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annotate planemo/lib/python3.7/site-packages/galaxy/tool_util/cwl/representation.py @ 1:56ad4e20f292 draft

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"planemo upload commit 6eee67778febed82ddd413c3ca40b3183a3898f1"
author guerler
date Fri, 31 Jul 2020 00:32:28 -0400
parents d30785e31577
children
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1 """ This module is responsible for converting between Galaxy's tool
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2 input description and the CWL description for a job json. """
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3
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4 import collections
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5 import json
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6 import logging
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7 import os
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8
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9 from six import string_types
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10
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11 from galaxy.exceptions import RequestParameterInvalidException
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12 from galaxy.util import safe_makedirs, string_as_bool
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13 from galaxy.util.bunch import Bunch
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14 from .util import set_basename_and_derived_properties
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15
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16
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17 log = logging.getLogger(__name__)
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18
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19 NOT_PRESENT = object()
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20
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21 NO_GALAXY_INPUT = object()
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22
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23 INPUT_TYPE = Bunch(
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24 DATA="data",
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25 INTEGER="integer",
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26 FLOAT="float",
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27 TEXT="text",
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28 BOOLEAN="boolean",
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29 SELECT="select",
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30 FIELD="field",
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31 CONDITIONAL="conditional",
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32 DATA_COLLECTON="data_collection",
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33 )
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34
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35 # There are two approaches to mapping CWL tool state to Galaxy tool state
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36 # one is to map CWL types to compound Galaxy tool parameters combinations
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37 # with conditionals and the other is to use a new Galaxy parameter type that
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38 # allows unions, optional specifications, etc.... The problem with the former
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39 # is that it doesn't work with the workflow parameters for instance and is
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40 # very complex on the backend. The problem with the latter is that the GUI
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41 # for this parameter type is undefined curently.
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42 USE_FIELD_TYPES = True
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43
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44 # There are two approaches to mapping CWL workflow inputs to Galaxy workflow
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45 # steps. The first is to simply map everything to expressions and stick them into
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46 # files and use data inputs - the second is to use parameter_input steps with
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47 # fields types. We are dispatching on USE_FIELD_TYPES for now - to choose but
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48 # may diverge later?
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49 # There are open issues with each approach:
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50 # - Mapping everything to files makes the GUI harder to imagine but the backend
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51 # easier to manage in someways.
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52 USE_STEP_PARAMETERS = USE_FIELD_TYPES
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53
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54 TypeRepresentation = collections.namedtuple("TypeRepresentation", ["name", "galaxy_param_type", "label", "collection_type"])
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55 TYPE_REPRESENTATIONS = [
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56 TypeRepresentation("null", NO_GALAXY_INPUT, "no input", None),
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57 TypeRepresentation("integer", INPUT_TYPE.INTEGER, "an integer", None),
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58 TypeRepresentation("float", INPUT_TYPE.FLOAT, "a decimal number", None),
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59 TypeRepresentation("double", INPUT_TYPE.FLOAT, "a decimal number", None),
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60 TypeRepresentation("file", INPUT_TYPE.DATA, "a dataset", None),
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61 TypeRepresentation("directory", INPUT_TYPE.DATA, "a directory", None),
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62 TypeRepresentation("boolean", INPUT_TYPE.BOOLEAN, "a boolean", None),
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63 TypeRepresentation("text", INPUT_TYPE.TEXT, "a simple text field", None),
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64 TypeRepresentation("record", INPUT_TYPE.DATA_COLLECTON, "record as a dataset collection", "record"),
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65 TypeRepresentation("json", INPUT_TYPE.TEXT, "arbitrary JSON structure", None),
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66 TypeRepresentation("array", INPUT_TYPE.DATA_COLLECTON, "as a dataset list", "list"),
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67 TypeRepresentation("enum", INPUT_TYPE.TEXT, "enum value", None), # TODO: make this a select...
