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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...

Microsoft HDInsight for Hadoop Cluster

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HDInsight is Microsoft's implementation of a Big Data solution with Apache Hadoop at its core. HDInsight is 100 percent compatible with Apache Hadoop and is built on open source components in conjunction with Hortonworks, a company focused toward getting Hadoop adopted on the Windows platform. HDInsight Microsoft Initiate Basically, Microsoft has taken the open source Hadoop project, added the functionalities needed to make it compatible with Windows (because Hadoop is based on Linux), and submitted the project back to the community.  All of the components are retested in typical scenarios to ensure that they work together correctly and that there are no versioning or compatibility issues. Features Microsoft's Hadoop-based distribution brings the robustness, manageability, and simplicity of Windows to the Hadoop environment.  The focus is on hardening security through integration with Active Directory, thus making it enterprise ready, simplifying manageability through in...