bigml-nodered
Version:
BigML bindings for Nodered
144 lines (127 loc) • 4.71 kB
HTML
<style>
.bigml_node_label { fill: white; }
#palette-BigML .palette_node { color: white; }
#red-ui-palette-BigML .red-ui-palette-label { color: white; }
</style>
<script type="text/javascript">
RED.nodes.registerType('stream', {
category: 'BigML',
color: '#454957',
defaults: {"name":{"value":"Stream","required":true},"endpoint":{},"label":{},"event_batch_size":{"value":200},"project":{},"event":{}},
inputs:1,
outputs:1,
inputLabels: 'event',
outputLabels: 'result',
icon: 'icon_generic.png',
label: function() {
return this.name || 'WhizzML Stream';
},
labelStyle: function() {
return this.name?"bigml_node_label":"";
},
});
</script>
<script type="text/x-red" data-template-name="stream">
<div class="form-row">
<label for="node-input-name">
<i class="icon-tag"></i> Name
</label>
<input type=text id=node-input-name value='Stream'>
</div>
<div class="form-row">
<label for="node-input-endpoint">
<i class="icon-tag"></i> Endpoint
</label>
<input type=text id=node-input-endpoint placeholder='bigml-streaming' >
</div>
<div class="form-row">
<label for="node-input-label">
<i class="icon-tag"></i> Label
</label>
<input type=text id=node-input-label >
</div>
<div class="form-row">
<label for="node-input-event_batch_size">
<i class="icon-tag"></i> Event batch size
</label>
<input type=number id=node-input-event_batch_size value='200'>
</div>
<div class="form-row">
<label for="node-input-project">
<i class="icon-tag"></i> Project
</label>
<input type=text id=node-input-project >
</div>
<div class="form-row">
<label for="node-input-event">
<i class="icon-tag"></i> Event
</label>
<input type=text id=node-input-event placeholder='{}' >
</div>
</script>
<script type="text/html" data-help-name="stream">
<p>This is a BigML Nodered node.</p>
<h3>Details</h3>
<p>This node support all inputs defined in
<a href='https://bigml.com/api/streams' target=blank>BigML REST
API</a>. By default, it expects to receive
a <code>event</code> input (see below for more details) and
it will output the <code>result</code> field of the created
resource.
</p>
<p>However, you can override default inputs and outputs by defining
the node port label so they match the desired input or output as
specified below.</p>
<p>Only when the node is used with the <code>reify</code> option
enabled, it will actually hit BigML and do its work there. This
generally means some resources will be created and sent through as
node outputs.</p>
<p>When the node is used with the <code>reify</code>option disabled,
it will generate WhizzML code and send it through to the next node
in the flow without hitting BigML. All WhizzML code created by this
node (and others) when not in <code>reify</code> mode is accumulated
and executed as a single WhizzML script by the first
downstream <code>reified</code> node.</p>
<h3>Inputs</h3>
<dl class="message-properties">
<dt>Name
<span class="property-type">:text</span>
</dt>
<dd></dd>
<dt>Endpoint
<span class="property-type">:text</span>
</dt>
<dd>The name of the endpoint to stream events to.</dd>
<dt>Label
<span class="property-type">:text</span>
</dt>
<dd>A label to use as tag prefix</dd>
<dt>Event batch size
<span class="property-type">:number</span>
</dt>
<dd>How many events to collect before creating a source</dd>
<dt>Project
<span class="property-type">:text</span>
</dt>
<dd>The project to assign to the source</dd>
<dt>Event
<span class="property-type">:json</span>
</dt>
<dd>The events to stream.</dd>
</dl>
<h3>Outputs</h3>
<ol class="node-ports">
<dl class="message-properties">
<dt>payload <span class="property-type">string or
JSON</span></dt>
<dd>the <code>result</code> of the created
BigML entity.</dd>
<dt>whizzml <span class="property-type">string</dt>
<dd>(only for <code>reified</code> nodes) the
generated WhizzML code which is fed into the next
node.
<dt>wzStack <span class="property-type">object</dt>
<dd>(only for <code>reified</code> nodes) private.
</dl>
</ol>
</script>