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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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RDBMS Vs Key-value Four Top Differences

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This post tells you differences between rdbms and distributed key-value storage.

Rdbms is quite  different from key-value storage.

RDBMS Vs Key-value Four Top Differences

RDBMS (Relational Database)

  1. You have already used a relational database management system — a storage product that's commonly referred to as RDBMS. 
  2. It is basically a structured data.
  3. RDBMS systems are fantastically useful to handle moderate data.
  4. The BIG challenge is in scaling beyond a single server. 
  5. You can't maintain redundant data in rdbms.
  6. All the data available on single server.
  7. The entire database runs on single server. So when server is down then database may not be available to normal business operations.
  8. Outages and server downs are common in this rdbms model of database.

Key-Value Database

  1. Key-value storage systems often make use of redundancy within hardware resources to prevent outages. This concept is important when you're running thousands of servers because they're bound to suffer hardware breakdowns. 
  2. Multiple copies same data available on multiple servers.
  3. The use of redundancy makes the key-value system always available — and, more importantly, your data is always available because it's protected from hardware outages.
  4. Literally, dozens of key-value storage products are available. Many of them were first developed by so-called webscale companies, such as Facebook and LinkedIn, to ensure that they can handle massive amounts of traffic. 
  5. Currently key-value storages under open source licenses are available. Now you (or anyone else) can use them in other environments too.

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