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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...

Python Program: JSON to CSV Conversion

JavaScript object notion is also called JSON file, it's data you can write to a CSV file. Here's a sample python logic for your ready reference. 




You can write a simple python program by importing the JSON, and CSV packages. This is your first step. It is helpful to use all the JSON methods in your python logic. That means the required package is JSON.

So far, so good. In the next step, I'll show you how to write a Python program. You'll also find each term explained.


What is JSON File

JSON is key value pair file. The popular use of JSON file is to transmit data between heterogeneous applications. Python supports JSON file.


What is CSV File

The CSV is comma separated file. It is popularly used to send and receive data.


How to Write JSON file data to a CSV file

Here the JSON data that has written to CSV file. It's simple method and you can use for CSV file conversion use.

import csv, json

json_string = '[{"value1": 1, "value2": 2,"value3": 1.234}]'
data = json.loads(json_string)
headers = data[0].keys()

with open('sample.csv', 'w') as f:
writer = csv.DictWriter(f, fieldnames=headers)
writer.writeheader()
writer.writerows(data)


with open('sample.csv', 'r') as f:
    print(f)
    for row in f:
        print(row)

Output:

<_io.TextIOWrapper name='file.csv' mode='r' encoding='UTF-8'>
value1,value2,value3

1,2,1.234


** Process exited - Return Code: 0 **
Press Enter to exit terminal

Conclusion

The output CSV file has both headers and rows, and the data is comma seprated.


References

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