pickle

问题 Dill.detect.children requires two arguments; obj and objtype . Inspecting an audiofile object I can call: dill.detect.children(audiofile, object) dill.detect.children(audiofile, dict) dill.detect.children(audiofile, list) Which return without error. But how about looking for instance methods? type(audiofile.save) returns instancemethod Tried dill.detect.children(audiofile, instancemethod) which returns NameError: name 'instancemethod' is not defined Tried dill.detect.children(audiofile,

问题 I would like to call Python's pickling routines ( dumps and loads ) from within c++ code. Are they exposed in the official API? I am currently calling those via boost::python from c++, looking for a simpler way perhaps. 回答1: You can call any Python code through the C API: static PyObject *module = NULL; PyObject *pickle; if (module == NULL && (module = PyImport_ImportModuleNoBlock("pickle")) == NULL) return NULL; now, you can either call it like: python-2.x pickle = PyObject_CallMethodObjArgs

问题 I create keras model and then save that model to pickle program code : print(base_learners) # 9) 앙상블 모델 저장하기 pickle.dump(meta_learner, open('./models/meta_learner.pkl', 'wb')) pickle.dump(base_learners, open('./models/base_learners.pkl', 'wb')) pickle.dump(models, open('./models/models.pkl', 'wb')) When I run the code, I get the following error: Traceback (most recent call last): File "MODEL02_ensemble.py", line 265, in <module> main() File "MODEL02_ensemble.py", line 246, in main pickle.dump

问题 I am using dill (advanced version of pickle) right now. I want to serialize my object, but I get this error: /usr/lib/python2.7/pickle.pyc in memoize(self, obj) 242 if self.fast: 243 return --> 244 assert id(obj) not in self.memo 245 memo_len = len(self.memo) 246 self.write(self.put(memo_len)) Can someone tell me the possibility that made this error or how can I solved this? 回答1: Without you posting a reduced version of your code, it's hard to help. However, dill has some builtin detection

问题 I have the following model: class Parameter(models.Model): par_type = = models.CharField(max_length=30) value = models.TextField() Majority of the time the value field will store a number ( value=3.2118 ). But sometimes I want to assign a list of other object IDs (like value="[32, 22, 45]" ) or a string object (like value="pass" ), etc. I will use value field in functions like the ones below based on the value of par_type : def foo(par): # par is a Parameter object. return float(par.value) /

问题 I have a use case where I need to build a list from the lines in a file. This operation will be performed potentially 100s of times on a distributed network. I've been using the obvious solution of: with open("file.txt") as f: ds = f.readlines() I just had the thought that perhaps I would be better off creating this list once, pickling it into a file and then using that file to unpickle the data on each node. Would there be any performance increase if I did this? 回答1: Would there be any

问题 Trying to render a large and (possibly very) unpicklable object to a file for later use. No complaints on the dill.dump(file) side: In [1]: import echonest.remix.audio as audio In [2]: import dill In [3]: audiofile = audio.LocalAudioFile("/Users/path/Track01.mp3") en-ffmpeg -i "/Users/path/audio/Track01.mp3" -y -ac 2 -ar 44100 "/var/folders/X2/X2KGhecyG0aQhzRDohJqtU+++TI/-Tmp-/tmpWbonbH.wav" Computed MD5 of file is b3820c166a014b7fb8abe15f42bbf26e Probing for existing analysis In [4]: with

问题 dill is a great tool for pickling most the Python objects, I use it in IPython parallel to serialize calculations. One issue I keep getting into is around dill-ing class definitions. One of the errors I get is explained below. While trying to serialize class definitions, I keep getting AssertionError from dill . I wonder why one of these works and the other fails: class MyClassEmpty(object): pass class MyClassInit(object): def __init__(self): super(MyClassInit).__init__() dill.dumps

问题 Can we save any of the created LSTM models themselves? I believe that “pickling” is the standard method to serialize python objects to a file. Ideally, I wanted to create a python module that contained one or more functions that either allowed me to specify an LSTM model to load or used a hard-coded pre-fit model to generate forecasts based on data passed in to initialize the model. I tried to use it but gave me an error. Code that I used: # create and fit the LSTM network batch_size = 1

问题 I made a class in python like the following: class myClass(): _fields_ = [1, 2] where field_1 & field_2 are supposed to be integers. Then I created an array that its elements are of the class myClass as following: array = [ myClass() for i in range(5)] When I wanted to check the values of the elements of array in the variable inspector, it gives my the following message: "Spyder was unable to retrieve the value of this variable from the console." "The error message was: Object array is not