Your way of generating x is overly convoluted import string import random data = string.ascii_lowercase + string.digits x = ''.join(random.choice(data) for n in range(20)) Now, you can simply print x to a file like this with open("data.txt", "a")) as fout: print(x, file=fout) If you wish to append N codes to...
Running pickletools.dis(cPickle.dumps(p)), you can see the handler object being referenced: ... 213: c GLOBAL 'traits.trait_handlers TraitListObject' ... But there's no further information on how it should be wired to the report method. So either the trait_handler doesn't pickle itself out properly, or it's an ephemeral thing like a file handle...
python,python-2.7,tkinter,treeview,pickle
I doubt there's any Python module that does what you want, and even if there was, I don't think you'd want to structure your application around using it. Instead you would probably be better off decoupling things and storing the primary data in something independent of the human interface (which...
What you are currently doing is equivalent to: groupA[name].append([count]) # this appends a list to the list Do it this way groupA[name].append(count) # count must be single value And in the else part groupA[name] = [count] # creating new single-element list Also, len(scores) will always be 1. Replace it with...
What kind of control is required? As you can see from the source, when you are running pickle.loads(content) it actually does: def loads(str): file = StringIO(str) return Unpickler(file).load() Then there is some magic. It reads a string as a file and dispatches its' content is based on specific keys: GLOBAL...
say you are using parameters a=2, b=3 for a particular run. write those parameter values into the file name using format(): filename = "NNa{0}b{1}.pk1".format(a,b) pickle.dump(nn, open(filename,'wb')) will give you a file NNa2b3.pk1....
There are several ways to deal with it. This is what they would have in common: def get_object_redis(key,r): saved = r.get(key) if saved is None: # maybe add code here return ... # return something you expect obj = pickle.loads(saved) return obj You need to make it clear what you...
The simple solution to this is that, as far as I can tell, no documentation I can find proves or disproves this, you cannot pickle list/dictionary of dictionary items.
python,dictionary,pickle,eoferror
Your code opened the pickle file for writing first: dataList = open('data.txt','wb') That truncates the file to 0; by the time you then try to load pickles from that same file it is empty. Only open the file for writing when you are actually going to write a new pickle...
my_dict_final = {} # Create an empty dictionary with open('pickle_file1', 'rb') as f: my_dict_final.update(pickle.load(f)) # Update contents of file1 to the dictionary with open('pickle_file2', 'rb') as f: my_dict_final.update(pickle.load(f)) # Update contents of file2 to the dictionary print my_dict_final ...
python,python-2.7,python-3.x,pickle
dill has pickle debugging tools in dill.detect. I can't see what object you'd like to debug as your code above is not due to pickle… but I can show an example below, regardless. >>> class Test(object): ... def __init__(self, x, y): ... self.x = x ... self.y = y ......
python,multiprocessing,pickle,python-multiprocessing
You could use pathos.multiprocessing, which is a fork of multiprocessing that uses the dill serializer instead of pickle. dill can serialize pretty much anything in python. Then, no need to edit your code. >>> from pathos.multiprocessing import ProcessingPool as Pool >>> >>> def calculate(x): ... def domath(y): ... return x*y...
You cannot run a python file from within a package like that; it wouldn't find the toplevel package names. I'd propose any of the following: Write a start script in at the top level (where the main.py is), that imports and runs the read_write_dill from moduleA.moduleB Instead in the top...
how did you serialize the data? (pickle/json/...) also note that elements in a dictionary are not sorted (except if you used a collections.OrderedDict). so retrieving a range of elements may not give what you expect. if the amount of data you are trying to handle exceeds the memory wouldn't it...
python,scikit-learn,pickle,joblib
Looks like a package/pythonpath problem. The system need to know where to locale your modules. Do you have __init.py__ in my_app and analytic folder? The __init__.py file mark directories on disk as Python package directories. And the structure should be like this |- sentiment/ |- run.py |- my_app/ |- __init__.py...
python,filter,sqlalchemy,pickle,flask-sqlalchemy
Short explanation : PickleType does not support any relational functionalities such as queries/filters. Its purpose is storing and retrieving. Use sqlalchemy.orm.relationship instead. Long explanation : The error message is actually right. Everything in the filter function will compile to an sql query, (print the query to see this), so the...
