Mercurial > repos > shellac > sam_consensus_v3
annotate env/lib/python3.9/site-packages/bioblend/galaxy/workflows/__init__.py @ 0:4f3585e2f14b draft default tip
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author | shellac |
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date | Mon, 22 Mar 2021 18:12:50 +0000 |
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1 """ |
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2 Contains possible interactions with the Galaxy Workflows |
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3 """ |
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4 import json |
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5 import os |
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6 |
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7 from bioblend.galaxy.client import Client |
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8 |
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9 |
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10 class WorkflowClient(Client): |
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11 def __init__(self, galaxy_instance): |
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12 self.module = 'workflows' |
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13 super().__init__(galaxy_instance) |
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14 |
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15 # the 'deleted' option is not available for workflows |
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16 def get_workflows(self, workflow_id=None, name=None, published=False): |
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17 """ |
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18 Get all workflows or filter the specific one(s) via the provided ``name`` |
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19 or ``workflow_id``. Provide only one argument, ``name`` or ``workflow_id``, |
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20 but not both. |
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21 |
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22 :type workflow_id: str |
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23 :param workflow_id: Encoded workflow ID (incompatible with ``name``) |
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24 |
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25 :type name: str |
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26 :param name: Filter by name of workflow (incompatible with |
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27 ``workflow_id``). If multiple names match the given name, all the |
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28 workflows matching the argument will be returned. |
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29 |
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30 :type published: bool |
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31 :param published: if ``True``, return also published workflows |
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32 |
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33 :rtype: list |
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34 :return: A list of workflow dicts. |
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35 For example:: |
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36 |
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37 [{'id': '92c56938c2f9b315', |
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38 'name': 'Simple', |
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39 'url': '/api/workflows/92c56938c2f9b315'}] |
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40 |
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41 """ |
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42 if workflow_id is not None and name is not None: |
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43 raise ValueError('Provide only one argument between name or workflow_id, but not both') |
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44 params = {} |
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45 if published: |
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46 params['show_published'] = True |
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47 workflows = self._get(params=params) |
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48 if workflow_id is not None: |
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49 workflow = next((_ for _ in workflows if _['id'] == workflow_id), None) |
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50 workflows = [workflow] if workflow is not None else [] |
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51 elif name is not None: |
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52 workflows = [_ for _ in workflows if _['name'] == name] |
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53 return workflows |
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54 |
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55 def show_workflow(self, workflow_id, version=None): |
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56 """ |
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57 Display information needed to run a workflow. |
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58 |
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59 :type workflow_id: str |
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60 :param workflow_id: Encoded workflow ID |
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61 |
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62 :type version: int |
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63 :param version: Workflow version to show |
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64 |
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65 :rtype: dict |
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66 :return: A description of the workflow and its inputs. |
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67 For example:: |
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68 |
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69 {'id': '92c56938c2f9b315', |
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70 'inputs': {'23': {'label': 'Input Dataset', 'value': ''}}, |
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71 'name': 'Simple', |
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72 'url': '/api/workflows/92c56938c2f9b315'} |
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73 """ |
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74 params = {} |
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75 if version is not None: |
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76 params['version'] = version |
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77 |
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78 return self._get(id=workflow_id, params=params) |
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79 |
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80 def get_workflow_inputs(self, workflow_id, label): |
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81 """ |
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82 Get a list of workflow input IDs that match the given label. |
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83 If no input matches the given label, an empty list is returned. |
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84 |
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85 :type workflow_id: str |
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86 :param workflow_id: Encoded workflow ID |
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87 |
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88 :type label: str |
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89 :param label: label to filter workflow inputs on |
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90 |
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91 :rtype: list |
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92 :return: list of workflow inputs matching the label query |
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93 """ |
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94 wf = self._get(id=workflow_id) |
