Are Private Variables Really Private in Python? The Truth Revealed

If you come from languages like Java, C++, or C#, you’re used to having strict access control: private, protected, public. But in Python, you might be surprised to find that private variables aren’t truly private.

In this article, we’ll break down:

• What “private” means in Python
• What __double_underscore really does
• How it compares to other languages
• What Python intends — and how you should handle it
• Code examples that clarify it all

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❓ Does Python Have Private Attributes?

Short answer: No, not really.

Python does not have real access modifiers like private. Instead, it uses naming conventions and soft barriers.

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🧪 Example 1: Normal Attribute (Public)

class Person:
    def __init__(self):
        self.name = "Alice"

p = Person()
print(p.name)  # ✅ Accessible directly

There are no restrictions — Python assumes you know what you’re doing.

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🔹 Example 2: _single_underscore — “Protected” by Convention

class Person:
    def __init__(self):
        self._age = 30  # intended for internal use

p = Person()
print(p._age)  # ✅ Still accessible

This is a warning to developers:

“This is an internal implementation. Please don’t touch unless you know what you’re doing.”

It’s not enforced by Python — purely conventional.

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🔒 Example 3: __double_underscore — Name Mangling

class Person:
    def __init__(self):
        self.__salary = 50000

p = Person()
print(p.__salary)        # ❌ AttributeError
print(p._Person__salary) # ✅ Accessed using mangled name

✅ What Happened?

Python renamed __salary to _Person__salary to make accidental access harder.
This is called name mangling.

So it’s not private — just obscured.

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🔧 Comparison: Python vs Java

Feature	Java	Python
private	Enforced	❌ Not supported
_var	Not allowed	⚠️ By convention (protected)
__var	N/A	🔒 Name mangling only
__var__	N/A	⚙️ Magic methods (dunders)

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🧠 Why Doesn’t Python Enforce Privacy?

Python follows a different philosophy:

“We are all consenting adults here.”

It trusts the developer to be responsible. You’re expected to follow conventions, not rely on enforced restrictions.

So rather than saying:

“You cannot access this.”

Python says:

“You shouldn’t access this — but I won’t stop you.”

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✅ Best Practices in Python

🔸 Use _var for protected-like fields

self._internal_id = 42

Use _ to indicate “don’t touch this unless you must.”

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🔸 Use __var when you want to avoid name clashes, not hide data

self.__config = {}

This is useful in inheritance, where subclasses might accidentally override your internal fields.

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🔸 Use @property to control access (like a getter)

class Bank:
    def __init__(self):
        self.__balance = 1000

    @property
    def balance(self):
        return self.__balance

You can even add a setter:

    @balance.setter
    def balance(self, value):
        if value < 0:
            raise ValueError("Balance cannot be negative")
        self.__balance = value

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✅ Summary

Naming	Purpose	Access Control?
var	Public	❌ No
_var	“Protected” by convention	❌ No
__var	Name mangling	⚠️ Yes (soft)
__var__	Special dunder methods (__init__)	✅ Yes (Python magic)

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🏁 Final Thoughts

Python doesn’t enforce privacy like Java — and that’s by design.

• If you’re writing a library or shared API, use _ and __ to signal intent
• If you’re trying to protect values, use @property, validation logic, or even custom descriptors
• And if you’re doing anything advanced — remember: name mangling is not encryption 😄

In Python, privacy is a gentleman’s agreement, not a jail cell.

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