Delighted API Python Client (Beta)

Official Python client for the Delighted API.

Installation

pip install --upgrade delighted-python

easy_install --upgrade delighted-python

Configuration

To get started, you need to configure the client with your secret API key.

import delighted
delighted.api_key = 'YOUR_API_KEY'

For further options, read the advanced configuration section.

Note: Your API key is secret, and you should treat it like a password. You can find your API key in your Delighted account, under Settings > API.

Usage

Adding/updating people and scheduling surveys:

# Add a new person, and schedule a survey immediately
person1 = delighted.Person.create(email='foo+test1@delighted.com')

# Add a new person, and schedule a survey after 1 minute (60 seconds)
person2 = delighted.Person.create(email='foo+test2@delighted.com', delay=60)

# Add a new person, but do not schedule a survey
person3 = delighted.Person.create(email='foo+test3@delighted.com', send=False)

# Add a new person with full set of attributes, including a custom question
# product name, and schedule a survey with a 30 second delay
person4 = delighted.Person.create(
        email='foo+test4@delighted.com',
        name='Joe Bloggs',
        properties={'customer_id': 123, 'country': 'USA',
                    'question_product_name': 'The London Trench'},
        delay=30)

# Update an existing person (identified by email), adding a name, without
# scheduling a survey
updated_person1 = delighted.Person.create(email='foo+test1@delighted.com',
                                          name='James Scott', send=False)

Unsubscribing people:

# Unsubscribe an existing person
delighted.Unsubscribe.create(person_email='foo+test1@delighted.com')

Deleting pending survey requests

# Delete all pending (scheduled but unsent) survey requests for a person, by email.
delighted.SurveyRequest.delete_pending(person_email='foo+test1@delighted.com')

Adding survey responses:

# Add a survey response, score only
survey_response1 = delighted.SurveyResponse.create(person=person1.id,
                                                   score=10)

# Add *another* survey response (for the same person), score and comment
survey_response2 = delighted.SurveyResponse.create(person=person1.id,
                                                   score=5,
                                                   comment='Really nice.')

Retrieving a survey response:

# Retrieve an existing survey response
survey_response3 = delighted.SurveyResponse.retrieve('123')

Updating survey responses:

# Update a survey response score
survey_response4 = delighted.SurveyResponse.retrieve('234')
survey_response4.score = 10
survey_response4.save
# <delighted.SurveyResponse object at 0xabc123>

# Update (or add) survey response properties
survey_response4.person_properties = {'segment': 'Online'}
survey_response4.save
# <delighted.SurveyResponse object at 0xabc123>

# Update person who recorded the survey response
survey_response4.person = '321'
survey_response4.save
# <delighted.SurveyResponse object at 0xabc123>

Listing survey responses:

# List all survey responses, 20 per page, first 2 pages
survey_responses_page1 = delighted.SurveyResponse.all
survey_responses_page2 = delighted.SurveyResponse.all(page=2)

# List all survey responses, 20 per page, expanding person object
survey_responses_page1_expanded = delighted.SurveyResponse.all(expand=['person'])
survey_responses_page1_expanded[0].person
# <delighted.Person object at 0xabc123>

# List all survey responses, 20 per page, for a specific trend (ID: 123)
survey_responses_page1_trend = delighted.SurveyResponse.all(trend='123')

# List all survey responses, 20 per page, in reverse chronological order (newest first)
survey_responses_page1_desc = delighted.SurveyResponse.all(order='desc')

# List all survey responses, 100 per page, page 5, with a time range
filtered_survey_responses = delighted.SurveyResponse.all(page=5,
    per_page=100,
    since=datetime.datetime(2014, 03, 01),
    until=datetime.datetime(2014, 04, 30))

Retrieving metrics:

# Get current metrics, 30-day simple moving average, from most recent response
metrics = delighted.Metrics.retrieve

# Get current metrics, 30-day simple moving average, from most recent response,
# for a specific trend (ID: 123)
metrics = delighted.Metrics.retrieve(trend='123')

# Get metrics, for given range
metrics = delighted.Metrics.retrieve(since=datetime.date(2013, 10, 01),
                                     until=datetime.date(2013, 11, 01))

Advanced configuration & testing

The following options are configurable for the client:

delighted.api_key
delighted.api_base_url # default: 'https://api.delighted.com/v1'
delighted.http_adapter # default: delighted.HTTPAdapter

By default, a shared instance of delighted.Client is created lazily in delighted.get_shared_client(). If you want to create your own client, perhaps for test or if you have multiple API keys, you can:

# Create an custom client instance, and pass as last argument to resource actions
import delighted
from delighted import Client
client = Client(api_key=‘API_KEY',
                api_base_url=‘https://api.delighted.com/v1',
                http_adapter=HTTPAdapter())
metrics_from_custom_client = delighted.Metrics.retrieve(client=client)

# Or, you can set Delighted.shared_client yourself
delighted.shared_client = delighted.Client(
    api_key='API_KEY',
    api_base_url='https://api.delighted.com/v1',
    http_adapter=delighted.HTTPAdapter()
)
metrics_from_custom_shared_client = delighted.Metrics.retrieve()

Supported versions

2.6, 2.7, 3.2, 3.3, 3.4
pypy, pypy3

Contributing

Fork it
Create your feature branch (git checkout -b my-new-feature)
Commit your changes (git commit -am 'Add some feature')
Push to the branch (git push origin my-new-feature)
Create new Pull Request