def setUpClass(cls):
factory = DataFactory()
cls.months = factory.create_months("2019-01-01", 3)
# This practice won't do any prescribing but it will have practice
# statistics so it should still show up in our data
cls.non_prescribing_practice = factory.create_practice()
# Create some practices that prescribe during the period
cls.prescribing_practices = factory.create_practices(3)
# Create some presentations and some prescribing
cls.presentations = factory.create_presentations(4)
cls.prescribing = factory.create_prescribing(
cls.presentations, cls.prescribing_practices, cls.months
)
# Create practices statistics for all active practices
cls.active_practices = cls.prescribing_practices + [
cls.non_prescribing_practice
]
cls.practice_statistics = factory.create_practice_statistics(
cls.active_practices, cls.months
)
# Create a presentation which changes its BNF code and create some
# prescribing with both old and new codes
cls.presentation_to_update = factory.create_presentation()
cls.updated_presentation = factory.update_bnf_code(cls.presentation_to_update)
cls.prescribing_with_old_code = factory.create_prescribing(
[cls.presentation_to_update], cls.active_practices, cls.months
)
cls.prescribing_with_new_code = factory.create_prescribing(
[cls.updated_presentation], cls.active_practices, cls.months
)
# Create a presenation without creating any prescribing for it so we can
# check it doesn't appear in the final file
cls.presentation_without_prescribing = factory.create_presentation()
# We deliberately import data for fewer months than we've created so we
# can test that only the right data is included
cls.months_to_import = cls.months[1:]
# This practice only has data for the month we don't import, so it
# shouldn't show up at all in our data
cls.closed_practice = factory.create_practice()
factory.create_prescription(
cls.presentations[0], cls.closed_practice, cls.months[0]
)
factory.create_statistics_for_one_practice_and_month(
cls.closed_practice, cls.months[0]
)
cls.data_factory = factory
# The format of `end_date` only uses year and month
cls.end_date = max(cls.months_to_import)[:7]
cls.number_of_months = len(cls.months_to_import)
cls.create_matrixstore(factory, cls.end_date, cls.number_of_months)
def setUpTestData(cls):
# Create some sets of substitutable presentations, which each consist
# of a generic plus some branded equivalents
substitution_sets = []
for i in range(4):
generic_code = invent_generic_bnf_code(i)
brands = invent_brands_from_generic_bnf_code(generic_code)
substitution_sets.append([generic_code] + brands)
# Create some practices and some prescribing for these presentations
factory = DataFactory()
factory.create_months("2020-01-01", 2)
factory.create_practices(10)
for bnf_codes in substitution_sets:
for bnf_code in bnf_codes:
factory.create_presentation(bnf_code=bnf_code)
factory.create_prescribing(factory.presentations, factory.practices,
factory.months)
# The DataFactory creates data that can be written to the MatrixStore
# but doesn't automatically create anything in the database, so we do
# that manually here
ccg = PCT.objects.create(name="CCG1", code="ABC", org_type="CCG")
for practice in factory.practices:
Practice.objects.create(name=practice["name"],
code=practice["code"],
setting=4,
ccg=ccg)
for presentation in factory.presentations:
Presentation.objects.create(bnf_code=presentation["bnf_code"],
name=presentation["name"])
cls.substitution_sets = substitution_sets
cls.factory = factory
cls._remove_patch = patch_global_matrixstore(
matrixstore_from_data_factory(factory))
# Clear the cache on this memoized function
get_substitution_sets.cache_clear()