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Step-by-Step Guide to Creating an AWS RDS Database Instance

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 Amazon Relational Database Service (AWS RDS) makes it easy to set up, operate, and scale a relational database in the cloud. Instead of managing servers, patching OS, and handling backups manually, AWS RDS takes care of the heavy lifting so you can focus on building applications and data pipelines. In this blog, we’ll walk through how to create an AWS RDS instance , key configuration choices, and best practices you should follow in real-world projects. What is AWS RDS? AWS RDS is a managed database service that supports popular relational engines such as: Amazon Aurora (MySQL / PostgreSQL compatible) MySQL PostgreSQL MariaDB Oracle SQL Server With RDS, AWS manages: Database provisioning Automated backups Software patching High availability (Multi-AZ) Monitoring and scaling Prerequisites Before creating an RDS instance, make sure you have: An active AWS account Proper IAM permissions (RDS, EC2, VPC) A basic understanding of: ...
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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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