NVIDIA Docs Hub NVIDIA Morpheus NVIDIA Morpheus (25.02.01) morpheus.stages.input.http_client_source_stage.HttpClientSourceStage

morpheus.stages.input.http_client_source_stage.HttpClientSourceStage

class HttpClientSourceStage(config, url, query_params=None, headers=None, method=HTTPMethod.GET, sleep_time=0.1, error_sleep_time=0.1, respect_retry_after_header=True, request_timeout_secs=30, accept_status_codes=(<HTTPStatus.OK: 200>, ), max_retries=10, lines=False, stop_after=0, payload_to_df_fn=None, message_type=SupportedMessageTypes.MESSAGE_META, task_type=None, task_payload=None, **request_kwargs)[source]

Bases: morpheus.pipeline.execution_mode_mixins.GpuAndCpuMixin, morpheus.pipeline.preallocator_mixin.PreallocatorMixin, morpheus.pipeline.configurable_output_source.ConfigurableOutputSource

Source stage that polls a remote HTTP server for incoming data.

Parameters

configmorpheus.config.Config: Pipeline configuration instance.
urlstr: Remote URL to poll for data, ex https://catalog.ngc.nvidia.com/api/collections. This should include protocol prefix (ex. “http://”, “https://”) and port if necessary. If the protocol is omitted, http:// will be used.
query_paramsdict, callable, default None: Query parameters to pass to the remote URL. Can either be a dictionary of key-value pairs or a callable that returns a dictionary of key-value pairs. If a callable is provided, it will be called with no arguments.
headers: dict, default None: Headers sent with the request.
methodmorpheus.utils.http_utils.HTTPMethod, optional, case_sensitive = False: HTTP method to use.
sleep_timefloat, default 0.1: Amount of time in seconds to sleep between successive requests. Setting this to 0 disables this feature.
error_sleep_timefloat, default 0.1: Amount of time in seconds to sleep after the client receives an error. The client will perform an exponential backoff starting at error_sleep_time. Setting this to 0 causes the client to retry the request as fast as possible. If the server sets a Retry-After header and respect_retry_after_header is True, then that value will take precedence over error_sleep_time.
respect_retry_after_header: bool, default True: If True, the client will respect the Retry-After header if it is set by the server. If False, the client will perform an exponential backoff starting at error_sleep_time.
request_timeout_secsint, optional: Number of seconds to wait for the server to send data before giving up and raising an exception.
max_errorsint, default 10: Maximum number of consequtive errors to receive before raising an error.
accept_status_codestyping.Iterable[int], optional, multiple = True: List of status codes to accept. If the response status code is not in this collection, then the request will be considered an error
max_retriesint, default 10: Maximum number of times to retry the request fails, receives a redirect or returns a status in the retry_status_codes list. Setting this to 0 disables this feature, and setting this to a negative number will raise a ValueError.
linesbool, default False: If False, the response payloads are expected to be a JSON array of objects. If True, the payloads are expected to contain a JSON objects separated by end-of-line characters.
stop_afterint, default 0: Stops ingesting after emitting stop_after records (rows in the dataframe). Useful for testing. Disabled if 0
payload_to_df_fncallable, default None: A callable that takes the HTTP payload bytes as the first argument and the lines parameter is passed in as the second argument and returns a DataFrame. If unset cudf.read_json is used in GPU mode and pandas.read_json in CPU mode.
message_typeSupportedMessageTypes, case_sensitive = False: The type of message to emit.
task_typestr, default = None: If specified, adds the specified task to the ControlMessage. This parameter is only valid when message_type is set to CONTROL_MESSAGE. If not None, task_payload must also be specified.
task_payloaddict, default = None: If specified, adds the specified task to the ControlMessage. This parameter is only valid when message_type is set to CONTROL_MESSAGE. If not None, task_type must also be specified.
**request_kwargsdict: Additional arguments to pass to the requests.request function.

Attributes

df_type_str: Returns the DataFrame module that should be used for the given execution mode.
has_multi_input_ports: Indicates if this stage has multiple input ports.
has_multi_output_ports: Indicates if this stage has multiple output ports.
input_count: Return None for no max intput count.
input_ports: Input ports to this stage.
is_built: Indicates if this stage has been built.
is_pre_built: Indicates if this stage has been built.
name: Unique name of the stage
output_ports: Output ports from this stage.
unique_name: Unique name of stage.

Methods

`build`(builder[, do_propagate])	Build this stage.
`can_build`([check_ports])	Determines if all inputs have been built allowing this node to be built.
`can_pre_build`([check_ports])	Determines if all inputs have been built allowing this node to be built.
`compute_schema`(schema)	Compute the schema for this stage based on the incoming schema from upstream stages.
`get_all_input_stages`()	Get all input stages to this stage.
`get_all_inputs`()	Get all input senders to this stage.
`get_all_output_stages`()	Get all output stages from this stage.
`get_all_outputs`()	Get all output receivers from this stage.
`get_df_class`()	Returns the DataFrame class that should be used for the given execution mode.
`get_df_pkg`()	Returns the DataFrame package that should be used for the given execution mode.
`get_needed_columns`()	Stages which need to have columns inserted into the dataframe, should populate the `self._needed_columns` dictionary with mapping of column names to `morpheus.common.TypeId`.
`is_stop_requested`()	Returns `True` if a stop has been requested.
`join`()	Awaitable method that stages can implement this to perform cleanup steps when pipeline is stopped.
`request_stop`()	Request the source to stop processing data.
`set_needed_columns`(needed_columns)	Sets the columns needed to perform preallocation.
`start_async`()	This function is called along with on_start during stage initialization.
`stop`()	This method is invoked by the pipeline whenever there is an unexpected shutdown.
`supported_execution_modes`()	Returns a tuple of supported execution modes of this stage.
`supports_cpp_node`()	Indicates whether or not this stage supports a C++ implementation

_build(builder, input_nodes)[source]

This function is responsible for constructing this stage’s internal mrc.SegmentObject object. The input of this function contains the returned value from the upstream stage.

