Add run_and_add_step() method in RenkuWorkflowBuilder and improve docstrings. The new method runs step and record renku metadata in a centralized workflow file in yaml format.

This commit is contained in:
2025-09-23 16:14:23 +02:00
parent 3663fce07c
commit 3140e1b05e

View File

@@ -1,5 +1,22 @@
import yaml
import os
import sys
import inspect
try:
thisFilePath = os.path.abspath(__file__)
print(thisFilePath)
except NameError:
print("[Notice] The __file__ attribute is unavailable in this environment (e.g., Jupyter or IDLE).")
print("When using a terminal, make sure the working directory is set to the script's location to prevent path issues (for the DIMA submodule)")
#print("Otherwise, path to submodule DIMA may not be resolved properly.")
thisFilePath = os.getcwd() # Use current directory or specify a default
projectPath = os.path.normpath(os.path.join(thisFilePath, "..", "..")) # Move up to project root
if projectPath not in sys.path:
sys.path.insert(0,projectPath)
import yaml
from collections import OrderedDict
def generate_command(base_command='python', inputs=None, outputs=None, parameters=None):
@@ -12,85 +29,170 @@ def generate_command(base_command='python', inputs=None, outputs=None, parameter
]
return f"{base_command} {' '.join(placeholders)}"
class RenkuWorkflowBuilder:
class RenkuWorkflowBuilder:
"""
Build and manage a Renku workflow definition (YAML-based).
Steps can be added, merged, serialized, and reloaded.
"""
def __init__(self, name):
"""
Initialize a workflow builder.
Args:
name (str): Workflow name.
"""
self.name = name
self.directory_path = os.path.join(projectPath, 'workflows').replace(os.sep, '/')
self.steps = OrderedDict()
def add_step(self, step_name, base_command, inputs=None, outputs=None, parameters=None):
command = generate_command(base_command, inputs, outputs,parameters)
step = {
'command': command
}
if inputs:
step['inputs'] = [{key: value} for key, value in inputs]
if outputs:
step['outputs'] = [{key: value} for key, value in outputs]
if parameters:
step['parameters'] = [{key: value} for key, value in parameters]
self.steps[step_name] = step
@staticmethod
def _hash_content(step_def):
"""
Compute a stable hash of a step definition (for collision detection).
"""
import json, hashlib
content_str = json.dumps(step_def, sort_keys=True, default=str)
return hashlib.md5(content_str.encode()).hexdigest()
@staticmethod
def _normalize_paths(items : list):
"""
Normalize file paths inside a list of (key, value) pairs.
"""
if not items:
return items
normalized = []
for key, value in items:
if isinstance(value, dict) and 'path' in value:
value['path'] = value['path'].replace(os.sep, '/')
normalized.append({key: value})
return normalized
def create_workflow_file(self):
"""
Create (or update) a workflow YAML file on disk.
"""
self.save_to_file(self.directory_path)
filepath = os.path.join(self.directory_path, f'{self.name}.yaml').replace(os.sep, '/')
if os.path.exists(filepath):
print(f'Workflow file created at : {filepath}')
# TODO: add else-case handling (currently silent if file not created)
def add_step(self, step_name, base_command,
inputs : list = [],
outputs : list = [],
parameters : list = []):
"""
Add a step to the workflow and persist it to file.
Normalizes input/output/parameter paths and avoids duplicates.
"""
command = generate_command(base_command, inputs, outputs, parameters)
step = {'command': command}
step['inputs'] = self._normalize_paths(inputs)
step['outputs'] = self._normalize_paths(outputs)
step['parameters'] = self._normalize_paths(parameters)
# Deduplicate or version step
if step_name not in self.steps:
self.steps[step_name] = step
elif self.steps[step_name] != step:
content_hash = self._hash_content(step)
hashed_name = f"{step_name}_{content_hash[:8]}"
print(f"[Added] Step '{step_name}' as '{hashed_name}'")
self.steps[hashed_name] = step
self.save_to_file(self.directory_path)
def run_and_add_step(self, step, *args, **kwargs):
"""
Run a step function, collect its provenance, and add it to the workflow.
"""
