Mercurial > repos > shellac > guppy_basecaller
annotate env/lib/python3.7/site-packages/cwltool/workflow.py @ 2:6af9afd405e9 draft
"planemo upload commit 0a63dd5f4d38a1f6944587f52a8cd79874177fc1"
author | shellac |
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date | Thu, 14 May 2020 14:56:58 -0400 |
parents | 26e78fe6e8c4 |
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1 from __future__ import absolute_import |
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2 |
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3 import copy |
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4 import datetime |
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5 import functools |
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6 import logging |
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7 import random |
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8 import tempfile |
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9 from collections import namedtuple |
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10 from typing import (Any, Callable, Dict, Generator, Iterable, List, |
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11 Mapping, MutableMapping, MutableSequence, |
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12 Optional, Sequence, Tuple, Union, cast) |
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13 from uuid import UUID # pylint: disable=unused-import |
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14 |
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15 import threading |
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16 from ruamel.yaml.comments import CommentedMap |
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17 from schema_salad import validate |
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18 from schema_salad.sourceline import SourceLine, indent |
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19 from six import string_types, iteritems |
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20 from six.moves import range |
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21 from future.utils import raise_from |
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22 from typing_extensions import Text # pylint: disable=unused-import |
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23 # move to a regular typing import when Python 3.3-3.6 is no longer supported |
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24 |
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25 from . import command_line_tool, context, expression, procgenerator |
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26 from .command_line_tool import CallbackJob, ExpressionTool |
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27 from .job import JobBase |
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28 from .builder import content_limit_respected_read |
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29 from .checker import can_assign_src_to_sink, static_checker |
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30 from .context import LoadingContext # pylint: disable=unused-import |
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31 from .context import RuntimeContext, getdefault |
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32 from .errors import WorkflowException |
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33 from .load_tool import load_tool |
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34 from .loghandler import _logger |
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35 from .mutation import MutationManager # pylint: disable=unused-import |
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36 from .pathmapper import adjustDirObjs, get_listing |
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37 from .process import Process, get_overrides, shortname, uniquename |
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38 from .provenance import ProvenanceProfile |
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39 from .software_requirements import ( # pylint: disable=unused-import |
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40 DependenciesConfiguration) |
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41 from .stdfsaccess import StdFsAccess |
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42 from .utils import DEFAULT_TMP_PREFIX, aslist, json_dumps |
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43 |
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44 WorkflowStateItem = namedtuple('WorkflowStateItem', ['parameter', 'value', 'success']) |
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45 |
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46 |
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47 def default_make_tool(toolpath_object, # type: MutableMapping[Text, Any] |
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48 loadingContext # type: LoadingContext |
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49 ): # type: (...) -> Process |
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50 if not isinstance(toolpath_object, MutableMapping): |
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51 raise WorkflowException(u"Not a dict: '%s'" % toolpath_object) |
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52 if "class" in toolpath_object: |
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53 if toolpath_object["class"] == "CommandLineTool": |
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54 return command_line_tool.CommandLineTool(toolpath_object, loadingContext) |
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55 if toolpath_object["class"] == "ExpressionTool": |
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56 return command_line_tool.ExpressionTool(toolpath_object, loadingContext) |
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57 if toolpath_object["class"] == "Workflow": |
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58 return Workflow(toolpath_object, loadingContext) |
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59 if toolpath_object["class"] == "ProcessGenerator": |
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60 return procgenerator.ProcessGenerator(toolpath_object, loadingContext) |
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61 |
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62 raise WorkflowException( |
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63 u"Missing or invalid 'class' field in " |
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64 "%s, expecting one of: CommandLineTool, ExpressionTool, Workflow" % |
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65 toolpath_object["id"]) |
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66 |
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67 |
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68 context.default_make_tool = default_make_tool |
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69 |
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70 def findfiles(wo, fn=None): # type: (Any, Optional[List[MutableMapping[Text, Any]]]) -> List[MutableMapping[Text, Any]] |
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71 if fn is None: |
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72 fn = [] |
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73 if isinstance(wo, MutableMapping): |
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74 if wo.get("class") == "File": |
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75 fn.append(wo) |
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76 findfiles(wo.get("secondaryFiles", None), fn) |
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77 else: |
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78 for w in wo.values(): |
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79 findfiles(w, fn) |
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80 elif isinstance(wo, MutableSequence): |
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81 for w in wo: |
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82 findfiles(w, fn) |
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83 return fn |
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84 |
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85 |
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86 def match_types(sinktype, # type: Union[List[Text], Text] |
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87 src, # type: WorkflowStateItem |
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88 iid, # type: Text |
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89 inputobj, # type: Dict[Text, Any] |
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90 linkMerge, # type: Text |
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91 valueFrom # type: Optional[Text] |
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92 ): # type: (...) -> bool |
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93 if isinstance(sinktype, MutableSequence): |
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94 # Sink is union type |
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95 for st in sinktype: |
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96 if match_types(st, src, iid, inputobj, linkMerge, valueFrom): |
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97 return True |
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98 elif isinstance(src.parameter["type"], MutableSequence): |
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99 # Source is union type |
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100 # Check that at least one source type is compatible with the sink. |
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101 original_types = src.parameter["type"] |
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102 for source_type in original_types: |
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103 src.parameter["type"] = source_type |
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104 match = match_types( |
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105 sinktype, src, iid, inputobj, linkMerge, valueFrom) |
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106 if match: |
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107 src.parameter["type"] = original_types |
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108 return True |
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109 src.parameter["type"] = original_types |
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110 return False |
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111 elif linkMerge: |
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112 if iid not in inputobj: |
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113 inputobj[iid] = [] |
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114 if linkMerge == "merge_nested": |
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115 inputobj[iid].append(src.value) |
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116 elif linkMerge == "merge_flattened": |
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117 if isinstance(src.value, MutableSequence): |
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118 inputobj[iid].extend(src.value) |
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119 else: |
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120 inputobj[iid].append(src.value) |
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121 else: |
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122 raise WorkflowException(u"Unrecognized linkMerge enum '%s'" % linkMerge) |
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123 return True |
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124 elif valueFrom is not None \ |
