Mercurial > repos > shellac > sam_consensus_v3
annotate env/lib/python3.9/site-packages/cwltool/workflow_job.py @ 0:4f3585e2f14b draft default tip
"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
author | shellac |
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date | Mon, 22 Mar 2021 18:12:50 +0000 |
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1 import copy |
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2 import datetime |
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3 import functools |
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4 import logging |
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5 import threading |
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6 from typing import ( |
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7 Dict, |
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8 List, |
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9 MutableMapping, |
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10 MutableSequence, |
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11 Optional, |
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12 Sized, |
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13 Tuple, |
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14 cast, |
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15 ) |
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16 |
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17 from schema_salad.sourceline import SourceLine |
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18 from schema_salad.utils import json_dumps |
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19 from typing_extensions import TYPE_CHECKING |
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20 |
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21 from . import expression |
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22 from .builder import content_limit_respected_read |
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23 from .checker import can_assign_src_to_sink |
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24 from .context import RuntimeContext, getdefault |
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25 from .errors import WorkflowException |
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26 from .loghandler import _logger |
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27 from .process import shortname, uniquename |
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28 from .stdfsaccess import StdFsAccess |
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29 from .utils import ( |
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30 CWLObjectType, |
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31 CWLOutputType, |
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32 JobsGeneratorType, |
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33 OutputCallbackType, |
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34 ParametersType, |
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35 ScatterDestinationsType, |
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36 ScatterOutputCallbackType, |
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37 SinkType, |
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38 WorkflowStateItem, |
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39 adjustDirObjs, |
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40 aslist, |
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41 get_listing, |
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42 ) |
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43 |
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44 if TYPE_CHECKING: |
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45 from .provenance_profile import ProvenanceProfile |
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46 from .workflow import Workflow, WorkflowStep |
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47 |
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48 |
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49 class WorkflowJobStep: |
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50 """Generated for each step in Workflow.steps().""" |
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51 |
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52 def __init__(self, step: "WorkflowStep") -> None: |
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53 """Initialize this WorkflowJobStep.""" |
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54 self.step = step |
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55 self.tool = step.tool |
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56 self.id = step.id |
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57 self.submitted = False |
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58 self.iterable = None # type: Optional[JobsGeneratorType] |
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59 self.completed = False |
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60 self.name = uniquename("step %s" % shortname(self.id)) |
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61 self.prov_obj = step.prov_obj |
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62 self.parent_wf = step.parent_wf |
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63 |
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64 def job( |
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65 self, |
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66 joborder: CWLObjectType, |
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67 output_callback: Optional[OutputCallbackType], |
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68 runtimeContext: RuntimeContext, |
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69 ) -> JobsGeneratorType: |
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70 runtimeContext = runtimeContext.copy() |
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71 runtimeContext.part_of = self.name |
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72 runtimeContext.name = shortname(self.id) |
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73 |
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74 _logger.info("[%s] start", self.name) |
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75 |
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76 yield from self.step.job(joborder, output_callback, runtimeContext) |
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77 |
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78 |
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79 class ReceiveScatterOutput: |
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80 """Produced by the scatter generators.""" |
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81 |
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82 def __init__( |
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83 self, |
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84 output_callback: ScatterOutputCallbackType, |
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85 dest: ScatterDestinationsType, |
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86 total: int, |
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87 ) -> None: |
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88 """Initialize.""" |
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89 self.dest = dest |
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90 self.completed = 0 |
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91 self.processStatus = "success" |
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92 self.total = total |
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93 self.output_callback = output_callback |
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94 self.steps = [] # type: List[Optional[JobsGeneratorType]] |
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95 |
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96 def receive_scatter_output( |
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97 self, index: int, jobout: CWLObjectType, processStatus: str |
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98 ) -> None: |
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99 for key, val in jobout.items(): |
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100 self.dest[key][index] = val |
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101 |
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102 # Release the iterable related to this step to |
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103 # reclaim memory. |
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104 if self.steps: |
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105 self.steps[index] = None |
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106 |
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107 if processStatus != "success": |
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108 if self.processStatus != "permanentFail": |
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109 self.processStatus = processStatus |
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110 |
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111 self.completed += 1 |
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112 |
