1､使用numpy.savez()实现

相关文档：numpy.savez()

a = np.array([[2,4],[6,8],[10,12]])
d = {"first": 1, "second": "two", "third": 3}
np.savez(whatever_name.npz, a=a, d=d)
data = np.load(whatever_name.npz)
arr = data['a']
dic = data['d'].tolist()

2､使用h5py实现

相关文档：h5py

import h5py, numpy as np
arr = np.random.randint(0, 10, (1000, 1000))
f = h5py.File('file.h5', 'w', libver='latest')  # use 'latest' for performance
dset = f.create_dataset('array', shape=(1000, 1000), data=arr, chunks=(100, 100),
                        compression='gzip', compression_opts=9)
#添加一些属性
dset.attrs['Description'] = 'Some text snippet'
dset.attrs['RowIndexArray'] = np.arange(1000)
#储存字典
for k, v in d.items():
    f.create_dataset('dictgroup/'+str(k), data=v)
#内存不足时访问方法
dictionary = f['dictgroup']
res = dictionary['my_key']

3､使用pyarrow实现

1) 安装引用

pip install pyarrow

2) 实现代码

import pyarrow as pa
import pyarrow.parquet as pq
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.normal(size=(1000, 10)))
tab = pa.Table.from_pandas(df)
tab = tab.replace_schema_metadata({'here' : 'it is'})
pq.write_table(tab, 'where_is_it.parq')
pq.read_table('where_is_it.parq')

相关文档：

read parquet

write parquet