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Question: Does Python have a for each or foreach loop? If so, how does it work? If not, what is the alternative?

This article will shed light on these questions. I’ll give you the summary first and dive into the details later:

Python has three alternatives to the “for each” loop:

1. A simple for ... in ... loop
2. A map() function
3. A list comprehension statement.

You’ll learn about those alternatives in the following paragraphs, so keep reading!

Let’s get started with the most important question:

What is a “Foreach Loop”?

Definition: A foreach or for each loop is a programming control flow statement for iterating over elements in a sequence or collection. Unlike other loop constructs, the foreach loop iterates over all elements rather than maintaining a counter, loop variable, or checking a condition after each loop iteration.

Here are three examples of a foreach loop in three different programming languages PHP, C#, and Perl:

// PHP

foreach ($set as $value) { // Do something to $value;

} // C#

foreach (String val in array) { console.writeline(val);

} // Perl

foreach (1, 2, 3, 4) { print $_;

}

Does Python have a foreach Loop?

The Python language doesn’t support the keywords foreach or for each loops in a literal syntactical way. However, “for each” in Python is done using the “for … in …” expression. For example, to iterate over each element in the list [10, 20, 30] in Python, you’d write for x in [10, 20, 30].

Here’s a full Python code example with semantical equivalence to a “foreach” statement:

# 'foreach' or 'for each' in Python is done using 'for'

for x in [10, 20, 30]: print(x)

Output:

10

20

30

Learn More: Feel free to check out our full article on Python loops on the Finxter blog.

“For Each” Meaning “Apply Function to Each Element”

If you’re reading this and you haven’t been satisfied with the answers provided so far, chances are that you’re really searching for the map function functionality in Python.

Many programming languages with “for each” support provide a syntax that applies a function to each element of an iterable like so:

# Other programming languages:

foreach(function, iterable)

This can be done in Python by means of the map() function:

# Python:
map(function, iterable)

Here’s a simple example of how you’d use the map() function in Python that applies the function f to each element of the list [1, 2, 3], incrementing each of its elements by 1 to obtain [2, 3, 4]:

lst = [1, 2, 3] def f(x): return x + 1 print(map(f, lst))

# [2, 3, 4]

You can watch my explainer video on map() in the following video:

Learn More: Feel free to check out our full article on map() on the Finxter blog.

“For Each” as Python List Comprehension

Python’s list comprehension feature is syntactical sugar to create a new iterable by applying a (possibly identity) function to each element of an existing iterable.

Many coders would view the list comprehension feature as Python’s way to provide a functional “foreach” statement because it enables you to perform a function “for each” element of an iterable such as a sequence.

List comprehension is a compact way of creating lists. The simple formula is [expression + context].

• Expression: What to do with each list element?
• Context: What elements to select? The context consists of an arbitrary number of for and if statements.

The example [x+10 for x in [1, 2, 3]] creates the list [11, 12, 13].

lst = [1, 2, 3]

new_lst = [x+10 for x in lst]

print(new_lst)

# [11, 12, 13]

You can watch my explainer video on list comprehension in case you’re interested in how it works:

Learn More: Feel free to check out our full article on Python list comprehension on the Finxter blog.

Programmer Humor

Problem Formulation and Solution Overview

This article works with the fictitious Finxter database to retrieve three (3) specific users, via a SQLite query using the IN command.

To follow along, click here to download this file and move it into the current working directory.

Preparation

Add the following code to the top of the code snippet. This snippet will allow the code in this article to run error-free.

import sqlite3

Note: The SQLite library is built into Python and does not need to be installed but must be referenced.

Overview

The Finxter database file contains 25 records in tuple format. Below is a snippet from this file.

The structure of the users table is as follows:

Now that the overview is complete, let’s connect to the database, filter, and output the results.

Connect to a SQLite Database

This code connects to an SQLite database and is placed inside a try/except statement to catch any possible errors.

try: conn = sqlite3.connect('finxter_users.db') cur = conn.cursor() except Exception as e: print(f'An error occurred: {e}.') exit()

The code inside the try statement executes first and attempts to connect to finxter_users.db. A Connection Object (conn), similar to below, is produced, if successful.

Next, the Connection Object created above (conn) is used in conjunction with the cursor() to create a Cursor Object. A Cursor Object (cur), similar to below, is produced, if successful.

Note: The Cursor Object allows interaction with database specifics, such as executing queries.

If the above line(s) fail, the code falls inside except capturing the error (e) and outputs this to the terminal. Code execution halts.

Prepare the SQLite Query

Before executing any query, you must decide the expected results and how to achieve this.

try: conn = sqlite3.connect('finxter_users.db') cur = conn.cursor() fid_list = [30022192, 30022450, 30022475] fid_tuple = tuple(fid_list) f_query = f'SELECT * FROM users WHERE FID IN {format(fid_tuple)}' except Exception as e: print(f'An error occurred: {e}.') exit()

In this example, the three (3) highlighted lines create, configure and save the following variables:

• fid_list: this contains a list of the selected Users’ FIDs to retrieve.
• fid_tuple: this converts fid_list into a tuple format. This is done to match the database format (see above).
• f_query: this constructs an SQLite query that returns all matching records when executed.

Query String Output

If f_query was output to the terminal (print(f_query)), the following would display. Perfect! That’s exactly what we want.

Executing the SQLite Query

Let’s execute the query created above and save the results.

try: conn = sqlite3.connect('finxter_users.db') cur = conn.cursor() fid_list = [30022192, 30022450, 30022475] fid_tuple = tuple(fid_list) f_query = f'SELECT * FROM users WHERE FID IN {format(fid_tuple)}' results = cur.execute(f_query)

except Exception as e: print(f'An error occurred: {e}.') exit()

The highlighted line appends the execute() method to the Cursor Object and passes the f_query string as an argument.

If the execution was successful, an iterable Cursor Object is produced, similar to below.

Displaying the Query Results

The standard way to display the query results is by using a for a loop.
We could add this loop inside/outside the try/except statement.

try: conn = sqlite3.connect('finxter_users.db') cur = conn.cursor() fid_list = [30022192, 30022450, 30022475] fid_tuple = tuple(fid_list) f_query = f'SELECT * FROM users WHERE FID IN {format(fid_tuple)}' results = cur.execute(f_query)

except Exception as e: print(f'An error occurred: {e}.') exit() for r in results: print®

conn.close()

The highlighted lines instantiate a for loop to navigate the query results one record at a time and output them to the terminal.

Query Results

Finally, the Connection Object created earlier needs to be closed.

Summary

In this article you learned how to:

• Create a Connection Object.
• Create a Cursor Object.
• Construct and Execute a SQLite Query.
• Output the results to the terminal.

We hope you enjoyed this article.

Happy Coding!

Programmer Humor

Programmer 1: We have a problem
Programmer 2: Let’s use RegEx!
Programmer 1: Now we have two problems

… yet – you can easily reduce the two problems to zero as you polish your “RegEx Superpower in Python“.