Mercurial > repos > shellac > guppy_basecaller

annotate env/lib/python3.7/site-packages/gxformat2/export.py @ 0:26e78fe6e8c4 draft

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"planemo upload commit c699937486c35866861690329de38ec1a5d9f783"
author shellac
date Sat, 02 May 2020 07:14:21 -0400
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1 """Functionality for converting a standard Galaxy workflow into a format 2 workflow."""
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2
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3 import json
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4 from collections import OrderedDict
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5
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6 from ._labels import Labels
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7 from ._yaml import ordered_dump
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8
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9
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10 def _copy_common_properties(from_native_step, to_format2_step):
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11 annotation = from_native_step.get("annotation", "")
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12 if annotation:
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13 to_format2_step["doc"] = annotation
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14 position = from_native_step.get("position", None)
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15 if position:
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16 to_format2_step["position"] = position
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17
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18
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19 def from_galaxy_native(native_workflow_dict, tool_interface=None, json_wrapper=False):
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20 """Convert native .ga workflow definition to a format2 workflow.
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21
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22 This is highly experimental and currently broken.
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23 """
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24 data = OrderedDict()
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25 data['class'] = 'GalaxyWorkflow'
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26 _copy_common_properties(native_workflow_dict, data)
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27 if "name" in native_workflow_dict:
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28 data["label"] = native_workflow_dict.pop("name")
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29 for top_level_key in ['tags', 'uuid', 'report']:
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30 value = native_workflow_dict.get(top_level_key)
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31 if value:
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32 data[top_level_key] = value
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33
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34 native_steps = native_workflow_dict.get("steps")
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35
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36 label_map = {}
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37 all_labeled = True
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38 for key, step in native_steps.items():
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39 label = step.get("label")
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40 if not label:
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41 all_labeled = False
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42 label_map[str(key)] = label
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43
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44 inputs = OrderedDict()
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45 outputs = OrderedDict()
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46 steps = []
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47
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48 labels = Labels()
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49
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50 # For each step, rebuild the form and encode the state
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51 for step in native_steps.values():
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52 for workflow_output in step.get("workflow_outputs", []):
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53 source = _to_source(workflow_output, label_map, output_id=step["id"])
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54 output_id = labels.ensure_new_output_label(workflow_output.get("label"))
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55 outputs[output_id] = {"outputSource": source}
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56
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57 module_type = step.get("type")
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58 if module_type in ['data_input', 'data_collection_input', 'parameter_input']:
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59 step_id = step["label"] # TODO: auto-label
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60 input_dict = {}
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61 if module_type == 'data_collection_input':
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62 input_dict['type'] = 'collection'
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63 elif module_type == 'data_input':
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64 input_dict['type'] = 'data'
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65 elif module_type == "parameter_input":
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66 tool_state = _tool_state(step)
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67 input_dict['type'] = tool_state.get("parameter_type")
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68 # TODO: handle parameter_input types
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69 _copy_common_properties(step, input_dict)
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70 # If we are only copying property - use the CWL-style short-hand
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71 if len(input_dict) == 1:
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72 inputs[step_id] = input_dict["type"]
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73 else:
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74 inputs[step_id] = input_dict
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75 continue
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76
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77 if module_type == "pause":
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78 step_dict = OrderedDict()
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79 optional_props = ['label']
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80 _copy_common_properties(step, step_dict)
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81 _copy_properties(step, step_dict, optional_props=optional_props)
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82 _convert_input_connections(step, step_dict, label_map)
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83 step_dict["type"] = "pause"
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84 steps.append(step_dict)
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85 continue
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86
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87 if module_type == 'subworkflow':
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88 step_dict = OrderedDict()
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89 optional_props = ['label']
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90 _copy_common_properties(step, step_dict)
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91 _copy_properties(step, step_dict, optional_props=optional_props)
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92 _convert_input_connections(step, step_dict, label_map)
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93 _convert_post_job_actions(step, step_dict)
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94 subworkflow_native_dict = step["subworkflow"]
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95 subworkflow = from_galaxy_native(subworkflow_native_dict, tool_interface=tool_interface, json_wrapper=False)
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96 step_dict["run"] = subworkflow
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97 steps.append(step_dict)
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98 continue
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99
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100 if module_type != 'tool':
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101 raise NotImplementedError("Unhandled module type %s" % module_type)
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102
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103 step_dict = OrderedDict()
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104 optional_props = ['label', 'tool_shed_repository']
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105 required_props = ['tool_id', 'tool_version']
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106 _copy_properties(step, step_dict, optional_props, required_props)
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107 _copy_common_properties(step, step_dict)
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108
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109 tool_state = _tool_state(step)
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110 tool_state.pop("__page__", None)
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111 tool_state.pop("__rerun_remap_job_id__", None)
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112 step_dict['tool_state'] = tool_state
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113
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114 _convert_input_connections(step, step_dict, label_map)
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115 _convert_post_job_actions(step, step_dict)
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116 steps.append(step_dict)
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117
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118 data['inputs'] = inputs
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119 data['outputs'] = outputs
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120
