Mercurial > repos > shellac > sam_consensus_v3
annotate env/lib/python3.9/site-packages/galaxy/tool_util/cwl/representation.py @ 0:4f3585e2f14b draft default tip
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author | shellac |
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date | Mon, 22 Mar 2021 18:12:50 +0000 |
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1 """ 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 json |
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5 import logging |
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6 import os |
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7 from enum import Enum |
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8 from typing import Any, NamedTuple, Optional |
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9 |
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10 from galaxy.exceptions import RequestParameterInvalidException |
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11 from galaxy.util import safe_makedirs, string_as_bool |
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12 from .util import set_basename_and_derived_properties |
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13 |
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14 |
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15 log = logging.getLogger(__name__) |
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16 |
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17 NOT_PRESENT = object() |
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18 |
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19 NO_GALAXY_INPUT = object() |
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20 |
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21 |
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22 class INPUT_TYPE(str, Enum): |
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23 DATA = "data" |
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24 INTEGER = "integer" |
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25 FLOAT = "float" |
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26 TEXT = "text" |
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27 BOOLEAN = "boolean" |
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28 SELECT = "select" |
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29 FIELD = "field" |
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30 CONDITIONAL = "conditional" |
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31 DATA_COLLECTON = "data_collection" |
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32 |
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33 |
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34 # There are two approaches to mapping CWL tool state to Galaxy tool state |
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35 # one is to map CWL types to compound Galaxy tool parameters combinations |
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36 # with conditionals and the other is to use a new Galaxy parameter type that |
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37 # allows unions, optional specifications, etc.... The problem with the former |
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38 # is that it doesn't work with the workflow parameters for instance and is |
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39 # very complex on the backend. The problem with the latter is that the GUI |
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40 # for this parameter type is undefined curently. |
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41 USE_FIELD_TYPES = True |
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42 |
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43 # There are two approaches to mapping CWL workflow inputs to Galaxy workflow |
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44 # steps. The first is to simply map everything to expressions and stick them into |
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45 # files and use data inputs - the second is to use parameter_input steps with |
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46 # fields types. We are dispatching on USE_FIELD_TYPES for now - to choose but |
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47 # may diverge later? |
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48 # There are open issues with each approach: |
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49 # - Mapping everything to files makes the GUI harder to imagine but the backend |
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50 # easier to manage in someways. |
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51 USE_STEP_PARAMETERS = USE_FIELD_TYPES |
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52 |
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53 |
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54 class TypeRepresentation(NamedTuple): |
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55 name: str |
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56 galaxy_param_type: Any |
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57 label: str |
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58 collection_type: Optional[str] |
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59 |
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60 @property |
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61 def uses_param(self): |
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62 return self.galaxy_param_type is not NO_GALAXY_INPUT |
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63 |
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64 |
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65 TYPE_REPRESENTATIONS = [ |
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66 TypeRepresentation("null", NO_GALAXY_INPUT, "no input", None), |
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67 TypeRepresentation("integer", INPUT_TYPE.INTEGER, "an integer", None), |
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68 TypeRepresentation("float", INPUT_TYPE.FLOAT, "a decimal number", None), |
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69 TypeRepresentation("double", INPUT_TYPE.FLOAT, "a decimal number", None), |
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70 TypeRepresentation("file", INPUT_TYPE.DATA, "a dataset", None), |
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71 TypeRepresentation("directory", INPUT_TYPE.DATA, "a directory", None), |
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72 TypeRepresentation("boolean", INPUT_TYPE.BOOLEAN, "a boolean", None), |
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73 TypeRepresentation("text", INPUT_TYPE.TEXT, "a simple text field", None), |
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74 TypeRepresentation("record", INPUT_TYPE.DATA_COLLECTON, "record as a dataset collection", "record"), |
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75 TypeRepresentation("json", INPUT_TYPE.TEXT, "arbitrary JSON structure", None), |
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76 TypeRepresentation("array", INPUT_TYPE.DATA_COLLECTON, "as a dataset list", "list"), |
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77 TypeRepresentation("enum", INPUT_TYPE.TEXT, "enum value", None), # TODO: make this a select... |
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78 TypeRepresentation("field", INPUT_TYPE.FIELD, "arbitrary JSON structure", None), |
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79 ] |
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80 FIELD_TYPE_REPRESENTATION = TYPE_REPRESENTATIONS[-1] |
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81 |
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82 if not USE_FIELD_TYPES: |