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95 inputs = wf['inputs'] |
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96 return [id for id in inputs if inputs[id]['label'] == label] |
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97 |
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98 def import_workflow_dict(self, workflow_dict, publish=False): |
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99 """ |
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100 Imports a new workflow given a dictionary representing a previously |
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101 exported workflow. |
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102 |
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103 :type workflow_dict: dict |
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104 :param workflow_dict: dictionary representing the workflow to be imported |
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105 |
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106 :type publish: bool |
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107 :param publish: if ``True`` the uploaded workflow will be published; |
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108 otherwise it will be visible only by the user which uploads it (default) |
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109 |
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110 :rtype: dict |
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111 :return: Information about the imported workflow. |
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112 For example:: |
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113 |
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114 {'name': 'Training: 16S rRNA sequencing with mothur: main tutorial', |
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115 'tags': [], |
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116 'deleted': false, |
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117 'latest_workflow_uuid': '368c6165-ccbe-4945-8a3c-d27982206d66', |
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118 'url': '/api/workflows/94bac0a90086bdcf', |
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119 'number_of_steps': 44, |
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120 'published': false, |
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121 'owner': 'jane-doe', |
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122 'model_class': 'StoredWorkflow', |
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123 'id': '94bac0a90086bdcf'} |
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124 """ |
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125 payload = {'workflow': workflow_dict, 'publish': publish} |
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126 |
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127 url = self._make_url() + "/upload" |
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128 return self._post(url=url, payload=payload) |
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129 |
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130 def import_workflow_from_local_path(self, file_local_path, publish=False): |
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131 """ |
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132 Imports a new workflow given the path to a file containing a previously |
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133 exported workflow. |
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134 |
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135 :type file_local_path: str |
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136 :param file_local_path: File to upload to the server for new workflow |
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137 |
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138 :type publish: bool |
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139 :param publish: if ``True`` the uploaded workflow will be published; |
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140 otherwise it will be visible only by the user which uploads it (default) |
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141 |
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142 :rtype: dict |
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143 :return: Information about the imported workflow. |
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144 For example:: |
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145 |
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146 {'name': 'Training: 16S rRNA sequencing with mothur: main tutorial', |
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147 'tags': [], |
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148 'deleted': false, |
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149 'latest_workflow_uuid': '368c6165-ccbe-4945-8a3c-d27982206d66', |
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150 'url': '/api/workflows/94bac0a90086bdcf', |
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151 'number_of_steps': 44, |
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152 'published': false, |
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153 'owner': 'jane-doe', |
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154 'model_class': 'StoredWorkflow', |
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155 'id': '94bac0a90086bdcf'} |
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156 |
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157 """ |
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158 with open(file_local_path) as fp: |
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159 workflow_json = json.load(fp) |
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160 |
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161 return self.import_workflow_dict(workflow_json, publish) |
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162 |
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163 def import_shared_workflow(self, workflow_id): |
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164 """ |
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165 Imports a new workflow from the shared published workflows. |
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166 |
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167 :type workflow_id: str |
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168 :param workflow_id: Encoded workflow ID |
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169 |
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170 :rtype: dict |
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171 :return: A description of the workflow. |
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172 For example:: |
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173 |
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174 {'id': 'ee0e2b4b696d9092', |
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175 'model_class': 'StoredWorkflow', |
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176 'name': 'Super workflow that solves everything!', |
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177 'published': False, |
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178 'tags': [], |
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179 'url': '/api/workflows/ee0e2b4b696d9092'} |
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180 """ |
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181 payload = {'shared_workflow_id': workflow_id} |
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182 url = self._make_url() |
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183 return self._post(url=url, payload=payload) |
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184 |
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185 def export_workflow_dict(self, workflow_id, version=None): |
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186 """ |
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187 Exports a workflow. |
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188 |
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189 :type workflow_id: str |
