def test_mapping_page(self):
"""
Make sure you can click mapping button on dataset page and mapping
loads.
"""
import_record = ImportRecord.objects.create(
owner=self.user,
super_organization=self.org
)
ImportFile.objects.create(
import_record=import_record,
cached_first_row=ROW_DELIMITER.join(
[u'name', u'address']
),
cached_second_to_fifth_row=ROW_DELIMITER.join(
['name', 'address.']
)
)
# Navigate to dataset detail view.
self.browser.get(self.live_server_url + '/app/#/data/%s' % import_record.pk)
# Wait for load.
self.wait_for_element_by_css('td.data_file_name')
# Click mapping button.
self.browser.find_element_by_id('data-mapping-0').click()
# Make sure mapping table is shown.
self.wait_for_element_by_css('div.mapping')
def cache_first_rows(import_file, parser):
"""Cache headers, and rows 2-6 for validation/viewing.
:param import_file: ImportFile inst.
:param parser: unicode-csv.Reader instance.
Unfortunately, this is duplicated logic from data_importer,
but since data_importer makes many faulty assumptions we need to do
it differently.
"""
parser.seek_to_beginning()
rows = parser.next()
validation_rows = []
for i in range(5):
try:
row = rows.next()
if row:
validation_rows.append(row)
except StopIteration:
"""Less than 5 rows in file"""
break
# This is a fix for issue #24 to use original field order when importing
# This is ultimately not the correct place for this fix. The correct fix
# is to update the mcm code to a newer version where the readers in mcm/reader.py
# have a headers() function defined and then just do
# first_row = parser.headers()
# But until we can patch the mcm code this should fix the issue.
local_reader = parser.reader
if isinstance(local_reader, reader.ExcelParser):
first_row = local_reader.sheet.row_values(local_reader.header_row)
elif isinstance(local_reader, reader.CSVParser):
first_row = local_reader.csvreader.fieldnames
first_row = [local_reader._clean_super(x) for x in first_row]
else:
# default to the original behavior if a new type of parser for lack of anything better
first_row = rows.next().keys()
tmp = []
for r in validation_rows:
tmp.append(ROW_DELIMITER.join([str(r[x]) for x in first_row]))
import_file.cached_second_to_fifth_row = "\n".join(tmp)
if first_row:
first_row = ROW_DELIMITER.join(first_row)
import_file.cached_first_row = first_row or ''
import_file.save()
# Reset our file pointer for mapping.
parser.seek_to_beginning()
def cache_first_rows(import_file, parser):
"""Cache headers, and rows 2-6 for validation/viewing.
:param import_file: ImportFile inst.
:param parser: unicode-csv.Reader instance.
Unfortunately, this is duplicated logic from data_importer,
but since data_importer makes many faulty assumptions we need to do
it differently.
"""
parser.seek_to_beginning()
rows = parser.next()
validation_rows = []
for i in range(5):
try:
row = rows.next()
if row:
validation_rows.append(row)
except StopIteration:
"""Less than 5 rows in file"""
break
# return the first row of the headers which are cleaned
first_row = parser.headers()
tmp = []
for r in validation_rows:
tmp.append(ROW_DELIMITER.join([str(r[x]) for x in first_row]))
import_file.cached_second_to_fifth_row = "\n".join(tmp)
if first_row:
first_row = ROW_DELIMITER.join(first_row)
import_file.cached_first_row = first_row or ''
import_file.save()
# Reset our file pointer for mapping.
parser.seek_to_beginning()
def create_models(data, import_file):
"""
Create a BuildingSnapshot, a CanonicalBuilding, and a Meter. Then, create
TimeSeries models for each meter reading in data.
