human
what is monkey-patching in Python?
gpt
Monkey-patching is when you alter the run-time behavior of an object at runtime. In Python, this is done by modifying the object's attributes, such as by assigning a new field, modifying a function, or dynamically changing the base class.

Here's an example of monkey-patching from the pandas documentation:

```python
import pandas as pd
def just_foo_cols(self):
    """Get a list of column names containing the string 'foo'

    """
    return [x for x in self.columns if 'foo' in x]

pd.DataFrame.just_foo_cols = just_foo_cols # monkey-patch the DataFrame class
df = pd.DataFrame([list(range(4))], columns=["A","foo","foozball","bar"])
df.just_foo_cols()
del pd.DataFrame.just_foo_cols # you can also remove the new method
```

The monkey-patching occurs in this line

```python
pd.DataFrame.just_foo_cols = just_foo_cols # monkey-patch the DataFrame class
```

Where we dynamically add a the method `just_foo_calls` to pandas `DataFrame`. Then we can call the method on all instances, as shown in this line

```python
df.just_foo_cols()
```

Monkey-patching also occurs in this-line

```python
del pd.DataFrame.just_foo_cols # you can also remove the new method
```

where we delete the method so it can no longer be called (we could delete an existing method, too).

Monkey-patching is often considered bad design. The patches may break other libraries and unrelated code which rely on the old behaviors. Furthermore, it makes the code harder to understand, because a single object is now defined in multiple places (the actual definition and where it's monkey-patched); it's almost always better to simply modify the base code.

But monkey-patching has its uses, primarily when you don't have the ability to modify the base code (because it's in an external library like pandas), and when your object modifications are highly unlikely to break downstream code (e.g. adding a new method with a unique name, or changing a class into a "Proxy" which has the exact same behavior but does something like trace calls).

Here are some external sites for more info:

- Stack overflow post clarifying monkey patching in Python, and providing some benefits and drawbacks: https://stackoverflow.com/questions/5626193/what-is-monkey-patching

- Wikipedia: https://en.wikipedia.org/wiki/Monkey_patch
human
Can I do monkey-patching in C++? And if not, how would I achieve similar capabilities?
gpt
Monkey-patching, which is the ability to modify the behavior of a class or function at runtime, is not directly supported in C++. However, you can achieve similar capabilities using techniques like function pointers, inheritance, and templates.

One way to achieve monkey-patching-like behavior in C++ is to use function pointers. You can define a function pointer type that matches the signature of the function you want to patch, and then assign a new function to that pointer at runtime. For example:

```
#include <iostream>

void foo() {
    std::cout << "Original foo\n";
}

void new_foo() {
    std::cout << "New foo\n";
}

int main() {
    void (*foo_ptr)() = foo;
    foo_ptr(); // prints "Original foo"
    foo_ptr = new_foo;
    foo_ptr(); // prints "New foo"
}
```

Another way to achieve similar behavior is to use inheritance. You can define a base class with a virtual function that provides the default behavior, and then create derived classes that override that function to provide new behavior. At runtime, you can create an instance of the derived class and use it instead of the original object. For example:

```
#include <iostream>

class Foo {
public:
    virtual void do_something() {
        std::cout << "Original Foo\n";
    }
};

class NewFoo : public Foo {
public:
    void do_something() override {
        std::cout << "New Foo\n";
    }
};

int main() {
    Foo foo;
    foo.do_something(); // prints "Original Foo"
    NewFoo new_foo;
    Foo& foo_ref = new_foo;
    foo_ref.do_something(); // prints "New Foo"
}
```

Templates can also be used in some cases to achieve similar behavior. You can define a function or class template that takes a function or class as a template parameter, and then specialize that template to provide new behavior. At runtime, you can instantiate the specialized template and use it instead of the original function or class. For example:

```
#include <iostream>

template <typename T>
void foo() {
    T t;
    t.do_something();
}

class Foo {
public:
    void do_something() {
        std::cout << "Original Foo\n";
    }
};

class NewFoo {
public:
    void do_something() {
        std::cout << "New Foo\n";
    }
};

template <>
void foo<NewFoo>() {
    NewFoo new_foo;
    new_foo.do_something();
}

int main() {
    foo<Foo>(); // prints "Original Foo"
    foo<NewFoo>(); // prints "New Foo"
}
```

These are just a few examples of how you can achieve monkey-patching-like behavior in C++. The specific approach you choose will depend on the specific requirements of your application.