Coverage for python/lsst/pipe/base/pipelineIR.py : 15%

Hot-keys on this page
r m x p toggle line displays
j k next/prev highlighted chunk
0 (zero) top of page
1 (one) first highlighted chunk
1# This file is part of pipe_base.
2#
3# Developed for the LSST Data Management System.
4# This product includes software developed by the LSST Project
5# (http://www.lsst.org).
6# See the COPYRIGHT file at the top-level directory of this distribution
7# for details of code ownership.
8#
9# This program is free software: you can redistribute it and/or modify
10# it under the terms of the GNU General Public License as published by
11# the Free Software Foundation, either version 3 of the License, or
12# (at your option) any later version.
13#
14# This program is distributed in the hope that it will be useful,
15# but WITHOUT ANY WARRANTY; without even the implied warranty of
16# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
17# GNU General Public License for more details.
18#
19# You should have received a copy of the GNU General Public License
20# along with this program. If not, see <http://www.gnu.org/licenses/>.
21from __future__ import annotations
23__all__ = ("ConfigIR", "ContractError", "ContractIR", "InheritIR", "PipelineIR", "TaskIR", "LabeledSubset")
25from collections import Counter
26from collections.abc import Iterable as abcIterable
27from dataclasses import dataclass, field
28from typing import Any, List, Set, Union, Generator, MutableMapping, Optional, Dict
30import copy
31import re
32import os
33import yaml
34import warnings
37class PipelineYamlLoader(yaml.SafeLoader):
38 """This is a specialized version of yaml's SafeLoader. It checks and raises
39 an exception if it finds that there are multiple instances of the same key
40 found inside a pipeline file at a given scope.
41 """
42 def construct_mapping(self, node, deep=False):
43 # do the call to super first so that it can do all the other forms of
44 # checking on this node. If you check the uniqueness of keys first
45 # it would save the work that super does in the case of a failure, but
46 # it might fail in the case that the node was the incorrect node due
47 # to a parsing error, and the resulting exception would be difficult to
48 # understand.
49 mapping = super().construct_mapping(node, deep)
50 # Check if there are any duplicate keys
51 all_keys = Counter(key_node.value for key_node, _ in node.value)
52 duplicates = {k for k, i in all_keys.items() if i != 1}
53 if duplicates:
54 raise KeyError("Pipeline files must not have duplicated keys, "
55 f"{duplicates} appeared multiple times")
56 return mapping
59class ContractError(Exception):
60 """An exception that is raised when a pipeline contract is not satisfied
61 """
62 pass
65@dataclass
66class ContractIR:
67 """Intermediate representation of contracts read from a pipeline yaml file.
68 """
69 contract: str
70 """A string of python code representing one or more conditions on configs
71 in a pipeline. This code-as-string should, once evaluated, should be True
72 if the configs are fine, and False otherwise.
73 """
74 msg: Union[str, None] = None
75 """An optional message to be shown to the user if a contract fails
76 """
78 def to_primitives(self) -> dict:
79 """Convert to a representation used in yaml serialization
80 """
81 accumulate = {"contract": self.contract}
82 if self.msg is not None:
83 accumulate['msg'] = self.msg
84 return accumulate
86 def __eq__(self, other: "ContractIR"):
87 if not isinstance(other, ContractIR):
88 return False
89 elif self.contract == other.contract and self.msg == other.msg:
90 return True
91 else:
92 return False
95@dataclass
96class LabeledSubset:
97 """Intermediate representation of named subset of task labels read from
98 a pipeline yaml file.
99 """
100 label: str
101 """The label used to identify the subset of task labels.
102 """
103 subset: Set[str]
104 """A set of task labels contained in this subset.
105 """
106 description: Optional[str]
107 """A description of what this subset of tasks is intended to do
108 """
110 @staticmethod
111 def from_primatives(label: str, value: Union[List[str], dict]) -> LabeledSubset:
112 """Generate `LabeledSubset` objects given a properly formatted object
113 that as been created by a yaml loader.
115 Parameters
116 ----------
117 label : `str`
118 The label that will be used to identify this labeled subset.
119 value : `list` of `str` or `dict`
120 Object returned from loading a labeled subset section from a yaml
121 document.
123 Returns
124 -------
125 labeledSubset : `LabeledSubset`
126 A `LabeledSubset` object build from the inputs.
128 Raises
129 ------
130 ValueError
131 Raised if the value input is not properly formatted for parsing
132 """
133 if isinstance(value, MutableMapping):
134 subset = value.pop("subset", None)
135 if subset is None:
136 raise ValueError("If a labeled subset is specified as a mapping, it must contain the key "
137 "'subset'")
138 description = value.pop("description", None)
139 elif isinstance(value, abcIterable):
140 subset = value
141 description = None
142 else:
143 raise ValueError(f"There was a problem parsing the labeled subset {label}, make sure the "
144 "definition is either a valid yaml list, or a mapping with keys "
145 "(subset, description) where subset points to a yaml list, and description is "
146 "associated with a string")
147 return LabeledSubset(label, set(subset), description)
149 def to_primitives(self) -> dict:
150 """Convert to a representation used in yaml serialization
151 """
152 accumulate: Dict[str, Any] = {"subset": list(self.subset)}
153 if self.description is not None:
154 accumulate["description"] = self.description
155 return accumulate
158@dataclass
159class ConfigIR:
160 """Intermediate representation of configurations read from a pipeline yaml
161 file.
162 """
163 python: Union[str, None] = None
164 """A string of python code that is used to modify a configuration. This can
165 also be None if there are no modifications to do.
166 """
167 dataId: Union[dict, None] = None
168 """A dataId that is used to constrain these config overrides to only quanta
169 with matching dataIds. This field can be None if there is no constraint.
170 This is currently an unimplemented feature, and is placed here for future
171 use.
172 """
173 file: List[str] = field(default_factory=list)
174 """A list of paths which points to a file containing config overrides to be
175 applied. This value may be an empty list if there are no overrides to
176 apply.
177 """
178 rest: dict = field(default_factory=dict)
179 """This is a dictionary of key value pairs, where the keys are strings
180 corresponding to qualified fields on a config to override, and the values
181 are strings representing the values to apply.
182 """
184 def to_primitives(self) -> dict:
185 """Convert to a representation used in yaml serialization
186 """
187 accumulate = {}
188 for name in ("python", "dataId", "file"):
189 # if this attribute is thruthy add it to the accumulation
190 # dictionary
191 if getattr(self, name):
192 accumulate[name] = getattr(self, name)
193 # Add the dictionary containing the rest of the config keys to the
194 # # accumulated dictionary
195 accumulate.update(self.rest)
196 return accumulate
198 def maybe_merge(self, other_config: "ConfigIR") -> Generator["ConfigIR", None, None]:
199 """Merges another instance of a `ConfigIR` into this instance if
200 possible. This function returns a generator that is either self
201 if the configs were merged, or self, and other_config if that could
202 not be merged.
204 Parameters
205 ----------
206 other_config : `ConfigIR`
207 An instance of `ConfigIR` to merge into this instance.
209 Returns
210 -------
211 Generator : `ConfigIR`
212 A generator containing either self, or self and other_config if
213 the configs could be merged or not respectively.
214 """
215 # Verify that the config blocks can be merged
216 if self.dataId != other_config.dataId or self.python or other_config.python or\
217 self.file or other_config.file:
218 yield from (self, other_config)
219 return
221 # create a set of all keys, and verify two keys do not have different
222 # values
223 key_union = self.rest.keys() & other_config.rest.keys()
224 for key in key_union:
225 if self.rest[key] != other_config.rest[key]:
226 yield from (self, other_config)
227 return
228 self.rest.update(other_config.rest)
230 # Combine the lists of override files to load
231 self_file_set = set(self.file)
232 other_file_set = set(other_config.file)
233 self.file = list(self_file_set.union(other_file_set))
235 yield self
237 def __eq__(self, other: "ConfigIR"):
238 if not isinstance(other, ConfigIR):
239 return False
240 elif all(getattr(self, attr) == getattr(other, attr) for attr in
241 ("python", "dataId", "file", "rest")):
242 return True
243 else:
244 return False
247@dataclass
248class TaskIR:
249 """Intermediate representation of tasks read from a pipeline yaml file.
250 """
251 label: str
252 """An identifier used to refer to a task.
253 """
254 klass: str
255 """A string containing a fully qualified python class to be run in a
256 pipeline.
257 """
258 config: Union[List[ConfigIR], None] = None
259 """List of all configs overrides associated with this task, and may be
260 `None` if there are no config overrides.