To summarize reactions from Kroltan and jonsrharpe: Technically it is OK Technically it will work and if you do it properly, it can be considered OK. Practically it is tricky, avoid that If you edit the code in future and touch __init__, then it is easy (even for you) to...
python,dictionary,storage,store,pickle
See my answer to a very closely related question http://stackoverflow.com/a/25244747/2379433, if you are ok with pickling to several files instead of a single file. Also see: http://stackoverflow.com/a/21948720/2379433 for other potential improvements, and here too: http://stackoverflow.com/a/24471659/2379433. If you are using numpy arrays, it can be very efficient, as both klepto and...
Indeed, the Kivy EventDispatcher object is at fault here; the object.__reduce_ex__ method searches for the first baseclass that is not a custom class (it does not have the Py_TPFLAGS_HEAPTYPE flag set), to call __init__ on that class. This fails for that base class, as it's __init__ method doesn't support passing...
Okay, a few issues. First: def load_data(var_file): try: with open(var_file) as f: listDocument = pickle.load(f) except: listDocuments = [] return listDocuments You use both listDocument and listDocuments. (Note one has a trailing s). Also, you're using these the variable listDocuments in the outer program which is hiding your errors. Let's...
python,save,pygame,pickle,renpy
The hook you're looking for is __reduce__. It should return a (callable, args) tuple; the callable and args will be serialized, and on deserialization, the object will be recreated through callable(*args). If your class's constructor takes an int, you can implement __reduce__ as class ComplicatedThing(object): def __reduce__(self): return (ComplicatedThing, (self.progress_int,))...
A simple workaround to the error is to use the class name as variable name so that pickle can find it: import sys, pickle class BC(object): pass NewClassName = type("NewClassName", (BC,), {}) pickle.dump(NewClassName, sys.stdout) However, this probably doesn't really do what you want. When loading the pickled class: pickle.loads("""c__main__ NewClassName...
I am, myself, a webpy newbie. Nevertheless, after doing some "research", it seems that webpy cannot pickle the subprocess.Popen object[1]. So, lets try the following approach -- that is, creating it in the end response and printing its output. In other words: import web import subprocess web.config.debug = False urls...
My suggestion is if you can work with numpy. Since already have your data in a list you can just do this: import numpy as np data = np.array(mylist) np.savez("Myfile", data) Now it might take a minute or two to save this file (depending on how much RAM you have...
Only picklable data types can be stored in a shelf -- in particular, types added by C extensions need explicit support to be picklable; lxml has not as of this date had that support written. Unless you're willing to provide a patch to upstream lxml and shepherd it through merge...
The pickler error comes from multiprocessing.Process trying to internally pickle itself to the subprocess. I'm pretty sure one of your instance variables doesn't pickle properly to the child process. Which one is not clear from your question # Store class vars self.send_queue = send_queue self.reply_queue = reply_queue self.control_pipe = control_pipe...
Most of the serialization libraries in the stdlib and on PyPI have a similar API. I'm pretty sure it was marshal that set the standard,* and pickle, json, PyYAML, etc. have just followed in its footsteps. So, the question is, why was marshal designed that way? Well, you obviously need...
I'm not sure what you want to do from your question, but I can guess... If you are looking for a package that will help you make a ssh connection and then ship a python object, pathos has the ability to establish a ssh-tunnel or a direct ssh connection --...
If you use the dill package, you should be able to pickle the session where pickle itself fails. >>> import dill as pickle >>> pickled = pickle.dumps(session) >>> restored = pickle.loads(pickled) Get dill here: https://github.com/uqfoundation/dill Actually, dill also makes it easy to store your python session across restarts, so you...
See the pickle protocol You can implement __getstate__ and __setstate__. With __getstate__ you can delete whatever you don't want from the object dictionary....
You are appending data to your file. so the first dataset is the empty dictionary, which you read in, and the second dataset is the filled dictionary, which you never read again. You have to seek back to 0 before writing.
For writing into strings you should use pickle.dumps. There are two families of functions in this module: loads and dumps do stuff with strings, and load and dump do stuff on streams. Incidentally, pickle is quite dated. You might consider, at the very least, cPickle, which is much faster....
With regard to #1, it's a bug… and an old one at that. There's an enlightening, albeit surprisingly old, discussion about this here: http://python.6.x6.nabble.com/test-gzip-test-tarfile-failure-om-AMD64-td1830323.html The reasons for the error are here: http://www.littleredbat.net/mk/files/grimoire.html#contents_item_2.1 The simplest and most basic type are integers, which are represented as a C long. Their size is...
