Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Add executor test #237

Merged
merged 4 commits into from
Aug 1, 2024
Merged

Add executor test #237

merged 4 commits into from
Aug 1, 2024

Conversation

jan-janssen
Copy link
Member

@jan-janssen jan-janssen commented Aug 1, 2024

Summary by CodeRabbit

  • New Features

    • Introduced unit testing for parallel execution of computational tasks in LAMMPS simulations.
    • Added a new test case to validate the functionality of the Executor class with a focus on energy retrieval from a bulk aluminum structure.
  • Bug Fixes

    • Enhanced reliability of parallel task execution in the computational workflow through improved testing.

Copy link

coderabbitai bot commented Aug 1, 2024

Walkthrough

The recent changes introduce a new unit test for the Executor class, specifically testing the execution of LAMMPS simulations through the calc_lmp function. This test ensures that computational tasks are executed in parallel correctly, validating the integration of simulation setups and confirming that the results align with expected outcomes, thereby enhancing the reliability of the codebase.

Changes

Files Change Summary
tests/test_executor.py Added unit test for Executor class, including a new calc_lmp function and TestWithExecutor class with a test method to validate LAMMPS simulation execution.

Poem

🐇 In the meadow where bunnies hop,
A new test blooms, we just can't stop!
With LAMMPS in tow, our tasks aligned,
Parallel dreams now intertwined.
Hooray for tests, they're quite the delight,
In code we trust, as day turns to night! 🌟


Thank you for using CodeRabbit. We offer it for free to the OSS community and would appreciate your support in helping us grow. If you find it useful, would you consider giving us a shout-out on your favorite social media?

Share
Tips

Chat

There are 3 ways to chat with CodeRabbit:

  • Review comments: Directly reply to a review comment made by CodeRabbit. Example:
    • I pushed a fix in commit <commit_id>.
    • Generate unit testing code for this file.
    • Open a follow-up GitHub issue for this discussion.
  • Files and specific lines of code (under the "Files changed" tab): Tag @coderabbitai in a new review comment at the desired location with your query. Examples:
    • @coderabbitai generate unit testing code for this file.
    • @coderabbitai modularize this function.
  • PR comments: Tag @coderabbitai in a new PR comment to ask questions about the PR branch. For the best results, please provide a very specific query, as very limited context is provided in this mode. Examples:
    • @coderabbitai generate interesting stats about this repository and render them as a table.
    • @coderabbitai show all the console.log statements in this repository.
    • @coderabbitai read src/utils.ts and generate unit testing code.
    • @coderabbitai read the files in the src/scheduler package and generate a class diagram using mermaid and a README in the markdown format.
    • @coderabbitai help me debug CodeRabbit configuration file.

Note: Be mindful of the bot's finite context window. It's strongly recommended to break down tasks such as reading entire modules into smaller chunks. For a focused discussion, use review comments to chat about specific files and their changes, instead of using the PR comments.

CodeRabbit Commands (invoked as PR comments)

  • @coderabbitai pause to pause the reviews on a PR.
  • @coderabbitai resume to resume the paused reviews.
  • @coderabbitai review to trigger an incremental review. This is useful when automatic reviews are disabled for the repository.
  • @coderabbitai full review to do a full review from scratch and review all the files again.
  • @coderabbitai summary to regenerate the summary of the PR.
  • @coderabbitai resolve resolve all the CodeRabbit review comments.
  • @coderabbitai configuration to show the current CodeRabbit configuration for the repository.
  • @coderabbitai help to get help.

Additionally, you can add @coderabbitai ignore anywhere in the PR description to prevent this PR from being reviewed.

CodeRabbit Configuration File (.coderabbit.yaml)

  • You can programmatically configure CodeRabbit by adding a .coderabbit.yaml file to the root of your repository.
  • Please see the configuration documentation for more information.
  • If your editor has YAML language server enabled, you can add the path at the top of this file to enable auto-completion and validation: # yaml-language-server: $schema=https://coderabbit.ai/integrations/schema.v2.json

Documentation and Community

  • Visit our Documentation for detailed information on how to use CodeRabbit.
  • Join our Discord Community to get help, request features, and share feedback.
  • Follow us on X/Twitter for updates and announcements.

