How to Rewrite a Class in a Third-Party Package

You can rewrite a class in a third-party package. The strategy you choose depends heavily on your programming language (dynamic vs. static) and the package architecture.

The core challenge isn’t writing the new class; it is forcing the internal logic of the package to use your new class instead of the original one (e.g., when the package calls new BadClass() internally).

Here are the four standard strategies.

1. Monkey Patching (Runtime Replacement)

Best for: Dynamic languages (Python, JavaScript/TypeScript, Ruby).

Monkey patching involves swapping out the class definition in memory at runtime before the package uses it.

How it works: Import the package, then explicitly overwrite the class symbol with your custom class.
Result: When the package’s internal code calls OriginalClass(), it unknowingly executes YourNewClass().

Python Example

import third_party_pkg.core

# 1. Define your replacement
class BetterClass:
    def __init__(self):
        print("This is the new logic!")

# 2. Overwrite the package's reference to the class
third_party_pkg.core.OriginalClass = BetterClass

# 3. Execution
# When logic inside the package runs: obj = OriginalClass()
# It now actually creates an instance of BetterClass.

2. Dependency Injection / Subclassing

Best for: Well-designed libraries in any language (Java, C#, TS).

If the library follows “Inversion of Control” principles, it won’t hard-code new ClassName(). Instead, it accepts a class definition or instance via configuration.

How it works: Create a class that inherits from the original (overriding specific methods) and pass it into the library’s initialization function.
Result: The library uses the instance you provided.

TypeScript/JS Example

import { BadClass, Processor } from 'library';

// 1. Extend the original class
class GoodClass extends BadClass {
    save() {
        console.log("Custom save logic executing...");
    }
}

// 2. Inject it via config
const proc = new Processor({
    storageDriver: new GoodClass() 
});

3. Classpath Shadowing (The “Ghost” Class)

Best for: Compiled/Static languages (Java, Scala) or specific build tools.

This relies on the order in which the compiler or runtime loads files (classpath precedence).

How it works: Create a file in your own source folder with the exact same directory structure and package name as the original class.
Result: Because local source code usually takes precedence over external JARs/dependencies in the load order, the runtime loads your file and ignores the one inside the library.

Java Example

If the target class is com.vendor.lib.utils.Helper:

Create src/main/java/com/vendor/lib/utils/Helper.java in your project.

Paste the original code into your file.

Modify the logic you dislike.

Compile. The JVM will load your class instead of the JAR version.

4. Forking (Vendoring)

Best for: Massive changes or Open Source libraries.

If the changes are complex, it is safer to own the code entirely.

How it works: Clone the repository, make changes, and point your dependency manager to your specific Git URL or local folder.
Result: You are now the maintainer of that specific version.

package.json Example (Node.js)

{
  "dependencies": {
    "my-library": "git+[https://github.com/my-username/my-forked-library.git](https://github.com/my-username/my-forked-library.git)"
  }
}

Recommendation

Check for Config: Always look for Dependency Injection options first.
Monkey Patch: Good for quick fixes in dynamic languages.
Shadow: Good for static languages if you can’t fork.
Fork: The nuclear option; use only when necessary.

Risk Comparison Matrix

Method	Risk Level	The Danger
Dependency Injection	Low	Requires the library author to have written flexible code.
Forking	Medium	You stop getting official updates or security patches unless you manually merge them.
Shadowing	High	If the library updates and adds a new method to that class, your shadowed version won’t have it, causing a crash.
Monkey Patching	High	Highly fragile. If the library changes internal variable names or import paths, your patch will silently fail.

Monkey Patching in Python

The Scenario

Imagine you are using a library called external_lib.

It has a class OriginalClass (which you don’t like).

It has a Worker class that internally calls OriginalClass.

The goal: Make Worker use MyBetterClass instead of OriginalClass.

Step 1: Create your “Better” Class

Create your replacement class. It usually helps to inherit from the original so you keep the methods you don’t want to change, but you don’t strictly have to.

# my_script.py
import external_lib

# Option A: Inherit and fix specific methods (Safer)
class MyBetterClass(external_lib.OriginalClass):
    def bad_method(self):
        print("I fixed the logic here!")

# Option B: Rewrite entirely (if the original is totally broken)
class MyBetterClass:
    def bad_method(self):
        print("New logic from scratch!")
    
    def other_method(self):
        print("Required method implementation")

Step 2: The Monkey Patch (The Swap)

You must perform this assignment before the library code runs or instantiates the class.

# my_script.py
import external_lib

# ... define MyBetterClass as shown above ...

print(f"Before patch: {external_lib.OriginalClass}")
# Output: <class 'external_lib.OriginalClass'>

# --- THE MAGIC HAPPENS HERE ---
# We overwrite the name 'OriginalClass' inside the library module
# with our new class.
external_lib.OriginalClass = MyBetterClass 
# ------------------------------

print(f"After patch: {external_lib.OriginalClass}")
# Output: <class '__main__.MyBetterClass'>

# Now, run the library logic
worker = external_lib.Worker() 
worker.do_job() 
# result: The 'Worker' thinks it is calling OriginalClass, 
# but it is actually calling MyBetterClass.

Patching specific methods

Sometimes you don’t need to rewrite the whole class. If you just hate one method, you can replace just that function on the existing class.

import external_lib

def my_fixed_function(self, arg1):
    print(f"Fixed logic with {arg1}")

# Overwrite only the specific method on the class
external_lib.OriginalClass.broken_method = my_fixed_function

# Now any instance (even existing ones!) will use the new method

The “Import” Trap

Warning: Python patching relies on where the class is looked up.

If external_lib looks like this internally:

# external_lib/worker.py
from .definitions import OriginalClass # <--- Direct import

def run():
    x = OriginalClass()

If you patch external_lib.definitions.OriginalClass, it might not update worker.py if worker.py has already been imported. worker.py might be holding onto a reference to the old class.

The Fix: Patch the module where the class is defined, and do it as early as possible in your program execution (at the very top of your main.py).

Rewrite A Class In A Third party Package

From Runtime Replacement To Classpath Shadowing