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125 or can_assign_src_to_sink(src.parameter["type"], sinktype) \ |
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126 or sinktype == "Any": |
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127 # simply assign the value from state to input |
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128 inputobj[iid] = copy.deepcopy(src.value) |
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129 return True |
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130 return False |
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131 |
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132 |
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133 def object_from_state(state, # type: Dict[Text, Optional[WorkflowStateItem]] |
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134 parms, # type: List[Dict[Text, Any]] |
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135 frag_only, # type: bool |
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136 supportsMultipleInput, # type: bool |
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137 sourceField, # type: Text |
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138 incomplete=False # type: bool |
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139 ): # type: (...) -> Optional[Dict[Text, Any]] |
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140 inputobj = {} # type: Dict[Text, Any] |
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141 for inp in parms: |
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142 iid = inp["id"] |
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143 if frag_only: |
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144 iid = shortname(iid) |
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145 if sourceField in inp: |
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146 connections = aslist(inp[sourceField]) |
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147 if (len(connections) > 1 and |
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148 not supportsMultipleInput): |
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149 raise WorkflowException( |
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150 "Workflow contains multiple inbound links to a single " |
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151 "parameter but MultipleInputFeatureRequirement is not " |
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152 "declared.") |
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153 for src in connections: |
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154 a_state = state.get(src, None) |
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155 if a_state is not None and (a_state.success == "success" or incomplete): |
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156 if not match_types( |
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157 inp["type"], a_state, iid, inputobj, |
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158 inp.get("linkMerge", ("merge_nested" |
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159 if len(connections) > 1 else None)), |
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160 valueFrom=inp.get("valueFrom")): |
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161 raise WorkflowException( |
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162 u"Type mismatch between source '%s' (%s) and " |
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163 "sink '%s' (%s)" % (src, |
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164 a_state.parameter["type"], inp["id"], |
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165 inp["type"])) |
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166 elif src not in state: |
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167 raise WorkflowException( |
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168 u"Connect source '%s' on parameter '%s' does not " |
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169 "exist" % (src, inp["id"])) |
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170 elif not incomplete: |
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171 return None |
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172 |
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173 if inputobj.get(iid) is None and "default" in inp: |
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174 inputobj[iid] = inp["default"] |
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175 |
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176 if iid not in inputobj and ("valueFrom" in inp or incomplete): |
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177 inputobj[iid] = None |
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178 |
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179 if iid not in inputobj: |
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180 raise WorkflowException(u"Value for %s not specified" % (inp["id"])) |
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181 return inputobj |
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182 |
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183 |
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184 class WorkflowJobStep(object): |
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185 def __init__(self, step): |
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186 # type: (WorkflowStep) -> None |
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187 """Initialize this WorkflowJobStep.""" |
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188 self.step = step |
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189 self.tool = step.tool |
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190 self.id = step.id |
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191 self.submitted = False |
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192 self.completed = False |
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193 self.iterable = None # type: Optional[Generator[Union[ExpressionTool.ExpressionJob, JobBase, CallbackJob, None], None, None]] |
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194 self.name = uniquename(u"step %s" % shortname(self.id)) |
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195 self.prov_obj = step.prov_obj |
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196 self.parent_wf = step.parent_wf |
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197 |
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198 def job(self, |
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199 joborder, # type: Mapping[Text, Text] |
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200 output_callback, # type: functools.partial[None] |
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201 runtimeContext # type: RuntimeContext |
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202 ): |
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203 # type: (...) -> Generator[Union[ExpressionTool.ExpressionJob, JobBase, CallbackJob], None, None] |
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204 runtimeContext = runtimeContext.copy() |
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205 runtimeContext.part_of = self.name |
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206 runtimeContext.name = shortname(self.id) |
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207 |
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208 _logger.info(u"[%s] start", self.name) |
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209 |
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210 for j in self.step.job(joborder, output_callback, runtimeContext): |
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211 yield j |
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212 |
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213 class WorkflowJob(object): |
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214 def __init__(self, workflow, runtimeContext): |
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215 # type: (Workflow, RuntimeContext) -> None |
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216 """Initialize this WorkflowJob.""" |
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217 self.workflow = workflow |
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218 self.prov_obj = None # type: Optional[ProvenanceProfile] |
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219 self.parent_wf = None # type: Optional[ProvenanceProfile] |
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220 self.tool = workflow.tool |
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221 if runtimeContext.research_obj is not None: |
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222 self.prov_obj = workflow.provenance_object |
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223 self.parent_wf = workflow.parent_wf |
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224 self.steps = [WorkflowJobStep(s) for s in workflow.steps] |
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225 self.state = {} # type: Dict[Text, Optional[WorkflowStateItem]] |
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226 self.processStatus = u"" |
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227 self.did_callback = False |
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228 self.made_progress = None # type: Optional[bool] |
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229 |
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230 if runtimeContext.outdir is not None: |
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231 self.outdir = runtimeContext.outdir |
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232 else: |
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233 self.outdir = tempfile.mkdtemp( |
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234 prefix=getdefault(runtimeContext.tmp_outdir_prefix, DEFAULT_TMP_PREFIX)) |
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235 |
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236 self.name = uniquename(u"workflow {}".format( |
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237 getdefault(runtimeContext.name, |
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238 shortname(self.workflow.tool.get("id", "embedded"))))) |
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239 |
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240 _logger.debug( |
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241 u"[%s] initialized from %s", self.name, |
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242 self.tool.get("id", "workflow embedded in %s" % runtimeContext.part_of)) |
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243 |
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244 def do_output_callback(self, final_output_callback): |
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245 # type: (Callable[[Any, Any], Any]) -> None |
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246 |
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247 supportsMultipleInput = bool(self.workflow.get_requirement("MultipleInputFeatureRequirement")[0]) |
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248 |
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249 wo = None # type: Optional[Dict[Text, Text]] |
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250 try: |
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251 wo = object_from_state( |
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252 self.state, self.tool["outputs"], True, supportsMultipleInput, |
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253 "outputSource", incomplete=True) |
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254 except WorkflowException as err: |