I believe the problem is that the HTTPAdapter class defines a __setstate__ method. This function is called upon unpickling, and restores the instance to the pickled state. However, the HTTPAdapter knows nothing of your source_address attribute, so that attribute isn't restored (or maybe not even pickled in the first place)....
python,sockets,python-2.7,pickle
The EOFError occurs if you do not pass the whole string to pickle but only parts of it. This can happen when you read incomplete strings from the socket with conn.recv(1024). I would change data = conn.recv(1024) boundaryarray = pickle.loads(data) because conn.recv(1024) receives 0 to 1024 bytes. I would change...
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; pickle = PyObject_CallMethodObjArgs(module, "dumps", to_dump_object, NULL); if (pickle != NULL) { ... } Py_XDECREF(pickle); but in the case of pickle you...
python,pickle,software-distribution
Sorry about the newbish question, i just found out i had been trying to reinvent the wheel. apparently, that already exists under the name Squeeze.
As a matter of fact, I had the same issue some days ago. Instead of saving the whole population, save the whole class (island or archipelago). I did use cPickle and pickle, and they both work fine. The trick to declare the class of your problem before dumping or loading...
You could make a dict with keys aList and bList and save it to the aFile like this: import pickle aList = ['useless', 'info'] bList = [1000,5000] aFile=open('aFile.dat', 'w') aFile.write(pickle.dumps({"aList":aList,"bList":bList})) aFile.close() If you wold like to append information you could do something more elaborated like this: import pickle def extract_dict(filename):...
If I understand correctly, the object you're trying to pickle / unpickle is the list of URLs in the lista variable. I'll make that assumption. Therefore, if lista = pickle.load( open( "save.p", "rb" ) ) print lista gives the output you expect, then the pickle load has worked. it seems...
You are misreading the article. Pickling and serialisation are not synonymous, nor does the text claim them to be. Paraphrasing slighly, the text says this: This module implements an algorithm for turning an object into a series of bytes. This process is also called serializing the object. I removed the...
python,google-app-engine,pickle,app-engine-ndb
In Python, default arguments are evaluated once -- so you're using a single dict (your default={} is a single dict per process, not one per entity!) across all entities of kind Test, which happen to be within the same process, and for which p is not explicitly set. If you...
django,pickle,django-cache,django-caching,django-redis
Turns out the main problems in storing querysets are that: QuerySets are lazy To evaluate them you need to serialize them [link] Not all QuerySets can be serialized because Python's serializer (Pickle) has it's own limitations [link] The best solution i found is to cache query results in template. So...
The following runs well. Rename your Player class with an uppercase initial to avoid name conflicts. I added some test calls at the end, and the player is loaded with the intended (not default) stats. import pickle class Player: def __init__(self, hp, dmg): self.hp = hp self.dmg = dmg def...
python,ipython,pickle,ipython-notebook,jsonpickle
In absence of some test code and version numbers, the only thing I can see is that you are using pandas.Dataframe objects. These guys often can need some special handling that is built-into pandas built-in pickling methods. I believe pandas gives both the to_pickle and the save method, which provide...
python,pickle,python-multithreading,pyparsing,python-multiprocessing
OK, here is the solution inspired by rocksportrocker: Python multiprocessing pickling error The idea is to dill the object that can't be pickled while passing it back and forth between processes and then "undill" it after it has been passed: from multiprocessing import Pool import dill def submit_decoder_process(decoder_dill, input_line): decoder...
I'm the dill author. There's a fairly comprehensive list of what pickles and what doesn't as part of dill. It can be run per version of python 2.5-3.4, and adjusted for what pickles with dill or what pickles with pickle by changing one flag. See here: https://github.com/uqfoundation/dill/blob/master/tests/test_objects.py and https://github.com/uqfoundation/dill/blob/master/dill/_objects.py. The...
From the verb to pickle: vegetables, such as cauliflowers, onions, etc, preserved in vinegar, brine, etc It is Python objects, preserved for later use. The name was taken from the Modula-3 concept, a language that inspired many Python features. Also see the Module-3 Pickle documentation. I suspect Guido picked the...
python,multithreading,login,pyqt4,pickle
The issue is that you're pickling objects defined in Settings by actually running the 'Settings' module, then you're trying to unpickle the objects from the GUI module. Remember that pickle doesn't actually store information about how a class/object is constructed, and needs access to the class when unpickling. See wiki...
You just did not rewind your buffer: bytes_io.seek(0) before pickle.load. Possibly you don't want to rewind to the front of the buffer, but just to the start of your pickled data. Then read out the stream position with bytes_io.tell() before pickling and seek to that position instead of 0....
The default representation for custom classes is to print their name and their id(): >>> class Foo: pass ... >>> Foo() <__main__.Foo instance at 0x106aeab90> You can give a class a __repr__ method to change the default representation, or a __str__ method to control how instances are converted to strings...
