Get up and running with the Akkio API using one of our convenient libraries.
API Keys
As noted in the code samples below, you must get your API keys and copy them into your API code. Those can be found under the team settings page at the bottom of the Akkio app.
Test Code
Installation
npm install akkio --save
Usage
constakkio=require('akkio')('your API key');#get your API key at https://app.akkio.com/team-settings(async() => {#create a new datasetletnewDataset=awaitakkio.createDataset('my new dataset');#populate it with some toy dataletrows= [];for (vari=0; i<1000; i++) {okayletx=Math.random();rows.push({'x':x,'value larger than 0.5':x>0.5, }); }awaitakkio.addRowsToDataset(newDataset.dataset_id,rows);# train a modelletmodel=awaitakkio.createModel(newDataset.dataset_id, ['value larger than 0.5'], [], {duration:1 });## field importancefor (let field in model.field_importance) {console.log('field:',field,'importance:',model.field_importance[field]); }# model statsfor (letfieldofmodel.stats) {for (letoutcomeoffield) {console.log(outcome); } }# use the trained model to make predictionsletpredictions=awaitakkio.makePrediction(model.model_id, [{'x':0.25 }, {'x':0.75 }], {explain:true });console.log(predictions);})();
Installation
The akkio library is available on Python 3 and can be installed easily on your python instance. Run the following command or search your available packages for akkio (image also below.
pip install akkio
Usage
import akkioakkio.api_key ='YOUR-API-KEY-HERE'# get your API key at https://app.akkio.com/team-settingsmodels = akkio.get_models()['models']for model in models:print(model)datasets = akkio.get_datasets()['datasets']for dataset in datasets:print(dataset)new_dataset = akkio.create_dataset('python api test')print(new_dataset)# create a toy datasetimport randomrows = []for i inrange(1000): rows.append({'x': random.random() }) rows[-1]['y'] = rows[-1]['x'] >0.5akkio.add_rows_to_dataset(new_dataset['dataset_id'], rows)new_model = akkio.create_model(new_dataset['dataset_id'], ['y'], [], {'duration': 1})print(new_model)prediction = akkio.make_prediction(new_model['model_id'], [{'x': 0.1}, {'x':0.7}], explain=True)print(prediction)
Once you have installed the Akkio custom package and run the above Usage code you should be able to go to app.akkio.com and see an api test project as shown here.