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255 _logger.error( |
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256 u"[%s] Cannot collect workflow output: %s", self.name, Text(err)) |
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257 self.processStatus = "permanentFail" |
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258 if self.prov_obj and self.parent_wf \ |
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259 and self.prov_obj.workflow_run_uri != self.parent_wf.workflow_run_uri: |
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260 process_run_id = None |
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261 self.prov_obj.generate_output_prov(wo or {}, process_run_id, self.name) |
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262 self.prov_obj.document.wasEndedBy( |
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263 self.prov_obj.workflow_run_uri, None, self.prov_obj.engine_uuid, |
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264 datetime.datetime.now()) |
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265 prov_ids = self.prov_obj.finalize_prov_profile(self.name) |
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266 # Tell parent to associate our provenance files with our wf run |
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267 self.parent_wf.activity_has_provenance(self.prov_obj.workflow_run_uri, prov_ids) |
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268 |
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269 _logger.info(u"[%s] completed %s", self.name, self.processStatus) |
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270 if _logger.isEnabledFor(logging.DEBUG): |
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271 _logger.debug(u"[%s] %s", self.name, json_dumps(wo, indent=4)) |
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272 |
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273 self.did_callback = True |
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274 |
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275 final_output_callback(wo, self.processStatus) |
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276 |
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277 def receive_output(self, step, outputparms, final_output_callback, jobout, processStatus): |
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278 # type: (WorkflowJobStep, List[Dict[Text,Text]], Callable[[Any, Any], Any], Dict[Text,Text], Text) -> None |
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279 |
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280 for i in outputparms: |
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281 if "id" in i: |
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282 if i["id"] in jobout: |
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283 self.state[i["id"]] = WorkflowStateItem(i, jobout[i["id"]], processStatus) |
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284 else: |
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285 _logger.error(u"[%s] Output is missing expected field %s", step.name, i["id"]) |
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286 processStatus = "permanentFail" |
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287 if _logger.isEnabledFor(logging.DEBUG): |
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288 _logger.debug(u"[%s] produced output %s", step.name, |
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289 json_dumps(jobout, indent=4)) |
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290 |
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291 if processStatus != "success": |
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292 if self.processStatus != "permanentFail": |
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293 self.processStatus = processStatus |
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294 |
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295 _logger.warning(u"[%s] completed %s", step.name, processStatus) |
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296 else: |
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297 _logger.info(u"[%s] completed %s", step.name, processStatus) |
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298 |
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299 step.completed = True |
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300 # Release the iterable related to this step to |
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301 # reclaim memory. |
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302 step.iterable = None |
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303 self.made_progress = True |
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304 |
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305 completed = sum(1 for s in self.steps if s.completed) |
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306 if completed == len(self.steps): |
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307 self.do_output_callback(final_output_callback) |
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308 |
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309 def try_make_job(self, |
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310 step, # type: WorkflowJobStep |
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311 final_output_callback, # type: Callable[[Any, Any], Any] |
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312 runtimeContext # type: RuntimeContext |
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313 ): # type: (...) -> Generator[Union[ExpressionTool.ExpressionJob, JobBase, CallbackJob, None], None, None] |
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314 |
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315 inputparms = step.tool["inputs"] |
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316 outputparms = step.tool["outputs"] |
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317 |
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318 supportsMultipleInput = bool(self.workflow.get_requirement( |
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319 "MultipleInputFeatureRequirement")[0]) |
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320 |
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321 try: |
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322 inputobj = object_from_state( |
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323 self.state, inputparms, False, supportsMultipleInput, "source") |
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324 if inputobj is None: |
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325 _logger.debug(u"[%s] job step %s not ready", self.name, step.id) |
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326 return |
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327 |
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328 if step.submitted: |
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329 return |
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330 _logger.info(u"[%s] starting %s", self.name, step.name) |
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331 |
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332 callback = functools.partial(self.receive_output, step, outputparms, final_output_callback) |
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333 |
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334 |
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335 valueFrom = { |
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336 i["id"]: i["valueFrom"] for i in step.tool["inputs"] |
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337 if "valueFrom" in i} |
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338 |
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339 loadContents = set(i["id"] for i in step.tool["inputs"] |
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340 if i.get("loadContents")) |
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341 |
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342 if len(valueFrom) > 0 and not bool(self.workflow.get_requirement("StepInputExpressionRequirement")[0]): |
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343 raise WorkflowException( |
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344 "Workflow step contains valueFrom but StepInputExpressionRequirement not in requirements") |
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345 |
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346 vfinputs = {shortname(k): v for k, v in iteritems(inputobj)} |
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347 |
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348 def postScatterEval(io): |
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349 # type: (MutableMapping[Text, Any]) -> Dict[Text, Any] |
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350 shortio = {shortname(k): v for k, v in iteritems(io)} |
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351 |
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352 fs_access = getdefault(runtimeContext.make_fs_access, StdFsAccess)("") |
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353 for k, v in io.items(): |
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354 if k in loadContents and v.get("contents") is None: |
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355 with fs_access.open(v["location"], "rb") as f: |
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356 v["contents"] = content_limit_respected_read(f) |
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357 |
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358 def valueFromFunc(k, v): # type: (Any, Any) -> Any |
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359 if k in valueFrom: |
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360 adjustDirObjs(v, functools.partial(get_listing, |
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361 fs_access, recursive=True)) |
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362 return expression.do_eval( |
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363 valueFrom[k], shortio, self.workflow.requirements, |
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364 None, None, {}, context=v, |
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365 debug=runtimeContext.debug, |
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366 js_console=runtimeContext.js_console, |
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367 timeout=runtimeContext.eval_timeout) |
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368 return v |
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369 |
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370 return {k: valueFromFunc(k, v) for k, v in io.items()} |
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371 |
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372 if "scatter" in step.tool: |
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373 scatter = aslist(step.tool["scatter"]) |
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374 method = step.tool.get("scatterMethod") |
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375 if method is None and len(scatter) != 1: |
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376 raise WorkflowException("Must specify scatterMethod when scattering over multiple inputs") |
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377 runtimeContext = runtimeContext.copy() |
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378 runtimeContext.postScatterEval = postScatterEval |
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379 |
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380 emptyscatter = [shortname(s) for s in scatter if len(inputobj[s]) == 0] |