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83 CWL_TYPE_TO_REPRESENTATIONS = { |
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84 "Any": ["integer", "float", "file", "boolean", "text", "record", "json"], |
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85 "array": ["array"], |
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86 "string": ["text"], |
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87 "boolean": ["boolean"], |
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88 "int": ["integer"], |
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89 "float": ["float"], |
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90 "File": ["file"], |
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91 "Directory": ["directory"], |
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92 "null": ["null"], |
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93 "record": ["record"], |
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94 } |
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95 else: |
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96 CWL_TYPE_TO_REPRESENTATIONS = { |
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97 "Any": ["field"], |
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98 "array": ["array"], |
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99 "string": ["text"], |
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100 "boolean": ["boolean"], |
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101 "int": ["integer"], |
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102 "float": ["float"], |
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103 "File": ["file"], |
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104 "Directory": ["directory"], |
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105 "null": ["null"], |
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106 "record": ["record"], |
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107 "enum": ["enum"], |
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108 "double": ["double"], |
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109 } |
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110 |
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111 |
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112 def type_representation_from_name(type_representation_name): |
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113 for type_representation in TYPE_REPRESENTATIONS: |
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114 if type_representation.name == type_representation_name: |
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115 return type_representation |
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116 |
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117 assert False |
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118 |
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119 |
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120 def type_descriptions_for_field_types(field_types): |
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121 type_representation_names = set() |
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122 for field_type in field_types: |
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123 if isinstance(field_type, dict) and field_type.get("type"): |
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124 field_type = field_type.get("type") |
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125 |
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126 try: |
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127 type_representation_names_for_field_type = CWL_TYPE_TO_REPRESENTATIONS.get(field_type) |
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128 except TypeError: |
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129 raise Exception("Failed to convert field_type %s" % field_type) |
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130 if type_representation_names_for_field_type is None: |
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131 raise Exception("Failed to convert type %s" % field_type) |
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132 type_representation_names.update(type_representation_names_for_field_type) |
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133 type_representations = [] |
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134 for type_representation in TYPE_REPRESENTATIONS: |
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135 if type_representation.name in type_representation_names: |
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136 type_representations.append(type_representation) |
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137 return type_representations |
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138 |
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139 |
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140 def dataset_wrapper_to_file_json(inputs_dir, dataset_wrapper): |
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141 if dataset_wrapper.ext == "expression.json": |
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142 with open(dataset_wrapper.file_name) as f: |
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143 return json.load(f) |
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144 |
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145 if dataset_wrapper.ext == "directory": |
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146 return dataset_wrapper_to_directory_json(inputs_dir, dataset_wrapper) |
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147 |
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148 extra_files_path = dataset_wrapper.extra_files_path |
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149 secondary_files_path = os.path.join(extra_files_path, "__secondary_files__") |
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150 path = str(dataset_wrapper) |
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151 raw_file_object = {"class": "File"} |
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152 |
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153 if os.path.exists(secondary_files_path): |
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154 safe_makedirs(inputs_dir) |
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155 name = os.path.basename(path) |
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156 new_input_path = os.path.join(inputs_dir, name) |
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157 os.symlink(path, new_input_path) |
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158 secondary_files = [] |
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159 for secondary_file_name in os.listdir(secondary_files_path): |
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160 secondary_file_path = os.path.join(secondary_files_path, secondary_file_name) |
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161 target = os.path.join(inputs_dir, secondary_file_name) |
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162 log.info(f"linking [{secondary_file_path}] to [{target}]") |
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163 os.symlink(secondary_file_path, target) |
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164 is_dir = os.path.isdir(os.path.realpath(secondary_file_path)) |
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165 secondary_files.append({"class": "File" if not is_dir else "Directory", "location": target}) |
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166 |
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167 raw_file_object["secondaryFiles"] = secondary_files |
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168 path = new_input_path |
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169 |
