Spaces:
Running
on
Zero
Running
on
Zero
File size: 1,934 Bytes
dcd4560 |
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 |
# Copyright (2024) Bytedance Ltd. and/or its affiliates
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import json
from json import JSONEncoder
import numpy
import pandas as pd
class NumpyArrayEncoder(JSONEncoder):
def default(self, obj):
if isinstance(obj, numpy.ndarray):
return obj.tolist()
return JSONEncoder.default(self, obj)
def write_txt(data, path):
with open(path, 'w', encoding='utf-8')as f:
for d in data:
f.write(f'{d}\n')
def read_txt(path):
with open(path, 'r', encoding='utf-8', errors='ignore') as f:
lines = [l.strip('\n') for l in f.readlines()]
return lines
def read_jsonlines(path):
objs = []
with open(path) as f:
for line in f:
line = json.loads(line)
objs.append(line)
return objs
def write_jsonlines(data, path, cls=None, ensure_ascii=False):
with open(path, 'w') as f:
for d in data:
d = json.dumps(d, ensure_ascii=ensure_ascii, cls=cls)
f.write(d)
f.write('\n')
def read_parquet(path):
data = pd.read_parquet(path)
return data.to_dict('records')
def write_parquet(data, path):
data = pd.DataFrame(data)
data.to_parquet(path)
def read_csv(path):
data = pd.read_csv(path)
return data.to_dict(orient='records')
def write_csv(data, path):
data = pd.DataFrame(data)
data.to_csv(path, index=False, sep='\t')
|