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381 if emptyscatter: |
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382 _logger.warning( |
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383 "[job %s] Notice: scattering over empty input in " |
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384 "'%s'. All outputs will be empty.", step.name, |
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385 "', '".join(emptyscatter)) |
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386 |
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387 if method == "dotproduct" or method is None: |
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388 jobs = dotproduct_scatter( |
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389 step, inputobj, scatter, callback, runtimeContext) |
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390 elif method == "nested_crossproduct": |
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391 jobs = nested_crossproduct_scatter( |
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392 step, inputobj, scatter, callback, runtimeContext) |
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393 elif method == "flat_crossproduct": |
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394 jobs = flat_crossproduct_scatter( |
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395 step, inputobj, scatter, callback, runtimeContext) |
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396 else: |
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397 if _logger.isEnabledFor(logging.DEBUG): |
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398 _logger.debug(u"[job %s] job input %s", step.name, |
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399 json_dumps(inputobj, indent=4)) |
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400 |
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401 inputobj = postScatterEval(inputobj) |
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402 |
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403 if _logger.isEnabledFor(logging.DEBUG): |
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404 _logger.debug(u"[job %s] evaluated job input to %s", |
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405 step.name, json_dumps(inputobj, indent=4)) |
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406 jobs = step.job(inputobj, callback, runtimeContext) |
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407 |
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408 step.submitted = True |
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409 |
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410 for j in jobs: |
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411 yield j |
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412 except WorkflowException: |
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413 raise |
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414 except Exception: |
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415 _logger.exception("Unhandled exception") |
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416 self.processStatus = "permanentFail" |
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417 step.completed = True |
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418 |
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419 |
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420 def run(self, |
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421 runtimeContext, # type: RuntimeContext |
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422 tmpdir_lock=None # type: Optional[threading.Lock] |
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423 ): # type: (...) -> None |
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424 """Log the start of each workflow.""" |
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425 _logger.info(u"[%s] start", self.name) |
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426 |
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427 def job(self, |
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428 joborder, # type: Mapping[Text, Any] |
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429 output_callback, # type: Callable[[Any, Any], Any] |
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430 runtimeContext # type: RuntimeContext |
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431 ): # type: (...) -> Generator[Union[ExpressionTool.ExpressionJob, JobBase, CallbackJob, None], None, None] |
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432 self.state = {} |
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433 self.processStatus = "success" |
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434 |
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435 if _logger.isEnabledFor(logging.DEBUG): |
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436 _logger.debug(u"[%s] %s", self.name, json_dumps(joborder, indent=4)) |
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437 |
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438 runtimeContext = runtimeContext.copy() |
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439 runtimeContext.outdir = None |
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440 |
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441 for index, inp in enumerate(self.tool["inputs"]): |
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442 with SourceLine(self.tool["inputs"], index, WorkflowException, |
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443 _logger.isEnabledFor(logging.DEBUG)): |
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444 inp_id = shortname(inp["id"]) |
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445 if inp_id in joborder: |
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446 self.state[inp["id"]] = WorkflowStateItem( |
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447 inp, joborder[inp_id], "success") |
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448 elif "default" in inp: |
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449 self.state[inp["id"]] = WorkflowStateItem( |
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450 inp, inp["default"], "success") |
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451 else: |
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452 raise WorkflowException( |
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453 u"Input '%s' not in input object and does not have a " |
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454 " default value." % (inp["id"])) |
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455 |
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456 for step in self.steps: |
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457 for out in step.tool["outputs"]: |
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458 self.state[out["id"]] = None |
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459 |
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460 completed = 0 |
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461 while completed < len(self.steps): |
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462 self.made_progress = False |
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463 |
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464 for step in self.steps: |
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465 if getdefault(runtimeContext.on_error, "stop") == "stop" and self.processStatus != "success": |
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466 break |
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467 |
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468 if not step.submitted: |
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469 try: |
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470 step.iterable = self.try_make_job( |
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471 step, output_callback, runtimeContext) |
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472 except WorkflowException as exc: |
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473 _logger.error(u"[%s] Cannot make job: %s", step.name, Text(exc)) |
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474 _logger.debug("", exc_info=True) |
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475 self.processStatus = "permanentFail" |
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476 |
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477 if step.iterable is not None: |
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478 try: |
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479 for newjob in step.iterable: |
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480 if getdefault(runtimeContext.on_error, "stop") == "stop" \ |
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481 and self.processStatus != "success": |
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482 break |
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483 if newjob is not None: |
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484 self.made_progress = True |
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485 yield newjob |
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486 else: |
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487 break |
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488 except WorkflowException as exc: |
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489 _logger.error(u"[%s] Cannot make job: %s", step.name, Text(exc)) |
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490 _logger.debug("", exc_info=True) |
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491 self.processStatus = "permanentFail" |
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492 |
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493 completed = sum(1 for s in self.steps if s.completed) |
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494 |
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495 if not self.made_progress and completed < len(self.steps): |
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496 if self.processStatus != "success": |
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497 break |
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498 else: |
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499 yield None |
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500 |
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501 if not self.did_callback: |
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502 self.do_output_callback(output_callback) # could have called earlier on line 336; |
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503 #depends which one comes first. All steps are completed |
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504 #or all outputs have been produced. |
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505 |
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506 class Workflow(Process): |
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507 def __init__(self, |
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508 toolpath_object, # type: MutableMapping[Text, Any] |
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509 loadingContext # type: LoadingContext |
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510 ): # type: (...) -> None |
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511 """Initializet this Workflow.""" |
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512 super(Workflow, self).__init__( |
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513 toolpath_object, loadingContext) |
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514 self.provenance_object = None # type: Optional[ProvenanceProfile] |
