pickle

问题 Closed . This question is opinion-based. It is not currently accepting answers. Want to improve this question? Update the question so it can be answered with facts and citations by editing this post. Closed 5 years ago . I am running a numerical experiment that requires many iterations. After each iteration, I would like to store the data in a pickle file or pickle-like file in case the program times-out or a data structure becomes tapped. What is the best way to proceed. Here is the skeleton

问题 What exactly is the relationship between pickle and copy.deepcopy ? What mechanisms do they share, and how? It is clear the two are closely-related operations, and share some of the mechanisms/protocols, but I can't wrap my head around the details. Some (confusing) things I found out: If a class defines __[gs]etstate__ , they get called upon a deepcopy of its instances. This surprised me at first, because I thought they are specific to pickle , but then I found that Classes can use the same

问题 I need to compute the sizes of some python objects, so I can break them up and store them in memcache without hitting size limits. ' sizeof ()' doesn't seem to be present on python objects in the GAE environment and sys.getsizeof() is also unavailable. GAE itself is clearly checking sizes behind the scenes to enforce the limits. Any ideas for how to accomplish this? Thanks. 回答1: memcache internally and invariably uses pickle and stores the resulting string, so you can check with len(pickle

问题 Putting aside whether the use of isinstance is harmful, I have run into the following conundrum when trying to evaluate isinstance after serializing/deserializing an object via Pickle: from __future__ import with_statement import pickle # Simple class definition class myclass(object): def __init__(self, data): self.data = data # Create an instance of the class x = myclass(100) # Pickle the instance to a file with open("c:\\pickletest.dat", "wb") as f: pickle.dump(x, f) # Replace class with

问题 I have the following two data frames: df_whitelist and df_text +-------+--------------------+ |keyword| whitelist_terms | +-------+--------------------+ | LA| LA city| | LA| US LA in da | | client|this client has i...| | client|our client has do...| +-------+--------------------+ +--------------------+----------+ | Text| Keywords| +--------------------+----------+ |the client as ada...|client;ada| |this client has l...| client;LA| +--------------------+----------+ In df_whitelist, each

问题 I create a tensorflow model which I would like to save to file so that I can predict against it later. In particular, I need to save the: input_placeholder ( = tf.placeholder(tf.float32, [None, iVariableLen]) ) solution_space ( = tf.nn.sigmoid(tf.matmul(input_placeholder, weight_variable) + bias_variable) ) session ( = tf.Session() ) I've tried using pickle which works on other objects like sklearn binarizers etc, but not on the above, for which I get the error at the bottom. How I pickle:

问题 If I have a script that defines a class: script = """ class myClass: def __init__(self): self.name = 'apple' self.color = 'green' """ and then exec this script in its own namespace dict: NS = {} exec script in NS and then create an instance of the class and pickle it: a = NS['myClass']() import pickle save = pickle.dumps(a) Now if I try to unpickle it: load = pickle.loads(save) I get the error AttributeError: 'module' object has no attribute 'myClass' I gather that this doesn't work because

问题 This question already has answers here : Pickle all attributes except one (6 answers) Closed 2 years ago . I am using gnosis.xml.pickle to convert an object of my own class to xml. The object is initialized so that: self.logger = MyLogger() But when I do dump the object to a string I get an exception stating that the pickler encountered an unpickleable type (thread.lock). Is there a way to 'tag' the logger attribute so that pickler will know not to try and pickle that attribute? 回答1: You can

问题 How do I create a pickleable file from a PIL Image object such that you could save those images as a single pickle file then maybe upload to another computer such as a server running PIL and unpickle it there? 回答1: You can convert the Image object into data then you can pickle it: image = { 'pixels': im.tostring(), 'size': im.size, 'mode': im.mode, } And back to an Image: im = Image.fromstring(image['mode'], image['size'], image['pixels']) NOTE: As astex mentioned, if you're using Pillow

问题 I an using python 2.7 and trying to pickle an object. I am wondering what the real difference is between the pickle protocols. import numpy as np import pickle class data(object): def __init__(self): self.a = np.zeros((100, 37000, 3), dtype=np.float32) d = data() print "data size: ", d.a.nbytes/1000000. print "highest protocol: ", pickle.HIGHEST_PROTOCOL pickle.dump(d,open("noProt", 'w')) pickle.dump(d,open("prot0", 'w'), protocol=0) pickle.dump(d,open("prot1", 'w'), protocol=1) pickle.dump(d