Copy link

@coderabbitai coderabbitai bot left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Actionable comments posted: 3

Review details

Configuration used: CodeRabbit UI
Review profile: CHILL

Commits

Files that changed from the base of the PR and between 9c68f4c and ff19b5e.

Files selected for processing (1)
  • tests/test_executor.py (1 hunks)

Comment on lines +7 to +9
def calc_lmp(structure):
from mpi4py import MPI

Copy link

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Move import statement outside the function.

Importing MPI inside the function might affect performance. It's better to move it to the top of the file.

- def calc_lmp(structure):
-     from mpi4py import MPI
+ from mpi4py import MPI
+ def calc_lmp(structure):
Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change
def calc_lmp(structure):
from mpi4py import MPI
from mpi4py import MPI
def calc_lmp(structure):

Comment on lines +10 to +18
lmp = LammpsASELibrary(
working_directory=None,
cores=1,
comm=MPI.COMM_SELF,
logger=None,
log_file=None,
library=None,
diable_log_file=True,
)
Copy link

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Fix typo in parameter name.

The parameter diable_log_file should be disable_log_file.

-        diable_log_file=True,
+        disable_log_file=True,
Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change
lmp = LammpsASELibrary(
working_directory=None,
cores=1,
comm=MPI.COMM_SELF,
logger=None,
log_file=None,
library=None,
diable_log_file=True,
)
lmp = LammpsASELibrary(
working_directory=None,
cores=1,
comm=MPI.COMM_SELF,
logger=None,
log_file=None,
library=None,
disable_log_file=True,
)

Comment on lines 38 to 43
class TestWithExecutor(unittest.TestCase):
def test_executor(self):
with Executor(max_cores=2, backend="local", hostname_localhost=True) as exe:
future = exe.submit(calc_lmp, bulk("Al", cubic=True).repeat([2, 2, 2]))
energy = future.result()
self.assertAlmostEqual(energy, -0.04342932384411344)
Copy link

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Avoid hardcoding expected values in tests.

Hardcoding the expected energy value might not be reliable across different environments. Consider using a range or a tolerance level instead.

-        self.assertAlmostEqual(energy, -0.04342932384411344)
+        expected_energy = -0.04342932384411344
+        tolerance = 1e-5
+        self.assertAlmostEqual(energy, expected_energy, delta=tolerance)
Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change
class TestWithExecutor(unittest.TestCase):
def test_executor(self):
with Executor(max_cores=2, backend="local", hostname_localhost=True) as exe:
future = exe.submit(calc_lmp, bulk("Al", cubic=True).repeat([2, 2, 2]))
energy = future.result()
self.assertAlmostEqual(energy, -0.04342932384411344)
class TestWithExecutor(unittest.TestCase):
def test_executor(self):
with Executor(max_cores=2, backend="local", hostname_localhost=True) as exe:
future = exe.submit(calc_lmp, bulk("Al", cubic=True).repeat([2, 2, 2]))
energy = future.result()
expected_energy = -0.04342932384411344
tolerance = 1e-5
self.assertAlmostEqual(energy, expected_energy, delta=tolerance)

@jan-janssen jan-janssen merged commit d2895e4 into main Aug 1, 2024
14 checks passed
@jan-janssen jan-janssen deleted the executor_test branch August 1, 2024 05:20
Copy link

@coderabbitai coderabbitai bot left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Actionable comments posted: 0

Review details

Configuration used: CodeRabbit UI
Review profile: CHILL

Commits

Files that changed from the base of the PR and between ff19b5e and 34525c9.

Files selected for processing (1)
  • tests/test_executor.py (1 hunks)
Files skipped from review as they are similar to previous changes (1)
  • tests/test_executor.py

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

1 participant