261 """
263 def to_primitives(self) -> dict:
264 """Convert to a representation used in yaml serialization
265 """
266 accumulate = {'class': self.klass}
267 if self.config:
268 accumulate['config'] = [c.to_primitives() for c in self.config]
269 return accumulate
271 def add_or_update_config(self, other_config: ConfigIR):
272 """Adds a `ConfigIR` to this task if one is not present. Merges configs
273 if there is a `ConfigIR` present and the dataId keys of both configs
274 match, otherwise adds a new entry to the config list. The exception to
275 the above is that if either the last config or other_config has a
276 python block, then other_config is always added, as python blocks can
277 modify configs in ways that cannot be predicted.
279 Parameters
280 ----------
281 other_config : `ConfigIR`
282 A `ConfigIR` instance to add or merge into the config attribute of
283 this task.
284 """
285 if not self.config:
286 self.config = [other_config]
287 return
288 self.config.extend(self.config.pop().maybe_merge(other_config))
290 def __eq__(self, other: "TaskIR"):
291 if not isinstance(other, TaskIR):
292 return False
293 elif all(getattr(self, attr) == getattr(other, attr) for attr in
294 ("label", "klass", "config")):
295 return True
296 else:
297 return False
300@dataclass
301class InheritIR:
302 """An intermediate representation of inherited pipelines
303 """
304 location: str
305 """This is the location of the pipeline to inherit. The path should be
306 specified as an absolute path. Environment variables may be used in the
307 path and should be specified as a python string template, with the name of
308 the environment variable inside braces.
309 """
310 include: Union[List[str], None] = None
311 """List of tasks that should be included when inheriting this pipeline.
312 Either the include or exclude attributes may be specified, but not both.
313 """
314 exclude: Union[List[str], None] = None
315 """List of tasks that should be excluded when inheriting this pipeline.
316 Either the include or exclude attributes may be specified, but not both.
317 """
318 importContracts: bool = True
319 """Boolean attribute to dictate if contracts should be inherited with the
320 pipeline or not.
321 """
323 def toPipelineIR(self) -> "PipelineIR":
324 """Convert to a representation used in yaml serialization
325 """
326 if self.include and self.exclude:
327 raise ValueError("Both an include and an exclude list cant be specified"
328 " when declaring a pipeline import")
329 tmp_pipeline = PipelineIR.from_file(os.path.expandvars(self.location))
330 if tmp_pipeline.instrument is not None:
331 warnings.warn("Any instrument definitions in imported pipelines are ignored. "
332 "if an instrument is desired please define it in the top most pipeline")
334 included_labels = set()
335 for label in tmp_pipeline.tasks:
336 if (self.include and label in self.include) or (self.exclude and label not in self.exclude)\
337 or (self.include is None and self.exclude is None):
338 included_labels.add(label)
340 # Handle labeled subsets being specified in the include or exclude
341 # list, adding or removing labels.
342 if self.include is not None:
343 subsets_in_include = tmp_pipeline.labeled_subsets.keys() & self.include
344 for label in subsets_in_include:
345 included_labels.update(tmp_pipeline.labeled_subsets[label].subset)
347 elif self.exclude is not None:
348 subsets_in_exclude = tmp_pipeline.labeled_subsets.keys() & self.exclude
349 for label in subsets_in_exclude:
350 included_labels.difference_update(tmp_pipeline.labeled_subsets[label].subset)
352 tmp_pipeline = tmp_pipeline.subset_from_labels(included_labels)
354 if not self.importContracts:
355 tmp_pipeline.contracts = []
357 return tmp_pipeline
359 def __eq__(self, other: "InheritIR"):
360 if not isinstance(other, InheritIR):
361 return False
362 elif all(getattr(self, attr) == getattr(other, attr) for attr in
363 ("location", "include", "exclude", "importContracts")):
364 return True
365 else:
366 return False
369class PipelineIR:
370 """Intermediate representation of a pipeline definition
372 Parameters
373 ----------
374 loaded_yaml : `dict`
375 A dictionary which matches the structure that would be produced by a
376 yaml reader which parses a pipeline definition document
378 Raises
379 ------
380 ValueError :
381 - If a pipeline is declared without a description
382 - If no tasks are declared in a pipeline, and no pipelines are to be
383 inherited
384 - If more than one instrument is specified
385 - If more than one inherited pipeline share a label
386 """
387 def __init__(self, loaded_yaml):