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113 if self.completed == self.total: |
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114 self.output_callback(self.dest, self.processStatus) |
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115 |
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116 def setTotal( |
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117 self, |
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118 total: int, |
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119 steps: List[Optional[JobsGeneratorType]], |
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120 ) -> None: |
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121 """ |
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122 Set the total number of expected outputs along with the steps. |
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123 |
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124 This is necessary to finish the setup. |
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125 """ |
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126 self.total = total |
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127 self.steps = steps |
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128 if self.completed == self.total: |
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129 self.output_callback(self.dest, self.processStatus) |
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130 |
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131 |
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132 def parallel_steps( |
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133 steps: List[Optional[JobsGeneratorType]], |
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134 rc: ReceiveScatterOutput, |
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135 runtimeContext: RuntimeContext, |
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136 ) -> JobsGeneratorType: |
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137 while rc.completed < rc.total: |
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138 made_progress = False |
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139 for index, step in enumerate(steps): |
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140 if getdefault( |
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141 runtimeContext.on_error, "stop" |
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142 ) == "stop" and rc.processStatus not in ("success", "skipped"): |
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143 break |
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144 if step is None: |
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145 continue |
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146 try: |
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147 for j in step: |
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148 if getdefault( |
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149 runtimeContext.on_error, "stop" |
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150 ) == "stop" and rc.processStatus not in ("success", "skipped"): |
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151 break |
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152 if j is not None: |
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153 made_progress = True |
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154 yield j |
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155 else: |
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156 break |
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157 if made_progress: |
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158 break |
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159 except WorkflowException as exc: |
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160 _logger.error("Cannot make scatter job: %s", str(exc)) |
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161 _logger.debug("", exc_info=True) |
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162 rc.receive_scatter_output(index, {}, "permanentFail") |
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163 if not made_progress and rc.completed < rc.total: |
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164 yield None |
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165 |
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166 |
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167 def nested_crossproduct_scatter( |
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168 process: WorkflowJobStep, |
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169 joborder: CWLObjectType, |
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170 scatter_keys: MutableSequence[str], |
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171 output_callback: ScatterOutputCallbackType, |
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172 runtimeContext: RuntimeContext, |
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173 ) -> JobsGeneratorType: |
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174 scatter_key = scatter_keys[0] |
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175 jobl = len(cast(Sized, joborder[scatter_key])) |
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176 output = {} # type: ScatterDestinationsType |
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177 for i in process.tool["outputs"]: |
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178 output[i["id"]] = [None] * jobl |
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179 |
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180 rc = ReceiveScatterOutput(output_callback, output, jobl) |
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181 |
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182 steps = [] # type: List[Optional[JobsGeneratorType]] |
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183 for index in range(0, jobl): |
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184 sjob = copy.copy(joborder) # type: Optional[CWLObjectType] |
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185 assert sjob is not None # nosec |
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186 sjob[scatter_key] = cast( |
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187 MutableMapping[int, CWLObjectType], joborder[scatter_key] |
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188 )[index] |
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189 |
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190 if len(scatter_keys) == 1: |
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191 if runtimeContext.postScatterEval is not None: |
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192 sjob = runtimeContext.postScatterEval(sjob) |
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193 curriedcallback = functools.partial(rc.receive_scatter_output, index) |
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194 if sjob is not None: |
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195 steps.append(process.job(sjob, curriedcallback, runtimeContext)) |
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196 else: |
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197 curriedcallback({}, "skipped") |
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198 steps.append(None) |
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199 else: |
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200 steps.append( |
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201 nested_crossproduct_scatter( |
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202 process, |
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203 sjob, |
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204 scatter_keys[1:], |
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205 functools.partial(rc.receive_scatter_output, index), |
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206 runtimeContext, |
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207 ) |
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208 ) |
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209 |
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210 rc.setTotal(jobl, steps) |
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211 return parallel_steps(steps, rc, runtimeContext) |
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212 |
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213 |
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214 def crossproduct_size( |
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215 joborder: CWLObjectType, scatter_keys: MutableSequence[str] |
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216 ) -> int: |
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217 scatter_key = scatter_keys[0] |
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218 if len(scatter_keys) == 1: |
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219 ssum = len(cast(Sized, joborder[scatter_key])) |
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220 else: |
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221 ssum = 0 |
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222 for _ in range(0, len(cast(Sized, joborder[scatter_key]))): |