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190 :param workflow_id: Encoded workflow ID |
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191 |
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192 :type version: int |
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193 :param version: Workflow version to export |
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194 |
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195 :rtype: dict |
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196 :return: Dictionary representing the requested workflow |
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197 """ |
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198 params = {} |
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199 if version is not None: |
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200 params['version'] = version |
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201 |
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202 url = '/'.join((self._make_url(), 'download', workflow_id)) |
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203 return self._get(url=url, params=params) |
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204 |
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205 def export_workflow_to_local_path(self, workflow_id, file_local_path, use_default_filename=True): |
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206 """ |
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207 Exports a workflow in JSON format to a given local path. |
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208 |
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209 :type workflow_id: str |
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210 :param workflow_id: Encoded workflow ID |
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211 |
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212 :type file_local_path: str |
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213 :param file_local_path: Local path to which the exported file will be saved. |
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214 (Should not contain filename if use_default_name=True) |
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215 |
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216 :type use_default_filename: bool |
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217 :param use_default_filename: If the use_default_name parameter is True, the exported |
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218 file will be saved as file_local_path/Galaxy-Workflow-%s.ga, where %s |
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219 is the workflow name. If use_default_name is False, file_local_path |
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220 is assumed to contain the full file path including filename. |
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221 |
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222 :rtype: None |
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223 :return: None |
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224 """ |
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225 workflow_dict = self.export_workflow_dict(workflow_id) |
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226 |
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227 if use_default_filename: |
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228 filename = 'Galaxy-Workflow-%s.ga' % workflow_dict['name'] |
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229 file_local_path = os.path.join(file_local_path, filename) |
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230 |
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231 with open(file_local_path, 'w') as fp: |
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232 json.dump(workflow_dict, fp) |
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233 |
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234 def update_workflow(self, workflow_id, **kwds): |
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235 """ |
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236 Update a given workflow. |
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237 |
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238 :type workflow_id: str |
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239 :param workflow_id: Encoded workflow ID |
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240 |
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241 :type workflow: dict |
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242 :param workflow: dictionary representing the workflow to be updated |
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243 |
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244 :type name: str |
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245 :param name: New name of the workflow |
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246 |
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247 :type annotation: str |
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248 :param annotation: New annotation for the workflow |
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249 |
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250 :type menu_entry: bool |
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251 :param menu_entry: Whether the workflow should appear in the user's menu |
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252 |
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253 :type tags: list of str |
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254 :param tags: Replace workflow tags with the given list |
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255 |
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256 :rtype: dict |
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257 :return: Dictionary representing the updated workflow |
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258 """ |
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259 return self._put(payload=kwds, id=workflow_id) |
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260 |
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261 def run_workflow(self, workflow_id, dataset_map=None, params=None, |
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262 history_id=None, history_name=None, |
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263 import_inputs_to_history=False, replacement_params=None): |
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264 """ |
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265 Run the workflow identified by ``workflow_id``. |
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266 |
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267 .. deprecated:: 0.7.0 |
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268 Use :meth:`invoke_workflow` instead. |
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269 |
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270 :type workflow_id: str |
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271 :param workflow_id: Encoded workflow ID |
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272 |
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273 :type dataset_map: dict |
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274 :param dataset_map: A mapping of workflow inputs to datasets. The datasets |
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275 source can be a LibraryDatasetDatasetAssociation (``ldda``), |
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276 LibraryDataset (``ld``), or HistoryDatasetAssociation (``hda``). |
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277 The map must be in the following format: |
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278 ``{'<input>': {'id': <encoded dataset ID>, 'src': '[ldda, ld, hda]'}}`` |
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279 (e.g. ``{'23': {'id': '29beef4fadeed09f', 'src': 'ld'}}``) |
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280 |
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281 :type params: dict |
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282 :param params: A mapping of non-datasets tool parameters (see below) |