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515 if loadingContext.research_obj is not None: |
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516 run_uuid = None # type: Optional[UUID] |
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517 is_master = not loadingContext.prov_obj # Not yet set |
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518 if is_master: |
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519 run_uuid = loadingContext.research_obj.ro_uuid |
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520 |
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521 self.provenance_object = ProvenanceProfile( |
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522 loadingContext.research_obj, |
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523 full_name=loadingContext.cwl_full_name, |
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524 host_provenance=loadingContext.host_provenance, |
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525 user_provenance=loadingContext.user_provenance, |
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526 orcid=loadingContext.orcid, |
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527 run_uuid=run_uuid, |
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528 fsaccess=loadingContext.research_obj.fsaccess) # inherit RO UUID for master wf run |
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529 # TODO: Is Workflow(..) only called when we are the master workflow? |
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530 self.parent_wf = self.provenance_object |
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531 |
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532 # FIXME: Won't this overwrite prov_obj for nested workflows? |
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533 loadingContext.prov_obj = self.provenance_object |
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534 loadingContext = loadingContext.copy() |
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535 loadingContext.requirements = self.requirements |
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536 loadingContext.hints = self.hints |
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537 |
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538 self.steps = [] # type: List[WorkflowStep] |
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539 validation_errors = [] |
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540 for index, step in enumerate(self.tool.get("steps", [])): |
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541 try: |
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542 self.steps.append(self.make_workflow_step(step, index, loadingContext, |
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543 loadingContext.prov_obj)) |
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544 except validate.ValidationException as vexc: |
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545 if _logger.isEnabledFor(logging.DEBUG): |
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546 _logger.exception("Validation failed at") |
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547 validation_errors.append(vexc) |
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548 |
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549 if validation_errors: |
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550 raise validate.ValidationException("\n".join(str(v) for v in validation_errors)) |
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551 |
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552 random.shuffle(self.steps) |
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553 |
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554 # statically validate data links instead of doing it at runtime. |
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555 workflow_inputs = self.tool["inputs"] |
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556 workflow_outputs = self.tool["outputs"] |
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557 |
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558 step_inputs = [] # type: List[Any] |
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559 step_outputs = [] # type: List[Any] |
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560 param_to_step = {} # type: Dict[Text, Dict[Text, Any]] |
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561 for step in self.steps: |
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562 step_inputs.extend(step.tool["inputs"]) |
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563 step_outputs.extend(step.tool["outputs"]) |
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564 for s in step.tool["inputs"]: |
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565 param_to_step[s["id"]] = step.tool |
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566 |
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567 if getdefault(loadingContext.do_validate, True): |
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568 static_checker(workflow_inputs, workflow_outputs, step_inputs, step_outputs, param_to_step) |
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569 |
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570 def make_workflow_step(self, |
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571 toolpath_object, # type: Dict[Text, Any] |
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572 pos, # type: int |
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573 loadingContext, # type: LoadingContext |
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574 parentworkflowProv=None # type: Optional[ProvenanceProfile] |
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575 ): # type: (...) -> WorkflowStep |
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576 return WorkflowStep(toolpath_object, pos, loadingContext, parentworkflowProv) |
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577 |
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578 def job(self, |
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579 job_order, # type: Mapping[Text, Any] |
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580 output_callbacks, # type: Callable[[Any, Any], Any] |
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581 runtimeContext # type: RuntimeContext |
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582 ): # type: (...) -> Generator[Union[WorkflowJob, ExpressionTool.ExpressionJob, JobBase, CallbackJob, None], None, None] |
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583 builder = self._init_job(job_order, runtimeContext) |
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584 |
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585 if runtimeContext.research_obj is not None: |
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586 if runtimeContext.toplevel: |
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587 # Record primary-job.json |
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588 runtimeContext.research_obj.fsaccess = runtimeContext.make_fs_access('') |
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589 runtimeContext.research_obj.create_job(builder.job, self.job) |
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590 |
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591 job = WorkflowJob(self, runtimeContext) |
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592 yield job |
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593 |
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594 runtimeContext = runtimeContext.copy() |
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595 runtimeContext.part_of = u"workflow %s" % job.name |
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596 runtimeContext.toplevel = False |
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597 |
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598 for wjob in job.job(builder.job, output_callbacks, runtimeContext): |
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599 yield wjob |
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600 |
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601 def visit(self, op): # type: (Callable[[MutableMapping[Text, Any]], Any]) -> None |
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602 op(self.tool) |
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603 for step in self.steps: |
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604 step.visit(op) |
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605 |
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606 |
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607 |
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608 class WorkflowStep(Process): |
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609 def __init__(self, |
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610 toolpath_object, # type: Dict[Text, Any] |
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611 pos, # type: int |
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612 loadingContext, # type: LoadingContext |
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613 parentworkflowProv=None # type: Optional[ProvenanceProfile] |
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614 ): # type: (...) -> None |
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615 """Initialize this WorkflowStep.""" |
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616 if "id" in toolpath_object: |
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617 self.id = toolpath_object["id"] |
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618 else: |
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619 self.id = "#step" + Text(pos) |
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620 |
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621 loadingContext = loadingContext.copy() |
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622 |
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623 loadingContext.requirements = copy.deepcopy(getdefault(loadingContext.requirements, [])) |
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624 assert loadingContext.requirements is not None # nosec |
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625 loadingContext.requirements.extend(toolpath_object.get("requirements", [])) |
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626 loadingContext.requirements.extend(get_overrides(getdefault(loadingContext.overrides_list, []), |
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627 self.id).get("requirements", [])) |
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628 |
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629 hints = copy.deepcopy(getdefault(loadingContext.hints, [])) |
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630 hints.extend(toolpath_object.get("hints", [])) |
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631 loadingContext.hints = hints |
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632 |
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633 |
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634 try: |
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635 if isinstance(toolpath_object["run"], MutableMapping): |
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636 self.embedded_tool = loadingContext.construct_tool_object( |
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637 toolpath_object["run"], loadingContext) # type: Process |
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638 else: |
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639 loadingContext.metadata = {} |
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640 self.embedded_tool = load_tool( |
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641 toolpath_object["run"], loadingContext) |