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223 ssum += crossproduct_size(joborder, scatter_keys[1:]) |
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224 return ssum |
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225 |
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226 |
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227 def flat_crossproduct_scatter( |
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228 process: WorkflowJobStep, |
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229 joborder: CWLObjectType, |
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230 scatter_keys: MutableSequence[str], |
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231 output_callback: ScatterOutputCallbackType, |
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232 runtimeContext: RuntimeContext, |
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233 ) -> JobsGeneratorType: |
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234 output = {} # type: ScatterDestinationsType |
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235 for i in process.tool["outputs"]: |
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236 output[i["id"]] = [None] * crossproduct_size(joborder, scatter_keys) |
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237 callback = ReceiveScatterOutput(output_callback, output, 0) |
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238 (steps, total) = _flat_crossproduct_scatter( |
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239 process, joborder, scatter_keys, callback, 0, runtimeContext |
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240 ) |
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241 callback.setTotal(total, steps) |
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242 return parallel_steps(steps, callback, runtimeContext) |
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243 |
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244 |
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245 def _flat_crossproduct_scatter( |
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246 process: WorkflowJobStep, |
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247 joborder: CWLObjectType, |
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248 scatter_keys: MutableSequence[str], |
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249 callback: ReceiveScatterOutput, |
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250 startindex: int, |
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251 runtimeContext: RuntimeContext, |
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252 ) -> Tuple[List[Optional[JobsGeneratorType]], int,]: |
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253 """Inner loop.""" |
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254 scatter_key = scatter_keys[0] |
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255 jobl = len(cast(Sized, joborder[scatter_key])) |
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256 steps = [] # type: List[Optional[JobsGeneratorType]] |
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257 put = startindex |
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258 for index in range(0, jobl): |
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259 sjob = copy.copy(joborder) # type: Optional[CWLObjectType] |
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260 assert sjob is not None # nosec |
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261 sjob[scatter_key] = cast( |
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262 MutableMapping[int, CWLObjectType], joborder[scatter_key] |
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263 )[index] |
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264 |
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265 if len(scatter_keys) == 1: |
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266 if runtimeContext.postScatterEval is not None: |
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267 sjob = runtimeContext.postScatterEval(sjob) |
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268 curriedcallback = functools.partial(callback.receive_scatter_output, put) |
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269 if sjob is not None: |
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270 steps.append(process.job(sjob, curriedcallback, runtimeContext)) |
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271 else: |
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272 curriedcallback({}, "skipped") |
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273 steps.append(None) |
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274 put += 1 |
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275 else: |
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276 (add, _) = _flat_crossproduct_scatter( |
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277 process, sjob, scatter_keys[1:], callback, put, runtimeContext |
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278 ) |
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279 put += len(add) |
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280 steps.extend(add) |
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281 |
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282 return (steps, put) |
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283 |
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284 |
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285 def dotproduct_scatter( |
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286 process: WorkflowJobStep, |
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287 joborder: CWLObjectType, |
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288 scatter_keys: MutableSequence[str], |
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289 output_callback: ScatterOutputCallbackType, |
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290 runtimeContext: RuntimeContext, |
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291 ) -> JobsGeneratorType: |
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292 jobl = None # type: Optional[int] |
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293 for key in scatter_keys: |
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294 if jobl is None: |
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295 jobl = len(cast(Sized, joborder[key])) |
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296 elif jobl != len(cast(Sized, joborder[key])): |
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297 raise WorkflowException( |
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298 "Length of input arrays must be equal when performing " |
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299 "dotproduct scatter." |
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300 ) |
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301 if jobl is None: |
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302 raise Exception("Impossible codepath") |
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303 |
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304 output = {} # type: ScatterDestinationsType |
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305 for i in process.tool["outputs"]: |
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306 output[i["id"]] = [None] * jobl |
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307 |
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308 rc = ReceiveScatterOutput(output_callback, output, jobl) |
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309 |
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310 steps = [] # type: List[Optional[JobsGeneratorType]] |
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311 for index in range(0, jobl): |
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312 sjobo = copy.copy(joborder) # type: Optional[CWLObjectType] |
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313 assert sjobo is not None # nosec |
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314 for key in scatter_keys: |
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315 sjobo[key] = cast(MutableMapping[int, CWLObjectType], joborder[key])[index] |
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316 |
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317 if runtimeContext.postScatterEval is not None: |
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318 sjobo = runtimeContext.postScatterEval(sjobo) |
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319 curriedcallback = functools.partial(rc.receive_scatter_output, index) |
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320 if sjobo is not None: |
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321 steps.append(process.job(sjobo, curriedcallback, runtimeContext)) |
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322 else: |
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323 curriedcallback({}, "skipped") |
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324 steps.append(None) |
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325 |
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326 rc.setTotal(jobl, steps) |
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327 return parallel_steps(steps, rc, runtimeContext) |
