1.使用dill保存当前变量区的全部变量
# 保存变量区变量到文件:
import numpy as np
import dill
T='Hiya'
val=[1,2,3]
a = np.zeros([4,5])
dill.dump_session('file_name.pkl') # 以上三个变量全部保存在了pkl文件中
# 读取文件内容到变量区:
import numpy as np
import dill
# load the session again
dill.load_session('file_name.pkl')
2.使用pickle保存某个或某些对象(变量)
# 保存单个变量
import pickle
f = open('store.pckl', 'wb')
pickle.dump(obj, f)
f.close()
# 读取单个变量
import pickle
f = open('store.pckl', 'rb')
obj = pickle.load(f)
f.close()
保存多个对象时将要保存的对象放在一个列表或元组中:
import pickle
# obj0, obj1, obj2 are created here...
# Saving the objects:
with open('objs.pkl', 'w') as f: # Python 3: open(..., 'wb')
pickle.dump([obj0, obj1, obj2], f)
# Getting back the objects:
with open('objs.pkl') as f: # Python 3: open(..., 'rb')
obj0, obj1, obj2 = pickle.load(f)
3.使用sklearn保存变量
from sklearn.externals import joblib、
# 保存x
joblib.dump(x, 'x.pkl')
# 加载x
x = joblib.load('x.pkl')
4.dataframe类型的数据保存
samples.to_pickle('samples')
pd.read_pickle('samples')
参考教程:
https://blog.csdn.net/lrs1353281004/article/details/81544490?depth_1-utm_source=distribute.pc_relevant.none-task&utm_source=distribute.pc_relevant.none-task
https://blog.csdn.net/u012605050/article/details/77940798
https://blog.csdn.net/jining11/article/details/81435899