:param data: dictionary of building data from a Green Button XML file
in the form returned by xml_importer.building_data
:param import_file: ImportFile referencing the original xml file; needed
for linking to BuildingSnapshot and for determining super_organization
:returns: the created CanonicalBuilding
"""
# cache data on import_file; this is a proof of concept and we
# only have two example files available so we hardcode the only
# heading present.
import_file.cached_first_row = ROW_DELIMITER.join(["address"])
import_file.cached_second_to_fifth_row = ROW_DELIMITER.join(
[data['address']]
)
import_file.save()
raw_bs = BuildingSnapshot()
raw_bs.import_file = import_file
# We require a save to get our PK
# We save here to set our initial source PKs.
raw_bs.save()
super_org = import_file.import_record.super_organization
raw_bs.super_organization = super_org
set_initial_sources(raw_bs)
raw_bs.address_line_1 = data['address']
raw_bs.source_type = GREEN_BUTTON_BS
raw_bs.save()
# create canonical building
cb = CanonicalBuilding.objects.create(canonical_snapshot=raw_bs)
raw_bs.canonical_building = cb
raw_bs.save()
# log building creation
AuditLog.objects.create(
organization=import_file.import_record.super_organization,
user=import_file.import_record.owner,
content_object=cb,
action="create_building",
action_note="Created building",
)
# create meter for this dataset (each dataset is a single energy type)
e_type = energy_type(data['service_category'])
e_type_string = next(
pair[1] for pair in seed.models.ENERGY_TYPES if pair[0] == e_type
)
m_name = "gb_{0}[{1}]".format(str(raw_bs.id), e_type_string)
m_energy_units = energy_units(data['meter']['uom'])
meter = Meter.objects.create(
name=m_name, energy_type=e_type, energy_units=m_energy_units
)
meter.building_snapshot.add(raw_bs)
meter.save()
# now time series data for the meter
for reading in data['interval']['readings']:
start_time = int(reading['start_time'])
duration = int(reading['duration'])
begin_time = datetime.fromtimestamp(start_time)
end_time = datetime.fromtimestamp(start_time + duration)
value = reading['value']
cost = reading['cost']
new_ts = TimeSeries.objects.create(
begin_time=begin_time,
end_time=end_time,
reading=value,
cost=cost
)
new_ts.meter = meter
new_ts.save()
return cb
def create_models(data, import_file):
"""
Create a BuildingSnapshot, a CanonicalBuilding, and a Meter. Then, create
TimeSeries models for each meter reading in data.
:params data: dictionary of building data from a green button xml file
in the form returned by xml_importer.building_data
:params import_file: ImportFile referencing the original xml file; needed
for linking to BuildingSnapshot and for determining super_organization
:returns: the created CanonicalBuilding
"""
# cache data on import_file; this is a proof of concept and we
# only have two example files available so we hardcode the only
# heading present.
import_file.cached_first_row = ROW_DELIMITER.join(["address"])
import_file.cached_second_to_fifth_row = ROW_DELIMITER.join(
[data['address']]
)
import_file.save()
raw_bs = BuildingSnapshot()
raw_bs.import_file = import_file
# We require a save to get our PK
# We save here to set our initial source PKs.
raw_bs.save()
super_org = import_file.import_record.super_organization
raw_bs.super_organization = super_org
set_initial_sources(raw_bs)
raw_bs.address_line_1 = data['address']
raw_bs.source_type = GREEN_BUTTON_BS
raw_bs.save()
# create canonical building
cb = CanonicalBuilding.objects.create(canonical_snapshot=raw_bs)
raw_bs.canonical_building = cb
raw_bs.save()
# log building creation
AuditLog.objects.create(
organization=import_file.import_record.super_organization,
user=import_file.import_record.owner,
content_object=cb,
action="create_building",
action_note="Created building",
)
# create meter for this dataset (each dataset is a single energy type)
e_type = energy_type(data['service_category'])
e_type_string = next(
pair[1] for pair in seed.models.ENERGY_TYPES if pair[0] == e_type
)
m_name = "gb_{0}[{1}]".format(str(raw_bs.id), e_type_string)
m_energy_units = energy_units(data['meter']['uom'])
meter = Meter.objects.create(
name=m_name, energy_type=e_type, energy_units=m_energy_units
)
meter.building_snapshot.add(raw_bs)
meter.save()
# now timeseries data for the meter
for reading in data['interval']['readings']:
start_time = int(reading['start_time'])
duration = int(reading['duration'])
begin_time = datetime.fromtimestamp(start_time)
end_time = datetime.fromtimestamp(start_time + duration)
value = reading['value']
cost = reading['cost']
new_ts = TimeSeries.objects.create(
begin_time=begin_time,
end_time=end_time,
reading=value,
cost=cost
)
new_ts.meter = meter
new_ts.save()
return cb
