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.

Sign up for GitHub

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

Updated the checklist for adding a new algorithm #90

Merged
merged 1 commit into from
Dec 20, 2024
Merged

Updated the checklist for adding a new algorithm #90

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
9 changes: 5 additions & 4 deletions CONTRIBUTING.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -121,11 +121,12 @@ The default chunking in nx-parallel is done by slicing the list of nodes (or edg
- The algorithm that you are considering to add to nx-parallel should be in the main networkx repository and it should have the `_dispatchable` decorator. If not, you can consider adding a sequential implementation in networkx first.
- check-list for adding a new function:
- [ ] Add the parallel implementation(make sure API doesn't break), the file structure should be the same as that in networkx.
- [ ] add the function to the `BackendInterface` class in [interface.py](./nx_parallel/interface.py) (take care of the `name` parameter in `_dispatchable` (ref. [docs](https://networkx.org/documentation/latest/reference/backends.html)))
- [ ] Include the `get_chunks` additional parameter. Currently, all algorithms in nx-parallel offer the user to pass their own custom chunks. Unless it is impossible to chunk, please do include this additional parameter.
- [ ] add the function to the `ALGORITHMS` list in [interface.py](./nx_parallel/interface.py). Take care of the `name` parameter in `_dispatchable` for the algorithms with same name but different implementations. The `name` parameter is used distinguish such algorithms in a single namespace. (ref. [docs](https://networkx.org/documentation/latest/reference/backends.html)))
- [ ] update the `__init__.py` files accordingly
- [ ] docstring following the above format
- [ ] run the [timing script](./timing/timing_individual_function.py) to get the performance heatmap
- [ ] add additional test(if any)
- [ ] add benchmark(s) for the new function(ref. the README in benchmarks folder for more details)
- [ ] add additional test, if needed. The smoke tests for the additional parameter `get_chunks` are done [here](https://github.com/networkx/nx-parallel/blob/main/nx_parallel/tests/test_get_chunks.py) together for all the algorithms.
- [ ] run the [timing script](./timing/timing_individual_function.py) to get the performance heatmap (ref. [Issue#51](https://github.com/networkx/nx-parallel/issues/51))
- [ ] add benchmark(s) for the new function(ref. the README in `benchmarks` folder for more details)

Happy contributing! 🎉
Loading