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283 |
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284 :type history_id: str |
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285 :param history_id: The encoded history ID where to store the workflow |
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286 output. Alternatively, ``history_name`` may be specified to create a |
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287 new history. |
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288 |
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289 :type history_name: str |
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290 :param history_name: Create a new history with the given name to store |
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291 the workflow output. If both ``history_id`` and ``history_name`` are |
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292 provided, ``history_name`` is ignored. If neither is specified, a new |
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293 'Unnamed history' is created. |
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294 |
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295 :type import_inputs_to_history: bool |
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296 :param import_inputs_to_history: If ``True``, used workflow inputs will be imported |
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297 into the history. If ``False``, only workflow outputs |
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298 will be visible in the given history. |
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299 |
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300 :type replacement_params: dict |
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301 :param replacement_params: pattern-based replacements for post-job actions (see below) |
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302 |
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303 :rtype: dict |
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304 :return: A dict containing the history ID where the outputs are placed |
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305 as well as output dataset IDs. For example:: |
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306 |
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307 {'history': '64177123325c9cfd', |
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308 'outputs': ['aa4d3084af404259']} |
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309 |
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310 The ``params`` dict should be specified as follows:: |
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311 |
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312 {STEP_ID: PARAM_DICT, ...} |
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313 |
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314 where PARAM_DICT is:: |
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315 |
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316 {PARAM_NAME: VALUE, ...} |
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317 |
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318 For backwards compatibility, the following (deprecated) format is |
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319 also supported for ``params``:: |
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320 |
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321 {TOOL_ID: PARAM_DICT, ...} |
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322 |
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323 in which case PARAM_DICT affects all steps with the given tool id. |
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324 If both by-tool-id and by-step-id specifications are used, the |
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325 latter takes precedence. |
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326 |
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327 Finally (again, for backwards compatibility), PARAM_DICT can also |
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328 be specified as:: |
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329 |
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330 {'param': PARAM_NAME, 'value': VALUE} |
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331 |
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332 Note that this format allows only one parameter to be set per step. |
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333 |
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334 The ``replacement_params`` dict should map parameter names in |
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335 post-job actions (PJAs) to their runtime values. For |
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336 instance, if the final step has a PJA like the following:: |
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337 |
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338 {'RenameDatasetActionout_file1': {'action_arguments': {'newname': '${output}'}, |
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339 'action_type': 'RenameDatasetAction', |
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340 'output_name': 'out_file1'}} |
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341 |
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342 then the following renames the output dataset to 'foo':: |
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343 |
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344 replacement_params = {'output': 'foo'} |
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345 |
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346 see also `this email thread |
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347 <http://lists.bx.psu.edu/pipermail/galaxy-dev/2011-September/006875.html>`_. |
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348 |
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349 .. warning:: |
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350 This method waits for the whole workflow to be scheduled before |
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351 returning and does not scale to large workflows as a result. This |
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352 method has therefore been deprecated in favor of |
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353 :meth:`invoke_workflow`, which also features improved default |
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354 behavior for dataset input handling. |
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355 """ |
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356 payload = {'workflow_id': workflow_id} |
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357 if dataset_map: |
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358 payload['ds_map'] = dataset_map |
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359 |
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360 if params: |
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361 payload['parameters'] = params |
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362 |
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363 if replacement_params: |
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364 payload['replacement_params'] = replacement_params |
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365 |
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366 if history_id: |
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367 payload['history'] = f'hist_id={history_id}' |
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368 elif history_name: |
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369 payload['history'] = history_name |
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370 if import_inputs_to_history is False: |
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371 payload['no_add_to_history'] = True |
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372 return self._post(payload) |
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373 |
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374 def invoke_workflow(self, workflow_id, inputs=None, params=None, |
