def make_uuid(*args: str) -> str:
"""
Generic wrapper of uuid.uuid3 method for uuid generation
:param args: variable list of strings
:return: string uuid
"""
path = as_path(*args)
return str(uuid.uuid3(uuid.NAMESPACE_OID, path))
def generate_context_uuid(*args: str):
"""
Generates uuid for a context
:param args: variable list of context elements
:return: string uuid
"""
context = as_path(*args)
contextid = str(uuid.uuid3(uuid.NAMESPACE_OID, context))
return contextid
counter = counter + 1
# Drop duplicates just as a check
contexts = contexts.drop_duplicates()
# Describe a pattern of compartment classes used in each context
# Create a clean list with no NAs
context_patterns = []
context_list_na_removed = list()
for index, row in contexts.iterrows():
pattern = [
compartment_classes[x] for x in range(0, max_compartment_classes)
if str(row[x]) != 'nan'
]
pattern = ','.join(pattern)
context_patterns.append(pattern)
row_list = row.values
row_list_na_removed = [x for x in row.values if str(x) != 'nan']
context_list_na_removed.append(row_list_na_removed)
# Using this clean list, generate context paths
context_paths = list()
for r in context_list_na_removed:
#Pass the uuid function the list as a series of string arguments
compartment_path = as_path(*r)
context_paths.append(compartment_path)
# Write the context paths and patterns to a dictionary, then df
d = {'Context': context_paths, 'Pattern': context_patterns}
all_contexts = pd.DataFrame(data=d)
# Read in flowable context membership
SecondaryContextMembership = import_secondary_context_membership()
secondary_context_classes = flow_list_specs["secondary_context_classes"]
context_patterns_used = pd.DataFrame(columns=[
'Class', 'Directionality', 'Environmental Media',
'Primary_Context_Path', 'Pattern', 'ContextPreferred'
])
for index, row in SecondaryContextMembership.iterrows():
pattern = [x for x in secondary_context_classes if row[x] != 0]
pattern_w_primary = flow_list_specs["primary_context_classes"].copy(
) + pattern
# convert to string
pattern_w_primary = ','.join(pattern_w_primary)
primary_context_path = as_path(row['Directionality'],
row['Environmental Media'])
context_patterns_used = context_patterns_used.append(
{
'Class': row['FlowClass'],
'Directionality': row['Directionality'],
'Environmental Media': row['Environmental Media'],
'Primary_Context_Path': primary_context_path,
'Pattern': pattern_w_primary,
'ContextPreferred': row['ContextPreferred']
},
ignore_index=True)
# Cycle through these class context patterns and get context_paths
log.info('Getting relevant contexts for each class ...')
field_to_keep = [
'Class', 'Directionality', 'Environmental Media', 'ContextPreferred'