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68 TypeRepresentation("field", INPUT_TYPE.FIELD, "arbitrary JSON structure", None),
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69 ]
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70 FIELD_TYPE_REPRESENTATION = TYPE_REPRESENTATIONS[-1]
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71 TypeRepresentation.uses_param = lambda self: self.galaxy_param_type is not NO_GALAXY_INPUT
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72
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73 if not USE_FIELD_TYPES:
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74 CWL_TYPE_TO_REPRESENTATIONS = {
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75 "Any": ["integer", "float", "file", "boolean", "text", "record", "json"],
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76 "array": ["array"],
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77 "string": ["text"],
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78 "boolean": ["boolean"],
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79 "int": ["integer"],
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80 "float": ["float"],
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81 "File": ["file"],
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82 "Directory": ["directory"],
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83 "null": ["null"],
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84 "record": ["record"],
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85 }
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86 else:
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87 CWL_TYPE_TO_REPRESENTATIONS = {
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88 "Any": ["field"],
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89 "array": ["array"],
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90 "string": ["text"],
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91 "boolean": ["boolean"],
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92 "int": ["integer"],
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93 "float": ["float"],
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94 "File": ["file"],
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95 "Directory": ["directory"],
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96 "null": ["null"],
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97 "record": ["record"],
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98 "enum": ["enum"],
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99 "double": ["double"],
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100 }
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101
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102
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103 def type_representation_from_name(type_representation_name):
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104 for type_representation in TYPE_REPRESENTATIONS:
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105 if type_representation.name == type_representation_name:
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106 return type_representation
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107
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108 assert False
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109
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110
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111 def type_descriptions_for_field_types(field_types):
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112 type_representation_names = set()
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113 for field_type in field_types:
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114 if isinstance(field_type, dict) and field_type.get("type"):
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115 field_type = field_type.get("type")
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116
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117 try:
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118 type_representation_names_for_field_type = CWL_TYPE_TO_REPRESENTATIONS.get(field_type)
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119 except TypeError:
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120 raise Exception("Failed to convert field_type %s" % field_type)
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121 if type_representation_names_for_field_type is None:
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122 raise Exception("Failed to convert type %s" % field_type)
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123 type_representation_names.update(type_representation_names_for_field_type)
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124 type_representations = []
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125 for type_representation in TYPE_REPRESENTATIONS:
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126 if type_representation.name in type_representation_names:
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127 type_representations.append(type_representation)
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128 return type_representations
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129
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130
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131 def dataset_wrapper_to_file_json(inputs_dir, dataset_wrapper):
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132 if dataset_wrapper.ext == "expression.json":
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133 with open(dataset_wrapper.file_name, "r") as f:
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134 return json.load(f)
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135
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136 if dataset_wrapper.ext == "directory":
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137 return dataset_wrapper_to_directory_json(inputs_dir, dataset_wrapper)
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138
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139 extra_files_path = dataset_wrapper.extra_files_path
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140 secondary_files_path = os.path.join(extra_files_path, "__secondary_files__")
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141 path = str(dataset_wrapper)
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142 raw_file_object = {"class": "File"}
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143
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144 if os.path.exists(secondary_files_path):
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145 safe_makedirs(inputs_dir)
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146 name = os.path.basename(path)
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147 new_input_path = os.path.join(inputs_dir, name)
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148 os.symlink(path, new_input_path)
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149 secondary_files = []
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150 for secondary_file_name in os.listdir(secondary_files_path):
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151 secondary_file_path = os.path.join(secondary_files_path, secondary_file_name)
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152 target = os.path.join(inputs_dir, secondary_file_name)
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153 log.info("linking [%s] to [%s]" % (secondary_file_path, target))
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154 os.symlink(secondary_file_path, target)
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155 is_dir = os.path.isdir(os.path.realpath(secondary_file_path))
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156 secondary_files.append({"class": "File" if not is_dir else "Directory", "location": target})
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157
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158 raw_file_object["secondaryFiles"] = secondary_files
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159 path = new_input_path
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160
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161 raw_file_object["location"] = path
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162
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163 # Verify it isn't a NoneDataset
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164 if dataset_wrapper.unsanitized:
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165 raw_file_object["size"] = int(dataset_wrapper.get_size())
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166
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167 set_basename_and_derived_properties(raw_file_object, str(dataset_wrapper.created_from_basename or dataset_wrapper.name))
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168 return raw_file_object
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169
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170
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171 def dataset_wrapper_to_directory_json(inputs_dir, dataset_wrapper):
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172 assert dataset_wrapper.ext == "directory"
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173
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174 # get directory name
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175 archive_name = str(dataset_wrapper.created_from_basename or dataset_wrapper.name)
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176 nameroot, nameext = os.path.splitext(archive_name)
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177 directory_name = nameroot # assume archive file name contains the directory name
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178
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179 # get archive location
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180 try:
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181 archive_location = dataset_wrapper.unsanitized.file_name
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182 except Exception:
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183 archive_location = None
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184
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185 directory_json = {"location": dataset_wrapper.extra_files_path,
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186 "class": "Directory",
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187 "name": directory_name,
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188 "archive_location": archive_location,
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189 "archive_nameext": nameext,
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190 "archive_nameroot": nameroot}
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191
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192 return directory_json
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193
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194
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195 def collection_wrapper_to_array(inputs_dir, wrapped_value):
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196 rval = []
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197 for value in wrapped_value:
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198 rval.append(dataset_wrapper_to_file_json(inputs_dir, value))
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199 return rval
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200
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201
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202 def collection_wrapper_to_record(inputs_dir, wrapped_value):
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203 rval = collections.OrderedDict()
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204 for key, value in wrapped_value.items():
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205 rval[key] = dataset_wrapper_to_file_json(inputs_dir, value)
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206 return rval
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207
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208
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209 def to_cwl_job(tool, param_dict, local_working_directory):
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210 """ tool is Galaxy's representation of the tool and param_dict is the
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211 parameter dictionary with wrapped values.
