Adventures in Machine Learning

Mastering File I/O in Python: Writing Strings on New Lines

Newline Character, Formatted String Literal, and for Loop in Writing Strings to a File

Writing strings to a file is a fundamental task in programming. However, it becomes more complex when those strings need to be written to a file on a new line every time.

To accomplish this, there are several methods that can be utilized.

One of the most direct ways to add a newline character to a string is by appending it directly.

For instance, if you wish to write the string “Hello World” to a file with a newline character, add the n escape character to the end of the string: “Hello Worldn”. This way, every time the string is written to the file, it will be on a new line.

Another simple way to write strings on a new line every time is through the use of formatted string literals. By using the “f” character before the string and adding curly braces {} with an expression inside, the content of the expression will be added to the string at that point.

For example, to add a variable called “name” on a new line, you could write f”{name}n”. The newline character (n) at the end will ensure that the string is written on a new line every time.

Additionally, for loops can be employed to write a list of strings to a file, with each string being written on a new line. This method makes it easy to loop through multiple strings and write them all to the file on separate lines.

As an example, a list of several strings can be defined, and then written to a file using a for loop:


lines = [‘First line’, ‘Second line’, ‘Third line’]

with open(‘file.txt’, ‘w’) as f:

for line in lines:

f.write(line + ‘n’)


In this case, each string in the list is written to the file using the write method, which has been given the string concatenated with the newline character. Therefore, when the next string in the list is written to the file, it will appear on a new line.

Defining a Reusable Function and Using str.join() Method

Using the above-mentioned methods can accomplish the task of writing strings to a file on new lines. However, if you need to perform this action repeatedly in your code, it is possible to define a reusable function.

A function can take in a filename and a list of lines and write them to the file with each line on a new line:


def write_lines_to_file(lines, filename):

with open(filename, ‘w’) as f:



In this way, the method write_lines_to_file can be called anywhere in the code where this functionality is required, saving time and effort for the programmer. Finally, one can use the str.join() method to add a sequence of strings to the file, separated by a specific separator.

If we want to add a list of strings to a file with a new line after each string, this can be accomplished using the join method, again with the newline character as a separator.


with open(‘file.txt’, ‘w’) as f:

lines = [‘First line’, ‘Second line’, ‘Third line’]



This method combines all strings in the list into one string with the separator added between them.

When this string is written to the file, each string will appear on a new line.

Issues with Using the Older open() Syntax

When opening a file in Python, there are two methods available: the older open() syntax and the with open() syntax. If the programmer uses the older open() method, they must remember to close the file manually when they’re done.

The unclosed file can cause problems, like running out of file handles, when too many files are open at the same time. Developers often forgot to close the file, causing memory leaks and unpredictability in the system.

The with open() syntax provides an automatic way to close the file once it is no longer needed. In addition, this statement provides error handling functionality, that allows the developer to catch any exceptions in accessing the file.

The with open() method ensures that the file is closed automatically without the need for manual intervention.


As we’ve seen, there are several ways to write strings to a file on a new line every time. By concatenating a newline character to the string, utilizing formatted string literals, using for loops, or defining a reusable function, developers can accomplish this task with ease.

Additionally, using the newer with open() syntax has significant advantages over the older open() method including automated closing of files and exception handling. With these techniques in hand, Python developers will have a smoother time working with files, saving time and error-prone manual actions.

In addition to the methods outlined previously, there are several other techniques that Python developers can use to write strings to a file on a new line every time. In this article’s expansion, we will cover these methods and provide further resources for those interested in exploring these topics in greater detail.

Revisiting the str.join() Method

The str.join() method is a powerful and versatile tool in Python that can be used to concatenate sequences of strings with a given delimiter. In the examples we covered earlier, we used the newline character (n) as a separator to write strings on new lines.

However, it’s important to remember that the join method can be used with any separator, including commas, spaces, and more. For example, suppose you have a list of words that you want to concatenate into a single string with spaces between each word.

