Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
multi-class-classification
Size:
100K - 1M
License:
Upload Dataset Loader Script
Browse files- java-cmpx.py +59 -0
java-cmpx.py
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import os
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import ast
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import csv
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import datasets
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_DESCRIPTION = "JEMMA Java CMPX"
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_CITATION = "NOT AVAILABLE"
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_HOMEPAGE = "NOT AVAILABLE"
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_LICENSE = "MIT"
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_BASE_TRAIN_FILE_URL = "https://huggingface.co/datasets/giganticode/java-cmpx/resolve/main/Jemma_Properties_Methods_CMPX__Huggingface_Dataset_TRAIN.csv"
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_BASE_TEST_FILE_URL = "https://huggingface.co/datasets/giganticode/java-cmpx/resolve/main/Jemma_Properties_Methods_CMPX__Huggingface_Dataset_TEST.csv"
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_URLS = {
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"train": _BASE_TRAIN_FILE_URL,
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"test": _BASE_TEST_FILE_URL
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}
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class JavaCMPX(datasets.GeneratorBasedBuilder):
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"""Java CMPX"""
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def _info(self):
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"""Returns Info"""
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"method_id": datasets.Value("string"),
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"cyclomatic_complexity": datasets.Value("int32"),
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"method_text": datasets.Value("string")
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}
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),
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators"""
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data_file = dl_manager.download(_URLS)
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return [
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_file["train"]}),
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_file["test"]}),
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]
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def _generate_examples(self, filepath):
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"""Yields Examples"""
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with open(filepath, encoding="utf-8") as f:
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reader = csv.reader(f)
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for id_, row in enumerate(reader):
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if id_ == 0:
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continue
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yield id_, {
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"method_id": row[0],
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"cyclomatic_complexity": row[1],
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"method_text": row[2],
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}
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