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This project uses GitHub API to fetch information from GitHub using a Python wrapper.
You can find the exhaustive list of supported features in the documentation. For instance, you can retrieve basic information about your pull request as follows:
from ghapi.pulls import Repository, PullRequest
pr = PullRequest(Repository("frgfm", "torch-cam"), 187)
# Get the PR information
pr.get_info()
{'title': 'fix: Fixed zero division for weight computation in gradient based methods',
'created_at': '2022-09-18T17:08:50Z',
'description': 'This PR introduces an `eps` to all divisions in gradient methods to avoid NaNs.\r\n\r\nCloses #186',
'labels': [{'id': 1929545961,
'node_id': 'MDU6TGFiZWwxOTI5NTQ1OTYx',
'url': 'https://api.github.com/repos/frgfm/torch-cam/labels/type:%20bug',
'name': 'type: bug',
'color': 'd73a4a',
'default': False,
'description': "Something isn't working"},
{'id': 1929975543,
'node_id': 'MDU6TGFiZWwxOTI5OTc1NTQz',
'url': 'https://api.github.com/repos/frgfm/torch-cam/labels/ext:%20tests',
'name': 'ext: tests',
'color': 'f7e101',
'default': False,
'description': 'Related to test'},
{'id': 1929975788,
'node_id': 'MDU6TGFiZWwxOTI5OTc1Nzg4',
'url': 'https://api.github.com/repos/frgfm/torch-cam/labels/module:%20methods',
'name': 'module: methods',
'color': 'f7e101',
'default': False,
'description': 'Related to torchcam.methods'}],
'user': 'frgfm',
'mergeable': None,
'changed_files': 3,
'additions': 15,
'deletions': 8,
'base': {'branch': 'main', 'sha': '0a5e06051440e27de6027ec382517a2c71686298'},
'head': {'repo': 'frgfm/torch-cam',
'branch': 'grad-nans',
'sha': 'd49f4a3d847e130e99c3d20311e1450f074fd29f'}}
If you're interested in reviewing the pull request, you might be interested in the code diff:
# Retrieve the code diff
full_diff = pr.get_diff()
# Print the first diff section
print(full_diff["torchcam/methods/gradient.py"][0]["text"])
which yields:
- def _get_weights(self, class_idx: Union[int, List[int]], scores: Tensor, **kwargs: Any) -> List[Tensor]:
+ def _get_weights(
+ self, class_idx: Union[int, List[int]], scores: Tensor, eps: float = 1e-8, **kwargs: Any
+ ) -> List[Tensor]:
Python 3.6 (or higher) and pip/conda are required to install ghapi
.
You can install the last stable release of the package using pypi as follows:
pip install ghapi-client
or using conda:
conda install -c frgfm ghapi-client
Alternatively, if you wish to use the latest features of the project that haven't made their way to a release yet, you can install the package from source:
git clone https://github.com/frgfm/ghapi.git
pip install -e ghapi/.
The full package documentation is available here for detailed specifications.
Feeling like extending the range of supported API feature? Or perhaps submitting a new feature idea? Any sort of contribution is greatly appreciated!
You can find a short guide in CONTRIBUTING
to help grow this project!
Distributed under the Apache 2.0 License. See LICENSE
for more information.
FAQs
Python client for the GitHub API
We found that ghapi-client demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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