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Showing posts with the label try and except logic

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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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How to Use Python Try and Except Logic Correctly

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In Python, you can avoid exceptions using Try and Except logic. The Error-free programs save a lot of time. Also, you can keep away defects in production.   How to Use Python Try and Except Logic Correctly In Python, you can handle un-known errors by using TRY and EXCEPT logic. If the programmer does not take care of this, the default is for  Python to print  an error message and stops execution.  So the responsibility of a programmer is upfront he/she has to find errors and handle them correctly. It is possible if you use the  TRY and EXCEPT. Python Syntax for Try and Except. try:       c = a/b except:       c = 1000000 Try ends with ':' it says that Try block start here. In this block, you can write actual logic. The Except: is another block. That means in this block programmer can specify some value. And that value populates when any error happens. Try and Except Examples. Example: 1. Below is the example to give the...
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