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328 |
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329 |
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330 def match_types( |
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331 sinktype: Optional[SinkType], |
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332 src: WorkflowStateItem, |
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333 iid: str, |
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334 inputobj: CWLObjectType, |
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335 linkMerge: Optional[str], |
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336 valueFrom: Optional[str], |
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337 ) -> bool: |
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338 if isinstance(sinktype, MutableSequence): |
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339 # Sink is union type |
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340 for st in sinktype: |
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341 if match_types(st, src, iid, inputobj, linkMerge, valueFrom): |
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342 return True |
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343 elif isinstance(src.parameter["type"], MutableSequence): |
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344 # Source is union type |
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345 # Check that at least one source type is compatible with the sink. |
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346 original_types = src.parameter["type"] |
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347 for source_type in original_types: |
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348 src.parameter["type"] = source_type |
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349 match = match_types(sinktype, src, iid, inputobj, linkMerge, valueFrom) |
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350 if match: |
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351 src.parameter["type"] = original_types |
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352 return True |
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353 src.parameter["type"] = original_types |
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354 return False |
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355 elif linkMerge: |
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356 if iid not in inputobj: |
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357 inputobj[iid] = [] |
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358 sourceTypes = cast(List[Optional[CWLOutputType]], inputobj[iid]) |
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359 if linkMerge == "merge_nested": |
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360 sourceTypes.append(src.value) |
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361 elif linkMerge == "merge_flattened": |
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362 if isinstance(src.value, MutableSequence): |
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363 sourceTypes.extend(src.value) |
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364 else: |
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365 sourceTypes.append(src.value) |
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366 else: |
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367 raise WorkflowException("Unrecognized linkMerge enum '%s'" % linkMerge) |
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368 return True |
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369 elif ( |
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370 valueFrom is not None |
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371 or can_assign_src_to_sink(cast(SinkType, src.parameter["type"]), sinktype) |
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372 or sinktype == "Any" |
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373 ): |
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374 # simply assign the value from state to input |
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375 inputobj[iid] = copy.deepcopy(src.value) |
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376 return True |
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377 return False |
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378 |
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379 |
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380 def object_from_state( |
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381 state: Dict[str, Optional[WorkflowStateItem]], |
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382 parms: ParametersType, |
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383 frag_only: bool, |
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384 supportsMultipleInput: bool, |
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385 sourceField: str, |
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386 incomplete: bool = False, |
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387 ) -> Optional[CWLObjectType]: |
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388 inputobj = {} # type: CWLObjectType |
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389 for inp in parms: |
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390 iid = original_id = cast(str, inp["id"]) |
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391 if frag_only: |
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392 iid = shortname(iid) |
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393 if sourceField in inp: |
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394 connections = aslist(inp[sourceField]) |
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395 if len(connections) > 1 and not supportsMultipleInput: |
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396 raise WorkflowException( |
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397 "Workflow contains multiple inbound links to a single " |
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398 "parameter but MultipleInputFeatureRequirement is not " |
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399 "declared." |
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400 ) |
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401 for src in connections: |
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402 a_state = state.get(src, None) |
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403 if a_state is not None and ( |
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404 a_state.success in ("success", "skipped") or incomplete |
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405 ): |
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406 if not match_types( |
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407 inp["type"], |
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408 a_state, |
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409 iid, |
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410 inputobj, |
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411 cast( |
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412 Optional[str], |
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413 inp.get( |
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414 "linkMerge", |
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415 ("merge_nested" if len(connections) > 1 else None), |
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416 ), |
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417 ), |
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418 valueFrom=cast(str, inp.get("valueFrom")), |
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419 ): |
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420 raise WorkflowException( |
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421 "Type mismatch between source '%s' (%s) and " |
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422 "sink '%s' (%s)" |
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423 % (src, a_state.parameter["type"], original_id, inp["type"]) |
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424 ) |
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425 elif src not in state: |
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426 raise WorkflowException( |
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427 "Connect source '%s' on parameter '%s' does not " |
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428 "exist" % (src, original_id) |
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429 ) |
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430 elif not incomplete: |
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431 return None |
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432 |
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433 if "pickValue" in inp and isinstance(inputobj.get(iid), MutableSequence): |
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434 seq = cast(MutableSequence[Optional[CWLOutputType]], inputobj.get(iid)) |
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435 if inp["pickValue"] == "first_non_null": |
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436 found = False |