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642 except validate.ValidationException as vexc: |
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643 if loadingContext.debug: |
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644 _logger.exception("Validation exception") |
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645 raise_from(WorkflowException( |
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646 u"Tool definition %s failed validation:\n%s" % |
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647 (toolpath_object["run"], indent(str(vexc)))), vexc) |
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648 |
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649 validation_errors = [] |
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650 self.tool = toolpath_object = copy.deepcopy(toolpath_object) |
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651 bound = set() |
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652 for stepfield, toolfield in (("in", "inputs"), ("out", "outputs")): |
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653 toolpath_object[toolfield] = [] |
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654 for index, step_entry in enumerate(toolpath_object[stepfield]): |
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655 if isinstance(step_entry, string_types): |
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656 param = CommentedMap() # type: CommentedMap |
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657 inputid = step_entry |
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658 else: |
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659 param = CommentedMap(iteritems(step_entry)) |
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660 inputid = step_entry["id"] |
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661 |
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662 shortinputid = shortname(inputid) |
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663 found = False |
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664 for tool_entry in self.embedded_tool.tool[toolfield]: |
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665 frag = shortname(tool_entry["id"]) |
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666 if frag == shortinputid: |
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667 #if the case that the step has a default for a parameter, |
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668 #we do not want the default of the tool to override it |
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669 step_default = None |
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670 if "default" in param and "default" in tool_entry: |
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671 step_default = param["default"] |
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672 param.update(tool_entry) |
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673 param["_tool_entry"] = tool_entry |
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674 if step_default is not None: |
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675 param["default"] = step_default |
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676 found = True |
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677 bound.add(frag) |
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678 break |
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679 if not found: |
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680 if stepfield == "in": |
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681 param["type"] = "Any" |
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682 param["not_connected"] = True |
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683 else: |
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684 if isinstance(step_entry, Mapping): |
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685 step_entry_name = step_entry['id'] |
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686 else: |
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687 step_entry_name = step_entry |
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688 validation_errors.append( |
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689 SourceLine(self.tool["out"], index).makeError( |
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690 "Workflow step output '%s' does not correspond to" |
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691 % shortname(step_entry_name)) |
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692 + "\n" + SourceLine(self.embedded_tool.tool, "outputs").makeError( |
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693 " tool output (expected '%s')" % ( |
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694 "', '".join( |
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695 [shortname(tool_entry["id"]) for tool_entry in |
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696 self.embedded_tool.tool['outputs']])))) |
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697 param["id"] = inputid |
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698 param.lc.line = toolpath_object[stepfield].lc.data[index][0] |
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699 param.lc.col = toolpath_object[stepfield].lc.data[index][1] |
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700 param.lc.filename = toolpath_object[stepfield].lc.filename |
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701 toolpath_object[toolfield].append(param) |
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702 |
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703 missing_values = [] |
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704 for _, tool_entry in enumerate(self.embedded_tool.tool["inputs"]): |
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705 if shortname(tool_entry["id"]) not in bound: |
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706 if "null" not in tool_entry["type"] and "default" not in tool_entry: |
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707 missing_values.append(shortname(tool_entry["id"])) |
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708 |
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709 if missing_values: |
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710 validation_errors.append(SourceLine(self.tool, "in").makeError( |
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711 "Step is missing required parameter%s '%s'" % |
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712 ("s" if len(missing_values) > 1 else "", "', '".join(missing_values)))) |
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713 |
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714 if validation_errors: |
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715 raise validate.ValidationException("\n".join(validation_errors)) |
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716 |
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717 super(WorkflowStep, self).__init__(toolpath_object, loadingContext) |
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718 |
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719 if self.embedded_tool.tool["class"] == "Workflow": |
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720 (feature, _) = self.get_requirement("SubworkflowFeatureRequirement") |
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721 if not feature: |
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722 raise WorkflowException( |
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723 "Workflow contains embedded workflow but " |
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724 "SubworkflowFeatureRequirement not in requirements") |
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725 |
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726 if "scatter" in self.tool: |
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727 (feature, _) = self.get_requirement("ScatterFeatureRequirement") |
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728 if not feature: |
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729 raise WorkflowException( |
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730 "Workflow contains scatter but ScatterFeatureRequirement " |
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731 "not in requirements") |
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732 |
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733 inputparms = copy.deepcopy(self.tool["inputs"]) |
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734 outputparms = copy.deepcopy(self.tool["outputs"]) |
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735 scatter = aslist(self.tool["scatter"]) |
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736 |
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737 method = self.tool.get("scatterMethod") |
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738 if method is None and len(scatter) != 1: |
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739 raise validate.ValidationException( |
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740 "Must specify scatterMethod when scattering over multiple inputs") |
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741 |
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742 inp_map = {i["id"]: i for i in inputparms} |
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743 for inp in scatter: |
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744 if inp not in inp_map: |
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745 raise validate.ValidationException( |
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746 SourceLine(self.tool, "scatter").makeError( |
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747 "Scatter parameter '%s' does not correspond to " |
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748 "an input parameter of this step, expecting '%s'" |
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749 % (shortname(inp), "', '".join( |
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750 shortname(k) for k in inp_map.keys())))) |
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751 |
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752 inp_map[inp]["type"] = {"type": "array", "items": inp_map[inp]["type"]} |
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753 |
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754 if self.tool.get("scatterMethod") == "nested_crossproduct": |
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755 nesting = len(scatter) |
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756 else: |
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757 nesting = 1 |
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758 |
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759 for _ in range(0, nesting): |
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760 for oparam in outputparms: |
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761 oparam["type"] = {"type": "array", "items": oparam["type"]} |
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762 self.tool["inputs"] = inputparms |
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763 self.tool["outputs"] = outputparms |
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764 self.prov_obj = None # type: Optional[ProvenanceProfile] |
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765 if loadingContext.research_obj is not None: |
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766 self.prov_obj = parentworkflowProv |
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767 if self.embedded_tool.tool["class"] == "Workflow": |
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768 self.parent_wf = self.embedded_tool.parent_wf |
