DeveloperCAP/MLCAT

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lib/analysis/author/community.py

Summary

Maintainability
D
3 days
Test Coverage

Function vertex_clustering has a Cognitive Complexity of 83 (exceeds 5 allowed). Consider refactoring.
Open

def vertex_clustering(json_filename, nodelist_filename, edgelist_filename, foldername, time_limit=None, ignore_lat=False):
    """
    This function performs vertex clustering on the dataset passed in the parameters and saves the dendrogram resulting
    from the vertex clustering as a PDF along with the visualization of the vertex cluster itself. It is recommended to
    limit these graphs to 200 authors as the visualization becomes incompehensible beyond that.
Severity: Minor
Found in lib/analysis/author/community.py - About 1 day to fix

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

Function vertex_clustering has 26 lines of code (exceeds 25 allowed). Consider refactoring.
Open

def vertex_clustering(json_filename, nodelist_filename, edgelist_filename, foldername, time_limit=None, ignore_lat=False):
    """
    This function performs vertex clustering on the dataset passed in the parameters and saves the dendrogram resulting
    from the vertex clustering as a PDF along with the visualization of the vertex cluster itself. It is recommended to
    limit these graphs to 200 authors as the visualization becomes incompehensible beyond that.
Severity: Minor
Found in lib/analysis/author/community.py - About 1 hr to fix

    Avoid deeply nested control flow statements.
    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']))
    Severity: Major
    Found in lib/analysis/author/community.py - About 45 mins to fix

      Avoid deeply nested control flow statements.
      Open

                          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:
      Severity: Major
      Found in lib/analysis/author/community.py - About 45 mins to fix

        Avoid deeply nested control flow statements.
        Open

                            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
                    if node['Cc'] is None:
        Severity: Major
        Found in lib/analysis/author/community.py - About 45 mins to fix

          Avoid deeply nested control flow statements.
          Open

                              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:
          Severity: Major
          Found in lib/analysis/author/community.py - About 45 mins to fix

            Avoid deeply nested control flow statements.
            Open

                                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
            
            
            Severity: Major
            Found in lib/analysis/author/community.py - About 45 mins to fix

              Function vertex_clustering has 6 arguments (exceeds 4 allowed). Consider refactoring.
              Open

              def vertex_clustering(json_filename, nodelist_filename, edgelist_filename, foldername, time_limit=None, ignore_lat=False):
              Severity: Minor
              Found in lib/analysis/author/community.py - About 45 mins to fix

                Identical blocks of code found in 2 locations. Consider refactoring.
                Open

                    for i in range(1, num_vertices+1):
                        line = lines_in_file[i].split()
                        line[1] = "\"" + line[1] + "\""
                        del line[2:]
                        line.append("\n")
                Severity: Major
                Found in lib/analysis/author/community.py and 1 other location - About 5 hrs to fix
                lib/analysis/author/graph/generate.py on lines 26..31

                Duplicated Code

                Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

                Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

                When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

                Tuning

                This issue has a mass of 96.

                We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

                The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

                If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

                See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

                Refactorings

                Further Reading

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