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212 """
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213 tool_proxy = tool._cwl_tool_proxy
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214 input_fields = tool_proxy.input_fields()
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215 inputs = tool.inputs
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216 input_json = {}
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217
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218 inputs_dir = os.path.join(local_working_directory, "_inputs")
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219
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220 def simple_value(input, param_dict_value, type_representation_name=None):
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221 type_representation = type_representation_from_name(type_representation_name)
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222 # Hmm... cwl_type isn't really the cwl type in every case,
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223 # like in the case of json for instance.
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224
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225 if type_representation.galaxy_param_type == NO_GALAXY_INPUT:
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226 assert param_dict_value is None
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227 return None
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228
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229 if type_representation.name == "file":
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230 dataset_wrapper = param_dict_value
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231 return dataset_wrapper_to_file_json(inputs_dir, dataset_wrapper)
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232 elif type_representation.name == "directory":
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233 dataset_wrapper = param_dict_value
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234 return dataset_wrapper_to_directory_json(inputs_dir, dataset_wrapper)
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235 elif type_representation.name == "integer":
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236 return int(str(param_dict_value))
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237 elif type_representation.name == "long":
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238 return int(str(param_dict_value))
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239 elif type_representation.name in ["float", "double"]:
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240 return float(str(param_dict_value))
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241 elif type_representation.name == "boolean":
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242 return string_as_bool(param_dict_value)
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243 elif type_representation.name == "text":
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244 return str(param_dict_value)
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245 elif type_representation.name == "enum":
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246 return str(param_dict_value)
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247 elif type_representation.name == "json":
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248 raw_value = param_dict_value.value
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249 return json.loads(raw_value)
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250 elif type_representation.name == "field":
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251 if param_dict_value is None:
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252 return None
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253 if hasattr(param_dict_value, "value"):
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254 # Is InputValueWrapper
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255 rval = param_dict_value.value
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256 if isinstance(rval, dict) and "src" in rval and rval["src"] == "json":
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257 # needed for wf_step_connect_undeclared_param, so non-file defaults?
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258 return rval["value"]
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259 return rval
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260 elif not param_dict_value.is_collection:
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261 # Is DatasetFilenameWrapper
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262 return dataset_wrapper_to_file_json(inputs_dir, param_dict_value)
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263 else:
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264 # Is DatasetCollectionWrapper
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265 hdca_wrapper = param_dict_value
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266 if hdca_wrapper.collection_type == "list":
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267 # TODO: generalize to lists of lists and lists of non-files...
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268 return collection_wrapper_to_array(inputs_dir, hdca_wrapper)
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269 elif hdca_wrapper.collection_type.collection_type == "record":
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270 return collection_wrapper_to_record(inputs_dir, hdca_wrapper)
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271
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272 elif type_representation.name == "array":
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273 # TODO: generalize to lists of lists and lists of non-files...
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274 return collection_wrapper_to_array(inputs_dir, param_dict_value)
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275 elif type_representation.name == "record":
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276 return collection_wrapper_to_record(inputs_dir, param_dict_value)
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277 else:
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278 return str(param_dict_value)
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279
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280 for input_name, input in inputs.items():
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281 if input.type == "repeat":
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282 only_input = next(iter(input.inputs.values()))
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283 array_value = []
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284 for instance in param_dict[input_name]:
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285 array_value.append(simple_value(only_input, instance[input_name[:-len("_repeat")]]))
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286 input_json[input_name[:-len("_repeat")]] = array_value
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287 elif input.type == "conditional":
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288 assert input_name in param_dict, "No value for %s in %s" % (input_name, param_dict)
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289 current_case = param_dict[input_name]["_cwl__type_"]
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290 if str(current_case) != "null": # str because it is a wrapped...
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291 case_index = input.get_current_case(current_case)
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292 case_input = input.cases[case_index].inputs["_cwl__value_"]
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293 case_value = param_dict[input_name]["_cwl__value_"]
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294 input_json[input_name] = simple_value(case_input, case_value, current_case)
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295 else:
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296 matched_field = None
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297 for field in input_fields:
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298 if field["name"] == input_name:
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299 matched_field = field
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300 field_type = field_to_field_type(matched_field)
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301 if isinstance(field_type, list):
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302 assert USE_FIELD_TYPES
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303 type_descriptions = [FIELD_TYPE_REPRESENTATION]
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304 else:
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305 type_descriptions = type_descriptions_for_field_types([field_type])
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306 assert len(type_descriptions) == 1
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307 type_description_name = type_descriptions[0].name
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308 input_json[input_name] = simple_value(input, param_dict[input_name], type_description_name)
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309
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310 log.debug("Galaxy Tool State is CWL State is %s" % input_json)
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311 return input_json
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312
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313
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314 def to_galaxy_parameters(tool, as_dict):
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315 """ Tool is Galaxy's representation of the tool and as_dict is a Galaxified
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316 representation of the input json (no paths, HDA references for instance).