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437 for v in seq: |
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438 if v is not None: |
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439 found = True |
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440 inputobj[iid] = v |
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441 break |
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442 if not found: |
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443 raise WorkflowException( |
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444 "All sources for '%s' are null" % (shortname(original_id)) |
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445 ) |
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446 elif inp["pickValue"] == "the_only_non_null": |
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447 found = False |
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448 for v in seq: |
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449 if v is not None: |
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450 if found: |
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451 raise WorkflowException( |
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452 "Expected only one source for '%s' to be non-null, got %s" |
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453 % (shortname(original_id), seq) |
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454 ) |
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455 found = True |
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456 inputobj[iid] = v |
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457 if not found: |
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458 raise WorkflowException( |
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459 "All sources for '%s' are null" % (shortname(original_id)) |
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460 ) |
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461 elif inp["pickValue"] == "all_non_null": |
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462 inputobj[iid] = [v for v in seq if v is not None] |
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463 |
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464 if inputobj.get(iid) is None and "default" in inp: |
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465 inputobj[iid] = inp["default"] |
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466 |
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467 if iid not in inputobj and ("valueFrom" in inp or incomplete): |
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468 inputobj[iid] = None |
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469 |
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470 if iid not in inputobj: |
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471 raise WorkflowException("Value for %s not specified" % original_id) |
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472 return inputobj |
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473 |
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474 |
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475 class WorkflowJob: |
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476 """Generates steps from the Workflow.""" |
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477 |
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478 def __init__(self, workflow: "Workflow", runtimeContext: RuntimeContext) -> None: |
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479 """Initialize this WorkflowJob.""" |
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480 self.workflow = workflow |
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481 self.prov_obj = None # type: Optional[ProvenanceProfile] |
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482 self.parent_wf = None # type: Optional[ProvenanceProfile] |
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483 self.tool = workflow.tool |
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484 if runtimeContext.research_obj is not None: |
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485 self.prov_obj = workflow.provenance_object |
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486 self.parent_wf = workflow.parent_wf |
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487 self.steps = [WorkflowJobStep(s) for s in workflow.steps] |
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488 self.state = {} # type: Dict[str, Optional[WorkflowStateItem]] |
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489 self.processStatus = "" |
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490 self.did_callback = False |
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491 self.made_progress = None # type: Optional[bool] |
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492 self.outdir = runtimeContext.get_outdir() |
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493 |
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494 self.name = uniquename( |
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495 "workflow {}".format( |
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496 getdefault( |
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497 runtimeContext.name, |
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498 shortname(self.workflow.tool.get("id", "embedded")), |
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499 ) |
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500 ) |
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501 ) |
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502 |
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503 _logger.debug( |
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504 "[%s] initialized from %s", |
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505 self.name, |
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506 self.tool.get("id", "workflow embedded in %s" % runtimeContext.part_of), |
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507 ) |
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508 |
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509 def do_output_callback(self, final_output_callback: OutputCallbackType) -> None: |
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510 |
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511 supportsMultipleInput = bool( |
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512 self.workflow.get_requirement("MultipleInputFeatureRequirement")[0] |
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513 ) |
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514 |
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515 wo = None # type: Optional[CWLObjectType] |
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516 try: |
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517 wo = object_from_state( |
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518 self.state, |
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519 self.tool["outputs"], |
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520 True, |
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521 supportsMultipleInput, |
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522 "outputSource", |
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523 incomplete=True, |
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524 ) |
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525 except WorkflowException as err: |
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526 _logger.error( |
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527 "[%s] Cannot collect workflow output: %s", self.name, str(err) |
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528 ) |
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529 self.processStatus = "permanentFail" |
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530 if ( |
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531 self.prov_obj |
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532 and self.parent_wf |
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533 and self.prov_obj.workflow_run_uri != self.parent_wf.workflow_run_uri |
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534 ): |
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535 process_run_id = None # type: Optional[str] |
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536 self.prov_obj.generate_output_prov(wo or {}, process_run_id, self.name) |
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537 self.prov_obj.document.wasEndedBy( |
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538 self.prov_obj.workflow_run_uri, |
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539 None, |
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540 self.prov_obj.engine_uuid, |
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541 datetime.datetime.now(), |
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542 ) |
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543 prov_ids = self.prov_obj.finalize_prov_profile(self.name) |
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544 # Tell parent to associate our provenance files with our wf run |
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545 self.parent_wf.activity_has_provenance( |
