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Python Set Operations Explained: From Theory to Real-Time Applications

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A  set  in Python is an unordered collection of unique elements. It is useful when storing distinct values and performing operations like union, intersection, or difference. Real-Time Example: Removing Duplicate Customer Emails in a Marketing Campaign Imagine you are working on an email marketing campaign for your company. You have a list of customer emails, but some are duplicated. Using a set , you can remove duplicates efficiently before sending emails. Code Example: # List of customer emails (some duplicates) customer_emails = [ "alice@example.com" , "bob@example.com" , "charlie@example.com" , "alice@example.com" , "david@example.com" , "bob@example.com" ] # Convert list to a set to remove duplicates unique_emails = set (customer_emails) # Convert back to a list (if needed) unique_email_list = list (unique_emails) # Print the unique emails print ( "Unique customer emails:" , unique_email_list) Ou...
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How to Understand Pickling and Unpickling in Python

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Here are the Python pickling and unpickling best examples and the differences between these two.


pickling and unpickling in python




These you can use to serialize and deserialize the python data structures. The concept of writing the total state of an object to the file is called pickling, and to read a Total Object from the file is called unpickling.


Pickle and Unpickle

The process of writing the state of an object to the file (converting a class object into a byte stream) and storing it in the file is called pickling. It is also called object serialization.

The process of reading the state of an object from the file ( converting a byte stream back into a class object) is called unpickling. It is an inverse operation of pickling. It is also called object deserialization. The pickling and unpickling can implement by using a pickling module since binary files support byte streams. Pickling and unpickling should be possible using binary files.


Data types you can pickle

  1. Integers
  2. Booleans
  3. Complex numbers
  4. Floats
  5. Normal and Unicode strings
  6. Tuple
  7. List
  8. Set and dictionaries which contains pickling objects
  9. Classes and built-in functions can define at the top level of a module.

Functions you need


dump()


The above function performs pickling. It returns the pickled representation of an object as a byte object instead of writing it to the file. It is called to serialize an object hierarchy.


Syntax:


import pickle

pickle.dump(object, file, protocol)


where

the object is a python object to serialize

a file is a file object in which the serialized python object will be stored


protocol if not specified is 0. If specified as HIGHEST PROTOCOL or negative, then the highest protocol version available will be used. 



load()


The above function performs unpickling. It reads a pickled object from a binary file and returns it as an object. It is used to deserialize a data stream.


Syntax:


import pickle

pickle.load(file)



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