What is monkey patching

Question

I am trying to understand  what is monkey patching or a monkey patch    Is that something like methods operators overloading or delegating    Does it have anything common with these things

User · Answer

What is monkey patching  Monkey patching is a technique used to dynamically update the behavior of a piece of code at run-time       Why use monkey patching  It allows us to modify or extend the behavior of libraries  modules  classes or methods at runtime without   actually modifying the source code      Conclusion Monkey patching is a cool technique and now we have learned how to do that in Python  However  as we discussed  it has its   own drawbacks and should be used carefully    For more info Please refer  1   https   medium com  nagillavenkatesh1234 monkey-patching-in-python-explained-with-examples-25eed0aea505

User · Answer

First  monkey patching is an evil hack  in my opinion    It is often used to replace a method on the module or class level with a custom implementation   The most common usecase is adding a workaround for a bug in a module or class when you can t replace the original code  In this case you replace the  wrong  code through monkey patching with an implementation inside your own module package

User · Answer

Monkey patching is reopening the existing classes or methods in class at runtime and changing the behavior  which should be used cautiously  or you should use it only when you really need to   As Python is a dynamic programming language  Classes are mutable so you can reopen them and modify or even replace them

User · Answer

A MonkeyPatch is a piece of Python code which extends or modifies   other code at runtime  typically at startup     A simple example looks like this   from SomeOtherProduct SomeModule import SomeClass  def speak self       return  ook ook eee eee eee    SomeClass speak   speak   Source  MonkeyPatch page on Zope wiki

User · Answer

According to Wikipedia      In Python  the term monkey patch only   refers to dynamic modifications of a   class or module at runtime  motivated   by the intent to patch existing   third-party code as a workaround to a   bug or feature which does not act as   you desire

User · Answer

No  it s not like any of those things  It s simply the dynamic replacement of attributes at runtime   For instance  consider a class that has a method get data  This method does an external lookup  on a database or web API  for example   and various other methods in the class call it  However  in a unit test  you don t want to depend on the external data source - so you dynamically replace the get data method with a stub that returns some fixed data   Because Python classes are mutable  and methods are just attributes of the class  you can do this as much as you like - and  in fact  you can even replace classes and functions in a module in exactly the same way   But  as a commenter pointed out  use caution when monkeypatching     If anything else besides your test logic calls get data as well  it will also call your monkey-patched replacement rather than the original -- which can be good or bad  Just beware   If some variable or attribute exists that also points to the get data function by the time you replace it  this alias will not change its meaning and will continue to point to the original get data   Why  Python just rebinds the name get data in your class to some other function object  other name bindings are not impacted at all

User · Answer

What is a monkey patch    Simply put  monkey patching is making changes to a module or class while the program is running    Example in usage  There s an example of monkey-patching in the Pandas documentation   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   To break this down  first we import our module   import pandas as pd   Next we create a method definition  which exists unbound and free outside the scope of any class definitions  since the distinction is fairly meaningless between a function and an unbound method  Python 3 does away with the unbound method    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    Next we simply attach that method to the class we want to use it on   pd DataFrame just foo cols   just foo cols   monkey-patch the DataFrame class   And then we can use the method on an instance of the class  and delete the method when we re done   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   Caveat for name-mangling  If you re using name-mangling  prefixing attributes with a double-underscore  which alters the name  and which I don t recommend  you ll have to name-mangle manually if you do this  Since I don t recommend name-mangling  I will not demonstrate it here   Testing Example  How can we use this knowledge  for example  in testing   Say we need to simulate a data retrieval call to an outside data source that results in an error  because we want to ensure correct behavior in such a case   We can monkey patch the data structure to ensure this behavior   So using a similar method name as suggested by Daniel Roseman    import datasource  def get data self          monkey patch datasource Structure with this to simulate error        raise datasource DataRetrievalError  datasource Structure get data   get data   And when we test it for behavior that relies on this method raising an error  if correctly implemented  we ll get that behavior in the test results   Just doing the above will alter the Structure object for the life of the process  so you ll want to use setups and teardowns in your unittests to avoid doing that  e g    def setUp self         retain a pointer to the actual real method      self real get data   datasource Structure get data       monkey patch it      datasource Structure get data   get data  def tearDown self         give the real method back to the Structure object      datasource Structure get data   self real get data    While the above is fine  it would probably be a better idea to use the mock library to patch the code  mock s patch decorator would be less error prone than doing the above  which would require more lines of code and thus more opportunities to introduce errors  I have yet to review the code in mock but I imagine it uses monkey-patching in a similar way

User · Answer

Monkey patching can only be done in dynamic languages  of which python is a good example   Changing a method at runtime instead of updating the object definition is one example similarly  adding attributes  whether methods or variables  at runtime is considered monkey patching   These are often done when working with modules you don t have the source for  such that the object definitions can t be easily changed   This is considered bad because it means that an object s definition does not completely or accurately describe how it actually behaves

[python] What is monkey patching?

Examples related to python

Examples related to terminology

Examples related to monkeypatching