![]() with open('my_file.txt', 'r') as r:īack to CSV now - You can use the built-in csv module to read and write CSV files in Python. ![]() Using this approach, the file is automatically closed eliminating the need to manually close the file using close() If we were to re-write the previous example using with open(), it would look like the one below. In the end, we closed the file by calling the close() method.Ī better approach to opening a file is to use with open() function.We then called the read() method on the File Object to read the contents of the file.We stored the File Object in a variable called r.Open() function returns a File Object that is simply another type of value in Python, just like lists and dictionaries.Print(r.read()) #Read the contents of the 'File Object' r = open('my_file.txt', 'r') #open a file which returns a 'File Object' The Python code would look like the one below. Let's say, I want to open a text file called ' my_file.txt' and read the contents. Specifying a mode (The default mode is r ) When you open a file, you will also need to specify a mode. Once you finished working with that specific file, you should always close the file using the close() function. You can use Python's built-in open() function to open a file. ![]() Reading and Writing Files in Pythonīefore we dive into working with CSV files, let's have a look at the fundamentals of working with files in Python. The delimiter can be any single character, but, is predominantly used. The elements are separated by 'commas' which is called the delimiter. ID, Hostname, LocationĪs you can see above, each line in a CSV file represents a row. Let's look at one of the CSV files - I first opened them as a text file and then open them as how you normally would open them in Excel. CSV files are plain-text files, making them easier to create, edit and move across various systems. OverviewĪ CSV is a comma-separated value file, which allows data to be saved in a tabular format. In this blog post, we will learn how to read, write and work with CSV files in Python. Once you start working with Python, sooner or later you will come across having to work with CSV files.
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