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546 self.prov_obj.workflow_run_uri, prov_ids |
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547 ) |
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548 |
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549 _logger.info("[%s] completed %s", self.name, self.processStatus) |
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550 if _logger.isEnabledFor(logging.DEBUG): |
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551 _logger.debug("[%s] outputs %s", self.name, json_dumps(wo, indent=4)) |
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552 |
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553 self.did_callback = True |
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554 |
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555 final_output_callback(wo, self.processStatus) |
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556 |
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557 def receive_output( |
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558 self, |
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559 step: WorkflowJobStep, |
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560 outputparms: List[CWLObjectType], |
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561 final_output_callback: OutputCallbackType, |
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562 jobout: CWLObjectType, |
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563 processStatus: str, |
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564 ) -> None: |
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565 |
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566 for i in outputparms: |
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567 if "id" in i: |
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568 iid = cast(str, i["id"]) |
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569 if iid in jobout: |
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570 self.state[iid] = WorkflowStateItem(i, jobout[iid], processStatus) |
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571 else: |
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572 _logger.error( |
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573 "[%s] Output is missing expected field %s", step.name, iid |
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574 ) |
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575 processStatus = "permanentFail" |
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576 if _logger.isEnabledFor(logging.DEBUG): |
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577 _logger.debug( |
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578 "[%s] produced output %s", step.name, json_dumps(jobout, indent=4) |
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579 ) |
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580 |
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581 if processStatus not in ("success", "skipped"): |
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582 if self.processStatus != "permanentFail": |
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583 self.processStatus = processStatus |
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584 |
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585 _logger.warning("[%s] completed %s", step.name, processStatus) |
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586 else: |
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587 _logger.info("[%s] completed %s", step.name, processStatus) |
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588 |
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589 step.completed = True |
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590 # Release the iterable related to this step to |
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591 # reclaim memory. |
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592 step.iterable = None |
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593 self.made_progress = True |
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594 |
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595 completed = sum(1 for s in self.steps if s.completed) |
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596 if completed == len(self.steps): |
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597 self.do_output_callback(final_output_callback) |
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598 |
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599 def try_make_job( |
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600 self, |
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601 step: WorkflowJobStep, |
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602 final_output_callback: Optional[OutputCallbackType], |
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603 runtimeContext: RuntimeContext, |
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604 ) -> JobsGeneratorType: |
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605 |
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606 if step.submitted: |
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607 return |
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608 |
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609 inputparms = step.tool["inputs"] |
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610 outputparms = step.tool["outputs"] |
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611 |
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612 supportsMultipleInput = bool( |
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613 self.workflow.get_requirement("MultipleInputFeatureRequirement")[0] |
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614 ) |
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615 |
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616 try: |
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617 inputobj = object_from_state( |
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618 self.state, inputparms, False, supportsMultipleInput, "source" |
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619 ) |
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620 if inputobj is None: |
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621 _logger.debug("[%s] job step %s not ready", self.name, step.id) |
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622 return |
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623 |
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624 if step.submitted: |
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625 return |
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626 _logger.info("[%s] starting %s", self.name, step.name) |
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627 |
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628 callback = functools.partial( |
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629 self.receive_output, step, outputparms, final_output_callback |
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630 ) |
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631 |
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632 valueFrom = { |
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633 i["id"]: i["valueFrom"] for i in step.tool["inputs"] if "valueFrom" in i |
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634 } |
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635 |
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636 loadContents = { |
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637 i["id"] for i in step.tool["inputs"] if i.get("loadContents") |
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638 } |
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639 |
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640 if len(valueFrom) > 0 and not bool( |
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641 self.workflow.get_requirement("StepInputExpressionRequirement")[0] |
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642 ): |
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643 raise WorkflowException( |
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644 "Workflow step contains valueFrom but StepInputExpressionRequirement not in requirements" |
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645 ) |
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646 |
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647 vfinputs = {shortname(k): v for k, v in inputobj.items()} |
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648 |
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649 def postScatterEval(io: CWLObjectType) -> Optional[CWLObjectType]: |
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650 shortio = cast(CWLObjectType, {shortname(k): v for k, v in io.items()}) |
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651 |
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652 fs_access = getdefault(runtimeContext.make_fs_access, StdFsAccess)("") |
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653 for k, v in io.items(): |
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654 if k in loadContents: |
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655 val = cast(CWLObjectType, v) |
