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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...

10 Tricky Apache-Storm Interview Questions

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The storm is a real-time computation system. It is a flagship software from Apache foundation. Has the capability to process in-stream data. You can integrate traditional databases easily in the Storm. The tricky and highly useful interview questions given in this post for your quick reference. Bench mark for Storm is a million tuples processed per second per node. Tricky Interview Questions 1) Real uses of Storm? A) You can use in real-time analytics, online machine learning, continuous computation, distributed RPC, ETL 2) What are different available layers on Storm? Flux SQL Streams API Trident   3)  The real use of SQL API on top of Storm? A) You can run SQL queries on stream data 4) Most popular integrations to Storm? HDFS Cassandra JDBC HIVE HBase 5) What are different possible Containers integration with Storm? YARN DOCKER MESOS 6) What is Local Mode? A) Running topologies in the Local server we can say as Local Mode. ...