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170 raw_file_object["location"] = path |
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171 |
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172 # Verify it isn't a NoneDataset |
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173 if dataset_wrapper.unsanitized: |
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174 raw_file_object["size"] = int(dataset_wrapper.get_size()) |
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175 |
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176 set_basename_and_derived_properties(raw_file_object, str(dataset_wrapper.created_from_basename or dataset_wrapper.name)) |
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177 return raw_file_object |
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178 |
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179 |
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180 def dataset_wrapper_to_directory_json(inputs_dir, dataset_wrapper): |
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181 assert dataset_wrapper.ext == "directory" |
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182 |
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183 # get directory name |
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184 archive_name = str(dataset_wrapper.created_from_basename or dataset_wrapper.name) |
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185 nameroot, nameext = os.path.splitext(archive_name) |
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186 directory_name = nameroot # assume archive file name contains the directory name |
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187 |
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188 # get archive location |
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189 try: |
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190 archive_location = dataset_wrapper.unsanitized.file_name |
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191 except Exception: |
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192 archive_location = None |
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193 |
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194 directory_json = {"location": dataset_wrapper.extra_files_path, |
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195 "class": "Directory", |
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196 "name": directory_name, |
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197 "archive_location": archive_location, |
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198 "archive_nameext": nameext, |
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199 "archive_nameroot": nameroot} |
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200 |
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201 return directory_json |
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202 |
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203 |
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204 def collection_wrapper_to_array(inputs_dir, wrapped_value): |
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205 rval = [] |
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206 for value in wrapped_value: |
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207 rval.append(dataset_wrapper_to_file_json(inputs_dir, value)) |
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208 return rval |
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209 |
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210 |
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211 def collection_wrapper_to_record(inputs_dir, wrapped_value): |
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212 rval = {} |
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213 for key, value in wrapped_value.items(): |
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214 rval[key] = dataset_wrapper_to_file_json(inputs_dir, value) |
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215 return rval |
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216 |
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217 |
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218 def to_cwl_job(tool, param_dict, local_working_directory): |
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219 """ tool is Galaxy's representation of the tool and param_dict is the |
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220 parameter dictionary with wrapped values. |
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221 """ |
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222 tool_proxy = tool._cwl_tool_proxy |
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223 input_fields = tool_proxy.input_fields() |
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224 inputs = tool.inputs |
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225 input_json = {} |
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226 |
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227 inputs_dir = os.path.join(local_working_directory, "_inputs") |
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228 |
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229 def simple_value(input, param_dict_value, type_representation_name=None): |
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230 type_representation = type_representation_from_name(type_representation_name) |
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231 # Hmm... cwl_type isn't really the cwl type in every case, |
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232 # like in the case of json for instance. |
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233 |
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234 if type_representation.galaxy_param_type == NO_GALAXY_INPUT: |
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235 assert param_dict_value is None |
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236 return None |
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237 |
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238 if type_representation.name == "file": |
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239 dataset_wrapper = param_dict_value |
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240 return dataset_wrapper_to_file_json(inputs_dir, dataset_wrapper) |
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241 elif type_representation.name == "directory": |
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242 dataset_wrapper = param_dict_value |
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243 return dataset_wrapper_to_directory_json(inputs_dir, dataset_wrapper) |
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244 elif type_representation.name == "integer": |
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245 return int(str(param_dict_value)) |
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246 elif type_representation.name == "long": |
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247 return int(str(param_dict_value)) |
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248 elif type_representation.name in ["float", "double"]: |
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249 return float(str(param_dict_value)) |
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250 elif type_representation.name == "boolean": |
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251 return string_as_bool(param_dict_value) |
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252 elif type_representation.name == "text": |
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253 return str(param_dict_value) |
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254 elif type_representation.name == "enum": |
