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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...

The Ultimate Cheat Sheet On Hadoop

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Top 20 frequently asked questions to test your Hadoop knowledge given in the below Hadoop cheat sheet . Try finding your own answers and match the answers given here. Question #1  You have written a MapReduce job that will process 500 million input records and generate 500 million key-value pairs. The data is not uniformly distributed. Your MapReduce job will create a significant amount of intermediate data that it needs to transfer between mappers and reducers which is a potential bottleneck. A custom implementation of which of the following interfaces is most likely to reduce the amount of intermediate data transferred across the network? A. Writable B. WritableComparable C. InputFormat D. OutputFormat E. Combiner F. Partitioner Ans: e Question #2  Where is Hive metastore stored by default ? A. In HDFS B. In client machine in the form of a flat file. C. In client machine in a derby database D. In lib directory of HADOOP_HOME, and requires HADOOP_CLASSPATH to be modif...