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Step-by-Step Guide to Reading Different Files in Python

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 In the world of data science, automation, and general programming, working with files is unavoidable. Whether you’re dealing with CSV reports, JSON APIs, Excel sheets, or text logs, Python provides rich and easy-to-use libraries for reading different file formats. In this guide, we’ll explore how to read different files in Python , with code examples and best practices. 1. Reading Text Files ( .txt ) Text files are the simplest form of files. Python’s built-in open() function handles them effortlessly. Example: # Open and read a text file with open ( "sample.txt" , "r" ) as file: content = file.read() print (content) Explanation: "r" mode means read . with open() automatically closes the file when done. Best Practice: Always use with to handle files to avoid memory leaks. 2. Reading CSV Files ( .csv ) CSV files are widely used for storing tabular data. Python has a built-in csv module and a powerful pandas library. Using cs...
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What is Cluster- In the age of Big data and Analytics

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A cluster is local in that all of its component subsystems are supervised within a single administrative domain, usually residing in a single room and managed as a single computer system.

The constituent computer nodes are commercial-off-the-shelf (COTS), are capable of full independent operation as is, and are of a type ordinarily employed individually for standalone mainstream workloads and applications.
Hadoop + Cluster + Nodes-Jobs
(Cluster in Hadoop- Career options)

The nodes may incorporate a single microprocessor or multiple microprocessors in a symmetric multiprocessor (SMP) configuration.

The interconnection network employs COTS local area network (LAN) or systems area network (SAN) technology that may be a hierarchy of or multiple separate network structures. A cluster network is dedicated to the integration of the cluster compute nodes and is separate from the cluster's external (worldly) environment.

A cluster may be employed in many modes including but no limited to: high capability or sustained performance on a single problem, high capacity or throughput on a job or process workload, high availability through redundancy of nodes, or high bandwidth through multiplicity of disks and disk access or I/O channels.

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