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Get a list of your datasets. By default, only the 20 most recent datasets will be returned.
A dataset is a structured version of a source where each field has been processed and serialized according to its type. A field can be numeric, categorical, or text.
Copy this URL into Tableau's Web Data Connector input:
in the top navigation pane to connect to data.
https://t.blockspring.com/bs/datasets-bigmlFinish the setup steps to use Datasets in Tableau.
Finish the setup steps to use Datasets in Slack.
Run this function with a POST request to Blockspring.
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Use this URL for webhooks. You'll want to make a POST request.
curl -H "Content-Type: application/json" -d "{ \"limit\": 0, \"offset\": 0, \"developer_mode\": false, \"bigml_username\": , \"bigml_api_key\": }" "https://run.blockspring.com/api_v2/blocks/datasets-bigml?"
var blockspring = require("blockspring");
blockspring.runParsed("datasets-bigml", { "limit": 0, "offset": 0, "developer_mode": false, bigml_username: , bigml_api_key: }, function(res) {
console.log(res.params);
});
var request = require("request");
request.post({
url: "https://run.blockspring.com/api_v2/blocks/datasets-bigml?",
form: { "limit": 0, "offset": 0, "developer_mode": false, bigml_username: , bigml_api_key: }
},
function(err, response, body) {
console.log(JSON.parse(body));
});
<?php
$url = 'https://run.blockspring.com/api_v2/blocks/datasets-bigml?';
$data = json_encode(array('limit' => 0, 'offset' => 0, "developer_mode" => false, "bigml_username" => , "bigml_api_key" => ));
// use key 'http' even if you send the request to https://...
$options = array(
'http' => array(
'header' => array("Accept: application/json", "Content-Type: application/json"),
'method' => 'POST',
'content' => $data,
),
);
$context = stream_context_create($options);
$result = file_get_contents($url, false, $context);
var_dump(json_decode($result));
?>
<?php
require('blockspring.php');
var_dump(Blockspring::runParsed("datasets-bigml", array('limit' => 0, 'offset' => 0, "developer_mode" => false, "bigml_username" => , "bigml_api_key" => ))->params);
import json
import urllib2
req = urllib2.Request("https://run.blockspring.com/api_v2/blocks/datasets-bigml?")
req.add_header('Content-Type', 'application/json')
data = { "limit": 0, "offset": 0, "developer_mode": False, "bigml_username": , "bigml_api_key": }
results = urllib2.urlopen(req, json.dumps(data)).read()
print json.loads(results)
import blockspring
import json
print blockspring.runParsed("datasets-bigml", { "limit": 0, "offset": 0, "developer_mode": False, "bigml_username": , "bigml_api_key": }).params
require 'rest_client'
response = RestClient.post 'https://run.blockspring.com/api_v2/blocks/datasets-bigml?', JSON.dump({ "limit" => 0, "offset" => 0, "developer_mode" => false, "bigml_username" => , "bigml_api_key" => }), :content_type => :json
puts JSON.load(response)
require 'blockspring'
puts Blockspring.runParsed("datasets-bigml", { "limit" => 0, "offset" => 0, "developer_mode" => false, "bigml_username" => , "bigml_api_key" => } ).params
require 'rest_client'
response = RestClient.post 'https://run.blockspring.com/api_v2/blocks/datasets-bigml?', JSON.dump({ "limit" = 0, "offset" = 0, "developer_mode" = FALSE, "bigml_username" = , "bigml_api_key" = }), :content_type => :json
puts JSON.load(response)
library('blockspring')
library('rjson')
print(blockspringRunParsed("datasets-bigml", list( "limit" = 0, "offset" = 0, "developer_mode" = FALSE, "bigml_username" = , "bigml_api_key" = ))$params)
<script src="https://code.jquery.com/jquery-1.10.1.min.js"></script>
<script src="https://cdn.blockspring.com/blockspring.js"></script>
<script>
blockspring.runParsed("datasets-bigml", { "limit": 0, "offset": 0, "developer_mode": false, bigml_username: , bigml_api_key: }, { "api_key": "" }, function(res){
console.log(res.params);
})
</script>
https://run.blockspring.com/api_v2/blocks/datasets-bigml?
Finish the setup steps to use Datasets in Code.