Extracting text from a file is a common task in scripting and programming, and Python makes it easy. In this guide, we'll discuss some simple ways to extract text from a file using the Python 3 programming language.

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Make sure you're using Python 3

In this guide, we'll be using Python version 3. Most systems come pre-installed with Python 2.7. While Python 2.7 is used in most legacy code, Python 3 is the present and future of the Python language. Unless you have a specific reason to write or support legacy Python code, we recommend working in Python 3.

For Microsoft Windows, Python 3 can be downloaded from the Python official website. When installing, make sure the 'Install launcher for all users' and 'Add Python to PATH' options are both checked, as shown in the image below.

On Linux, you can install Python 3 with your package manager. For instance, on Debian or Ubuntu, you can install it with the following command:

For macOS, the Python 3 installer can be downloaded from python.org, as linked above. If you are using the Homebrew package manager, it can also be installed by opening a terminal window (Applications → Utilities), and running this command:

Running Python

On Linux and macOS, the command to run the Python 3 interpreter is python3. On Windows, if you installed the launcher, the command is py. The commands on this page use python3; if you're on Windows, substitute py for python3 in all commands.

Running Python with no options starts the interactive interpreter. For more information about using the interpreter, see Python overview: using the Python interpreter. If you accidentally enter the interpreter, you can exit it using the command exit() or quit().

Running Python with a file name will interpret that python program. For instance:

..runs the program contained in the file program.py.

Okay, how can we use Python to extract text from a text file?

Reading data from a text file

First, let's read a text file. Let's say we're working with a file named lorem.txt, which contains a few lines of Latin:

Note

In all the examples that follow, we work with text contained in this file. Feel free to copy and paste the latin text above into a text file, and save it as lorem.txt, so that you can run the example code using this file as input.

A Python program can read a text file using the built-in open() function. For example, below is a Python 3 program that opens lorem.txt for reading in text mode, reads the contents into a string variable named contents, closes the file, and then prints the data.

Here, myfile is the name we give to our file object.

The 'rt' parameter in the open() function means 'we're opening this file to read text data'

The hash mark ('#') means that everything on the rest of that line is a comment, and it is ignored by the Python interpreter.

If you save this program in a file called read.py, you can run it with the following command.

The command above outputs the contents of lorem.txt:

Using 'with open'

It's important to close your open files as soon as possible: open the file, perform your operation, and close it. Don't leave it open for extended periods of time.

When you're working with files, it's good practice to use the with open..as compound statement. It's the cleanest way to open a file, operate on it, and close the file, all in one easy-to-read block of code. The file is automatically closed when the code block completes.

Using with open..as, we can rewrite our program to look like this:

Note

Indentation is important in Python. Python programs use white space at the beginning of a line to define scope, such as a block of code. We recommend you use four spaces per level of indentation, and that you use spaces rather than tabs. In the following examples, make sure your code is indented exactly as it's presented here.

Example

Save the program as read.py and execute it:

Output

Reading text files line-by-line

In the examples so far, we've been reading in the whole file at once. Reading a full file is no big deal with small files, but generally speaking, it's not a great idea. For one thing, if your file is bigger than the amount of available memory, you'll encounter an error.

In almost every case, it's a better idea to read a text file one line at a time.

In Python, the file object is an iterator. An iterator is a type of Python object which behaves in certain ways when operated on repeatedly. For instance, you can use a for loop to operate on a file object repeatedly, and each time the same operation is performed, you'll receive a different, or 'next,' result.

Example

For text files, the file object iterates one line of text at a time. It considers one line of text a 'unit' of data, so we can use a for..in loop statement to iterate on the data one line at a time:

Output

Notice that we're getting an extra line break ('newline') after every line. That's because two newlines are being printed. The first one is the newline at the end of every line of our text file. The second newline happens because, by default, print() adds a linebreak of its own at the end of whatever you've asked it to print.

Let's store our lines of text in a variable — specifically, a list variable — so we can look at it more closely.

Storing text data in a list variable

In Python, lists are similar to, but not the same as, an array in C or Java. A Python list contains indexed data, of varying lengths and types.

Example

The output of this program is a little different. Instead of printing the contents of the list, this program prints our list object, which looks like this:

Output

Here, we see the raw contents of the list. In its raw object form, a list is represented as a comma-delimited list. Here, each element is represented as a string, and each newline is represented as its escape character sequence, n.

Much like an array in C or Java, we can access the elements of a list by specifying an index number after the variable name, in brackets. Index numbers start at zero — other words, the nth element of a list has the numeric index n-1.

Note

If you're wondering why the index numbers start at zero instead of one, you're not alone. Computer scientists have debated the usefulness of zero-based numbering systems in the past. In 1982, Edsger Dijkstra gave his opinion on the subject, explaining why zero-based numbering is the best way to index data in computer science. You can read the memo yourself — he makes a compelling argument.

Example

We can print the first element of lines by specifying index number 0, contained in brackets after the name of the list:

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