Showing 81 of 109 total issues
Function test_generate_crt_curve_fits
has 6 arguments (exceeds 4 allowed). Consider refactoring. Open
Open
def test_generate_crt_curve_fits(mock_figure, mock_plot, mock_legend, mock_ylabel, mock_xlabel, mock_savefig):
Avoid deeply nested control flow statements. Open
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if time_lbound <= json_obj['Time'] < time_ubound:
# print("\nFrom", json_obj['From'], "\nTo", json_obj['To'], "\nCc", json_obj['Cc'])
from_addr = email_re.search(json_obj['From'])
json_obj['From'] = from_addr.group(0) if from_addr is not None else json_obj['From']
json_obj['To'] = set(email_re.findall(json_obj['To']))
Avoid deeply nested control flow statements. Open
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if console_output:
print("\n-----\n")
else:
out_file.write("\n-----\n")
# with open("author_top_index.json", 'w') as json_file:
Function remove_unwanted_headers
has a Cognitive Complexity of 8 (exceeds 5 allowed). Consider refactoring. Open
Open
def remove_unwanted_headers(self, to_remove=unwanted_uid, json_headers="headers.json", output_file="headers.json"):
"""
This function removes all the UIDs specified in the to_remove parameter. By default, it removes all the unwanted
entries in the JSON file, i.e. the list of UIDs of mails that are not forwarded from LKML subscription.
- Read upRead up
Cognitive Complexity
Cognitive Complexity is a measure of how difficult a unit of code is to intuitively understand. Unlike Cyclomatic Complexity, which determines how difficult your code will be to test, Cognitive Complexity tells you how difficult your code will be to read and comprehend.
A method's cognitive complexity is based on a few simple rules:
- Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one
- Code is considered more complex for each "break in the linear flow of the code"
- Code is considered more complex when "flow breaking structures are nested"
Further reading
Avoid deeply nested control flow statements. Open
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if to_addr not in author_map:
author_map[to_addr] = index
author_graph.add_vertex(name=to_addr, label=to_addr)
index += 1
if author_graph[node['From'], to_addr] == 0:
Avoid deeply nested control flow statements. Open
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if edge[0] in msgs_before_time and edge[1] in msgs_before_time:
discussion_graph.add_edge(*edge)
edge_file.close()
Avoid deeply nested control flow statements. Open
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if time_lbound <= json_obj['Time'] < time_ubound:
# print("\nFrom", json_obj['From'], "\nTo", json_obj['To'], "\nCc", json_obj['Cc'])
from_addr = email_re.search(json_obj['From'])
json_obj['From'] = from_addr.group(0) if from_addr is not None else json_obj['From']
json_obj['To'] = set(email_re.findall(json_obj['To']))
Avoid deeply nested control flow statements. Open
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if edge[0] in msgs_before_time and edge[1] in msgs_before_time:
discussion_graph.add_edge(*edge)
edge_file.close()
Avoid deeply nested control flow statements. Open
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if to_addr not in author_map:
author_map[to_addr] = index
author_graph.add_vertex(name=to_addr, label=to_addr)
index += 1
if author_graph[node['From'], to_addr] == 0:
Avoid deeply nested control flow statements. Open
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if time_lbound <= json_obj['Time'] < time_ubound:
# print("\nFrom", json_obj['From'], "\nTo", json_obj['To'], "\nCc", json_obj['Cc'])
from_addr = email_re.search(json_obj['From'])
json_obj['From'] = from_addr.group(0) if from_addr is not None else json_obj['From']
json_obj['To'] = set(email_re.findall(json_obj['To']))
Function generate_hyperedge_distribution
has 6 arguments (exceeds 4 allowed). Consider refactoring. Open
Open
def generate_hyperedge_distribution(nodelist_filename, edgelist_filename, clean_headers_filename, foldername, time_limit=None, ignore_lat=False):
Avoid deeply nested control flow statements. Open
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if edge[0] in msgs_before_time and edge[1] in msgs_before_time:
discussion_graph.add_edge(*edge)
edge_file.close()
Avoid deeply nested control flow statements. Open
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if not console_output:
out_file.write(author_email + "\n")
author_features = list()
for i in indices:
author_features.append(feature_names[i])
Function vertex_clustering
has 6 arguments (exceeds 4 allowed). Consider refactoring. Open
Open
def vertex_clustering(json_filename, nodelist_filename, edgelist_filename, foldername, time_limit=None, ignore_lat=False):
Avoid deeply nested control flow statements. Open
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if author_graph[node['From'], to_addr] == 0:
author_graph.add_edge(node['From'], to_addr, weight=1)
else:
author_graph[node['From'], to_addr] += 1
Avoid deeply nested control flow statements. Open
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if edge[0] in msgs_before_time and edge[1] in msgs_before_time:
discussion_graph.add_edge(*edge)
edge_file.close()
Avoid deeply nested control flow statements. Open
Open
if json_obj['Time'] < time_limit:
# print("\nFrom", json_obj['From'], "\nTo", json_obj['To'], "\nCc", json_obj['Cc'])
from_addr = email_re.search(json_obj['From'])
json_obj['From'] = from_addr.group(0) if from_addr is not None else json_obj['From']
json_obj['To'] = set(email_re.findall(json_obj['To']))
Avoid deeply nested control flow statements. Open
Open
if json_obj['Time'] < time_limit:
# print("\nFrom", json_obj['From'], "\nTo", json_obj['To'], "\nCc", json_obj['Cc'])
from_addr = email_re.search(json_obj['From'])
json_obj['From'] = from_addr.group(0) if from_addr is not None else json_obj['From']
json_obj['To'] = set(email_re.findall(json_obj['To']))
Avoid deeply nested control flow statements. Open
Open
if edge[0] in msgs_before_time and edge[1] in msgs_before_time:
discussion_graph.add_edge(*edge)
edge_file.close()
Function test_generate_rt_curve_fits
has 6 arguments (exceeds 4 allowed). Consider refactoring. Open
Open
def test_generate_rt_curve_fits(mock_figure, mock_plot, mock_legend, mock_ylabel, mock_xlabel, mock_savefig):