In that case, you can use the join method with an empty space as the separator like this:


words = [‘hello’, ‘world’, ‘this’, ‘is’, ‘Python’]

with open(‘file.txt’, ‘w’) as f:

f.write(‘ ‘.join(words))


The result will be a single string with each word separated by a single space. Similarly, you can use the join method with commas or any other delimiter you wish to use.

Context Managers

Context managers are a powerful concept in Python that can simplify file I/O operations and improve code readability. A context manager is a Python object that defines two methods: __enter__() and __exit__().

These methods are called automatically when you use the object with Python’s with statement. Using a context manager to manage file I/O operations in Python is a popular technique.

Instead of opening and closing the file manually, the context manager handles these steps automatically, ensuring that the file is properly closed even if an exception is thrown. For example, suppose we want to open a file to write some data to it.

Instead of manually opening the file and closing it when we’re done, we can use the with statement to open and close the file automatically.


with open(‘file.txt’, ‘w’) as f:

f.write(‘Hello, world!’)


Python will automatically open the file with the specified mode (‘w’) and assign it to the variable f.

The code block inside the with statement executes, and when it’s done, Python will automatically close the file.

Using a context manager provides several benefits.

First, it eliminates the need for manual file handling, which saves time and reduces the chance of introducing errors. Second, it ensures that the file is properly closed, even in the event of an exception being thrown.

Finally, it improves code readability by making the code more concise and easier to understand.

Reading and Writing Binary Data

In the previous examples, we discussed how to write text data to a file on a new line each time. However, sometimes you might need to write and read binary data to and from a file.

Binary data refers to data that is stored in a non-human-readable format, such as binary code. Common examples of binary data include images, audio files, and executable programs.

When dealing with binary data, it’s essential to use the correct mode when opening files. For example, when opening a file for reading binary data, use the mode ‘rb’ instead of ‘r’.

Similarly, when opening a file for writing binary data, use the mode ‘wb’ instead of ‘w’.

Here is an example of how to write a binary file in Python:


with open(‘binary_file.bin’, ‘wb’) as f:

data = b’x00x01x02x03x04x05x06x07x08x09′



In this example, we used the ‘wb’ mode to write binary data to the file.

We defined the data as a byte string using the “b” character before the string, and then wrote it to the file using the write method. To read the binary data from a file, we can use a similar technique, but this time using the ‘rb’ mode:


with open(‘binary_file.bin’, ‘rb’) as f:

data =


In this case, we used the ‘rb’ mode to read binary data from the file.

We then used the read() method to read the binary data into a variable called data.

Further Resources

Developing file I/O skills is essential for Python developers. To further explore the topics covered in this article, here are some recommended resources:


The Python documentation on file I/O: The official documentation provides a comprehensive guide to file I/O operations in Python. It includes examples and explanations of the various methods and techniques covered in this article.

2. Automate the Boring Stuff with Python by Al Sweigart: This book covers practical Python programming tasks, including file I/O, with step-by-step instructions and plenty of examples.

3. Python for Data Science Handbook by Jake VanderPlas: This book covers data analysis techniques using Python and includes a section on file I/O.

It provides a practical approach to file handling and provides many real-world examples.

These resources cover a wide variety of topics related to file I/O, from basic to advanced techniques, and provide a solid foundation for developing your file handling skills in Python.

In conclusion, writing strings to a file on a new line every time is an essential task for Python programmers. This article explored several methods to accomplish this task, including appending newline characters to strings, using formatted string literals, for loops, defining reusable functions, and the str.join() method.

Additionally, we highlighted the benefits of using the with open() statement over the older open() syntax and discussed the use of context managers for file I/O operations and handling binary data. Developing file I/O skills is a necessity for Python developers and provides numerous benefits that improve code quality, reliability, and readability.

With the tips and techniques discussed in this article, including the recommended resources, you can improve your file I/O skills and avoid common errors in Python programming.

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