In the vast majority of programming languages, if you remove all indentation from the entire source code and then apply auto-formatting, the program will remain fully functional and will also be formatted in a consistent style.
At first glance, such an operation seems impossible in Python.
At least, I couldn’t find a way to instantly detect accidentally shifted indentation in Python. So I had to come up with my own solution.
---
Introduction
Dear reader!
If you agree with at least one of the following statements:
1. Programming is a high art.
2. When programming in a language, you should use its full power and variety to minimize the source code as much as possible.
3. Your code should demonstrate a high level of expertise so that no one can call it “dumb”.
If so — please don’t read this article. Don’t waste your time on it.
This article discusses a rather artificial and arguably absurd aspect of programming.
---
Dear reader!
If instead you agree with the following:
1. Programming is routine, repetitive work, similar to digging an endlessly winding trench.
2. You should use a minimal and optimal subset of a language so that even a junior developer can easily understand your code.
3. Your program should be somewhat “simple” so that after deployment, you can hand it over to a junior developer for maintenance.
If all three apply to you, then you might relate to the problem I’m addressing.
---
Main drawbacks of Python
1. Python is not optimized for resource usage, making it unsuitable for resource-critical applications such as mobile apps or low-level software.
2. Python is slow and effectively single-threaded due to the Global Interpreter Lock (GIL).
3. Python relies entirely on indentation for code blocks. Because of this:
Readability may suffer
Full auto-formatting is difficult
Accidental indentation errors can occur and be hard to detect
---
The first issue is inherent and acceptable.
The second is mitigated by Python’s excellent interoperability with C/C++.
But for the third issue, I propose a solution.
---
The problem
In most languages, auto-formatting fixes indentation.
In Python, this seems impossible.
In real-world development, code is constantly moved, refactored, and modified.
A small accidental shift in indentation can:
Keep the program running
But silently change its logic
These bugs are extremely hard to detect.
---
Solution: Explicit block endings
Python blocks are formed by:
class
def
for / while
if
try
with
I propose introducing explicit “closing statements” for each block.
---
class / def
Problem: nested functions
Solution: add return at the end
---
for / while
Add continue at the end:
for ...:
...
continue
This ensures indentation errors cause runtime issues instead of silent logic bugs.
---
if
Use:
if ...:
...
elif ...:
...
elif 1: # instead of else
...
elif 0: pass # end of block
This makes block boundaries explicit and prevents silent errors.
---
try
Same idea:
try:
...
except ...:
...
except 1:
...
except 0: pass
For finally, move logic into a function:
def my_func():
...
return
finally:
my_func()
---
with
No natural closing statement exists.
Options:
Move logic into a function
Or avoid using with entirely
---
Benefits
Using these conventions:
You can auto-format code safely
Block boundaries become explicit
Accidental indentation errors are easier to detect
---
Conclusion
If you:
Structure blocks explicitly
Use C/C++ where needed
Avoid Python in resource-critical systems
Then Python has almost no serious drawbacks.
---
Advantages of Python
Simplicity
Fast development cycle
Powerful ecosystem
Together, these make Python nearly ideal under the right conditions.
At first glance, such an operation seems impossible in Python.
At least, I couldn’t find a way to instantly detect accidentally shifted indentation in Python. So I had to come up with my own solution.
---
Introduction
Dear reader!
If you agree with at least one of the following statements:
1. Programming is a high art.
2. When programming in a language, you should use its full power and variety to minimize the source code as much as possible.
3. Your code should demonstrate a high level of expertise so that no one can call it “dumb”.
If so — please don’t read this article. Don’t waste your time on it.
This article discusses a rather artificial and arguably absurd aspect of programming.
---
Dear reader!
If instead you agree with the following:
1. Programming is routine, repetitive work, similar to digging an endlessly winding trench.
2. You should use a minimal and optimal subset of a language so that even a junior developer can easily understand your code.
3. Your program should be somewhat “simple” so that after deployment, you can hand it over to a junior developer for maintenance.
If all three apply to you, then you might relate to the problem I’m addressing.
---
Main drawbacks of Python
1. Python is not optimized for resource usage, making it unsuitable for resource-critical applications such as mobile apps or low-level software.
2. Python is slow and effectively single-threaded due to the Global Interpreter Lock (GIL).
3. Python relies entirely on indentation for code blocks. Because of this:
Readability may suffer
Full auto-formatting is difficult
Accidental indentation errors can occur and be hard to detect
---
The first issue is inherent and acceptable.
The second is mitigated by Python’s excellent interoperability with C/C++.
But for the third issue, I propose a solution.
---
The problem
In most languages, auto-formatting fixes indentation.
In Python, this seems impossible.
In real-world development, code is constantly moved, refactored, and modified.
A small accidental shift in indentation can:
Keep the program running
But silently change its logic
These bugs are extremely hard to detect.
---
Solution: Explicit block endings
Python blocks are formed by:
class
def
for / while
if
try
with
I propose introducing explicit “closing statements” for each block.
---
class / def
Problem: nested functions
Solution: add return at the end
---
for / while
Add continue at the end:
for ...:
...
continue
This ensures indentation errors cause runtime issues instead of silent logic bugs.
---
if
Use:
if ...:
...
elif ...:
...
elif 1: # instead of else
...
elif 0: pass # end of block
This makes block boundaries explicit and prevents silent errors.
---
try
Same idea:
try:
...
except ...:
...
except 1:
...
except 0: pass
For finally, move logic into a function:
def my_func():
...
return
finally:
my_func()
---
with
No natural closing statement exists.
Options:
Move logic into a function
Or avoid using with entirely
---
Benefits
Using these conventions:
You can auto-format code safely
Block boundaries become explicit
Accidental indentation errors are easier to detect
---
Conclusion
If you:
Structure blocks explicitly
Use C/C++ where needed
Avoid Python in resource-critical systems
Then Python has almost no serious drawbacks.
---
Advantages of Python
Simplicity
Fast development cycle
Powerful ecosystem
Together, these make Python nearly ideal under the right conditions.