388 # Check required fields are present
389 if "description" not in loaded_yaml:
390 raise ValueError("A pipeline must be declared with a description")
391 if "tasks" not in loaded_yaml and "inherits" not in loaded_yaml:
392 raise ValueError("A pipeline must be declared with one or more tasks")
394 # These steps below must happen in this call order
396 # Process pipeline description
397 self.description = loaded_yaml.pop("description")
399 # Process tasks
400 self._read_tasks(loaded_yaml)
402 # Process instrument keys
403 inst = loaded_yaml.pop("instrument", None)
404 if isinstance(inst, list):
405 raise ValueError("Only one top level instrument can be defined in a pipeline")
406 self.instrument = inst
408 # Process any contracts
409 self._read_contracts(loaded_yaml)
411 # Process any named label subsets
412 self._read_labeled_subsets(loaded_yaml)
414 # Process any inherited pipelines
415 self._read_inherits(loaded_yaml)
417 # verify named subsets, must be done after inheriting
418 self._verify_labeled_subsets()
420 def _read_contracts(self, loaded_yaml):
421 """Process the contracts portion of the loaded yaml document
423 Parameters
424 ---------
425 loaded_yaml : `dict`
426 A dictionary which matches the structure that would be produced by
427 a yaml reader which parses a pipeline definition document
428 """
429 loaded_contracts = loaded_yaml.pop("contracts", [])
430 if isinstance(loaded_contracts, str):
431 loaded_contracts = [loaded_contracts]
432 self.contracts = []
433 for contract in loaded_contracts:
434 if isinstance(contract, dict):
435 self.contracts.append(ContractIR(**contract))
436 if isinstance(contract, str):
437 self.contracts.append(ContractIR(contract=contract))
439 def _read_labeled_subsets(self, loaded_yaml: dict):
440 """Process the subsets portion of the loaded yaml document
442 Parameters
443 ----------
444 loaded_yaml: `MutableMapping`
445 A dictionary which matches the structure that would be produced
446 by a yaml reader which parses a pipeline definition document
447 """
448 loaded_subsets = loaded_yaml.pop("subsets", {})
449 self.labeled_subsets = {}
450 if not loaded_subsets and "subset" in loaded_yaml:
451 raise ValueError("Top level key should be subsets and not subset, add an s")
452 for key, value in loaded_subsets.items():
453 self.labeled_subsets[key] = LabeledSubset.from_primatives(key, value)
455 def _verify_labeled_subsets(self):
456 """Verifies that all the labels in each named subset exist within the
457 pipeline.
458 """
459 # Verify that all labels defined in a labeled subset are in the
460 # Pipeline
461 for labeled_subset in self.labeled_subsets.values():
462 if not labeled_subset.subset.issubset(self.tasks.keys()):
463 raise ValueError(f"Labels {labeled_subset.subset - self.tasks.keys()} were not found in the "
464 "declared pipeline")
465 # Verify subset labels are not already task labels
466 label_intersection = self.labeled_subsets.keys() & self.tasks.keys()
467 if label_intersection:
468 raise ValueError(f"Labeled subsets can not use the same label as a task: {label_intersection}")
470 def _read_inherits(self, loaded_yaml):
471 """Process the inherits portion of the loaded yaml document
473 Parameters
474 ---------
475 loaded_yaml : `dict`
476 A dictionary which matches the structure that would be produced by
477 a yaml reader which parses a pipeline definition document
478 """
479 def process_args(argument: Union[str, dict]) -> dict:
480 if isinstance(argument, str):
481 return {"location": argument}
482 elif isinstance(argument, dict):
483 if "exclude" in argument and isinstance(argument["exclude"], str):
484 argument["exclude"] = [argument["exclude"]]
485 if "include" in argument and isinstance(argument["include"], str):
486 argument["include"] = [argument["include"]]
487 return argument
488 tmp_inherit = loaded_yaml.pop("inherits", None)
489 if tmp_inherit is None:
490 self.inherits = []
491 elif isinstance(tmp_inherit, list):
492 self.inherits = [InheritIR(**process_args(args)) for args in tmp_inherit]
493 else:
494 self.inherits = [InheritIR(**process_args(tmp_inherit))]
496 # integrate any imported pipelines
497 accumulate_tasks = {}
498 accumulate_labeled_subsets = {}
499 for other_pipeline in self.inherits:
500 tmp_IR = other_pipeline.toPipelineIR()
501 if accumulate_tasks.keys() & tmp_IR.tasks.keys():
502 raise ValueError("Task labels in the imported pipelines must "
503 "be unique")
504 accumulate_tasks.update(tmp_IR.tasks)
505 self.contracts.extend(tmp_IR.contracts)
506 # verify that tmp_IR has unique labels for named subset among
507 # existing labeled subsets, and with existing task labels.
