| 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 |
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| 36 | def main(metadata_path, output_path, print_source=False): |
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| 37 | metadata_path = os.path.abspath(metadata_path) |
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| 38 | metadata_dir = os.path.dirname(metadata_path) |
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| 39 | |||
| 40 | meta_loader = MetaLoader() |
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| 41 | data = meta_loader.load(metadata_path) |
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| 42 | |||
| 43 | action_name = data['name'] |
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| 44 | entry_point = data['entry_point'] |
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| 45 | |||
| 46 | workflow_metadata_path = os.path.join(metadata_dir, entry_point) |
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| 47 | chainspec = meta_loader.load(workflow_metadata_path) |
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| 48 | |||
| 49 | chain_holder = ChainHolder(chainspec, 'workflow') |
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| 50 | |||
| 51 | graph_label = '%s action-chain workflow visualization' % (action_name) |
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| 52 | |||
| 53 | graph_attr = { |
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| 54 | 'rankdir': 'TD', |
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| 55 | 'labelloc': 't', |
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| 56 | 'fontsize': '15', |
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| 57 | 'label': graph_label |
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| 58 | } |
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| 59 | node_attr = {} |
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| 60 | dot = Digraph(comment='Action chain work-flow visualization', |
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| 61 | node_attr=node_attr, graph_attr=graph_attr, format='png') |
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| 62 | # dot.body.extend(['rankdir=TD', 'size="10,5"']) |
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| 63 | |||
| 64 | # Add all nodes |
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| 65 | node = chain_holder.get_next_node() |
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| 66 | while node: |
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| 67 | dot.node(node.name, node.name) |
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| 68 | node = chain_holder.get_next_node(curr_node_name=node.name) |
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| 69 | |||
| 70 | # Add connections |
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| 71 | node = chain_holder.get_next_node() |
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| 72 | processed_nodes = sets.Set([node.name]) |
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| 73 | nodes = [node] |
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| 74 | while nodes: |
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| 75 | previous_node = nodes.pop() |
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| 76 | success_node = chain_holder.get_next_node(curr_node_name=previous_node.name, |
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| 77 | condition='on-success') |
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| 78 | failure_node = chain_holder.get_next_node(curr_node_name=previous_node.name, |
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| 79 | condition='on-failure') |
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| 80 | |||
| 81 | # Add success node (if any) |
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| 82 | if success_node: |
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| 83 | dot.edge(previous_node.name, success_node.name, constraint='true', |
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| 84 | color='green', label='on success') |
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| 85 | if success_node.name not in processed_nodes: |
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| 86 | nodes.append(success_node) |
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| 87 | processed_nodes.add(success_node.name) |
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| 88 | |||
| 89 | # Add failure node (if any) |
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| 90 | if failure_node: |
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| 91 | dot.edge(previous_node.name, failure_node.name, constraint='true', |
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| 92 | color='red', label='on failure') |
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| 93 | if failure_node.name not in processed_nodes: |
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| 94 | nodes.append(failure_node) |
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| 95 | processed_nodes.add(failure_node.name) |
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| 96 | |||
| 97 | if print_source: |
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| 98 | print(dot.source) |
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| 99 | |||
| 100 | if output_path: |
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| 101 | output_path = os.path.join(output_path, action_name) |
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| 102 | else: |
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| 103 | output_path = output_path or os.path.join(os.getcwd(), action_name) |
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| 104 | |||
| 105 | dot.format = 'png' |
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| 106 | dot.render(output_path) |
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| 107 | |||
| 108 | print('Graph saved at %s' % (output_path + '.png')) |
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| 109 | |||
| 122 |