Pickling is unrelated to the opening and closing of the file. It only says something about the contents of the file. Hence, in your one-liner the file is opened but not closed. As such, it's better to do: with open("objectname.p","w") as f: pickle.dump(objectname, f) This uses the with statement with...
If you want to pickle the dict don't call str on it just dump the dict, if you actually want human readable output use json.dump: import json f = open("test.txt","w") # <- no b for json import pickle json.dump(f,a) pickle is not meant to be in human readable format, when...
python,hbase,apache-spark,pickle,happybase
Spark tries to serialize the connect object so it can be used inside the executors, which will surely fail because a deserialized db connect object can't grant read/write permission to another scope (or even computer). The problem can be reproduced by trying to broadcast the connect object. For this instance...
python,serialization,nlp,pickle,trie
I ended up storing the trie in MongoDB. There is a network overhead, but provided the database is on localhost it isn't too bad....
python,python-multiprocessing,pickle
If you look further down in the link you posted… to my answer (http://stackoverflow.com/a/21345273/2379433), you'll see you can indeed do what you want to do… even if you use lambdas and default dicts and all sorts of other python constructs. All you have to do is replace multiprocessing with pathos.multiprocessing…...
python,python-2.7,multiprocessing,pickle
The pickle module normally can't pickle instance methods: >>> import pickle >>> class A(object): ... def z(self): print "hi" ... >>> a = A() >>> pickle.dumps(a.z) Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/usr/local/lib/python2.7/pickle.py", line 1374, in dumps Pickler(file, protocol).dump(obj) File "/usr/local/lib/python2.7/pickle.py", line 224, in...
python,memory,dictionary,memory-leaks,pickle
If your data in the dictionaries are numpy arrays, there are packages (such as joblib and klepto) that make pickling large arrays efficient, as both the klepto and joblib understand how to use minimal state representation for a numpy.array. If you don't have array data, my suggestion would be to...
python,multithreading,sockets,pickle
The recv_msg method returns None when EOF is reached, and you pass that None to pickle.loads, which is an error. To fix the problem, place the call to pickle.loads() after the EOF-check: data = self.recv_msg(sock) if is not None: data = pickle.loads(data) msg = struct.pack('>I', len(data)) + data self.client.sendall(msg) else:...
This has nothing to do with pickling. I'll write new sample code that shows why it doesn't work. library = [] library.append("user_input_goes_here") print(library[0]) # OUTPUT: "user_input_goes_here") print(library[1]) # IndexError occurs here. You're only appending one thing to your empty list. Why do you think there are two elements? :) If...
python,python-2.7,multiprocessing,pickle
As the error suggests, you can't pickle instance methods. The problem is this line: pool.map(job.do_me, ((x[i], y[i]),)) for i in range(len(x)) The mechanism behind this is that when the map function sends the function (the first argument) to all of the workers, it has to serialize it to data somehow,...
python,scikit-learn,svm,pickle
pickle.dumps doesn't take the file argument. pickle.dump does. The interpreter is assuming that both open('svm.p', 'wb') and protocol=pickle.HIGHEST_PROTOCOL are being passed in as the protocol version, based on the order of parameters in the method definition. use pickle.dump as that will write the svm.p file....
json,serialization,flask,celery,pickle
To use json, You need to specify CELERY_ACCEPT_CONTENT = ['json'] CELERY_TASK_SERIALIZER = 'json' CELERY_RESULT_SERIALIZER = 'json' Looks like you are missing CELERY_RESULT_SERIALIZER = 'json' ...
python,nlp,scikit-learn,pickle,text-mining
Firstly, it's better to leave the import at the top of your code instead of within your class: from sklearn.feature_extraction.text import TfidfVectorizer class changeToMatrix(object): def __init__(self,ngram_range=(1,1),tokenizer=StemTokenizer()): ... Next StemTokenizer don't seem to be a canonical class. Possibly you've got it from http://sahandsaba.com/visualizing-philosophers-and-scientists-by-the-words-they-used-with-d3js-and-python.html or maybe somewhere else so we'll assume it...
The issue as somewhat loosely stated in the question is due to a gmpy backend vs python backend when storing complex numbers more info here: http://docs.sympy.org/dev/modules/mpmath/setup.html Now the default backend in ipython in my setup was "gmpy" and as per the website above in order to disable the gmpy mode...
python,list,file,python-3.x,pickle
I decided I didn't want to use a pickle because I wanted to be able to open the text file and change its contents easily during testing. Therefore, I did this: score = [1,2,3,4,5] with open("file.txt", "w") as f: for s in score: f.write(str(s) +"\n") with open("file.txt", "r") as f:...
