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codesearchnet.py
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codesearchnet.py
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import json
import csv
import gzip
from typing import NamedTuple
import io
import itertools
from pathlib import Path
import ir_datasets
from ir_datasets.util import DownloadConfig, TarExtract, ZipExtractCache
from ir_datasets.formats import BaseDocs, BaseQueries, BaseQrels
from ir_datasets.formats import GenericDoc, GenericQuery, TrecQrel
from ir_datasets.indices import PickleLz4FullStore
from ir_datasets.datasets.base import Dataset, YamlDocumentation
NAME = 'codesearchnet'
QREL_DEFS = {
1: 'Matches docstring',
}
QREL_DEFS_CHALLENGE = {
0: 'Irrelevant',
1: 'Weak Match',
2: 'String Match',
3: 'Exact Match',
}
class CodeSearchNetDoc(NamedTuple):
doc_id: str
repo: str
path: str
func_name: str
code: str
language: str
class CodeSearchNetChallengeQrel(NamedTuple):
query_id: str
doc_id: str
relevance: str
note: str
class CodeSearchNetDocs(BaseDocs):
def __init__(self, docs_dlcs):
super().__init__()
self.docs_dlcs = docs_dlcs
@ir_datasets.util.use_docstore
def docs_iter(self):
for dlc in self.docs_dlcs:
base_path = Path(dlc.path())
for file in sorted(base_path.glob('**/*.gz')):
with gzip.open(file, 'rt') as f:
for line in f:
data = json.loads(line)
yield CodeSearchNetDoc(
data['url'], # doc_id = url
data['repo'],
data['path'],
data['func_name'],
data['code'],
data['language'],
)
def docs_cls(self):
return CodeSearchNetDoc
def docs_store(self, field='doc_id'):
return PickleLz4FullStore(
path=f'{ir_datasets.util.home_path()/NAME}/docs.pklz4',
init_iter_fn=self.docs_iter,
data_cls=self.docs_cls(),
lookup_field=field,
index_fields=['doc_id'],
)
def docs_count(self):
return self.docs_store().count()
def docs_namespace(self):
return NAME
def docs_lang(self):
return None # not natural languages
class CodeSearchNetQueries(BaseQueries):
def __init__(self, queries_dlcs, split):
super().__init__()
self.queries_dlcs = queries_dlcs
self.split = split
def queries_iter(self):
for dlc in self.queries_dlcs:
base_path = Path(dlc.path())
for file in sorted(base_path.glob(f'**/{self.split}/*.gz')):
with gzip.open(file, 'rt') as f:
for line in f:
data = json.loads(line)
yield GenericQuery(
data['url'], # query_id = url
data['docstring'], # text = docstring
)
def queries_cls(self):
return GenericQuery
def queries_namespace(self):
return NAME
def queries_lang(self):
return 'en'
class CodeSearchNetQrels(BaseQrels):
def __init__(self, qrels_dlcs, split):
super().__init__()
self.qrels_dlcs = qrels_dlcs
self.split = split
def qrels_iter(self):
for dlc in self.qrels_dlcs:
base_path = Path(dlc.path())
for file in sorted(base_path.glob(f'**/{self.split}/*.gz')):
with gzip.open(file, 'rt') as f:
for line in f:
data = json.loads(line)
yield TrecQrel(
query_id=data['url'],
doc_id=data['url'],
relevance=1,
iteration='0',
)
def qrels_cls(self):
return TrecQrel
def qrels_defs(self):
return QREL_DEFS
def queries_lang(self):
return 'en'
class CodeSearchNetChallengeQueries(BaseQueries):
def __init__(self, queries_dlc):
super().__init__()
self.queries_dlc = queries_dlc
def queries_path(self):
return self.queries_dlc.path()
def queries_iter(self):
with self.queries_dlc.stream() as stream:
stream = io.TextIOWrapper(stream)
for i, line in enumerate(stream):
if i == 0:
continue # skip first (header) line
yield GenericQuery(str(i), line.rstrip())
def queries_cls(self):
return GenericQuery
def queries_namespace(self):
return NAME
class CodeSearchNetChallengeQrels(BaseQrels):
def __init__(self, qrels_dlc, queries_handler):
super().__init__()
self.qrels_dlc = qrels_dlc
self._queries_handler = queries_handler
def qrels_path(self):
return self.qrels_dlc.path()
def qrels_iter(self):
query_map = {q.text: q.query_id for q in self._queries_handler.queries_iter()}
with self.qrels_dlc.stream() as stream:
stream = io.TextIOWrapper(stream)
for data in csv.DictReader(stream):
yield CodeSearchNetChallengeQrel(
query_id=query_map[data['Query']],
doc_id=data['GitHubUrl'],
relevance=data['Relevance'],
note=data['Notes'])
def qrels_cls(self):
return CodeSearchNetChallengeQrel
def qrels_defs(self):
return QREL_DEFS_CHALLENGE
def _init():
documentation = YamlDocumentation(f'docs/{NAME}.yaml')
base_path = ir_datasets.util.home_path()/NAME
dlc = DownloadConfig.context(NAME, base_path)
subsets = {}
langs = ['python', 'java', 'go', 'php', 'ruby', 'javascript']
dlcs = {lang: ZipExtractCache(dlc[lang], base_path/lang) for lang in langs}
all_dlcs = [dlcs[lang] for lang in langs]
base = Dataset(
CodeSearchNetDocs(all_dlcs),
documentation('_'),
)
subsets['train'] = Dataset(
CodeSearchNetDocs(all_dlcs),
CodeSearchNetQueries(all_dlcs, 'train'),
CodeSearchNetQrels(all_dlcs, 'train'),
documentation('train'),
)
subsets['valid'] = Dataset(
CodeSearchNetDocs(all_dlcs),
CodeSearchNetQueries(all_dlcs, 'valid'),
CodeSearchNetQrels(all_dlcs, 'valid'),
documentation('valid'),
)
subsets['test'] = Dataset(
CodeSearchNetDocs(all_dlcs),
CodeSearchNetQueries(all_dlcs, 'test'),
CodeSearchNetQrels(all_dlcs, 'test'),
documentation('test'),
)
challenge_queries = CodeSearchNetChallengeQueries(dlc['challenge/queries'])
subsets['challenge'] = Dataset(
CodeSearchNetDocs(all_dlcs),
challenge_queries,
CodeSearchNetChallengeQrels(dlc['challenge/qrels'], challenge_queries),
documentation('challenge'),
)
ir_datasets.registry.register(NAME, base)
for s in sorted(subsets):
ir_datasets.registry.register(f'{NAME}/{s}', subsets[s])
return base, subsets
base, subsets = _init()