def get_IRM_report_data_set(input_file, sheet_name):
print("Reading from file {}...".format(input_file))
data_book = Databook().load('xlsx', open(input_file, 'rb').read())
sheets = data_book.sheets()
try:
return next(data_set for data_set in sheets
if data_set.title.strip() == sheet_name)
except StopIteration:
sys.exit('Sheet not found in xlsx file.')
def gen_xls_data(book_name, sheet_name):
book_name += '.xls'
book_path = HOMEPATH/'xls_case'/book_name
book = Databook().load('xls', open(str(book_path), 'rb').read())
for sheet in book.sheets():
if sheet.title == sheet_name:
ret = json.loads(sheet.json)
return map(parse, ret)
return []
def gen_data(book_name, sheet_name):
book_name += '.xls'
sheet_name = sheet_name.partition('_')[-1]
book_path = HOMEPATH / 'datas' / book_name
dbook = Databook().load('xls', open(str(book_path), 'rb').read())
for sheet in dbook.sheets():
if sheet.title == sheet_name:
ret = json.loads(sheet.json)
return map(parse, ret)
return []
def import_snapshot(file, irm_snapshot_id):
data_book = Databook().load(file, "xlsx")
dataset = data_book.sheets()[0]
preprocessed_dataset = preprocess(dataset)
# Ensure projects exist
for IRM_project_id in preprocessed_dataset["Project ID"]:
if IRM_project_id:
models.ProvInfraProject.objects.get_or_create(
IRM_project_id=IRM_project_id)
if len(preprocessed_dataset) > 0:
preprocessed_dataset.append_col([irm_snapshot_id] *
len(preprocessed_dataset),
header="irm_snapshot")
resource = ProvInfraProjectSnapshotResource()
result = resource.import_data(preprocessed_dataset)
return result
def import_snapshot(snapshot):
file = snapshot.file.read()
data_book = Databook().load(file, "xlsx")
dataset = data_book.sheets()[0]
preprocessed_dataset = preprocess(dataset)
# Ensure projects exist
for IRM_project_id in preprocessed_dataset["Project ID"]:
if IRM_project_id:
models.InfraProject.objects.get_or_create(
IRM_project_id=IRM_project_id,
sphere_slug=snapshot.sphere.slug)
if len(preprocessed_dataset) > 0:
preprocessed_dataset.append_col([snapshot.id] *
len(preprocessed_dataset),
header="irm_snapshot")
preprocessed_dataset.append_col([snapshot.sphere.slug] *
len(preprocessed_dataset),
header="sphere_slug")
resource = InfraProjectSnapshotResource()
result = resource.import_data(preprocessed_dataset)
return result