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375 history_id=None, history_name=None, |
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376 import_inputs_to_history=False, replacement_params=None, |
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377 allow_tool_state_corrections=None, inputs_by=None): |
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378 """ |
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379 Invoke the workflow identified by ``workflow_id``. This will |
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380 cause a workflow to be scheduled and return an object describing |
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381 the workflow invocation. |
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382 |
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383 :type workflow_id: str |
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384 :param workflow_id: Encoded workflow ID |
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385 |
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386 :type inputs: dict |
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387 :param inputs: A mapping of workflow inputs to datasets and dataset collections. |
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388 The datasets source can be a LibraryDatasetDatasetAssociation (``ldda``), |
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389 LibraryDataset (``ld``), HistoryDatasetAssociation (``hda``), or |
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390 HistoryDatasetCollectionAssociation (``hdca``). |
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391 |
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392 The map must be in the following format: |
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393 ``{'<input_index>': {'id': <encoded dataset ID>, 'src': '[ldda, ld, hda, hdca]'}}`` |
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394 (e.g. ``{'2': {'id': '29beef4fadeed09f', 'src': 'hda'}}``) |
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395 |
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396 This map may also be indexed by the UUIDs of the workflow steps, |
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397 as indicated by the ``uuid`` property of steps returned from the |
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398 Galaxy API. Alternatively workflow steps may be addressed by |
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399 the label that can be set in the workflow editor. If using |
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400 uuid or label you need to also set the ``inputs_by`` parameter |
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401 to ``step_uuid`` or ``name``. |
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402 |
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403 :type params: dict |
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404 :param params: A mapping of non-datasets tool parameters (see below) |
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405 |
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406 :type history_id: str |
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407 :param history_id: The encoded history ID where to store the workflow |
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408 output. Alternatively, ``history_name`` may be specified to create a |
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409 new history. |
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410 |
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411 :type history_name: str |
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412 :param history_name: Create a new history with the given name to store |
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413 the workflow output. If both ``history_id`` and ``history_name`` are |
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414 provided, ``history_name`` is ignored. If neither is specified, a new |
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415 'Unnamed history' is created. |
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416 |
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417 :type import_inputs_to_history: bool |
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418 :param import_inputs_to_history: If ``True``, used workflow inputs will |
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419 be imported into the history. If ``False``, only workflow outputs will |
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420 be visible in the given history. |
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421 |
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422 :type allow_tool_state_corrections: bool |
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423 :param allow_tool_state_corrections: If True, allow Galaxy to fill in |
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424 missing tool state when running workflows. This may be useful for |
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425 workflows using tools that have changed over time or for workflows |
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426 built outside of Galaxy with only a subset of inputs defined. |
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427 |
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428 :type replacement_params: dict |
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429 :param replacement_params: pattern-based replacements for post-job |
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430 actions (see below) |
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431 |
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432 :type inputs_by: str |
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433 :param inputs_by: Determines how inputs are referenced. Can be |
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434 "step_index|step_uuid" (default), "step_index", "step_id", "step_uuid", or "name". |
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435 |
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436 :rtype: dict |
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437 :return: A dict containing the workflow invocation describing the |
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438 scheduling of the workflow. For example:: |
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439 |
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440 {'history_id': '2f94e8ae9edff68a', |
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441 'id': 'df7a1f0c02a5b08e', |
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442 'inputs': {'0': {'id': 'a7db2fac67043c7e', |
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443 'src': 'hda', |
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444 'uuid': '7932ffe0-2340-4952-8857-dbaa50f1f46a'}}, |
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445 'model_class': 'WorkflowInvocation', |
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446 'state': 'ready', |
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447 'steps': [{'action': None, |
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448 'id': 'd413a19dec13d11e', |
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449 'job_id': None, |
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450 'model_class': 'WorkflowInvocationStep', |
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451 'order_index': 0, |
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452 'state': None, |
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453 'update_time': '2015-10-31T22:00:26', |
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454 'workflow_step_id': 'cbbbf59e8f08c98c', |
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455 'workflow_step_label': None, |
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456 'workflow_step_uuid': 'b81250fd-3278-4e6a-b269-56a1f01ef485'}, |
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457 {'action': None, |
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458 'id': '2f94e8ae9edff68a', |
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459 'job_id': 'e89067bb68bee7a0', |
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460 'model_class': 'WorkflowInvocationStep', |