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656 if val.get("contents") is None: |
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657 with fs_access.open(cast(str, val["location"]), "rb") as f: |
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658 val["contents"] = content_limit_respected_read(f) |
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659 |
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660 def valueFromFunc( |
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661 k: str, v: Optional[CWLOutputType] |
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662 ) -> Optional[CWLOutputType]: |
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663 if k in valueFrom: |
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664 adjustDirObjs( |
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665 v, functools.partial(get_listing, fs_access, recursive=True) |
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666 ) |
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667 return expression.do_eval( |
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668 valueFrom[k], |
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669 shortio, |
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670 self.workflow.requirements, |
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671 None, |
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672 None, |
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673 {}, |
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674 context=v, |
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675 debug=runtimeContext.debug, |
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676 js_console=runtimeContext.js_console, |
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677 timeout=runtimeContext.eval_timeout, |
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678 ) |
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679 return v |
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680 |
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681 psio = {k: valueFromFunc(k, v) for k, v in io.items()} |
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682 if "when" in step.tool: |
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683 evalinputs = {shortname(k): v for k, v in psio.items()} |
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684 whenval = expression.do_eval( |
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685 step.tool["when"], |
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686 evalinputs, |
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687 self.workflow.requirements, |
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688 None, |
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689 None, |
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690 {}, |
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691 context=cast(Optional[CWLObjectType], v), |
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692 debug=runtimeContext.debug, |
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693 js_console=runtimeContext.js_console, |
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694 timeout=runtimeContext.eval_timeout, |
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695 ) |
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696 if whenval is True: |
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697 pass |
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698 elif whenval is False: |
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699 _logger.debug( |
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700 "[%s] conditional %s evaluated to %s", |
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701 step.name, |
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702 step.tool["when"], |
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703 whenval, |
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704 ) |
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705 _logger.debug( |
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706 "[%s] inputs was %s", |
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707 step.name, |
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708 json_dumps(evalinputs, indent=2), |
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709 ) |
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710 return None |
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711 else: |
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712 raise WorkflowException( |
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713 "Conditional 'when' must evaluate to 'true' or 'false'" |
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714 ) |
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715 return psio |
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716 |
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717 if "scatter" in step.tool: |
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718 scatter = cast(List[str], aslist(step.tool["scatter"])) |
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719 method = step.tool.get("scatterMethod") |
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720 if method is None and len(scatter) != 1: |
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721 raise WorkflowException( |
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722 "Must specify scatterMethod when scattering over multiple inputs" |
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723 ) |
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724 runtimeContext = runtimeContext.copy() |
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725 runtimeContext.postScatterEval = postScatterEval |
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726 |
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727 emptyscatter = [ |
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728 shortname(s) for s in scatter if len(cast(Sized, inputobj[s])) == 0 |
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729 ] |
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730 if emptyscatter: |
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731 _logger.warning( |
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732 "[job %s] Notice: scattering over empty input in " |
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733 "'%s'. All outputs will be empty.", |
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734 step.name, |
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735 "', '".join(emptyscatter), |
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736 ) |
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737 |
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738 if method == "dotproduct" or method is None: |
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739 jobs = dotproduct_scatter( |
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740 step, inputobj, scatter, callback, runtimeContext |
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741 ) |
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742 elif method == "nested_crossproduct": |
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743 jobs = nested_crossproduct_scatter( |
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744 step, inputobj, scatter, callback, runtimeContext |
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745 ) |
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746 elif method == "flat_crossproduct": |
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747 jobs = flat_crossproduct_scatter( |
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748 step, inputobj, scatter, callback, runtimeContext |
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749 ) |
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750 else: |
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751 if _logger.isEnabledFor(logging.DEBUG): |
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752 _logger.debug( |
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753 "[%s] job input %s", step.name, json_dumps(inputobj, indent=4) |
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754 ) |
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755 |
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756 inputobj = postScatterEval(inputobj) |
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757 if inputobj is not None: |
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758 if _logger.isEnabledFor(logging.DEBUG): |
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759 _logger.debug( |
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760 "[%s] evaluated job input to %s", |
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761 step.name, |
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762 json_dumps(inputobj, indent=4), |
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763 ) |
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764 jobs = step.job(inputobj, callback, runtimeContext) |
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765 else: |
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766 _logger.info("[%s] will be skipped", step.name) |
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767 callback({k["id"]: None for k in outputparms}, "skipped") |
