite binary protocol documentation on this topic: https://ignite.apache.org/docs/latest/binary-client-protocol/data-format#schema
  • partition_aware – (optional) try to calculate the exact data placement from the key before to issue the key operation to the server node, True by default.
close()
connect(*args)

Connect to Ignite cluster node(s).

Parameters:args – (optional) host(s) and port(s) to connect to.
create_cache(settings: Union[str, dict]) → pyignite.aio_cache.AioCache

Creates Ignite cache by name. Raises CacheError if such a cache is already exists.

Parameters:settings – cache name or dict of cache properties’ codes and values. All cache properties are documented here: Cache Properties. See also the cache creation example,
Returns:Cache object.
get_best_node()

Returns the node from the list of the nodes, opened by client, that most probably contains the needed key-value pair. See IEP-23.

This method is not a part of the public API. Unless you wish to extend the pyignite capabilities (with additional testing, logging, examining connections, et c.) you probably should not use it.

Parameters:
  • cache – Ignite cache, cache name or cache id,
  • key – (optional) pythonic key,
  • key_hint – (optional) Ignite data type, for which the given key should be converted,
Returns:

Ignite connection object.
get_binary_type(binary_type: Union[str, int]) → dict

Gets the binary type information from the Ignite server. This is quite a low-level implementation of Ignite thin client protocol’s OP_GET_BINARY_TYPE operation. You would probably want to use query_binary_type() instead.

Parameters:binary_type – binary type name or ID,
Returns:binary type description − a dict with the following fields:
  • type_exists: True if the type is registered, False otherwise. In the latter case all the following fields are omitted,
  • type_id: Complex object type ID,
  • type_name: Complex object type name,
  • affinity_key_field: string value or None,
  • is_enum: False in case of Complex object registration,
  • schemas: a list, containing the Complex object schemas in format: OrderedDict[field name: field type hint]. A schema can be empty.
get_cache(settings: Union[str, dict]) → pyignite.aio_cache.AioCache

Creates Cache object with a given cache name without checking it up on server. If such a cache does not exist, some kind of exception (most probably CacheError) may be raised later.

Parameters:settings – cache name or cache properties (but only PROP_NAME property is allowed),
Returns:Cache object.
get_cache_names() → list

Gets existing cache names.

Returns:list of cache names.
get_cluster() → pyignite.aio_cluster.AioCluster

Get client cluster facade.

Returns:AioCluster instance.
get_or_create_cache(settings: Union[str, dict]) → pyignite.aio_cache.AioCache

Creates Ignite cache, if not exist.

Parameters:settings – cache name or dict of cache properties’ codes and values. All cache properties are documented here: Cache Properties. See also the cache creation example,
Returns:Cache object.
put_binary_type(type_name: str, affinity_key_field: str = None, is_enum=False, schema: dict = None)

Registers binary type information in cluster. Do not update binary registry. This is a literal implementation of Ignite thin client protocol’s OP_PUT_BINARY_TYPE operation. You would probably want to use register_binary_type() instead.

Parameters:
  • type_name – name of the data type being registered,
  • affinity_key_field – (optional) name of the affinity key field,
  • is_enum – (optional) register enum if True, binary object otherwise. Defaults to False,
  • schema – (optional) when register enum, pass a dict of enumerated parameter names as keys and an integers as values. When register binary type, pass a dict of field names: field types. Binary type with no fields is OK.
query_binary_type(binary_type: Union[int, str], schema: Union[int, dict] = None)

Queries the registry of Complex object classes.

Parameters:
  • binary_type – Complex object type name or ID,
  • schema – (optional) Complex object schema or schema ID,
Returns:

found dataclass or None, if schema parameter is provided, a dict of {schema ID: dataclass} format otherwise.
random_node() → pyignite.connection.aio_connection.AioConnection

Returns random usable node.

This method is not a part of the public API. Unless you wish to extend the pyignite capabilities (with additional testing, logging, examining connections, et c.) you probably should not use it.

register_binary_type(data_class: Type[CT_co], affinity_key_field: str = None)

Register the given class as a representation of a certain Complex object type. Discards autogenerated or previously registered class.

Parameters:
  • data_class – Complex object class,
  • affinity_key_field – (optional) affinity parameter.
sql()

Runs an SQL query and returns its result.

Parameters:
  • query_str – SQL query string,
  • page_size – (optional) cursor page size. Default is 1024, which means that client makes one server call per 1024 rows,
  • query_args – (optional) query arguments. List of values or (value, type hint) tuples,
  • schema – (optional) schema for the query. Defaults to PUBLIC,
  • statement_type –

    (optional) statement type. Can be:

    • StatementType.ALL − any type (default),
    • StatementType.SELECT − select,
    • StatementType.UPDATE − update.
  • distributed_joins – (optional) distributed joins. Defaults to False,
  • local – (optional) pass True if this query should be executed on local node only. Defaults to False,
  • replicated_only – (optional) whether query contains only replicated tables or not. Defaults to False,
  • enforce_join_order – (optional) enforce join order. Defaults to False,
  • collocated – (optional) whether your data is co-located or not. Defaults to False,
  • lazy – (optional) lazy query execution. Defaults to False,
  • include_field_names – (optional) include field names in result. Defaults to False,
  • max_rows – (optional) query-wide maximum of rows. Defaults to -1 (all rows),
  • timeout – (optional) non-negative timeout value in ms. Zero disables timeout (default),
  • cache – (optional) Name or ID of the cache to use to infer schema. If set, ‘schema’ argument is ignored,
Returns:

async sql fields cursor with result rows as a lists. If include_field_names was set, the first row will hold field names.
tx_start(concurrency: pyignite.datatypes.transactions.TransactionConcurrency = <TransactionConcurrency.PESSIMISTIC: 1>, isolation: pyignite.datatypes.transactions.TransactionIsolation = <TransactionIsolation.REPEATABLE_READ: 1>, timeout: int = 0, label: Union[str, NoneType] = None) → pyignite.transaction.AioTransaction

Start async thin client transaction. Supported only python 3.7+

Parameters:
  • concurrency – (optional) transaction concurrency, see TransactionConcurrency,
  • isolation – (optional) transaction isolation level, see TransactionIsolation,
  • timeout – (optional) transaction timeout in milliseconds,
  • label – (optional) transaction label.
Returns:

AioTransaction instance.
unwrap_binary(value: Any) → Any

Detects and recursively unwraps Binary Object.

Parameters:value – anything that could be a Binary Object,
Returns:the result of the Binary Object unwrapping with all other data left intact.