It seems a bit strange that you get that error when executing predict_edu.py, as it is in the same directory as predictors.py, and thus, using absolute import such as from predictors import predictor_transformer (without the dot . operator) should normally work as expected. However, below are a few options that you could try out, if … Read more
Sure, you can use PowerShell’s native CliXml format: @{ a = 1 b = [pscustomobject]@{ prop = “value” } } | Export-Clixml -Path hashtable.ps1xml Deserialize with Import-CliXml: PS C:\> $ht = Import-CliXml hashtable.ps1xml PS C:\> $ht[‘b’].prop -eq ‘value’ True
So this actually turned out to be a memory issue. When the computer would run out of RAM and try to unpickle or load the data, the process would fail claiming this EOFError. I increase the RAM on the computer and this never was an issue again. Thanks for all the comments and help.
Always use b mode when reading and writing pickles (open(f, ‘wb’) for writing, open(f, ‘rb’) for reading). To “fix” the file you already have, convert its newlines using dos2unix.
If you pass the filehandle directly into pickle you can get the result you want. import pickle # write a file f = open(“example”, “w”) pickle.dump([“hello”, “world”], f) pickle.dump([2, 3], f) f.close() f = open(“example”, “r”) value1 = pickle.load(f) value2 = pickle.load(f) f.close() pickle.dump will append to the end of the file, so you can … Read more
There is lots of information about this available. For the “official word” on the issue, read the (closed) Python bugtracker issue. The core reasoning, by one of the people who made the decision, is detailed on this blog: Since a generator is essentially a souped-up function, we would need to save its bytecode, which is … Read more
“are much more likely than a never-observed bug in Python itself in a functionality that’s used billions of times a day all over the world”: it always amazes me how cross people get in these forums. One easy way to get this problem is by forgetting to close the stream that you’re using for dumping … Read more
r+ is used for reading, and writing mode. b is for binary. r+b mode is open the binary file in read or write mode. You can read more here.
Create the named tuple outside of the function: from collections import namedtuple import pickle P = namedtuple(“P”, “one two three four”) def pickle_test(): my_list = [] abe = P(“abraham”, “lincoln”, “vampire”, “hunter”) my_list.append(abe) with open(‘abe.pickle’, ‘wb’) as f: pickle.dump(abe, f) pickle_test() Now pickle can find it; it is a module global now. When unpickling, all … Read more
Here’s a very simple example for Python that should supplement the pickle docs. class Foo(object): def __init__(self, val=2): self.val = val def __getstate__(self): print(“I’m being pickled”) self.val *= 2 return self.__dict__ def __setstate__(self, d): print(“I’m being unpickled with these values: ” + repr(d)) self.__dict__ = d self.val *= 3 import pickle f = Foo() f_data … Read more