comparison env/lib/python3.9/site-packages/gxformat2/export.py @ 0:4f3585e2f14b draft default tip

"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
author shellac
date Mon, 22 Mar 2021 18:12:50 +0000
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-1:000000000000 0:4f3585e2f14b
1 """Functionality for converting a standard Galaxy workflow into a format 2 workflow."""
2 import argparse
3 import json
4 import sys
5 from collections import OrderedDict
6
7 from ._labels import Labels
8 from .model import native_input_to_format2_type
9 from .yaml import ordered_dump
10
11 SCRIPT_DESCRIPTION = """
12 Convert a native Galaxy workflow description into a Format 2 description.
13 """
14
15
16 def _copy_common_properties(from_native_step, to_format2_step):
17 annotation = from_native_step.get("annotation", "")
18 if annotation:
19 to_format2_step["doc"] = annotation
20 position = from_native_step.get("position", None)
21 if position:
22 to_format2_step["position"] = position
23
24
25 def from_galaxy_native(format2_dict, tool_interface=None, json_wrapper=False):
26 """Convert native .ga workflow definition to a format2 workflow.
27
28 This is highly experimental and currently broken.
29 """
30 data = OrderedDict()
31 data['class'] = 'GalaxyWorkflow'
32 _copy_common_properties(format2_dict, data)
33 if "name" in format2_dict:
34 data["label"] = format2_dict.pop("name")
35 for top_level_key in ['tags', 'uuid', 'report']:
36 value = format2_dict.get(top_level_key)
37 if value:
38 data[top_level_key] = value
39
40 native_steps = format2_dict.get("steps")
41
42 label_map = {}
43 all_labeled = True
44 for key, step in native_steps.items():
45 label = step.get("label")
46 if not label:
47 all_labeled = False
48 label_map[str(key)] = label
49
50 inputs = OrderedDict()
51 outputs = OrderedDict()
52 steps = []
53
54 labels = Labels()
55
56 # For each step, rebuild the form and encode the state
57 for step in native_steps.values():
58 for workflow_output in step.get("workflow_outputs", []):
59 source = _to_source(workflow_output, label_map, output_id=step["id"])
60 output_id = labels.ensure_new_output_label(workflow_output.get("label"))
61 outputs[output_id] = {"outputSource": source}
62
63 module_type = step.get("type")
64 if module_type in ['data_input', 'data_collection_input', 'parameter_input']:
65 step_id = step["label"] # TODO: auto-label
66 input_dict = {}
67 tool_state = _tool_state(step)
68 input_dict['type'] = native_input_to_format2_type(step, tool_state)
69 for tool_state_key in ['optional', 'format', 'default', 'restrictions', 'suggestions', 'restrictOnConnections']:
70 if tool_state_key in tool_state:
71 input_dict[tool_state_key] = tool_state[tool_state_key]
72
73 _copy_common_properties(step, input_dict)
74 # If we are only copying property - use the CWL-style short-hand
75 if len(input_dict) == 1:
76 inputs[step_id] = input_dict["type"]
77 else:
78 inputs[step_id] = input_dict
79 continue
80
81 if module_type == "pause":
82 step_dict = OrderedDict()
83 optional_props = ['label']
84 _copy_common_properties(step, step_dict)
85 _copy_properties(step, step_dict, optional_props=optional_props)
86 _convert_input_connections(step, step_dict, label_map)
87 step_dict["type"] = "pause"
88 steps.append(step_dict)
89 continue
90
91 if module_type == 'subworkflow':
92 step_dict = OrderedDict()
93 optional_props = ['label']
94 _copy_common_properties(step, step_dict)
95 _copy_properties(step, step_dict, optional_props=optional_props)
96 _convert_input_connections(step, step_dict, label_map)
97 _convert_post_job_actions(step, step_dict)
98 subworkflow_native_dict = step["subworkflow"]
99 subworkflow = from_galaxy_native(subworkflow_native_dict, tool_interface=tool_interface, json_wrapper=False)
100 step_dict["run"] = subworkflow
101 steps.append(step_dict)
102 continue
103
104 if module_type != 'tool':
105 raise NotImplementedError("Unhandled module type %s" % module_type)
106
107 step_dict = OrderedDict()
108 optional_props = ['label', 'tool_shed_repository']
109 required_props = ['tool_id', 'tool_version']
110 _copy_properties(step, step_dict, optional_props, required_props)
111 _copy_common_properties(step, step_dict)
112
113 tool_state = _tool_state(step)
114 tool_state.pop("__page__", None)
115 tool_state.pop("__rerun_remap_job_id__", None)
116 step_dict['tool_state'] = tool_state
117
118 _convert_input_connections(step, step_dict, label_map)
119 _convert_post_job_actions(step, step_dict)
120 steps.append(step_dict)
121
122 data['inputs'] = inputs
123 data['outputs'] = outputs
124
125 if all_labeled:
126 steps_dict = OrderedDict()
127 for step in steps:
128 label = step.pop("label")
129 steps_dict[label] = step
130 data['steps'] = steps_dict
131 else:
132 data['steps'] = steps
133