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255 return str(param_dict_value) |
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256 elif type_representation.name == "json": |
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257 raw_value = param_dict_value.value |
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258 return json.loads(raw_value) |
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259 elif type_representation.name == "field": |
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260 if param_dict_value is None: |
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261 return None |
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262 if hasattr(param_dict_value, "value"): |
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263 # Is InputValueWrapper |
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264 rval = param_dict_value.value |
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265 if isinstance(rval, dict) and "src" in rval and rval["src"] == "json": |
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266 # needed for wf_step_connect_undeclared_param, so non-file defaults? |
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267 return rval["value"] |
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268 return rval |
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269 elif not param_dict_value.is_collection: |
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270 # Is DatasetFilenameWrapper |
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271 return dataset_wrapper_to_file_json(inputs_dir, param_dict_value) |
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272 else: |
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273 # Is DatasetCollectionWrapper |
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274 hdca_wrapper = param_dict_value |
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275 if hdca_wrapper.collection_type == "list": |
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276 # TODO: generalize to lists of lists and lists of non-files... |
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277 return collection_wrapper_to_array(inputs_dir, hdca_wrapper) |
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278 elif hdca_wrapper.collection_type.collection_type == "record": |
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279 return collection_wrapper_to_record(inputs_dir, hdca_wrapper) |
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280 |
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281 elif type_representation.name == "array": |
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282 # TODO: generalize to lists of lists and lists of non-files... |
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283 return collection_wrapper_to_array(inputs_dir, param_dict_value) |
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284 elif type_representation.name == "record": |
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285 return collection_wrapper_to_record(inputs_dir, param_dict_value) |
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286 else: |
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287 return str(param_dict_value) |
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288 |
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289 for input_name, input in inputs.items(): |
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290 if input.type == "repeat": |
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291 only_input = next(iter(input.inputs.values())) |
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292 array_value = [] |
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293 for instance in param_dict[input_name]: |
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294 array_value.append(simple_value(only_input, instance[input_name[:-len("_repeat")]])) |
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295 input_json[input_name[:-len("_repeat")]] = array_value |
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296 elif input.type == "conditional": |
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297 assert input_name in param_dict, f"No value for {input_name} in {param_dict}" |
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298 current_case = param_dict[input_name]["_cwl__type_"] |
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299 if str(current_case) != "null": # str because it is a wrapped... |
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300 case_index = input.get_current_case(current_case) |
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301 case_input = input.cases[case_index].inputs["_cwl__value_"] |
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302 case_value = param_dict[input_name]["_cwl__value_"] |
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303 input_json[input_name] = simple_value(case_input, case_value, current_case) |
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304 else: |
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305 matched_field = None |
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306 for field in input_fields: |
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307 if field["name"] == input_name: |
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308 matched_field = field |
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309 field_type = field_to_field_type(matched_field) |
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310 if isinstance(field_type, list): |
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311 assert USE_FIELD_TYPES |
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312 type_descriptions = [FIELD_TYPE_REPRESENTATION] |
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313 else: |
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314 type_descriptions = type_descriptions_for_field_types([field_type]) |
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315 assert len(type_descriptions) == 1 |
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316 type_description_name = type_descriptions[0].name |
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317 input_json[input_name] = simple_value(input, param_dict[input_name], type_description_name) |
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318 |
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319 log.debug("Galaxy Tool State is CWL State is %s" % input_json) |
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320 return input_json |
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321 |
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322 |
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323 def to_galaxy_parameters(tool, as_dict): |
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324 """ Tool is Galaxy's representation of the tool and as_dict is a Galaxified |
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325 representation of the input json (no paths, HDA references for instance). |
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326 """ |
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327 inputs = tool.inputs |
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328 galaxy_request = {} |
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329 |
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330 def from_simple_value(input, param_dict_value, type_representation_name=None): |
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331 if type_representation_name == "json": |
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332 return json.dumps(param_dict_value) |
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333 else: |
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334 return param_dict_value |
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335 |
