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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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Amazon Web Service Import/Export Commands

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In the process like Hadoop cluster, which is already installed on CLOUD, the main input for data processing is huge volume of data. The big questions is how to send data to CLOUD from local machine.
It is NOT so easy to send huge volume of data to CLOUD through network.

AWS Import or Export

AWS introduced new feature called Import/Export, so that you can send hard drive to AWS, they will upload your data to S3 storage.

Different calculations:

How networking causes hurdle to move data to cloud?

A) Your internet speed is 1.544 MBPS it takes 82 days - So your data is 100 GB or more, based on your net speed you need to go for Import/Export.

Your internet speed is 10 MBPS it takes 13 days - So your data is 600 GB or more, based on your net speed you need to go for Import/Export.

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