NewData / dummy.py
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import os
import pandas as pd
import datasets
from glob import glob
import zipfile
import json
class dummy(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo(features=datasets.Features({'Name':datasets.Value('string'),'Age':datasets.Value('string'),'label': datasets.features.ClassLabel(names=['female', 'male'])}))
def extract_all(self, dir):
zip_files = glob(dir+'/**/**.zip', recursive=True)
for file in zip_files:
with zipfile.ZipFile(file) as item:
item.extractall('/'.join(file.split('/')[:-1]))
def get_all_files(self, dir):
files = []
valid_file_ext = ['txt', 'csv', 'tsv', 'xlsx', 'xls', 'xml', 'json', 'jsonl', 'html', 'wav', 'mp3', 'jpg', 'png']
for ext in valid_file_ext:
files += glob(f"{dir}/**/**.{ext}", recursive = True)
return files
def _split_generators(self, dl_manager):
url = [os.path.abspath(os.path.expanduser(dl_manager.manual_dir))]
downloaded_files = url
return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'filepaths': {'inputs':downloaded_files} })]
def read_json(self, filepath, json_key, lines = False):
if json_key:
data = json.load(open(filepath))
df = pd.DataFrame(data[json_key])
else:
df = pd.read_json(filepath, lines=lines)
return df
def _generate_examples(self, filepaths):
_id = 0
for i,filepath in enumerate(filepaths['inputs']):
df = self.read_json(filepath, lines=True, json_key='data')
if len(df.columns) != 3:
continue
df.columns = ['Name', 'Age', 'Gender']
for _, record in df.iterrows():
yield str(_id), {'Name':record['Name'],'Age':record['Age'],'label':str(record['Gender'])}
_id += 1