Sean MacAvaney
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Browse files- README.md +46 -0
- codesearchnet.py +43 -0
README.md
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---
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pretty_name: '`codesearchnet`'
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viewer: false
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source_datasets: []
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task_categories:
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- text-retrieval
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---
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# Dataset Card for `codesearchnet`
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The `codesearchnet` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
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For more information about the dataset, see the [documentation](https://ir-datasets.com/codesearchnet#codesearchnet).
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# Data
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This dataset provides:
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- `docs` (documents, i.e., the corpus); count=2,070,536
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This dataset is used by: [`codesearchnet_challenge`](https://huggingface.co/datasets/irds/codesearchnet_challenge), [`codesearchnet_test`](https://huggingface.co/datasets/irds/codesearchnet_test), [`codesearchnet_train`](https://huggingface.co/datasets/irds/codesearchnet_train), [`codesearchnet_valid`](https://huggingface.co/datasets/irds/codesearchnet_valid)
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## Usage
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```python
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from datasets import load_dataset
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docs = load_dataset('irds/codesearchnet', 'docs')
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for record in docs:
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record # {'doc_id': ..., 'repo': ..., 'path': ..., 'func_name': ..., 'code': ..., 'language': ...}
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```
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Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
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data in 🤗 Dataset format.
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## Citation Information
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```
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@article{Husain2019CodeSearchNet,
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title={CodeSearchNet Challenge: Evaluating the State of Semantic Code Search},
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author={Hamel Husain and Ho-Hsiang Wu and Tiferet Gazit and Miltiadis Allamanis and Marc Brockschmidt},
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journal={ArXiv},
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year={2019}
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}
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```
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codesearchnet.py
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"""
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""" # TODO
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try:
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import ir_datasets
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except ImportError as e:
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raise ImportError('ir-datasets package missing; `pip install ir-datasets`')
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import datasets
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IRDS_ID = 'codesearchnet'
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IRDS_ENTITY_TYPES = {'docs': {'doc_id': 'string', 'repo': 'string', 'path': 'string', 'func_name': 'string', 'code': 'string', 'language': 'string'}}
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_CITATION = '@article{Husain2019CodeSearchNet,\n title={CodeSearchNet Challenge: Evaluating the State of Semantic Code Search},\n author={Hamel Husain and Ho-Hsiang Wu and Tiferet Gazit and Miltiadis Allamanis and Marc Brockschmidt},\n journal={ArXiv},\n year={2019}\n}'
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_DESCRIPTION = "" # TODO
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class codesearchnet(datasets.GeneratorBasedBuilder):
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BUILDER_CONFIGS = [datasets.BuilderConfig(name=e) for e in IRDS_ENTITY_TYPES]
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features({k: datasets.Value(v) for k, v in IRDS_ENTITY_TYPES[self.config.name].items()}),
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homepage=f"https://ir-datasets.com/codesearchnet#codesearchnet",
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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return [datasets.SplitGenerator(name=self.config.name)]
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def _generate_examples(self):
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dataset = ir_datasets.load(IRDS_ID)
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for i, item in enumerate(getattr(dataset, self.config.name)):
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key = i
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if self.config.name == 'docs':
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key = item.doc_id
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elif self.config.name == 'queries':
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key = item.query_id
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yield key, item._asdict()
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def as_dataset(self, split=None, *args, **kwargs):
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split = self.config.name # always return split corresponding with this config to avid returning a redundant DatasetDict layer
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return super().as_dataset(split, *args, **kwargs)
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