A few months ago, I had a discussion with some friends online. The premise of the discussion was that even if you account for complexity, shorter code is more likely to be bug-free code.
As a C programmer for decades, my mind rebelled against the idea. "Nonsense," "Absurd" and "Too simple" were my knee-jerk reactions.
Taken to its ultimate end, this premise suggests that code golf -- code intentionally reduced to the absolute minimum number of characters -- is the most bug-free code. Code golf is, by definition, dense and barely readable code. How is that a good thing?
But the more I thought about the idea, the more interesting the underlying question became. Code golf itself is not evidence that shorter programs are safer: aggressively minimizing characters can make code harder to understand, test and maintain. The more useful question is whether reducing unnecessary code and boilerplate can reduce the number of places where defects can hide.
Python's tradeoffs: Performance and parallel execution
Python can be slower than languages such as Java, C# and C++ for some CPU-bound workloads, particularly when code executes primarily in the interpreter. That statement needs an important qualification: Python applications frequently delegate computationally intensive work to highly optimized native libraries, and real-world performance depends heavily on the workload and implementation.
It is also too broad to say that Python was not designed to support multithreading. In traditional CPython, the Global Interpreter Lock (GIL) has historically limited simultaneous execution of Python bytecode by multiple threads, which matters for CPU-bound threaded programs. Threads can still be effective for I/O-bound work, and Python also provides multiprocessing, asynchronous programming and native extensions for other concurrency models.
Python's runtime story continues to evolve, so performance and parallelism should be evaluated against the Python version, interpreter, libraries and workload actually used rather than treated as one universal limitation of the language.
With such performance and multithreading issues, why still consider Python? There is, in fact, a very good reason.
Python's saving grace: Shorter, cleaner code
Python's saving grace can be found within the original premise above: all other things being equal, shorter code is more likely to be bug-free.
Python's compact syntax and extensive standard functionality often let developers express an operation with less ceremony than languages that require more explicit type and class structure. When the shorter version remains readable, eliminating boilerplate can reduce cognitive load and reduce the amount of application-specific code that must be reviewed and maintained.
However, lines of code are not a direct measure of defect probability. Ten obscure lines can be harder to reason about than 30 straightforward ones. A better version of the argument is that unnecessary code creates additional maintenance surface, while concise and readable code can reduce it.
Code examples: Python vs. Java
Start with the traditional "Hello, World" example. Java requires a class and entry-point method, while Python can execute a top-level statement directly:
public class HelloWorld {
public static void main(String[] args) {
System.out.println("Hello, World!");
}
}The same thing in Python is only one line:
print("Hello, World!")That comparison mostly measures Java application boilerplate, so a class provides a more useful example. Here is a small Java class with a constructor and method:
public class Person {
private final String name;
public Person(String name) {
this.name = name;
}
public void greet() {
System.out.println("Hello, my name is " + name);
}
public static void main(String[] args) {
Person person = new Person("Alice");
person.greet();
}
}The equivalent Python class requires less structural syntax:
class Person:
def __init__(self, name):
self.name = name
def greet(self):
print(f"Hello, my name is {self.name}")
person = Person("Alice")
person.greet()Sometimes the difference is less about raw line count and more about how much syntax surrounds the operation. The following Java stream squares every value in a list:
import java.util.List;
public class LambdaExample {
public static void main(String[] args) {
List<Integer> numbers = List.of(1, 2, 3, 4, 5);
List<Integer> squared = numbers.stream()
.map(n -> n * n)
.toList();
System.out.println(squared);
}
}And here is the code to achieve the same thing in Python:
numbers = [1, 2, 3, 4, 5]
squared = [n * n for n in numbers]
print(squared)Finally, consider removing duplicate values. A set provides a compact solution in both languages. One caveat is important: converting through a hash-based set should not be used when preserving the original list order is a requirement.
public static List<Integer> removeDuplicates(List<Integer> items) {
return new ArrayList<>(new HashSet<>(items));
}The equivalent in Python is as follows:
def remove_duplicate_set(items):
return list(set(items))Less code is not the same as code golf
There is an important distinction between concise code and compressed code. Concise code removes ceremony while preserving intent. Code golf deliberately minimizes source text, often at the expense of names, structure and readability.
For maintainable software, the goal should not be the smallest possible program. The goal should be the smallest amount of clear code necessary to express the design.
Rebuttals: Versatility, libraries, dynamic vs. static typing
There are several rebuttals to this premise that shorter code is less buggy.
Probably the first and simplest point is that a programming language's aim is not the fewest number of keystrokes. (Again, code golf.) That can mean it is less versatile than comparable, more eloquent languages.
Another complication is abstraction. A short Python statement may invoke substantial functionality implemented in the standard library, a third-party package or native code. But the same is true of modern Java and most other high-level languages. Source line count measures the code an application developer maintains, not the total implementation underneath every API call.
Complexity is a stronger objection to using line count as a quality metric. Dense code can hide complicated control flow and assumptions even when it occupies very little space. Measures such as cyclomatic complexity, test coverage, cohesion and readability often tell developers more than a simple count of physical lines.
Python is dynamically typed, so some errors that a statically typed language can reject during compilation may instead surface during testing or execution. Python also supports optional type hints and static analysis tools, so teams can choose more compile-time-like checking without giving up Python's runtime type model.
Conclusion: Is Python code both shorter and less buggy?
All these rebuttals have truth to them -- but so does the original premise.
Python often requires less application code than Java for the same small task, as the examples above demonstrate. That can be a genuine productivity and maintainability advantage, but it does not establish a general rule that fewer lines automatically produce fewer bugs.
The more defensible lesson is to minimize accidental complexity rather than minimize characters. Code should be as concise as it can be while remaining explicit, testable and easy for another developer to understand. Python is particularly good at reaching that balance for many workloads, and that is a stronger advantage than line count alone.
David "Walker" Aldridge is a programmer with 40 years of experience in multiple languages and remote programming. He is also an experienced systems admin and infosec blue team member with interest in retrocomputing.