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Python Pickle Alternatives? Top Answer Update

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An alternative is cPickle. It is nearly identical to pickle , but written in C, which makes it up to 1000 times faster. For small files, however, you won’t notice the difference in speed. Both produce the same data streams, which means that Pickle and cPickle can use the same files.Pickle is unsafe because it constructs arbitrary Python objects by invoking arbitrary functions. However, this is also gives it the power to serialize almost any Python object, without any boilerplate or even white-/black-listing (in the common case).The insecurity is not because pickles contain code, but because they create objects by calling constructors named in the pickle. Any callable can be used in place of your class name to construct objects. Malicious pickles will use other Python callables as the “constructors.” For example, instead of executing “models.

Depending on what exactly you want to store, there are other alternatives:
  • Apache Feather.
  • Apache Avro.
  • Apache Parquet.
Python Pickle Alternatives
Python Pickle Alternatives

Table of Contents

What can I use instead of pickle in Python?

Depending on what exactly you want to store, there are other alternatives:
  • Apache Feather.
  • Apache Avro.
  • Apache Parquet.

Why pickle is not good in Python?

Pickle is unsafe because it constructs arbitrary Python objects by invoking arbitrary functions. However, this is also gives it the power to serialize almost any Python object, without any boilerplate or even white-/black-listing (in the common case).


Machine Learning Tutorial Python – 5: Save Model Using Joblib And Pickle

Machine Learning Tutorial Python – 5: Save Model Using Joblib And Pickle
Machine Learning Tutorial Python – 5: Save Model Using Joblib And Pickle

Images related to the topicMachine Learning Tutorial Python – 5: Save Model Using Joblib And Pickle

Machine Learning Tutorial Python - 5: Save Model Using Joblib And Pickle
Machine Learning Tutorial Python – 5: Save Model Using Joblib And Pickle

Why are pickles so insecure?

The insecurity is not because pickles contain code, but because they create objects by calling constructors named in the pickle. Any callable can be used in place of your class name to construct objects. Malicious pickles will use other Python callables as the “constructors.” For example, instead of executing “models.

Why is JSON more secure than pickle?

json is more secure because it’s fundamentally more limited. The only python types that a json document can encode are unicode , int , float , NoneType , bool , list and dict . these are marshaled/unmarshalled in a basically trivial fashion that isn’t vulnerable to code injection attacks.

Are pickles faster than JSON?

JSON is a lightweight format and is much faster than Pickling. There is always a security risk with Pickle. Unpickling data from unknown sources should be avoided as it may contain malicious or erroneous data. There are no loopholes in security using JSON, and it is free from security threats.

Is Jsonpickle secure?

jsonpickle Usage

The jsonpickle module is not secure. Only unpickle data you trust. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling. Never unpickle data that could have come from an untrusted source, or that could have been tampered with.

Is Python pickling slow?

Pickle on the other hand is slow, insecure, and can be only parsed in Python. The only real advantage to pickle is that it can serialize arbitrary Python objects, whereas both JSON and MessagePack have limits on the type of data they can write out.


See some more details on the topic python pickle alternatives here:


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What is the difference between pickle and Joblib?

While Pickle requires a file object to be passed as an argument, Joblib works with both file objects and string filenames. In case your model contains large arrays of data, each array will be stored in a separate file, but the save and restore procedure will remain the same.

What is the difference between pickle and cPickle?

The pickle data format is standardized, so strings serialized with pickle can be deserialized with cPickle and vice versa. The main difference between cPickle and pickle is performance. The cPickle module is many times faster to execute because it’s written in C and because its methods are functions instead of classes.

What is Unpickling in Python?

“Pickling” is the process whereby a Python object hierarchy is converted into a byte stream, and “unpickling” is the inverse operation, whereby a byte stream (from a binary file or bytes-like object) is converted back into an object hierarchy.

What is pickle dump?

Overview: The dump() method of the pickle module in Python, converts a Python object hierarchy into a byte stream. This process is also called as serilaization. The converted byte stream can be written to a buffer or to a disk file.


The BEST way to store data in python pandas.. spoiler: it’s not CSV

The BEST way to store data in python pandas.. spoiler: it’s not CSV
The BEST way to store data in python pandas.. spoiler: it’s not CSV

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What is pickling 1 point?

The process to converts any kind of python objects (list, dict, etc.) into byte streams (0s and 1s) is called pickling or serialization or flattening or marshalling. We can converts the byte stream (generated through pickling) back into python objects by a process called as unpickling.

Are Python pickles cross platform?

Python’s pickle is perfectly cross-platform. This is likely due to EOL (End-Of-Line) differences between Windows and Linux. Make sure to open your pickle files in binary mode both when writing them and when reading them, using open()’s “wb” and “rb” modes respectively.

Should I use pickle?

Cons-1: Pickle is Unsafe

Unlike JSON, which is just a piece of string, it is possible to construct malicious pickle data which will execute arbitrary code during unpickling. Therefore, we should NEVER unpickle data that could have come from an untrusted source, or that could have been tampered with.

What is dill Python?

About Dill

Serialization is the process of converting an object to a byte stream, and the inverse of which is converting a byte stream back to a python object hierarchy. dill provides the user the same interface as the pickle module, and also includes some additional features.

What is the PKL extension?

A PKL file is a file created by pickle, a Python module that enabless objects to be serialized to files on disk and deserialized back into the program at runtime. It contains a byte stream that represents the objects.

What is the difference between JSON and dictionary in Python?

oranges comparison: JSON is a data format (a string), Python dictionary is a data structure (in-memory object). If you need to exchange data between different (perhaps even non-Python) processes then you could use JSON format to serialize your Python dictionary.

Can pickle store tuples in string format?

Here are the things that the pickle module store: All the native datatypes that Python supports: booleans, integers, floating point numbers, complex numbers, strings, bytes objects, byte arrays, and None. Lists, tuples, dictionaries, and sets containing any combination of native datatypes.

What is __ reduce __?

Whenever an object is pickled, the __reduce__ method defined by it gets called. This method returns either a string, which may represent the name of a Python global, or a tuple describing how to reconstruct this object when unpickling.

What can you replace dill pickles with?

Dill substitute for pickling
  • Linda Ziedrich says that if a recipe calls for a fresh dill umbel and you don’t have one, use one teaspoon of dried dill seed instead. …
  • The National Center for Home Food Preservation says, “For each quart, try 3 heads of fresh dill or 1 to 2 tablespoons dill seed (dill weed = 2 tablespoons).”

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Is Dill faster than pickle?

Yes, dill is slower typically, but that’s the penalty you pay for more robust serialization. If you are serializing a lot of classes and functions, then you might want to try one of the dill variants in dill.

How fast is pickling Python?

Loading this pickle takes around 15 seconds. How can I reduce this time? The code bellow shows how much time takes to dump or load a file using json, pickle, cPickle. After dumping, file size would be around 300MB.

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