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Delighted API Python Client.

Project description

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Delighted API Python Client

Official Python client for the Delighted API.

Installation

pip install --upgrade delighted

or

easy_install --upgrade delighted

Upgrading from delighted-python

If you previously used the python package named delighted-python, please note that the package name is now just delighted.

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')

Listing people:

# List all people, auto pagination
# Note: Make sure to handle the possible rate limits error
people = delighted.Person.list()
while True:
    try:
        for person in people.auto_paging_iter():
            # Do something with person
    except TooManyRequestsError as e:
        # Indicates how long to wait (in seconds) before making this request again
        e.retry_after
        continue

# For convenience, this method can use a sleep to automatically handle rate limits
people = delighted.Person.list(auto_handle_rate_limits=True)
for person in people.auto_paging_iter():
    # Do something with person

Listing people who have unsubscribed:

# List all people who have unsubscribed, 20 per page, first 2 pages
delighted.Unsubscribe.all()
delighted.Unsubscribe.all(page=2)

Listing people whose emails have bounced:

# List all people whose emails have bounced, 20 per page, first 2 pages
delighted.Bounce.all()
delighted.Bounce.all(page=2)

Deleting a person and all of the data associated with them:

# Delete by person id
delighted.Person.delete(id=42)
# Delete by email address
delighted.Person.delete(email='test@example.com')
# Delete by phone number (must be E.164 format)
delighted.Person.delete(phone_number='+14155551212')

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
import pytz
timezone = pytz.timezone('America/Chicago')
filtered_survey_responses = delighted.SurveyResponse.all(
    page=5,
    per_page=100,
    since=timezone.localize(datetime.datetime(2014, 3, 1)),
    until=timezone.localize(datetime.datetime(2014, 4, 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 time range
import pytz
timezone = pytz.timezone('America/Chicago')
metrics = delighted.Metrics.retrieve(
    since=timezone.localize(datetime.datetime(2013, 10, 1)),
    until=timezone.localize(datetime.datetime(2013, 11, 1))
)

Managing Autopilot:

# Get Autopilot configuration for the `email` platform
autopilot = delighted.AutopilotConfiguration.retrieve('email')

# List people in AutopilotMembership for the `email` platform
people_autopilot = delighted.AutopilotMembership.forEmail().list(auto_handle_rate_limits=True)
for person in people_autopilot.auto_paging_iter():
  # Do something with person

# Add people to AutopilotMembership
autopilot = delighted.AutopilotMembership.forEmail().create(person_email='test@example.com')

# Add people to AutopilotMembership, with a full set of attributes
properties = {'customer_id': 123, 'country': 'USA', 'question_product_name': 'The London Trench'}
autopilot = delighted.AutopilotMembership.forSms().create(person_phone_number='+14155551212', properties=properties)

# Delete by person id
delighted.AutopilotMembership.forSms().delete(person_id=42)

# Delete by email address
delighted.AutopilotMembership.forEmail().delete(person_email='test@example.com')

# Delete by phone number (must be E.164 format)
delighted.AutopilotMembership.forSms().delete(person_phone_number='+14155551212')

Rate limits

If a request is rate limited, a TooManyRequestsError exception is raised. You can rescue that exception to implement exponential backoff or retry strategies. The exception provides a retry_after attribute to tell you how many seconds you should wait before retrying. For example:

try:
    metrics = delighted.Metrics.retrieve()
except delighted.errors.TooManyRequestsError as err:
    retry_after_seconds = err.retry_after
    # wait for retry_after_seconds before retrying
    # add your retry strategy here ...

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+, 3.3+ (PyPy supported)

Contributing

  1. Fork it
  2. Create your feature branch (git checkout -b my-new-feature)
  3. Run the tests (tox)
  4. Commit your changes (git commit -am 'Add some feature')
  5. Push to the branch (git push origin my-new-feature)
  6. Create new Pull Request

Releasing

  1. Bump the version in delighted/__init__.py.
  2. Update the README and CHANGELOG as needed.
  3. Tag the commit for release.
  4. Create the distribution python setup.py sdist
  5. Update the package against PyPI's test server with twine twine upload --repository-url https://test.pypi.org/legacy/ dist/TEST_PACKAGE_NAME.
  6. If (4 and 5) work, repeat all steps, then push to PyPI's live servers with twine upload dist/PACKAGE_NAME.

Author

Originally by Jason Pearson. Graciously transfered and now officially maintained by Delighted.

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delighted-4.1.0.tar.gz (17.0 kB view hashes)

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