The most Pythonic way to concatenate a list of objects is the expression
''.join(str(x) for x in lst) that converts each object to a string using the built-in
str(...) function in a generator expression. You can concatenate the resulting list of strings using the
join() method on the empty string as a delimiter. The result is a single string value that’s the concatenation of the objects’ string representations.
Writing Pythonic code is at the heart of being an effective coder—and if you choose the wrong ways of solving a problem, you’ll open yourself up for criticism and struggles throughout your programming career. So, what’s the most Pythonic way of solving the following problem?
Example: You have the following list of objects.
class Obj: def __init__(self, val): self.val = val def __str__(self): return str(self.val) lst = [Obj(0), Obj(1), Obj(2), Obj(4)]
You want to obtain the following result of concatenated string representations of the objects in the list.
Want to play? Run the following interactive code shell:
Exercise: Run the interactive code snippet. Which method do you like most?
Method 1: Join + List Comprehension + Str
This method uses three Python features.
string.join(iterable) method expects an
iterable of strings as input and concatenates those using the
string delimiter. You can read more about the
join() function in our ultimate blog guide.
Second, list comprehension is the Pythonic way to create Python lists in a single line. You use the syntax
[expression + statement].
- In the
expression, you define how each element should be modified before adding it into a new list.
- In the
statement, you define which elements to modify and add to the list in the first place.
str(...) function converts any Python object into a string representation. If you define your custom objects, you should overwrite the
__str__() method to customize how exactly your objects are represented as strings.
Combining those three features results in the following simple solution to concatenate the string representations of a list of objects.
print(''.join([str(x) for x in lst])) # 0124
But there’s a slight simplification lurking around. Read on to learn which!
Method 2: Join + Generator Expression + Str
The previous method has shown a quite effective way to concatenate the string representations of some objects using the
join() function of Python strings. As the
join() function expects a list of strings, you need to convert all objects
x into plain strings using the
However, there’s no need to create a separate list in which you store the string representations. Converting one object at a time is enough because the join function needs only an iterable as an input—and not necessarily a Python list. (All Python lists are iterables but not all iterables are Python lists.)
To free up the memory, you can use a generator expression (without the square brackets needed to create a list):
print(''.join(str(x) for x in lst)) # 0124
In contrast to Method 1, this ensures that the original list does not exist in memory twice—once as a list of objects and once as a list of string represenations of those exact objects. Therefore, this method can be considered the most Pythonic one.
Method 3: Join + Generator Expression + Custom String Representation
A slight modification of the previous version is to use your own custom string representation—rather than the one implemented by the
print(''.join(str(x.val) for x in lst)) # 0124
This gives you some flexibility how you can represent each object for your specific application.
Method 4: Join + Map + Lambda
map() function transforms each tuple into a string value, and the
join() method transforms the collection of strings to a single string—using the given delimiter
'--'. If you forget to transform each tuple into a string with the
map() function, you’ll get a
TypeError because the
join() method expects a collection of strings.
Lambda functions are anonymous functions that are not defined in the namespace (they have no names). The syntax is:
lambda <argument name(s)> : <return expression>. You’ll see an example next, where each function argument is mapped to its string representation.
print(''.join(map(lambda x: str(x), lst))) # 0124
This method is a more functional programming style—and some Python coders prefer that. However, Python’s creator Guido van Rossum preferred list comprehension over functional programming because of the readability. That’s why Methods 1-3 should be preferred in general.
If you absolutely want to take functional programming, use the next version:
Method 5: Join + Map + Str
There’s no need to use the lambda function to transform each list element to a string representation—if there’s a built-in function that’s already doing exactly this: the
str(...) function you’ve already seen!
print(''.join(map(str, lst))) # 0124
Because of its conciseness and elegance, passing the
str function name as a function argument into the
map function is the most Pythonic functional way of solving this problem.
Method 6: Simple Loop + Str (Naive)
Sure, you can also solve the problem in a non-Pythonic way by using a simple for loop and build up the string:
s = '' for x in lst: s += str(x) print(s) # 0124
But that’s not only less concise, it’s also less efficient. So, a master coder in Python would never use such a method!
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Where to Go From Here?
Enough theory, let’s get some practice!
To become successful in coding, you need to get out there and solve real problems for real people. That’s how you can become a six-figure earner easily. And that’s how you polish the skills you really need in practice. After all, what’s the use of learning theory that nobody ever needs?
Practice projects is how you sharpen your saw in coding!
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Then become a Python freelance developer! It’s the best way of approaching the task of improving your Python skills—even if you are a complete beginner.
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While working as a researcher in distributed systems, Dr. Christian Mayer found his love for teaching computer science students.
To help students reach higher levels of Python success, he founded the programming education website Finxter.com. He’s author of the popular programming book Python One-Liners (NoStarch 2020), coauthor of the Coffee Break Python series of self-published books, computer science enthusiast, freelancer, and owner of one of the top 10 largest Python blogs worldwide.
His passions are writing, reading, and coding. But his greatest passion is to serve aspiring coders through Finxter and help them to boost their skills. You can join his free email academy here.