Last Updated : 12 Jul, 2025
Python allows users to handle files (read, write, save and delete files and many more). Because of Python, it is very easy for us to save multiple file formats. Python has in-built functions to save multiple file formats.
Opening a text file in PythonOpening a file refers to getting the file ready either for reading or for writing. This can be done using the
open()
function.
Syntax:File_object = open("File_Name", "Access_Mode")Parameters:
By default, Python assumes the access mode as read i.e ("r")
Python3
# Python program to demonstrate
# opening a file
# Open function to open the file "myfile.txt"
# (same directory) in read mode and store
# it's reference in the variable file1
file1 = open("myfile.txt")
# Reading from file
print(file1.read())
file1.close()
Note:
For more information, refer to
Open a File in Python.
Saving a Text File in PythonAfter learning about opening a File in Python, let's see the ways to save it. Opening a new file in write mode will create a file and after closing the file, the files get saved automatically. However, we can also write some text to the file. Python provides two methods for the same.
File_object.write(str1)
File_object.writelines(L) for L = [str1, str2, str3]
# Python program to demonstrate
# saving a text file
file = open('read.txt', 'w')
file.write('Welcome to Geeks for Geeks')
file.close()
Output: With Statementwith
statement in Python is used in exception handling to make the code cleaner and much more readable. It simplifies the management of common resources like file streams. Unlike the above implementations, there is no need to call
file.close()
when using
with
statement. The
with
statement itself ensures proper acquisition and release of resources.
Syntax:with open filename as file: statement(s)Example: Python3
# Python program to demonstrate
# saving a text file
with open('read.txt', 'w') as file:
books = ['Welcome\n',
'Geeks\n',
'to\n',
'Geeks\n',
'for\n',
'Geeks\n',
'world\n']
file.writelines("% s\n" % data for data in books)
Output: Note:
For more information, refer to
Writing to file in Python.
Saving a CSV File in PythonCSV is a Comma Separated Values files are most widely utilized for putting tabular data. CSV file stores tabular data (numbers and text) in plain text. Each line of the file is a data record. Each record consists of one or more fields, separated by commas. Python has built-in module called
csv
to write and Save a CSV File.
To save a CSV File:
# Python program to demonstrate
# writing to CSV
import csv
# field names
fields = ['Name', 'Branch', 'Year', 'CGPA']
# data rows of csv file
rows = [ ['Nikhil', 'COE', '2', '9.0'],
['Sanchit', 'COE', '2', '9.1'],
['Aditya', 'IT', '2', '9.3'],
['Sagar', 'SE', '1', '9.5'],
['Prateek', 'MCE', '3', '7.8'],
['Sahil', 'EP', '2', '9.1']]
# name of csv file
filename = "university_records.csv"
# writing to csv file
with open(filename, 'w') as csvfile:
# creating a csv writer object
csvwriter = csv.writer(csvfile)
# writing the fields
csvwriter.writerow(fields)
# writing the data rows
csvwriter.writerows(rows)
Output: Note:
For more information, refer to
Writing CSV files in Python.
Saving a JSON File in PythonThe full-form of JSON is JavaScript Object Notation. It means that a script (executable) file which is made of text in a programming language, is used to store and transfer the data. Python supports JSON through a built-in package called
json
. The text in JSON is done through quoted-string which contains the value in key-value mapping within
{ }
. This module provides a method called
dump()
which converts the Python objects into appropriate json objects.
Python3
import json
# python object(dictionary) to be dumped
dict1 ={
"emp1": {
"name": "Lisa",
"designation": "programmer",
"age": "34",
"salary": "54000"
},
"emp2": {
"name": "Elis",
"designation": "Trainee",
"age": "24",
"salary": "40000"
},
}
# the json file where the output must be stored
out_file = open("myfile.json", "w")
json.dump(dict1, out_file, indent = 6)
out_file.close()
Output: Note:
For more information, refer to
Working With JSON Data in Python.
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