Showing 10 of 107 total issues
Consider simplifying this complex logical expression. Open
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if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Format and clean Jupyter notebooks by removing TensorFlow warnings "
"and stderr outputs, formatting and numbering the code cells, and setting the kernel. "Avoid deeply nested control flow statements. Open
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if dv == d:
u_v_edge_type = (nodes_dict[u[0]], nodes_dict[v])
# if no edge between u and next_node[0] then this is the sample, so record and stop
# searching
# Note: The if statement below is very expensive to evaluate because it need to checksAvoid deeply nested control flow statements. Open
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if original != updated:
check_failed.append(str(file_loc))
if on_ci:
# CI doesn't provide enough state to diagnose a peculiar orAvoid deeply nested control flow statements. Open
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with open(file_loc) as f:
original = f.read()
Avoid deeply nested control flow statements. Open
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if dv == d:
# if no edge between u and next_node[0] then this is the sample, so record and stop
# searching
if (
(u != v)Avoid deeply nested control flow statements. Open
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for et in current_edge_types:
neigh_et = adj[et][current_node]
# If there are no neighbours of this type then we return None
# in the place of the nodes that would have been sampledAvoid deeply nested control flow statements. Open
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with builder.element("td"):
self._render_cell(builder, algorithm.columns[heading])
Avoid deeply nested control flow statements. Open
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if len(neighbours) == 0:
# if no neighbours of the required type as dictated by the metapath exist, then stop.
break
# select one of the neighbours uniformly at random
current_node = rs.choice(Avoid deeply nested control flow statements. Open
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with open(f"{nb_file_loc}.ipynb") as f:
updated = f.read()
Avoid too many return statements within this function. Open
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return T(inp)