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769 else: |
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770 self.parent_wf = self.prov_obj |
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771 |
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772 def receive_output(self, output_callback, jobout, processStatus): |
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773 # type: (Callable[...,Any], Dict[Text, Text], Text) -> None |
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774 output = {} |
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775 for i in self.tool["outputs"]: |
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776 field = shortname(i["id"]) |
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777 if field in jobout: |
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778 output[i["id"]] = jobout[field] |
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779 else: |
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780 processStatus = "permanentFail" |
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781 output_callback(output, processStatus) |
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782 |
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783 def job(self, |
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784 job_order, # type: Mapping[Text, Text] |
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785 output_callbacks, # type: Callable[[Any, Any], Any] |
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786 runtimeContext, # type: RuntimeContext |
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787 ): # type: (...) -> Generator[Union[ExpressionTool.ExpressionJob, JobBase, CallbackJob], None, None] |
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788 #initialize sub-workflow as a step in the parent profile |
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789 |
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790 if self.embedded_tool.tool["class"] == "Workflow" \ |
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791 and runtimeContext.research_obj and self.prov_obj \ |
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792 and self.embedded_tool.provenance_object: |
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793 self.embedded_tool.parent_wf = self.prov_obj |
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794 process_name = self.tool["id"].split("#")[1] |
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795 self.prov_obj.start_process( |
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796 process_name, datetime.datetime.now(), |
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797 self.embedded_tool.provenance_object.workflow_run_uri) |
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798 |
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799 step_input = {} |
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800 for inp in self.tool["inputs"]: |
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801 field = shortname(inp["id"]) |
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802 if not inp.get("not_connected"): |
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803 step_input[field] = job_order[inp["id"]] |
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804 |
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805 try: |
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806 for tool in self.embedded_tool.job( |
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807 step_input, |
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808 functools.partial(self.receive_output, output_callbacks), |
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809 runtimeContext): |
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810 yield tool |
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811 except WorkflowException: |
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812 _logger.error(u"Exception on step '%s'", runtimeContext.name) |
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813 raise |
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814 except Exception as exc: |
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815 _logger.exception("Unexpected exception") |
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816 raise_from(WorkflowException(Text(exc)), exc) |
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817 |
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818 def visit(self, op): # type: (Callable[[MutableMapping[Text, Any]], Any]) -> None |
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819 self.embedded_tool.visit(op) |
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820 |
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821 |
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822 class ReceiveScatterOutput(object): |
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823 def __init__(self, |
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824 output_callback, # type: Callable[..., Any] |
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825 dest, # type: Dict[Text, List[Optional[Text]]] |
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826 total # type: int |
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827 ): # type: (...) -> None |
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828 """Initialize.""" |
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829 self.dest = dest |
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830 self.completed = 0 |
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831 self.processStatus = u"success" |
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832 self.total = total |
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833 self.output_callback = output_callback |
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834 self.steps = [] # type: List[Optional[Generator[Union[ExpressionTool.ExpressionJob, JobBase, CallbackJob, None], None, None]]] |
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835 |
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836 def receive_scatter_output(self, index, jobout, processStatus): |
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837 # type: (int, Dict[Text, Text], Text) -> None |
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838 for key, val in jobout.items(): |
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839 self.dest[key][index] = val |
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840 |
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841 # Release the iterable related to this step to |
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842 # reclaim memory. |
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843 if self.steps: |
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844 self.steps[index] = None |
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845 |
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846 if processStatus != "success": |
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847 if self.processStatus != "permanentFail": |
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848 self.processStatus = processStatus |
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849 |
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850 self.completed += 1 |
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851 |
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852 if self.completed == self.total: |
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853 self.output_callback(self.dest, self.processStatus) |
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854 |
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855 def setTotal(self, total, steps): # type: (int, List[Optional[Generator[Union[ExpressionTool.ExpressionJob, JobBase, CallbackJob, None], None, None]]]) -> None |
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856 self.total = total |
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857 self.steps = steps |
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858 if self.completed == self.total: |
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859 self.output_callback(self.dest, self.processStatus) |
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860 |
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861 |
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862 def parallel_steps(steps, rc, runtimeContext): |
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863 # type: (List[Optional[Generator[Union[ExpressionTool.ExpressionJob, JobBase, CallbackJob, None], None, None]]], ReceiveScatterOutput, RuntimeContext) -> Generator[Union[ExpressionTool.ExpressionJob, JobBase, CallbackJob, None], None, None] |
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864 while rc.completed < rc.total: |
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865 made_progress = False |
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866 for index, step in enumerate(steps): |
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867 if getdefault(runtimeContext.on_error, "stop") == "stop" and rc.processStatus != "success": |
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868 break |
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869 if step is None: |
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870 continue |
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871 try: |
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872 for j in step: |
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"planemo upload commit c699937486c35866861690329de38ec1a5d9f783"
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873 if getdefault(runtimeContext.on_error, "stop") == "stop" and rc.processStatus != "success": |
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874 break |
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875 if j is not None: |
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876 made_progress = True |
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877 yield j |
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|
878 else: |
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879 break |
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880 if made_progress: |
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881 break |
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882 except WorkflowException as exc: |
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883 _logger.error(u"Cannot make scatter job: %s", Text(exc)) |
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884 _logger.debug("", exc_info=True) |
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885 rc.receive_scatter_output(index, {}, "permanentFail") |
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886 if not made_progress and rc.completed < rc.total: |
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887 yield None |
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|
888 |
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|
889 |
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"planemo upload commit c699937486c35866861690329de38ec1a5d9f783"
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890 def dotproduct_scatter(process, # type: WorkflowJobStep |
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891 joborder, # type: MutableMapping[Text, Any] |
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892 scatter_keys, # type: MutableSequence[Text] |
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893 output_callback, # type: Callable[..., Any] |
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894 runtimeContext # type: RuntimeContext |
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895 ): # type: (...) -> Generator[Union[ExpressionTool.ExpressionJob, JobBase, CallbackJob, None], None, None] |