file_path = inspect.getfile(step)
step_name = os.path.splitext(os.path.basename(file_path))[0]
provenance = step(*args, **kwargs)
# TODO: validate provenance has 'inputs', 'outputs', 'parameters'
self.add_step(step_name, "python",
provenance["inputs"],
provenance["outputs"],
provenance["parameters"])
return provenance
@staticmethod
def parse_workflow(yaml_content: str):
"""
Parse YAML content and return a populated RenkuWorkflowBuilder.
"""
data = yaml.safe_load(yaml_content)
builder = RenkuWorkflowBuilder(data['name'])
for step_name, step_def in data['steps'].items():
command = step_def.get('command')
inputs = step_def.get('inputs', [])
outputs = step_def.get('outputs', [])
parameters = step_def.get('parameters', [])
builder.steps[step_name] = {
'command': command,
'inputs': inputs,
'outputs': outputs,
'parameters': parameters
'command': step_def.get('command'),
'inputs': [{k: v} for item in step_def.get('inputs', []) for k, v in item.items()] if step_def.get('inputs') else [],
'outputs': [{k: v} for item in step_def.get('outputs', []) for k, v in item.items()] if step_def.get('outputs') else [],
'parameters': [{k: v} for item in step_def.get('parameters', []) for k, v in item.items()] if step_def.get('parameters') else []
}
return builder
@staticmethod
def from_file(filepath):
"""
Load a workflow from file, or return a new empty one if file does not exist.
"""
if not os.path.exists(filepath):
return None
workflow_name = os.path.splitext(os.path.basename(filepath))[0]
return RenkuWorkflowBuilder(name=workflow_name)
with open(filepath, 'r') as f:
return RenkuWorkflowBuilder.parse_workflow(f.read())
def to_dict(self):
"""
Return workflow definition as a dict, normalizing paths in inputs/outputs.
"""
for step_name, step_value in self.steps.items():
for segment in ['inputs','outputs']:
for item in step_value.get(segment,[]):# ['inputs', 'outputs']:
# Go over either inputs or outputs
for name, value in item.items():
for segment in ['inputs', 'outputs']:
for item in step_value.get(segment, []):
for _, value in item.items():
if not isinstance(value, dict):
raise ValueError(f"Invalid input. Step {step_name} must have {segment} of either dict or str type.")
if isinstance(value, str):
continue
if isinstance(value, dict) and 'path' in value.keys():
raise ValueError(
f"Invalid input. Step {step_name} must have {segment} as dict or str type."
)
if 'path' in value:
value['path'] = value['path'].replace(os.sep, '/')
return {
'name': self.name,
'steps': { key : value for key, value in self.steps.items()}
}
return {'name': self.name, 'steps': dict(self.steps)}
def to_yaml(self):
"""
Serialize workflow definition to YAML.
"""
return yaml.dump(self.to_dict(), sort_keys=False)
def append_from(self, other, force=False):
"""
Merge steps from another workflow into this one.
If step content differs, a hashed suffix is added.
"""
if other.name != self.name:
raise ValueError(f"Cannot merge workflows with different names: {self.name} != {other.name}")
curr_steps = self.steps.copy()
for step_name, step_def in other.steps.items():
if step_name in self.steps:
if force:
print(f"[Overwriting] Step '{step_name}' was overwritten as 'force=True'.")
self.steps[step_name] = step_def
else:
print(f"[Skipping] Step '{step_name}' already exists. Use 'force=True' to overwrite.")
else:
if step_name not in curr_steps:
self.steps[step_name] = step_def
elif self.steps[step_name] != step_def:
content_hash = self._hash_content(step_def)
hashed_name = f"{step_name}_{content_hash[:8]}"
if hashed_name not in self.steps:
self.steps[hashed_name] = step_def
print(f"[Added] Step '{step_name}''{hashed_name}'")
def save_to_file(self, directory):
"""
Save workflow definition to a YAML file in the given directory.
Merges with existing file if present.
"""
os.makedirs(directory, exist_ok=True)
filepath = os.path.join(directory, f"{self.name}.yaml")
@@ -101,7 +203,7 @@ class RenkuWorkflowBuilder:
with open(filepath, 'w') as f:
f.write(existing.to_yaml())
return
# Save as new
with open(filepath, 'w') as f:
f.write(self.to_yaml())