问题:如何在python中保存和恢复多个变量?

我需要将大约十二个对象保存到文件中,然后稍后将其还原。我尝试过使用带咸菜和搁置的for循环,但效果不佳。

编辑。
我试图保存的所有对象都在同一个类中(我之前应该提到过),但我没有意识到我可以像这样保存整个类:

import pickle
def saveLoad(opt):
    global calc
    if opt == "save":
        f = file(filename, 'wb')
        pickle.dump(calc, f, 2)
        f.close
        print 'data saved'
    elif opt == "load":
        f = file(filename, 'rb')
        calc = pickle.load(f)
    else:
        print 'Invalid saveLoad option'

I need to save about a dozen objects to a file and then restore them later. I’ve tried to use a for loop with pickle and shelve but it didn’t work right.

Edit.
All of the objects that I was trying to save were in the same class (I should have mentioned this before), and I didn’t realize that I could just save the whole class like this:

import pickle
def saveLoad(opt):
    global calc
    if opt == "save":
        f = file(filename, 'wb')
        pickle.dump(calc, f, 2)
        f.close
        print 'data saved'
    elif opt == "load":
        f = file(filename, 'rb')
        calc = pickle.load(f)
    else:
        print 'Invalid saveLoad option'

回答 0

如果需要保存多个对象,则可以简单地将它们放在单个列表或元组中,例如:

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)

如果您有大量数据,可以通过传递protocol=-1dump(); 来减小文件大小。pickle然后将使用最佳的可用协议,而不是默认的历史记录(以及向后兼容的协议)。在这种情况下,必须以二进制模式打开文件(分别为wbrb)。

二进制模式也应该与Python 3一起使用,因为它的默认协议会生成二进制(即非文本)数据(写入模式'wb'和读取模式'rb')。

If you need to save multiple objects, you can simply put them in a single list, or tuple, for instance:

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)

If you have a lot of data, you can reduce the file size by passing protocol=-1 to dump(); pickle will then use the best available protocol instead of the default historical (and more backward-compatible) protocol. In this case, the file must be opened in binary mode (wb and rb, respectively).

The binary mode should also be used with Python 3, as its default protocol produces binary (i.e. non-text) data (writing mode 'wb' and reading mode 'rb').


回答 1

有一个名为的内置库pickle。使用,pickle您可以将对象转储到文件中并在以后加载它们。

import pickle

f = open('store.pckl', 'wb')
pickle.dump(obj, f)
f.close()

f = open('store.pckl', 'rb')
obj = pickle.load(f)
f.close()

There is a built-in library called pickle. Using pickle you can dump objects to a file and load them later.

import pickle

f = open('store.pckl', 'wb')
pickle.dump(obj, f)
f.close()

f = open('store.pckl', 'rb')
obj = pickle.load(f)
f.close()

回答 2

您应该查看一下货架泡菜模块。如果您需要存储大量数据,最好使用数据库

You should look at the shelve and pickle modules. If you need to store a lot of data it may be better to use a database


回答 3

将多个变量保存到pickle文件的另一种方法是:

import pickle

a = 3; b = [11,223,435];
pickle.dump([a,b], open("trial.p", "wb"))

c,d = pickle.load(open("trial.p","rb"))

print(c,d) ## To verify

Another approach to saving multiple variables to a pickle file is:

import pickle

a = 3; b = [11,223,435];
pickle.dump([a,b], open("trial.p", "wb"))

c,d = pickle.load(open("trial.p","rb"))

print(c,d) ## To verify

回答 4

您可以使用klepto,它为内存,磁盘或数据库提供持久缓存。

dude@hilbert>$ python
Python 2.7.6 (default, Nov 12 2013, 13:26:39) 
[GCC 4.2.1 Compatible Apple Clang 4.1 ((tags/Apple/clang-421.11.66))] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> from klepto.archives import file_archive
>>> db = file_archive('foo.txt')
>>> db['1'] = 1
>>> db['max'] = max
>>> squared = lambda x: x**2
>>> db['squared'] = squared
>>> def add(x,y):
...   return x+y
... 
>>> db['add'] = add
>>> class Foo(object):
...   y = 1
...   def bar(self, x):
...     return self.y + x
... 
>>> db['Foo'] = Foo
>>> f = Foo()
>>> db['f'] = f  
>>> db.dump()
>>> 

然后,在解释器重新启动后…

dude@hilbert>$ python
Python 2.7.6 (default, Nov 12 2013, 13:26:39) 
[GCC 4.2.1 Compatible Apple Clang 4.1 ((tags/Apple/clang-421.11.66))] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> from klepto.archives import file_archive
>>> db = file_archive('foo.txt')
>>> db
file_archive('foo.txt', {}, cached=True)
>>> db.load()
>>> db
file_archive('foo.txt', {'1': 1, 'add': <function add at 0x10610a0c8>, 'f': <__main__.Foo object at 0x10510ced0>, 'max': <built-in function max>, 'Foo': <class '__main__.Foo'>, 'squared': <function <lambda> at 0x10610a1b8>}, cached=True)
>>> db['add'](2,3)
5
>>> db['squared'](3)
9
>>> db['f'].bar(4)
5
>>> 

在此处获取代码:https : //github.com/uqfoundation

You could use klepto, which provides persistent caching to memory, disk, or database.

dude@hilbert>$ python
Python 2.7.6 (default, Nov 12 2013, 13:26:39) 
[GCC 4.2.1 Compatible Apple Clang 4.1 ((tags/Apple/clang-421.11.66))] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> from klepto.archives import file_archive
>>> db = file_archive('foo.txt')
>>> db['1'] = 1
>>> db['max'] = max
>>> squared = lambda x: x**2
>>> db['squared'] = squared
>>> def add(x,y):
...   return x+y
... 
>>> db['add'] = add
>>> class Foo(object):
...   y = 1
...   def bar(self, x):
...     return self.y + x
... 
>>> db['Foo'] = Foo
>>> f = Foo()
>>> db['f'] = f  
>>> db.dump()
>>> 

Then, after interpreter restart…

dude@hilbert>$ python
Python 2.7.6 (default, Nov 12 2013, 13:26:39) 
[GCC 4.2.1 Compatible Apple Clang 4.1 ((tags/Apple/clang-421.11.66))] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> from klepto.archives import file_archive
>>> db = file_archive('foo.txt')
>>> db
file_archive('foo.txt', {}, cached=True)
>>> db.load()
>>> db
file_archive('foo.txt', {'1': 1, 'add': <function add at 0x10610a0c8>, 'f': <__main__.Foo object at 0x10510ced0>, 'max': <built-in function max>, 'Foo': <class '__main__.Foo'>, 'squared': <function <lambda> at 0x10610a1b8>}, cached=True)
>>> db['add'](2,3)
5
>>> db['squared'](3)
9
>>> db['f'].bar(4)
5
>>> 

Get the code here: https://github.com/uqfoundation


回答 5

以下方法似乎很简单,可以与不同大小的变量一起使用:

import hickle as hkl
# write variables to filename [a,b,c can be of any size]
hkl.dump([a,b,c], filename)

# load variables from filename
a,b,c = hkl.load(filename)

The following approach seems simple and can be used with variables of different size:

import hickle as hkl
# write variables to filename [a,b,c can be of any size]
hkl.dump([a,b,c], filename)

# load variables from filename
a,b,c = hkl.load(filename)

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