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461 'order_index': 1, |
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462 'state': 'new', |
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463 'update_time': '2015-10-31T22:00:26', |
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464 'workflow_step_id': '964b37715ec9bd22', |
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465 'workflow_step_label': None, |
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466 'workflow_step_uuid': 'e62440b8-e911-408b-b124-e05435d3125e'}], |
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467 'update_time': '2015-10-31T22:00:26', |
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468 'uuid': 'c8aa2b1c-801a-11e5-a9e5-8ca98228593c', |
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469 'workflow_id': '03501d7626bd192f'} |
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470 |
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471 The ``params`` dict should be specified as follows:: |
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472 |
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473 {STEP_ID: PARAM_DICT, ...} |
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474 |
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475 where PARAM_DICT is:: |
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476 |
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477 {PARAM_NAME: VALUE, ...} |
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478 |
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479 For backwards compatibility, the following (deprecated) format is |
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480 also supported for ``params``:: |
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481 |
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482 {TOOL_ID: PARAM_DICT, ...} |
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483 |
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484 in which case PARAM_DICT affects all steps with the given tool id. |
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485 If both by-tool-id and by-step-id specifications are used, the |
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486 latter takes precedence. |
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487 |
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488 Finally (again, for backwards compatibility), PARAM_DICT can also |
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489 be specified as:: |
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490 |
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491 {'param': PARAM_NAME, 'value': VALUE} |
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492 |
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493 Note that this format allows only one parameter to be set per step. |
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494 |
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495 For a ``repeat`` parameter, the names of the contained parameters needs |
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496 to be specified as ``<repeat name>_<repeat index>|<param name>``, with |
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497 the repeat index starting at 0. For example, if the tool XML contains:: |
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498 |
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499 <repeat name="cutoff" title="Parameters used to filter cells" min="1"> |
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500 <param name="name" type="text" value="n_genes" label="Name of param..."> |
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501 <option value="n_genes">n_genes</option> |
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502 <option value="n_counts">n_counts</option> |
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503 </param> |
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504 <param name="min" type="float" min="0" value="0" label="Min value"/> |
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505 </repeat> |
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506 |
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507 then the PARAM_DICT should be something like:: |
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508 |
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509 {... |
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510 "cutoff_0|name": "n_genes", |
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511 "cutoff_0|min": "2", |
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512 "cutoff_1|name": "n_counts", |
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513 "cutoff_1|min": "4", |
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514 ...} |
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515 |
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516 At the time of this writing, it is not possible to change the number of |
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517 times the contained parameters are repeated. Therefore, the parameter |
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518 indexes can go from 0 to n-1, where n is the number of times the |
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519 repeated element was added when the workflow was saved in the Galaxy UI. |
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520 |
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521 The ``replacement_params`` dict should map parameter names in |
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522 post-job actions (PJAs) to their runtime values. For |
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523 instance, if the final step has a PJA like the following:: |
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524 |
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525 {'RenameDatasetActionout_file1': {'action_arguments': {'newname': '${output}'}, |
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526 'action_type': 'RenameDatasetAction', |
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527 'output_name': 'out_file1'}} |
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528 |
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529 then the following renames the output dataset to 'foo':: |
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530 |
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531 replacement_params = {'output': 'foo'} |
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532 |
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533 see also `this email thread |
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534 <http://lists.bx.psu.edu/pipermail/galaxy-dev/2011-September/006875.html>`_. |
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535 |
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536 .. warning:: |
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537 Historically, the ``run_workflow`` method consumed a ``dataset_map`` |
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538 data structure that was indexed by unencoded workflow step IDs. These |
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539 IDs would not be stable across Galaxy instances. The new ``inputs`` |
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540 property is instead indexed by either the ``order_index`` property |
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541 (which is stable across workflow imports) or the step UUID which is |
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542 also stable. |
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543 """ |
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544 payload = {'workflow_id': workflow_id} |
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545 if inputs: |
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546 payload['inputs'] = inputs |
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547 |
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548 if params: |
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549 payload['parameters'] = params |
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550 |
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551 if replacement_params: |