508 overlapping_subsets = accumulate_labeled_subsets.keys() & tmp_IR.labeled_subsets.keys()
509 task_subset_overlap = ((accumulate_labeled_subsets.keys() | tmp_IR.labeled_subsets.keys())
510 & accumulate_tasks.keys())
511 if overlapping_subsets or task_subset_overlap:
512 raise ValueError("Labeled subset names must be unique amongst imports in both labels and "
513 f" named Subsets. Duplicate: {overlapping_subsets | task_subset_overlap}")
514 accumulate_labeled_subsets.update(tmp_IR.labeled_subsets)
516 # verify that any accumulated labeled subsets dont clash with a label
517 # from this pipeline
518 if accumulate_labeled_subsets.keys() & self.tasks.keys():
519 raise ValueError("Labeled subset names must be unique amongst imports in both labels and "
520 " named Subsets")
521 # merge in the named subsets for self so this document can override any
522 # that have been delcared
523 accumulate_labeled_subsets.update(self.labeled_subsets)
524 self.labeled_subsets = accumulate_labeled_subsets
526 # merge the dict of label:TaskIR objects, preserving any configs in the
527 # imported pipeline if the labels point to the same class
528 for label, task in self.tasks.items():
529 if label not in accumulate_tasks:
530 accumulate_tasks[label] = task
531 elif accumulate_tasks[label].klass == task.klass:
532 if task.config is not None:
533 for config in task.config:
534 accumulate_tasks[label].add_or_update_config(config)
535 else:
536 accumulate_tasks[label] = task
537 self.tasks = accumulate_tasks
539 def _read_tasks(self, loaded_yaml):
540 """Process the tasks portion of the loaded yaml document
542 Parameters
543 ---------
544 loaded_yaml : `dict`
545 A dictionary which matches the structure that would be produced by
546 a yaml reader which parses a pipeline definition document
547 """
548 self.tasks = {}
549 tmp_tasks = loaded_yaml.pop("tasks", None)
550 if tmp_tasks is None:
551 tmp_tasks = {}
553 for label, definition in tmp_tasks.items():
554 if isinstance(definition, str):
555 definition = {"class": definition}
556 config = definition.get('config', None)
557 if config is None:
558 task_config_ir = None
559 else:
560 if isinstance(config, dict):
561 config = [config]
562 task_config_ir = []
563 for c in config:
564 file = c.pop("file", None)
565 if file is None:
566 file = []
567 elif not isinstance(file, list):
568 file = [file]
569 task_config_ir.append(ConfigIR(python=c.pop("python", None),
570 dataId=c.pop("dataId", None),
571 file=file,
572 rest=c))
573 self.tasks[label] = TaskIR(label, definition["class"], task_config_ir)
575 def _remove_contracts(self, label: str):
576 """Remove any contracts that contain the given label
578 String comparison used in this way is not the most elegant and may
579 have issues, but it is the only feasible way when users can specify
580 contracts with generic strings.
581 """
582 new_contracts = []
583 for contract in self.contracts:
584 # match a label that is not preceded by an ASCII identifier, or
585 # is the start of a line and is followed by a dot
586 if re.match(f".*([^A-Za-z0-9_]|^){label}[.]", contract.contract):
587 continue
588 new_contracts.append(contract)
589 self.contracts = new_contracts
591 def subset_from_labels(self, labelSpecifier: Set[str]) -> PipelineIR:
592 """Subset a pipelineIR to contain only labels specified in
593 labelSpecifier.