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317 """
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318 inputs = tool.inputs
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319 galaxy_request = {}
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320
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321 def from_simple_value(input, param_dict_value, type_representation_name=None):
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322 if type_representation_name == "json":
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323 return json.dumps(param_dict_value)
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324 else:
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325 return param_dict_value
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326
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327 for input_name, input in inputs.items():
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328 as_dict_value = as_dict.get(input_name, NOT_PRESENT)
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329 galaxy_input_type = input.type
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330
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331 if galaxy_input_type == "repeat":
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332 if input_name not in as_dict:
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333 continue
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334
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335 only_input = next(iter(input.inputs.values()))
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336 for index, value in enumerate(as_dict_value):
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337 key = "%s_repeat_0|%s" % (input_name, only_input.name)
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338 galaxy_value = from_simple_value(only_input, value)
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339 galaxy_request[key] = galaxy_value
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340 elif galaxy_input_type == "conditional":
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341 case_strings = input.case_strings
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342 # TODO: less crazy handling of defaults...
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343 if (as_dict_value is NOT_PRESENT or as_dict_value is None) and "null" in case_strings:
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344 type_representation_name = "null"
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345 elif (as_dict_value is NOT_PRESENT or as_dict_value is None):
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346 raise RequestParameterInvalidException(
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347 "Cannot translate CWL datatype - value [%s] of type [%s] with case_strings [%s]. Non-null property must be set." % (
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348 as_dict_value, type(as_dict_value), case_strings
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349 )
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350 )
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351 elif isinstance(as_dict_value, bool) and "boolean" in case_strings:
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352 type_representation_name = "boolean"
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353 elif isinstance(as_dict_value, int) and "integer" in case_strings:
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354 type_representation_name = "integer"
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355 elif isinstance(as_dict_value, int) and "long" in case_strings:
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356 type_representation_name = "long"
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357 elif isinstance(as_dict_value, (int, float)) and "float" in case_strings:
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358 type_representation_name = "float"
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359 elif isinstance(as_dict_value, (int, float)) and "double" in case_strings:
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360 type_representation_name = "double"
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361 elif isinstance(as_dict_value, string_types) and "string" in case_strings:
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362 type_representation_name = "string"
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363 elif isinstance(as_dict_value, dict) and "src" in as_dict_value and "id" in as_dict_value and "file" in case_strings:
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364 type_representation_name = "file"
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365 elif isinstance(as_dict_value, dict) and "src" in as_dict_value and "id" in as_dict_value and "directory" in case_strings:
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366 # TODO: can't disambiuate with above if both are available...
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367 type_representation_name = "directory"
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368 elif "field" in case_strings:
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369 type_representation_name = "field"
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370 elif "json" in case_strings and as_dict_value is not None:
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371 type_representation_name = "json"
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372 else:
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373 raise RequestParameterInvalidException(
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374 "Cannot translate CWL datatype - value [%s] of type [%s] with case_strings [%s]." % (
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375 as_dict_value, type(as_dict_value), case_strings
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376 )
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377 )
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378 galaxy_request["%s|_cwl__type_" % input_name] = type_representation_name
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379 if type_representation_name != "null":
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380 current_case_index = input.get_current_case(type_representation_name)
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381 current_case_inputs = input.cases[current_case_index].inputs
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382 current_case_input = current_case_inputs["_cwl__value_"]
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383 galaxy_value = from_simple_value(current_case_input, as_dict_value, type_representation_name)
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384 galaxy_request["%s|_cwl__value_" % input_name] = galaxy_value
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385 elif as_dict_value is NOT_PRESENT:
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386 continue
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387 else:
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388 galaxy_value = from_simple_value(input, as_dict_value)
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389 galaxy_request[input_name] = galaxy_value
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390
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391 log.info("Converted galaxy_request is %s" % galaxy_request)
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392 return galaxy_request
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393
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394
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395 def field_to_field_type(field):
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396 field_type = field["type"]
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397 if isinstance(field_type, dict):
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398 field_type = field_type["type"]
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399 if isinstance(field_type, list):
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400 field_type_length = len(field_type)
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401 if field_type_length == 0:
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402 raise Exception("Zero-length type list encountered, invalid CWL?")
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403 elif len(field_type) == 1:
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404 field_type = field_type[0]
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405
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406 return field_type