Datasets:

Modalities:
Text
Languages:
English
ArXiv:
Tags:
code
Libraries:
Datasets
License:
File size: 4,773 Bytes
0713411
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3587674
5b43763
 
3587674
 
0713411
 
d621d88
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5b43763
 
 
 
 
 
 
 
 
 
 
d621d88
 
 
 
 
 
 
 
 
5b43763
d621d88
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0713411
 
 
d621d88
 
 
 
 
 
 
 
 
 
 
 
3587674
 
 
5b43763
3587674
 
 
d621d88
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
import json

import datasets

_DESCRIPTION = """Translating Python Programming Puzzles (TP3) is a code translation benchmark created from the verification functions from the questions in the original Python Programming Puzzles dataset (Schuster et al., 2021) to create this dataset. These functions are hand-crafted by the authors and are used to check if an answer satisfies the constraints of the puzzle. These puzzles range in difficulty from basic character checking to competitive programming problems. Thus, each verification function is written by an expert python programmer and requires a significant understanding of programming to translate. In total, there are 370 python functions to translate."""

_URL = "https://raw.githubusercontent.com/google-research/babelcode/main/data/hf_datasets/tp3.jsonl"

_LANGUAGES = {
    "C++",
    "CSharp",
    "Dart",
    "Go",
    "Haskell",
    "Java",
    "Javascript",
    "Julia",
    "Kotlin",
    "Lua",
    "PHP",
    "R",
    "Rust",
    "Scala",
    "TypeScript",
}

_CITATION = """\
@article{orlanski2023measuring,
  title={Measuring The Impact Of Programming Language Distribution},
  author={Orlanski, Gabriel and Xiao, Kefan and Garcia, Xavier and Hui, Jeffrey and Howland, Joshua and Malmaud, Jonathan and Austin, Jacob and Singh, Rishah and Catasta, Michele},
  journal={arXiv preprint arXiv:2302.01973},
  year={2023}
}
@inproceedings{
    schuster2021programming,
    title={Programming Puzzles},
    author={Tal Schuster and Ashwin Kalyan and Alex Polozov and Adam Tauman Kalai},
    booktitle={Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
    year={2021},
    url={https://arxiv.org/abs/2106.05784}
}"""

_HOMEPAGE = "https://github.com/google-research/babelcode"

_LICENSE = "CC-BY-4.0"

_VERSION = "1.0.0"

_QUESTION_INFO_KEYS = {
    "entry_fn_name", "entry_cls_name", "test_code", "test_list",
    "test_case_ids", "commands", "timeouts", "extension"
}


class TP3(datasets.GeneratorBasedBuilder):
  """TP3"""

  VERSION = datasets.Version(_VERSION)

  BUILDER_CONFIGS = [
      datasets.BuilderConfig(
          name="all",
          version=datasets.Version(_VERSION),
          description=_DESCRIPTION,
      ),
  ] + [
      datasets.BuilderConfig(
          name=lang,
          version=datasets.Version(_VERSION),
          description=_DESCRIPTION + f" Examples are only in {lang}.",
      ) for lang in _LANGUAGES
  ]

  DEFAULT_CONFIG_NAME = "all"

  def _info(self):
    list_keys = ['timeouts', 'commands', 'test_case_ids']
    question_info_type = {
        k: datasets.Value(dtype="string")
        for k in _QUESTION_INFO_KEYS
        if k not in list_keys
    }
    question_info_type['test_case_ids'] = datasets.Sequence(
        datasets.Value('string'))
    question_info_type['commands'] = datasets.Sequence(
        datasets.Sequence(datasets.Value('string')))
    question_info_type['timeouts'] = datasets.Sequence(datasets.Value('int32'))
    features = datasets.Features({
        "qid": datasets.Value("string"),
        "title": datasets.Value("string"),
        "language": datasets.Value("string"),
        "text": datasets.Value("string"),
        "signature_with_docstring": datasets.Value("string"),
        "signature": datasets.Value("string"),
        "arguments": datasets.Sequence(datasets.Value("string")),
        "source": datasets.Value("string"),
        "question_info": datasets.Features(question_info_type)
    })
    description = _DESCRIPTION
    if self.config.name != 'all':
      description = _DESCRIPTION + f" Examples are only in {self.config.name}."
    return datasets.DatasetInfo(
        description=description,
        features=features,
        supervised_keys=None,
        homepage=_HOMEPAGE,
        license=_LICENSE,
        citation=_CITATION,
    )

  def _split_generators(self, dl_manager):
    """Returns SplitGenerators."""
    data_dir = dl_manager.download_and_extract(_URL)
    return [
        datasets.SplitGenerator(
            name=datasets.Split.TEST,
            gen_kwargs={"filepath": data_dir},
        ),
    ]

  def _generate_examples(self, filepath):
    """ Yields the examples from the dataset"""
    with open(filepath, encoding='utf-8') as file:
      id_ = 0
      for l in file:
        if not l.strip():
          continue
        d = json.loads(l)

        if self.config.name != 'all' and d['language'] != self.config.name:
          continue

        question_info = {}
        for k in _QUESTION_INFO_KEYS:
          question_info[k] = d.pop(k)

        question_info['test_list'] = json.dumps(question_info['test_list'])

        d['question_info'] = question_info
        d['source'] = d.pop('solution_python')

        yield id_, d
        id_ += 1