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121 if all_labeled:
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122 steps_dict = OrderedDict()
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123 for step in steps:
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124 label = step.pop("label")
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125 steps_dict[label] = step
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126 data['steps'] = steps_dict
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127 else:
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128 data['steps'] = steps
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129
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130 if json_wrapper:
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131 return {
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132 "yaml_content": ordered_dump(data)
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133 }
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134
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135 return data
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136
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137
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138 def _tool_state(step):
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139 tool_state = json.loads(step['tool_state'])
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140 return tool_state
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141
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142
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143 def _copy_properties(from_native_step, to_format2_step, optional_props=[], required_props=[]):
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144 for prop in optional_props:
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145 value = from_native_step.get(prop)
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146 if value:
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147 to_format2_step[prop] = value
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148 for prop in required_props:
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149 value = from_native_step.get(prop)
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150 to_format2_step[prop] = value
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151
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152
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153 def _convert_input_connections(from_native_step, to_format2_step, label_map):
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154 in_dict = from_native_step.get("in", {}).copy()
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155 input_connections = from_native_step['input_connections']
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156 for input_name, input_defs in input_connections.items():
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157 if not isinstance(input_defs, list):
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158 input_defs = [input_defs]
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159 for input_def in input_defs:
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160 source = _to_source(input_def, label_map)
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161 if input_name == "__NO_INPUT_OUTPUT_NAME__":
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162 input_name = "$step"
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163 assert source.endswith("/__NO_INPUT_OUTPUT_NAME__")
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164 source = source[:-len("/__NO_INPUT_OUTPUT_NAME__")]
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165 in_dict[input_name] = {
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166 "source": source
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167 }
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168 to_format2_step["in"] = in_dict
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169
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170
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171 def _convert_post_job_actions(from_native_step, to_format2_step):
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172
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173 def _ensure_output_def(key):
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174 if "outputs" in to_format2_step:
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175 to_format2_step["out"] = to_format2_step.pop("outputs")
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176 elif "out" not in to_format2_step:
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177 to_format2_step["out"] = {}
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178
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179 outputs_dict = to_format2_step["out"]
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180 if key not in outputs_dict:
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181 outputs_dict[key] = {}
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182 return outputs_dict[key]
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183
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184 if "post_job_actions" in from_native_step:
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185 post_job_actions = from_native_step["post_job_actions"].copy()
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186 to_remove_keys = []
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187
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188 for post_job_action_key, post_job_action_value in post_job_actions.items():
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189 action_type = post_job_action_value["action_type"]
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190 output_name = post_job_action_value.get("output_name")
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191 action_args = post_job_action_value.get("action_arguments", {})
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192
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193 handled = True
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194 if action_type == "RenameDatasetAction":
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195 output_dict = _ensure_output_def(output_name)
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196 output_dict["rename"] = action_args["newname"]
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197 handled = True
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198 elif action_type == "HideDatasetAction":
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199 output_dict = _ensure_output_def(output_name)
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200 output_dict["hide"] = True
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201 handled = True
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202 elif action_type == "DeleteIntermediatesAction":
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203 output_dict = _ensure_output_def(output_name)
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204 output_dict["delete_intermediate_datasets"] = True
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205 elif action_type == "ChangeDatatypeAction":
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206 output_dict = _ensure_output_def(output_name)
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207 output_dict['change_datatype'] = action_args
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208 handled = True
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209 elif action_type == "TagDatasetAction":
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210 output_dict = _ensure_output_def(output_name)
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211 output_dict["add_tags"] = action_args["tags"].split(",")
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212 elif action_type == "RemoveTagDatasetAction":
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213 output_dict = _ensure_output_def(output_name)
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214 output_dict["remove_tags"] = action_args["tags"].split(",")
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215 elif action_type == "ColumnSetAction":
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216 output_dict = _ensure_output_def(output_name)
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217 output_dict["set_columns"] = action_args
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218 else:
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219 handled = False
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220
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221 if handled:
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222 to_remove_keys.append(post_job_action_key)
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223
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224 for to_remove in to_remove_keys:
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225 del post_job_actions[to_remove]
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226
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227 if post_job_actions:
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228 to_format2_step["post_job_actions"] = post_job_actions
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229
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230
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231 def _to_source(has_output_name, label_map, output_id=None):
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232 output_id = output_id if output_id is not None else has_output_name['id']
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233 output_id = str(output_id)
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234 output_name = has_output_name['output_name']
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235 output_label = label_map.get(output_id) or output_id
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236 if output_name == "output":
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237 source = output_label
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238 else:
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239 source = "%s/%s" % (output_label, output_name)
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240 return source
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241
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242
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243 __all__ = (
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244 'from_galaxy_native',
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245 )