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552 payload['replacement_params'] = replacement_params |
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553 |
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554 if history_id: |
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555 payload['history'] = f'hist_id={history_id}' |
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556 elif history_name: |
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557 payload['history'] = history_name |
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558 if import_inputs_to_history is False: |
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559 payload['no_add_to_history'] = True |
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560 if allow_tool_state_corrections is not None: |
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561 payload['allow_tool_state_corrections'] = allow_tool_state_corrections |
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562 if inputs_by is not None: |
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563 payload['inputs_by'] = inputs_by |
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564 url = self._invocations_url(workflow_id) |
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565 return self._post(payload, url=url) |
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566 |
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567 def show_invocation(self, workflow_id, invocation_id): |
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568 """ |
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569 Get a workflow invocation object representing the scheduling of a |
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570 workflow. This object may be sparse at first (missing inputs and |
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571 invocation steps) and will become more populated as the workflow is |
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572 actually scheduled. |
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573 |
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574 :type workflow_id: str |
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575 :param workflow_id: Encoded workflow ID |
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576 |
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577 :type invocation_id: str |
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578 :param invocation_id: Encoded workflow invocation ID |
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579 |
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580 :rtype: dict |
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581 :return: The workflow invocation. |
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582 For example:: |
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583 |
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584 {'history_id': '2f94e8ae9edff68a', |
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585 'id': 'df7a1f0c02a5b08e', |
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586 'inputs': {'0': {'id': 'a7db2fac67043c7e', |
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587 'src': 'hda', |
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588 'uuid': '7932ffe0-2340-4952-8857-dbaa50f1f46a'}}, |
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589 'model_class': 'WorkflowInvocation', |
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590 'state': 'ready', |
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591 'steps': [{'action': None, |
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592 'id': 'd413a19dec13d11e', |
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593 'job_id': None, |
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594 'model_class': 'WorkflowInvocationStep', |
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595 'order_index': 0, |
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596 'state': None, |
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597 'update_time': '2015-10-31T22:00:26', |
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598 'workflow_step_id': 'cbbbf59e8f08c98c', |
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599 'workflow_step_label': None, |
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600 'workflow_step_uuid': 'b81250fd-3278-4e6a-b269-56a1f01ef485'}, |
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601 {'action': None, |
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602 'id': '2f94e8ae9edff68a', |
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603 'job_id': 'e89067bb68bee7a0', |
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604 'model_class': 'WorkflowInvocationStep', |
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605 'order_index': 1, |
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606 'state': 'new', |
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607 'update_time': '2015-10-31T22:00:26', |
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608 'workflow_step_id': '964b37715ec9bd22', |
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609 'workflow_step_label': None, |
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610 'workflow_step_uuid': 'e62440b8-e911-408b-b124-e05435d3125e'}], |
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611 'update_time': '2015-10-31T22:00:26', |
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612 'uuid': 'c8aa2b1c-801a-11e5-a9e5-8ca98228593c', |
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613 'workflow_id': '03501d7626bd192f'} |
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614 """ |
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615 url = self._invocation_url(workflow_id, invocation_id) |
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616 return self._get(url=url) |
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617 |
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618 def get_invocations(self, workflow_id): |
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619 """ |
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620 Get a list containing all the workflow invocations corresponding to the |
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621 specified workflow. |
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622 |
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623 :type workflow_id: str |
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624 :param workflow_id: Encoded workflow ID |
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625 |
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626 :rtype: list |
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627 :return: A list of workflow invocations. |
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628 For example:: |
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629 |
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630 [{'history_id': '2f94e8ae9edff68a', |
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631 'id': 'df7a1f0c02a5b08e', |
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632 'model_class': 'WorkflowInvocation', |
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633 'state': 'new', |
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634 'update_time': '2015-10-31T22:00:22', |
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635 'uuid': 'c8aa2b1c-801a-11e5-a9e5-8ca98228593c', |
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636 'workflow_id': '03501d7626bd192f'}] |
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637 """ |
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638 url = self._invocations_url(workflow_id) |
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639 return self._get(url=url) |
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640 |
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641 def cancel_invocation(self, workflow_id, invocation_id): |
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642 """ |
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643 Cancel the scheduling of a workflow. |
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644 |
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645 :type workflow_id: str |