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768 step.completed = True |
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769 jobs = (_ for _ in ()) |
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770 |
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771 step.submitted = True |
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772 |
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773 yield from jobs |
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774 except WorkflowException: |
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775 raise |
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776 except Exception: |
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777 _logger.exception("Unhandled exception") |
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778 self.processStatus = "permanentFail" |
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779 step.completed = True |
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780 |
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781 def run( |
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782 self, |
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783 runtimeContext: RuntimeContext, |
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784 tmpdir_lock: Optional[threading.Lock] = None, |
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785 ) -> None: |
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786 """Log the start of each workflow.""" |
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787 _logger.info("[%s] start", self.name) |
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788 |
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789 def job( |
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790 self, |
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791 joborder: CWLObjectType, |
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792 output_callback: Optional[OutputCallbackType], |
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793 runtimeContext: RuntimeContext, |
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794 ) -> JobsGeneratorType: |
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795 self.state = {} |
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796 self.processStatus = "success" |
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797 |
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798 if _logger.isEnabledFor(logging.DEBUG): |
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799 _logger.debug("[%s] inputs %s", self.name, json_dumps(joborder, indent=4)) |
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800 |
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801 runtimeContext = runtimeContext.copy() |
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802 runtimeContext.outdir = None |
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803 |
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804 for index, inp in enumerate(self.tool["inputs"]): |
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805 with SourceLine( |
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806 self.tool["inputs"], |
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807 index, |
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808 WorkflowException, |
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809 _logger.isEnabledFor(logging.DEBUG), |
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810 ): |
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811 inp_id = shortname(inp["id"]) |
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812 if inp_id in joborder: |
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813 self.state[inp["id"]] = WorkflowStateItem( |
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814 inp, joborder[inp_id], "success" |
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815 ) |
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816 elif "default" in inp: |
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817 self.state[inp["id"]] = WorkflowStateItem( |
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818 inp, inp["default"], "success" |
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819 ) |
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820 else: |
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821 raise WorkflowException( |
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822 "Input '%s' not in input object and does not have a " |
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823 " default value." % (inp["id"]) |
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824 ) |
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825 |
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826 for step in self.steps: |
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827 for out in step.tool["outputs"]: |
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828 self.state[out["id"]] = None |
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829 |
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830 completed = 0 |
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831 while completed < len(self.steps): |
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832 self.made_progress = False |
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833 |
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834 for step in self.steps: |
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835 if ( |
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836 getdefault(runtimeContext.on_error, "stop") == "stop" |
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837 and self.processStatus != "success" |
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838 ): |
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839 break |
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840 |
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841 if not step.submitted: |
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842 try: |
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843 step.iterable = self.try_make_job( |
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844 step, output_callback, runtimeContext |
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845 ) |
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846 except WorkflowException as exc: |
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847 _logger.error("[%s] Cannot make job: %s", step.name, str(exc)) |
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848 _logger.debug("", exc_info=True) |
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849 self.processStatus = "permanentFail" |
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850 |
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851 if step.iterable is not None: |
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852 try: |
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853 for newjob in step.iterable: |
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854 if ( |
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855 getdefault(runtimeContext.on_error, "stop") == "stop" |
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856 and self.processStatus != "success" |
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857 ): |
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858 break |
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859 if newjob is not None: |
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860 self.made_progress = True |
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861 yield newjob |
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862 else: |
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863 break |
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864 except WorkflowException as exc: |
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865 _logger.error("[%s] Cannot make job: %s", step.name, str(exc)) |
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866 _logger.debug("", exc_info=True) |
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867 self.processStatus = "permanentFail" |
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868 |
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869 completed = sum(1 for s in self.steps if s.completed) |
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870 |
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871 if not self.made_progress and completed < len(self.steps): |
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872 if self.processStatus != "success": |
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873 break |
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874 else: |
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875 yield None |
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876 |
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877 if not self.did_callback and output_callback: |
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878 # could have called earlier on line 336; |
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879 self.do_output_callback(output_callback) |
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880 # depends which one comes first. All steps are completed |
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881 # or all outputs have been produced. |