You can get an unknown amount of pickled objects from a file by repeatedly calling load on a file handle object. >>> import string >>> # make a sequence of stuff to pickle >>> stuff = string.ascii_letters >>> # iterate over the sequence, pickling one object at a time >>>...
python,pickle,python-decorators
Yep, well-known pickle problem -- can't pickle functions or classes that can't just be retrieved by their name in the module. See e.g https://code.google.com/p/modwsgi/wiki/IssuesWithPickleModule for clear examples (specifically on how this affects modwsgi, but also of the issue in general). In this case since all you're doing is adding attributes...
python,python-3.x,pickle,python-2.4,2to3
You'll have to tell pickle.load() how to convert Python bytestring data to Python 3 strings, or you can tell pickle to leave them as bytes. The default is to try and decode all string data as ASCII, and that decoding fails. See the pickle.load() documentation: Optional keyword arguments are fix_imports,...
I found the error to the problem actually, it's pretty simple. What happened was that i copyed and pasted the content of a pickle output file into my txt and because pickle doesn't use only ascii characters it didn't copy properly. All i did was redump the dict onto the...
python,python-2.7,tkinter,pickle
The code you posted doesn't cause the error you say it does. Regardless, the error is telling you exactly what the problem is: you're referencing the "write" method on a string. Maybe you think you're referencing it via an open file object but you are actually referencing it on a...
python,parallel-processing,multiprocessing,pickle
It's hard to tell what's going on b/c you haven't given reproducible code or an error. However, your issue is very likely because you are using multiprocessing from inside a class. See: Using multiprocessing in a class and Multiprocessing: using Pool.map on a function defined in a class...
You need to pull the list from your database (i.e. your pickle file) first before appending to it. import pickle import os high_scores_filename = 'high_scores.dat' scores = [] # first time you run this, "high_scores.dat" won't exist # so we need to check for its existence before we load #...
Your load_dict function stores the result of unpickling into a local variable 'name'. This will not modify the object that you passed as a parameter to the function. Instead, you need to return the result of calling pickle.load() from your load_dict() function: def load_dict(filename): return pickle.load(open('{0}.p'.format(filename), 'rb')) And then assign...
python,list,dictionary,pickle,pop
This may be a simpler way to accomplish this: for index, Player in enumerate(PlayerID): if Player['ID'] == SearchID: PlayerID.pop(index) print("The user with ID", SearchID, ", has been deleted") break else: print("The ID provided does not exist.") ...
You are opening your pickle file with mode wb, which truncates (set's the file back to empty before writing anything new). The mode you want is a which opens for appending.
From Davies Liu (DataBricks): "Currently, PySpark can not support pickle a class object in current script ( 'main'), the workaround could be put the implementation of the class into a separate module, then use "bin/spark-submit --py-files xxx.py" in deploy it. in xxx.py: class test(object): def __init__(self, a, b): self.total =...
I've found a very nice solution here: Dynamically importing Python module And a code to solve the above problem is this: import pickle import sys import imp foo = imp.new_module("foo") sys.modules["foo"] = foo exec "def f(): print 'Hi!'" in foo.__dict__ code = pickle.dumps(foo.f) print code As you can see, the...
After pickling and unpickling, obviously command and command2 will never be the same object. That means commands == commands2 will always return False, unless you implement comparision for your class, for example: class KeyCommand(Command): ... def __eq__(self, other): return self.data == other.data def __ne__(self, other): return self.data != other.data ......
Well, I got inspired a lot by the comments from you guys and I came up with a solution that compress the HTML content using zlib and POST the data to API server, on the Flask API server side, I extract the data and push to mongodb for storage. Here...
If you are happy to assume the structure is the same all the way through, this has a natural recursive solution: def layers(data): try: keys = [data.keys()] except ValueError: return rest = layers(next(iter(data.values()))) return keys + rest if rest else keys Or in 3.x: from collections.abc import Mapping def layers(data):...
Pickle loads the components of a class instance in a non-deterministic order. This error is happening during the load but before it has deserialized the Person.profile_url attribute. Notice that it fails during load_setitem, which means it is probably trying to load the friend_set attribute, which is a set. Your custom...
python,counter,pickle,python-3.4
You can create a class variable directly inside the class, and then access it using Class.<variable> and also in __init__() function use this Class.<variable> to initialize the counter for each variable and increment the counter. Example - class TempClass counterInit = 0 def __init__(self): self.counter = TempClass.counterInit TempClass.counterInit += 1...