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The API clients should just deal with calling the API and returning the data from it. Inferring things from the data is more logically done at the model layer. But we couldn’t do that before, because we didn’t have a model layer for jobs.
153 lines
3.9 KiB
Python
153 lines
3.9 KiB
Python
import pytest
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from app.models.job import Job
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from app.statistics_utils import (
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add_rates_to,
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statistics_by_state,
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sum_of_statistics,
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)
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@pytest.mark.parametrize('delivery_statistics', [
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None,
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[{}],
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[{'emails_requested': 0}, {'emails_requested': 0}]
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])
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def test_sum_of_statistics_puts_in_defaults_of_zero(delivery_statistics):
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resp = sum_of_statistics(delivery_statistics)
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assert resp == {
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'emails_delivered': 0,
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'emails_requested': 0,
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'emails_failed': 0,
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'sms_requested': 0,
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'sms_delivered': 0,
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'sms_failed': 0
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}
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def test_sum_of_statistics_sums_inputs():
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delivery_statistics = [
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{
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'emails_delivered': 1,
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'emails_requested': 2,
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'emails_failed': 3,
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'sms_requested': 4,
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'sms_delivered': 5,
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'sms_failed': 6
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},
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{
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'emails_delivered': 10,
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'emails_requested': 20,
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'emails_failed': 30,
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'sms_requested': 40,
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'sms_delivered': 50,
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'sms_failed': 60
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}
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]
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resp = sum_of_statistics(delivery_statistics)
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assert resp == {
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'emails_delivered': 11,
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'emails_requested': 22,
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'emails_failed': 33,
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'sms_requested': 44,
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'sms_delivered': 55,
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'sms_failed': 66
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}
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@pytest.mark.parametrize('emails_failed,emails_requested,expected_failure_rate', [
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(0, 0, '0'),
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(0, 1, '0.0'),
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(1, 3, '33.3')
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])
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def test_add_rates_sets_email_failure_rate(emails_failed, emails_requested, expected_failure_rate):
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resp = add_rates_to({
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'emails_failed': emails_failed,
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'emails_requested': emails_requested,
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'sms_failed': 0,
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'sms_requested': 0
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})
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assert resp['emails_failure_rate'] == expected_failure_rate
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@pytest.mark.parametrize('sms_failed,sms_requested,expected_failure_rate', [
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(0, 0, '0'),
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(0, 1, '0.0'),
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(1, 3, '33.3')
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])
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def test_add_rates_sets_sms_failure_rate(sms_failed, sms_requested, expected_failure_rate):
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resp = add_rates_to({
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'emails_failed': 0,
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'emails_requested': 0,
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'sms_failed': sms_failed,
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'sms_requested': sms_requested
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})
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assert resp['sms_failure_rate'] == expected_failure_rate
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def test_add_rates_keeps_original_raw_data():
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resp = add_rates_to({
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'emails_failed': 1,
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'emails_requested': 2,
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'sms_failed': 3,
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'sms_requested': 4
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})
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assert resp['emails_failed'] == 1
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assert resp['emails_requested'] == 2
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assert resp['sms_failed'] == 3
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assert resp['sms_requested'] == 4
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def test_service_statistics_by_state():
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resp = statistics_by_state({
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'emails_requested': 3,
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'emails_failed': 1,
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'emails_delivered': 1,
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'sms_requested': 3,
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'sms_failed': 1,
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'sms_delivered': 1
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})
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for message_type in ['email', 'sms']:
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assert resp[message_type]['processed'] == 3
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assert resp[message_type]['sending'] == 1
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assert resp[message_type]['delivered'] == 1
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assert resp[message_type]['failed'] == 1
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@pytest.mark.parametrize('failed, delivered, expected_failure_rate', [
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(0, 0, 0),
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(0, 1, 0),
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(1, 1, 50),
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(1, 0, 100),
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(1, 4, 20)
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])
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def test_add_rate_to_job_calculates_rate(failed, delivered, expected_failure_rate):
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resp = Job({
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'statistics': [
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{'status': 'failed', 'count': failed},
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{'status': 'delivered', 'count': delivered},
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],
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'id': 'foo',
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})
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assert resp.failure_rate == expected_failure_rate
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def test_add_rate_to_job_preserves_initial_fields():
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resp = Job({
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'statistics': [
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{'status': 'failed', 'count': 0},
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{'status': 'delivered', 'count': 0},
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],
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'id': 'foo',
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})
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assert resp.notifications_failed == resp.notifications_delivered == resp.failure_rate == 0
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assert resp.id == 'foo'
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