Handling output files generated inside an electron #1627
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This is copied from #1592, which included some useful advice from @santoshkumarradha that I want to make more visible. The original question was essentially: how do you deal with handling output files generated inside an electron such that they don't overwrite one another in the working directory? |
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EDIT: See #1628 and the PRs linked therein for an updated answer! @santoshkumarradha's answer was: When manually reading or writing files within Covalent, it's always a good practice to use absolute paths. By doing so, you can avoid potential confusion or issues related to file handling. Here's an example that demonstrates the use of absolute paths in a Covalent workflow: import covalent as ct
from pathlib import Path
@ct.electron
def job(val1, val2,file):
with open(file, "w") as w:
w.write(str(val1 + val2))
return "Done!"
@ct.lattice
def workflow(input_file, val1, val2, val3, val4):
job1 = job(val1, val2,input_file)
return job1
input_file = Path("./example1.txt").absolute()
dispatch_id = ct.dispatch(workflow)(input_file, 1, 2, 3, 4)
result = ct.get_result(dispatch_id, wait=True)
print(result) For chemistry codes that generate output files during calculations, it is crucial to ensure that these files are not overwritten when multiple calculations are executed simultaneously. To achieve this, you can create separate folders for each calculation and use a decorator that changes the working directory to the desired absolute path before executing the function. import covalent as ct
from pathlib import Path
import os
from functools import wraps
def change_dir_and_execute(directory):
def decorator(func):
@wraps(func)
def wrapper(*args, **kwargs):
current_dir = os.getcwd()
try:
os.chdir(directory)
result = func(*args, **kwargs)
finally:
os.chdir(current_dir)
return result
return wrapper
return decorator
path=Path(".").absolute()
@ct.electron
@change_dir_and_execute(path)
def job(val1, val2,file):
with open(file, "w") as w:
w.write(str(val1 + val2))
return Path(".").absolute()
@ct.lattice
def workflow(file, val1, val2, val3, val4):
job1 = job(val1, val2,file)
return job1
file="example.txt"
dispatch_id = ct.dispatch(workflow)(file, 1, 2, 3, 4)
result = ct.get_result(dispatch_id, wait=True)
print(result) In this example, the Electron is executed in the specified path (the current directory), ensuring that output files from different calculations are written to separate directories and not overwritten. |
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EDIT: See #1628 and the PRs linked therein for an updated answer!
@santoshkumarradha's answer was:
When manually reading or writing files within Covalent, it's always a good practice to use absolute paths. By doing so, you can avoid potential confusion or issues related to file handling.
Here's an example that demonstrates the use of absolute paths in a Covalent workflow: