How to use the pyignite.datatypes.Byte function in pyignite

To help you get started, we’ve selected a few pyignite examples, based on popular ways it is used in public projects.

Secure your code as it's written. Use Snyk Code to scan source code in minutes - no build needed - and fix issues immediately.

github gridgain / gridgain / modules / platforms / python / pyignite / api / key_value.py View on Github external
the given sample should be converted
    :param binary: (optional) pass True to keep the value in binary form.
     False by default,
    :param query_id: (optional) a value generated by client and returned
     as-is in response.query_id. When the parameter is omitted, a random
     value is generated,
    :return: API result data object. Contains zero status and a boolean
     success code, or non-zero status and an error description if something
     has gone wrong.
    """

    query_struct = Query(
        OP_CACHE_REMOVE_IF_EQUALS,
        [
            ('hash_code', Int),
            ('flag', Byte),
            ('key', key_hint or AnyDataObject),
            ('sample', sample_hint or AnyDataObject),
        ],
        query_id=query_id,
    )
    result = query_struct.perform(
        connection,
        query_params={
            'hash_code': cache_id(cache),
            'flag': 1 if binary else 0,
            'key': key,
            'sample': sample,
        },
        response_config=[
            ('success', Bool),
        ],
github gridgain / gridgain / modules / platforms / python / pyignite / api / cache_config.py View on Github external
:param connection: connection to Ignite server,
    :param cache: name or ID of the cache,
    :param flags: Ignite documentation is unclear on this subject,
    :param query_id: (optional) a value generated by client and returned as-is
     in response.query_id. When the parameter is omitted, a random value
     is generated,
    :return: API result data object. Result value is OrderedDict with
     the cache configuration parameters.
    """

    query_struct = Query(
        OP_CACHE_GET_CONFIGURATION,
        [
            ('hash_code', Int),
            ('flags', Byte),
        ],
        query_id=query_id,
    )
    result = query_struct.perform(
        connection,
        query_params={
            'hash_code': cache_id(cache),
            'flags': flags,
        },
        response_config=[
            ('cache_config', cache_config_struct),
        ],
    )
    if result.status == 0:
        result.value = compact_cache_config(result.value['cache_config'])
    return result
github gridgain / gridgain / modules / platforms / python / pyignite / connection / handshake.py View on Github external
def read_response(client):
    response_start = Struct([
        ('length', Int),
        ('op_code', Byte),
    ])
    start_class, start_buffer = response_start.parse(client)
    start = start_class.from_buffer_copy(start_buffer)
    data = response_start.to_python(start)
    if data['op_code'] == 0:
        response_end = Struct([
            ('version_major', Short),
            ('version_minor', Short),
            ('version_patch', Short),
            ('message', String),
        ])
        end_class, end_buffer = response_end.parse(client)
        end = end_class.from_buffer_copy(end_buffer)
        data.update(response_end.to_python(end))
    return data
github gridgain / gridgain / modules / platforms / python / pyignite / api / sql.py View on Github external
of type dict with results on success, non-zero status and an error
     description otherwise.

     Value dict is of following format:

     * `cursor`: int, cursor ID,
     * `data`: dict, result rows as key-value pairs,
     * `more`: bool, True if more data is available for subsequent
       ‘scan_cursor_get_page’ calls.
    """

    query_struct = Query(
        OP_QUERY_SCAN,
        [
            ('hash_code', Int),
            ('flag', Byte),
            ('filter', Null),
            ('page_size', Int),
            ('partitions', Int),
            ('local', Bool),
        ],
        query_id=query_id,
    )
    result = query_struct.perform(
        connection,
        query_params={
            'hash_code': cache_id(cache),
            'flag': 1 if binary else 0,
            'filter': None,
            'page_size': page_size,
            'partitions': partitions,
            'local': 1 if local else 0,