595 Parameters
596 ----------
597 labelSpecifier : `set` of `str`
598 Set containing labels that describes how to subset a pipeline.
600 Returns
601 -------
602 pipeline : `PipelineIR`
603 A new pipelineIR object that is a subset of the old pipelineIR
605 Raises
606 ------
607 ValueError
608 Raised if there is an issue with specified labels
610 Notes
611 -----
612 This method attempts to prune any contracts that contain labels which
613 are not in the declared subset of labels. This pruning is done using a
614 string based matching due to the nature of contracts and may prune more
615 than it should. Any labeled subsets defined that no longer have all
616 members of the subset present in the pipeline will be removed from the
617 resulting pipeline.
618 """
620 pipeline = copy.deepcopy(self)
622 # update the label specifier to expand any named subsets
623 toRemove = set()
624 toAdd = set()
625 for label in labelSpecifier:
626 if label in pipeline.labeled_subsets:
627 toRemove.add(label)
628 toAdd.update(pipeline.labeled_subsets[label].subset)
629 labelSpecifier.difference_update(toRemove)
630 labelSpecifier.update(toAdd)
631 # verify all the labels are in the pipeline
632 if not labelSpecifier.issubset(pipeline.tasks.keys()
633 | pipeline.labeled_subsets):
634 difference = labelSpecifier.difference(pipeline.tasks.keys())
635 raise ValueError("Not all supplied labels (specified or named subsets) are in the pipeline "
636 f"definition, extra labels: {difference}")
637 # copy needed so as to not modify while iterating
638 pipeline_labels = set(pipeline.tasks.keys())
639 # Remove the labels from the pipelineIR, and any contracts that contain
640 # those labels (see docstring on _remove_contracts for why this may
641 # cause issues)
642 for label in pipeline_labels:
643 if label not in labelSpecifier:
644 pipeline.tasks.pop(label)
645 pipeline._remove_contracts(label)
647 # create a copy of the object to iterate over
648 labeled_subsets = copy.copy(pipeline.labeled_subsets)
649 # remove any labeled subsets that no longer have a complete set
650 for label, labeled_subset in labeled_subsets.items():
651 if labeled_subset.subset - pipeline.tasks.keys():
652 pipeline.labeled_subsets.pop(label)
654 return pipeline
656 @classmethod
657 def from_string(cls, pipeline_string: str):
658 """Create a `PipelineIR` object from a string formatted like a pipeline
659 document
661 Parameters
662 ----------
663 pipeline_string : `str`
664 A string that is formatted according like a pipeline document
665 """
666 loaded_yaml = yaml.load(pipeline_string, Loader=PipelineYamlLoader)
667 return cls(loaded_yaml)
669 @classmethod
670 def from_file(cls, filename: str):
671 """Create a `PipelineIR` object from the document specified by the
672 input path.
674 Parameters
675 ----------
676 filename : `str`
677 Location of document to use in creating a `PipelineIR` object.
678 """
679 with open(filename, 'r') as f:
680 loaded_yaml = yaml.load(f, Loader=PipelineYamlLoader)
681 return cls(loaded_yaml)
683 def to_file(self, filename: str):
684 """Serialize this `PipelineIR` object into a yaml formatted string and
685 write the output to a file at the specified path.
687 Parameters
688 ----------
689 filename : `str`
690 Location of document to write a `PipelineIR` object.
691 """
692 with open(filename, 'w') as f:
693 yaml.dump(self.to_primitives(), f, sort_keys=False)
695 def to_primitives(self):
696 """Convert to a representation used in yaml serialization
697 """
698 accumulate = {"description": self.description}
699 if self.instrument is not None:
700 accumulate['instrument'] = self.instrument
701 accumulate['tasks'] = {m: t.to_primitives() for m, t in self.tasks.items()}
702 if len(self.contracts) > 0:
703 accumulate['contracts'] = [c.to_primitives() for c in self.contracts]
704 if self.labeled_subsets:
705 accumulate['subsets'] = {k: v.to_primitives() for k, v in self.labeled_subsets.items()}
706 return accumulate
708 def __str__(self) -> str:
709 """Instance formatting as how it would look in yaml representation
710 """
711 return yaml.dump(self.to_primitives(), sort_keys=False)
713 def __repr__(self) -> str:
714 """Instance formatting as how it would look in yaml representation
715 """
716 return str(self)
718 def __eq__(self, other: "PipelineIR"):
719 if not isinstance(other, PipelineIR):
720 return False
721 elif all(getattr(self, attr) == getattr(other, attr) for attr in
722 ("contracts", "tasks", "instrument")):
723 return True
724 else:
725 return False