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646 :param workflow_id: Encoded workflow ID |
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647 |
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648 :type invocation_id: str |
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649 :param invocation_id: Encoded workflow invocation ID |
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650 |
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651 :rtype: dict |
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652 :return: The workflow invocation being cancelled |
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653 """ |
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654 url = self._invocation_url(workflow_id, invocation_id) |
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655 return self._delete(url=url) |
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656 |
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657 def show_invocation_step(self, workflow_id, invocation_id, step_id): |
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658 """ |
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659 See the details of a particular workflow invocation step. |
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660 |
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661 :type workflow_id: str |
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662 :param workflow_id: Encoded workflow ID |
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663 |
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664 :type invocation_id: str |
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665 :param invocation_id: Encoded workflow invocation ID |
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666 |
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667 :type step_id: str |
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668 :param step_id: Encoded workflow invocation step ID |
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669 |
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670 :rtype: dict |
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671 :return: The workflow invocation step. |
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672 For example:: |
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673 |
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674 {'action': None, |
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675 'id': '63cd3858d057a6d1', |
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676 'job_id': None, |
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677 'model_class': 'WorkflowInvocationStep', |
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678 'order_index': 2, |
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679 'state': None, |
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680 'update_time': '2015-10-31T22:11:14', |
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681 'workflow_step_id': '52e496b945151ee8', |
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682 'workflow_step_label': None, |
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683 'workflow_step_uuid': '4060554c-1dd5-4287-9040-8b4f281cf9dc'} |
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684 """ |
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685 url = self._invocation_step_url(workflow_id, invocation_id, step_id) |
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686 return self._get(url=url) |
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687 |
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688 def run_invocation_step_action(self, workflow_id, invocation_id, step_id, action): |
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689 """ Execute an action for an active workflow invocation step. The |
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690 nature of this action and what is expected will vary based on the |
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691 the type of workflow step (the only currently valid action is True/False |
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692 for pause steps). |
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693 |
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694 :type workflow_id: str |
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695 :param workflow_id: Encoded workflow ID |
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696 |
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697 :type invocation_id: str |
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698 :param invocation_id: Encoded workflow invocation ID |
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699 |
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700 :type step_id: str |
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701 :param step_id: Encoded workflow invocation step ID |
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702 |
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703 :type action: object |
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704 :param action: Action to use when updating state, semantics depends on |
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705 step type. |
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706 |
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707 :rtype: dict |
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708 :return: Representation of the workflow invocation step |
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709 """ |
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710 url = self._invocation_step_url(workflow_id, invocation_id, step_id) |
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711 payload = {"action": action} |
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712 return self._put(payload=payload, url=url) |
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713 |
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714 def delete_workflow(self, workflow_id): |
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715 """ |
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716 Delete a workflow identified by `workflow_id`. |
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717 |
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718 :type workflow_id: str |
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719 :param workflow_id: Encoded workflow ID |
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720 |
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721 :rtype: str |
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722 :return: A message about the deletion |
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723 |
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724 .. warning:: |
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725 Deleting a workflow is irreversible - all workflow data |
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726 will be permanently deleted. |
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727 """ |
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728 return self._delete(id=workflow_id) |
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729 |
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730 def _invocation_step_url(self, workflow_id, invocation_id, step_id): |
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731 return '/'.join((self._invocation_url(workflow_id, invocation_id), "steps", step_id)) |
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732 |
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733 def _invocation_url(self, workflow_id, invocation_id): |
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734 return '/'.join((self._invocations_url(workflow_id), invocation_id)) |
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735 |
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736 def _invocations_url(self, workflow_id): |
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737 return '/'.join((self._make_url(workflow_id), 'invocations')) |
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738 |
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739 |
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740 __all__ = ('WorkflowClient',) |