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896 jobl = None # type: Optional[int] |
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897 for key in scatter_keys: |
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898 if jobl is None: |
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899 jobl = len(joborder[key]) |
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900 elif jobl != len(joborder[key]): |
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901 raise WorkflowException( |
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902 "Length of input arrays must be equal when performing " |
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903 "dotproduct scatter.") |
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904 if jobl is None: |
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905 raise Exception("Impossible codepath") |
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906 |
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907 output = {} # type: Dict[Text,List[Optional[Text]]] |
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908 for i in process.tool["outputs"]: |
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909 output[i["id"]] = [None] * jobl |
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910 |
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911 rc = ReceiveScatterOutput(output_callback, output, jobl) |
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912 |
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913 steps = [] # type: List[Optional[Generator[Union[ExpressionTool.ExpressionJob, JobBase, CallbackJob, None], None, None]]] |
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914 for index in range(0, jobl): |
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915 sjobo = copy.copy(joborder) |
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916 for key in scatter_keys: |
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917 sjobo[key] = joborder[key][index] |
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918 |
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919 if runtimeContext.postScatterEval is not None: |
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920 sjobo = runtimeContext.postScatterEval(sjobo) |
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921 |
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922 steps.append(process.job( |
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923 sjobo, functools.partial(rc.receive_scatter_output, index), |
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924 runtimeContext)) |
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925 |
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926 rc.setTotal(jobl, steps) |
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927 return parallel_steps(steps, rc, runtimeContext) |
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928 |
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929 |
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930 def nested_crossproduct_scatter(process, # type: WorkflowJobStep |
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931 joborder, # type: MutableMapping[Text, Any] |
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932 scatter_keys, # type: MutableSequence[Text] |
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933 output_callback, # type: Callable[..., Any] |
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934 runtimeContext # type: RuntimeContext |
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935 ): # type: (...) -> Generator[Union[ExpressionTool.ExpressionJob, JobBase, CallbackJob, None], None, None] |
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936 scatter_key = scatter_keys[0] |
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937 jobl = len(joborder[scatter_key]) |
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938 output = {} # type: Dict[Text, List[Optional[Text]]] |
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939 for i in process.tool["outputs"]: |
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940 output[i["id"]] = [None] * jobl |
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941 |
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942 rc = ReceiveScatterOutput(output_callback, output, jobl) |
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943 |
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944 steps = [] # type: List[Optional[Generator[Union[ExpressionTool.ExpressionJob, JobBase, CallbackJob, None], None, None]]] |
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945 for index in range(0, jobl): |
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946 sjob = copy.copy(joborder) |
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947 sjob[scatter_key] = joborder[scatter_key][index] |
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948 |
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949 if len(scatter_keys) == 1: |
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950 if runtimeContext.postScatterEval is not None: |
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951 sjob = runtimeContext.postScatterEval(sjob) |
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952 steps.append(process.job( |
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953 sjob, functools.partial(rc.receive_scatter_output, index), |
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954 runtimeContext)) |
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955 else: |
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956 steps.append(nested_crossproduct_scatter( |
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957 process, sjob, scatter_keys[1:], |
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958 functools.partial(rc.receive_scatter_output, index), |
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959 runtimeContext)) |
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960 |
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961 rc.setTotal(jobl, steps) |
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962 return parallel_steps(steps, rc, runtimeContext) |
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963 |
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964 |
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965 def crossproduct_size(joborder, scatter_keys): |
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966 # type: (MutableMapping[Text, Any], MutableSequence[Text]) -> int |
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967 scatter_key = scatter_keys[0] |
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968 if len(scatter_keys) == 1: |
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969 ssum = len(joborder[scatter_key]) |
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970 else: |
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971 ssum = 0 |
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972 for _ in range(0, len(joborder[scatter_key])): |
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973 ssum += crossproduct_size(joborder, scatter_keys[1:]) |
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974 return ssum |
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975 |
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976 def flat_crossproduct_scatter(process, # type: WorkflowJobStep |
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977 joborder, # type: MutableMapping[Text, Any] |
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978 scatter_keys, # type: MutableSequence[Text] |
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979 output_callback, # type: Callable[..., Any] |
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980 runtimeContext # type: RuntimeContext |
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981 ): # type: (...) -> Generator[Union[ExpressionTool.ExpressionJob, JobBase, CallbackJob, None], None, None] |
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982 output = {} # type: Dict[Text, List[Optional[Text]]] |
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983 for i in process.tool["outputs"]: |
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984 output[i["id"]] = [None] * crossproduct_size(joborder, scatter_keys) |
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985 callback = ReceiveScatterOutput(output_callback, output, 0) |
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986 (steps, total) = _flat_crossproduct_scatter( |
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987 process, joborder, scatter_keys, callback, 0, runtimeContext) |
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988 callback.setTotal(total, steps) |
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989 return parallel_steps(steps, callback, runtimeContext) |
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990 |
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991 def _flat_crossproduct_scatter(process, # type: WorkflowJobStep |
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992 joborder, # type: MutableMapping[Text, Any] |
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993 scatter_keys, # type: MutableSequence[Text] |
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994 callback, # type: ReceiveScatterOutput |
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995 startindex, # type: int |
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996 runtimeContext # type: RuntimeContext |
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997 ): # type: (...) -> Tuple[List[Optional[Generator[Union[ExpressionTool.ExpressionJob, JobBase, CallbackJob, None], None, None]]], int] |
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998 """Inner loop.""" |
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999 scatter_key = scatter_keys[0] |
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1000 jobl = len(joborder[scatter_key]) |
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1001 steps = [] # type: List[Optional[Generator[Union[ExpressionTool.ExpressionJob, JobBase, CallbackJob, None], None, None]]] |
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1002 put = startindex |
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1003 for index in range(0, jobl): |
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1004 sjob = copy.copy(joborder) |
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1005 sjob[scatter_key] = joborder[scatter_key][index] |
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1006 |
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1007 if len(scatter_keys) == 1: |
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1008 if runtimeContext.postScatterEval is not None: |
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1009 sjob = runtimeContext.postScatterEval(sjob) |
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1010 steps.append(process.job( |
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1011 sjob, functools.partial(callback.receive_scatter_output, put), |
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1012 runtimeContext)) |
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1013 put += 1 |
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1014 else: |
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1015 (add, _) = _flat_crossproduct_scatter( |
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1016 process, sjob, scatter_keys[1:], callback, put, runtimeContext) |
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1017 put += len(add) |
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1018 steps.extend(add) |
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1019 |
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1020 return (steps, put) |