134 if json_wrapper:
135 return {
136 "yaml_content": ordered_dump(data)
137 }
138
139 return data
140
141
142 def _tool_state(step):
143 tool_state = json.loads(step['tool_state'])
144 return tool_state
145
146
147 def _copy_properties(from_native_step, to_format2_step, optional_props=[], required_props=[]):
148 for prop in optional_props:
149 value = from_native_step.get(prop)
150 if value:
151 to_format2_step[prop] = value
152 for prop in required_props:
153 value = from_native_step.get(prop)
154 to_format2_step[prop] = value
155
156
157 def _convert_input_connections(from_native_step, to_format2_step, label_map):
158 in_dict = from_native_step.get("in", {}).copy()
159 input_connections = from_native_step['input_connections']
160 for input_name, input_defs in input_connections.items():
161 if not isinstance(input_defs, list):
162 input_defs = [input_defs]
163 for input_def in input_defs:
164 source = _to_source(input_def, label_map)
165 if input_name == "__NO_INPUT_OUTPUT_NAME__":
166 input_name = "$step"
167 assert source.endswith("/__NO_INPUT_OUTPUT_NAME__")
168 source = source[:-len("/__NO_INPUT_OUTPUT_NAME__")]
169 in_dict[input_name] = {
170 "source": source
171 }
172 to_format2_step["in"] = in_dict
173
174
175 def _convert_post_job_actions(from_native_step, to_format2_step):
176
177 def _ensure_output_def(key):
178 if "outputs" in to_format2_step:
179 to_format2_step["out"] = to_format2_step.pop("outputs")
180 elif "out" not in to_format2_step:
181 to_format2_step["out"] = {}
182
183 outputs_dict = to_format2_step["out"]
184 if key not in outputs_dict:
185 outputs_dict[key] = {}
186 return outputs_dict[key]
187
188 if "post_job_actions" in from_native_step:
189 post_job_actions = from_native_step["post_job_actions"].copy()
190 to_remove_keys = []
191
192 for post_job_action_key, post_job_action_value in post_job_actions.items():
193 action_type = post_job_action_value["action_type"]
194 output_name = post_job_action_value.get("output_name")
195 action_args = post_job_action_value.get("action_arguments", {})
196
197 handled = True
198 if action_type == "RenameDatasetAction":
199 output_dict = _ensure_output_def(output_name)
200 output_dict["rename"] = action_args["newname"]
201 handled = True
202 elif action_type == "HideDatasetAction":
203 output_dict = _ensure_output_def(output_name)
204 output_dict["hide"] = True
205 handled = True
206 elif action_type == "DeleteIntermediatesAction":
207 output_dict = _ensure_output_def(output_name)
208 output_dict["delete_intermediate_datasets"] = True
209 elif action_type == "ChangeDatatypeAction":
210 output_dict = _ensure_output_def(output_name)
211 output_dict['change_datatype'] = action_args
212 handled = True
213 elif action_type == "TagDatasetAction":
214 output_dict = _ensure_output_def(output_name)
215 output_dict["add_tags"] = action_args["tags"].split(",")
216 elif action_type == "RemoveTagDatasetAction":
217 output_dict = _ensure_output_def(output_name)
218 output_dict["remove_tags"] = action_args["tags"].split(",")
219 elif action_type == "ColumnSetAction":
220 output_dict = _ensure_output_def(output_name)
221 output_dict["set_columns"] = action_args
222 else:
223 handled = False
224
225 if handled:
226 to_remove_keys.append(post_job_action_key)
227
228 for to_remove in to_remove_keys:
229 del post_job_actions[to_remove]
230
231 if post_job_actions:
232 to_format2_step["post_job_actions"] = post_job_actions
233
234
235 def _to_source(has_output_name, label_map, output_id=None):
236 output_id = output_id if output_id is not None else has_output_name['id']
237 output_id = str(output_id)
238 output_name = has_output_name['output_name']
239 output_label = label_map.get(output_id) or output_id
240 if output_name == "output":
241 source = output_label
242 else:
243 source = "%s/%s" % (output_label, output_name)
244 return source
245
246
247 def main(argv=None):
248 """Entry point for script to convert native workflows to Format 2."""
249 if argv is None:
250 argv = sys.argv[1:]
251
252 args = _parser().parse_args(argv)
253
254 format2_path = args.input_path
255 output_path = args.output_path or (format2_path + ".gxwf.yml")
256 with open(format2_path, "r") as f:
257 native_workflow_dict = json.load(f)
258
259 as_dict = from_galaxy_native(native_workflow_dict)
260 with open(output_path, "w") as f:
261 ordered_dump(as_dict, f)
262
263
264 def _parser():
265 parser = argparse.ArgumentParser(description=SCRIPT_DESCRIPTION)
266 parser.add_argument('input_path', metavar='INPUT', type=str,
267 help='input workflow path (.ga)')
268 parser.add_argument('output_path', metavar='OUTPUT', type=str, nargs="?",
269 help='output workflow path (.gxfw.yml)')
270 return parser
271
272
273 __all__ = (
274 'from_galaxy_native',
275 'main',
276 )