The input values are the mrc.Builder for this stage and a list of parent nodes.

Parameters

buildermrc.Builder: mrc.Builder object for the pipeline. This should be used to construct/attach the internal mrc.SegmentObject.
input_nodeslist[mrc.SegmentObject]: List containing the input mrc.SegmentObject objects.

Returns

list[mrc.SegmentObject]: List of tuples containing the output mrc.SegmentObject object from this stage.

_build_source(builder)[source]

Abstract method all derived Source classes should implement. Returns the same value as build.

Returns

mrc.SegmentObject:: The MRC node for this stage.

_build_sources(builder)[source]

Abstract method all derived Source classes should implement. Returns the same value as build.

Returns

mrc.SegmentObject:: The MRC nodes for this stage.

build(builder, do_propagate=True)[source]

Build this stage.

Parameters

buildermrc.Builder: MRC segment for this stage.
do_propagatebool, optional: Whether to propagate to build output stages, by default True.

can_build(check_ports=False)[source]

Determines if all inputs have been built allowing this node to be built.

Parameters

check_portsbool, optional: Check if we can build based on the input ports, by default False.

Returns

bool: True if we can build, False otherwise.

can_pre_build(check_ports=False)[source]

Determines if all inputs have been built allowing this node to be built.

Parameters

check_portsbool, optional: Check if we can build based on the input ports, by default False.

Returns

bool: True if we can build, False otherwise.

compute_schema(schema)[source]

Compute the schema for this stage based on the incoming schema from upstream stages.

Incoming schema and type information from upstream stages is available via the schema.input_schemas and schema.input_types properties.

Derived classes need to override this method, can set the output type(s) on schema by calling set_type for all output ports. For example a simple pass-thru stage might perform the following:

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            >>> for (port_idx, port_schema) in enumerate(schema.input_schemas):
...     schema.output_schemas[port_idx].set_type(port_schema.get_type())
>>>

If the port types in upstream_schema are incompatible the stage should raise a RuntimeError.

property df_type_str: Literal['cudf', 'pandas']: Returns the DataFrame module that should be used for the given execution mode.

get_all_input_stages()[source]

Get all input stages to this stage.

Returns

list[morpheus.pipeline.pipeline.StageBase]: All input stages.

get_all_inputs()[source]

Get all input senders to this stage.

Returns

list[morpheus.pipeline.pipeline.Sender]: All input senders.

get_all_output_stages()[source]

Get all output stages from this stage.

Returns

list[morpheus.pipeline.pipeline.StageBase]: All output stages.

get_all_outputs()[source]

Get all output receivers from this stage.

Returns

list[morpheus.pipeline.pipeline.Receiver]: All output receivers.

get_df_class()[source]

Returns the DataFrame class that should be used for the given execution mode.

get_df_pkg()[source]

Returns the DataFrame package that should be used for the given execution mode.

get_needed_columns()[source]: Stages which need to have columns inserted into the dataframe, should populate the self._needed_columns dictionary with mapping of column names to morpheus.common.TypeId. This will ensure that the columns are allocated and populated with null values.

property has_multi_input_ports: bool

Indicates if this stage has multiple input ports.

Returns

bool: True if stage has multiple input ports, False otherwise.

property has_multi_output_ports: bool

Indicates if this stage has multiple output ports.

Returns

bool: True if stage has multiple output ports, False otherwise.

property input_count: int: Return None for no max intput count.

property input_ports: list[morpheus.pipeline.receiver.Receiver]

Input ports to this stage.

Returns

list[morpheus.pipeline.pipeline.Receiver]: Input ports to this stage.

property is_built: bool

Indicates if this stage has been built.

Returns

bool: True if stage is built, False otherwise.

property is_pre_built: bool

Indicates if this stage has been built.

Returns

bool: True if stage is built, False otherwise.

is_stop_requested()[source]

Returns True if a stop has been requested.

Returns

bool:: True if a stop has been requested, False otherwise.

async join()[source]: Awaitable method that stages can implement this to perform cleanup steps when pipeline is stopped. Typically this is called after stop during a graceful shutdown, but may not be called if the pipeline is terminated on its own.

property name: str: Unique name of the stage

property output_ports: list[morpheus.pipeline.sender.Sender]

Output ports from this stage.

Returns

list[morpheus.pipeline.pipeline.Sender]: Output ports from this stage.

request_stop()[source]: Request the source to stop processing data.

set_needed_columns(needed_columns)[source]

Sets the columns needed to perform preallocation. This should only be called by the Pipeline at build time. The needed_columns shoudl contain the entire set of columns needed by any other stage in this segment.

async start_async()[source]: This function is called along with on_start during stage initialization. Allows stages to utilize the asyncio loop if needed.

stop()[source]: This method is invoked by the pipeline whenever there is an unexpected shutdown. Subclasses should override this method to perform any necessary cleanup operations.

supported_execution_modes()[source]

Returns a tuple of supported execution modes of this stage.

supports_cpp_node()[source]

Indicates whether or not this stage supports a C++ implementation

property unique_name: str

Unique name of stage. Generated by appending stage id to stage name.

Returns

str: Unique name of stage.

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