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336 for input_name, input in inputs.items(): |
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337 as_dict_value = as_dict.get(input_name, NOT_PRESENT) |
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338 galaxy_input_type = input.type |
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339 |
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340 if galaxy_input_type == "repeat": |
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341 if input_name not in as_dict: |
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342 continue |
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343 |
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344 only_input = next(iter(input.inputs.values())) |
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345 for index, value in enumerate(as_dict_value): |
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346 key = f"{input_name}_repeat_0|{only_input.name}" |
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347 galaxy_value = from_simple_value(only_input, value) |
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348 galaxy_request[key] = galaxy_value |
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349 elif galaxy_input_type == "conditional": |
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350 case_strings = input.case_strings |
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351 # TODO: less crazy handling of defaults... |
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352 if (as_dict_value is NOT_PRESENT or as_dict_value is None) and "null" in case_strings: |
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353 type_representation_name = "null" |
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354 elif (as_dict_value is NOT_PRESENT or as_dict_value is None): |
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355 raise RequestParameterInvalidException( |
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356 "Cannot translate CWL datatype - value [{}] of type [{}] with case_strings [{}]. Non-null property must be set.".format( |
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357 as_dict_value, type(as_dict_value), case_strings |
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358 ) |
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359 ) |
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360 elif isinstance(as_dict_value, bool) and "boolean" in case_strings: |
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361 type_representation_name = "boolean" |
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362 elif isinstance(as_dict_value, int) and "integer" in case_strings: |
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363 type_representation_name = "integer" |
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364 elif isinstance(as_dict_value, int) and "long" in case_strings: |
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365 type_representation_name = "long" |
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366 elif isinstance(as_dict_value, (int, float)) and "float" in case_strings: |
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367 type_representation_name = "float" |
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368 elif isinstance(as_dict_value, (int, float)) and "double" in case_strings: |
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369 type_representation_name = "double" |
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370 elif isinstance(as_dict_value, str) and "string" in case_strings: |
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371 type_representation_name = "string" |
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372 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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373 type_representation_name = "file" |
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374 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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375 # TODO: can't disambiuate with above if both are available... |
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376 type_representation_name = "directory" |
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377 elif "field" in case_strings: |
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378 type_representation_name = "field" |
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379 elif "json" in case_strings and as_dict_value is not None: |
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380 type_representation_name = "json" |
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381 else: |
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382 raise RequestParameterInvalidException( |
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383 "Cannot translate CWL datatype - value [{}] of type [{}] with case_strings [{}].".format( |
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384 as_dict_value, type(as_dict_value), case_strings |
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385 ) |
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386 ) |
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387 galaxy_request["%s|_cwl__type_" % input_name] = type_representation_name |
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388 if type_representation_name != "null": |
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389 current_case_index = input.get_current_case(type_representation_name) |
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390 current_case_inputs = input.cases[current_case_index].inputs |
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391 current_case_input = current_case_inputs["_cwl__value_"] |
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392 galaxy_value = from_simple_value(current_case_input, as_dict_value, type_representation_name) |
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393 galaxy_request["%s|_cwl__value_" % input_name] = galaxy_value |
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394 elif as_dict_value is NOT_PRESENT: |
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395 continue |
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396 else: |
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397 galaxy_value = from_simple_value(input, as_dict_value) |
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398 galaxy_request[input_name] = galaxy_value |
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399 |
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400 log.info("Converted galaxy_request is %s" % galaxy_request) |
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401 return galaxy_request |
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402 |
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403 |
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404 def field_to_field_type(field): |
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405 field_type = field["type"] |
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406 if isinstance(field_type, dict): |
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407 field_type = field_type["type"] |
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408 if isinstance(field_type, list): |
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409 field_type_length = len(field_type) |
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410 if field_type_length == 0: |
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411 raise Exception("Zero-length type list encountered, invalid CWL?") |
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412 elif len(field_type) == 1: |
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413 field_type = field_type[0] |
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414 |
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415 return field_type |