| Conditions | 9 | 
| Total Lines | 73 | 
| Lines | 0 | 
| Ratio | 0 % | 
Small methods make your code easier to understand, in particular if combined with a good name. Besides, if your method is small, finding a good name is usually much easier.
For example, if you find yourself adding comments to a method's body, this is usually a good sign to extract the commented part to a new method, and use the comment as a starting point when coming up with a good name for this new method.
Commonly applied refactorings include:
If many parameters/temporary variables are present:
| 1 | #!/usr/bin/env python | ||
| 36 | def main(metadata_path, output_path, print_source=False): | ||
| 37 | metadata_path = os.path.abspath(metadata_path) | ||
| 38 | metadata_dir = os.path.dirname(metadata_path) | ||
| 39 | |||
| 40 | meta_loader = MetaLoader() | ||
| 41 | data = meta_loader.load(metadata_path) | ||
| 42 | |||
| 43 | action_name = data['name'] | ||
| 44 | entry_point = data['entry_point'] | ||
| 45 | |||
| 46 | workflow_metadata_path = os.path.join(metadata_dir, entry_point) | ||
| 47 | chainspec = meta_loader.load(workflow_metadata_path) | ||
| 48 | |||
| 49 | chain_holder = ChainHolder(chainspec, 'workflow') | ||
| 50 | |||
| 51 | graph_label = '%s action-chain workflow visualization' % (action_name) | ||
| 52 | |||
| 53 |     graph_attr = { | ||
| 54 | 'rankdir': 'TD', | ||
| 55 | 'labelloc': 't', | ||
| 56 | 'fontsize': '15', | ||
| 57 | 'label': graph_label | ||
| 58 | } | ||
| 59 |     node_attr = {} | ||
| 60 | dot = Digraph(comment='Action chain work-flow visualization', | ||
| 61 | node_attr=node_attr, graph_attr=graph_attr, format='png') | ||
| 62 | # dot.body.extend(['rankdir=TD', 'size="10,5"']) | ||
| 63 | |||
| 64 | # Add all nodes | ||
| 65 | node = chain_holder.get_next_node() | ||
| 66 | while node: | ||
| 67 | dot.node(node.name, node.name) | ||
| 68 | node = chain_holder.get_next_node(curr_node_name=node.name) | ||
| 69 | |||
| 70 | # Add connections | ||
| 71 | node = chain_holder.get_next_node() | ||
| 72 | processed_nodes = sets.Set([node.name]) | ||
| 73 | nodes = [node] | ||
| 74 | while nodes: | ||
| 75 | previous_node = nodes.pop() | ||
| 76 | success_node = chain_holder.get_next_node(curr_node_name=previous_node.name, | ||
| 77 | condition='on-success') | ||
| 78 | failure_node = chain_holder.get_next_node(curr_node_name=previous_node.name, | ||
| 79 | condition='on-failure') | ||
| 80 | |||
| 81 | # Add success node (if any) | ||
| 82 | if success_node: | ||
| 83 | dot.edge(previous_node.name, success_node.name, constraint='true', | ||
| 84 | color='green', label='on success') | ||
| 85 | if success_node.name not in processed_nodes: | ||
| 86 | nodes.append(success_node) | ||
| 87 | processed_nodes.add(success_node.name) | ||
| 88 | |||
| 89 | # Add failure node (if any) | ||
| 90 | if failure_node: | ||
| 91 | dot.edge(previous_node.name, failure_node.name, constraint='true', | ||
| 92 | color='red', label='on failure') | ||
| 93 | if failure_node.name not in processed_nodes: | ||
| 94 | nodes.append(failure_node) | ||
| 95 | processed_nodes.add(failure_node.name) | ||
| 96 | |||
| 97 | if print_source: | ||
| 98 | print(dot.source) | ||
| 99 | |||
| 100 | if output_path: | ||
| 101 | output_path = os.path.join(output_path, action_name) | ||
| 102 | else: | ||
| 103 | output_path = output_path or os.path.join(os.getcwd(), action_name) | ||
| 104 | |||
| 105 | dot.format = 'png' | ||
| 106 | dot.render(output_path) | ||
| 107 | |||
| 108 |     print('Graph saved at %s' % (output_path + '.png')) | ||
| 109 | |||
| 122 |