def f(...):
...
return ...
def g:
... = f(...)def g:
f = lambda ... : ...
... = f(...)You're redefining the lambda ##f## in every iteration of ##g##. Put the lambda definition of ##f## outside the body of ##g## and see what happens.ergospherical said:any reasons why?
The speed of function in Python depends on various factors such as the complexity of the function, the hardware and operating system used, and the efficiency of the code. Generally, Python functions are considered to be slower than functions in other programming languages due to its interpreted nature.
Lambda functions in Python are generally faster than regular functions because they are implemented as anonymous functions and do not require a name lookup. However, this difference in speed is minimal and may not be significant in most cases.
Yes, the number of lambda calls can affect the speed of the function. Each lambda call requires the creation of a new function object, which can impact the overall performance of the code. Therefore, it is recommended to limit the number of lambda calls for better speed.
To improve the speed of functions in Python, you can follow some best practices such as avoiding unnecessary lambda calls, using built-in functions instead of custom functions, and optimizing the code by reducing unnecessary operations. You can also use third-party libraries like NumPy or Cython for faster computations.
Yes, there can be trade-offs between speed and readability when using lambda functions. While lambda functions can improve the speed of your code, they can also make it less readable and harder to debug. Therefore, it is important to strike a balance between speed and readability when deciding to use lambda functions in your code.