It is analogous to ordering too much food than you can generally handle and by the end, you will feel tired and difficult to finish. It is very easy to include all the libraries that you know in a code and never need to worry about importing anything else but in practice, that is one of the worst ways to code actually. Always go for the second option as it is much faster and efficient in this method. For example consider two scenarios where you are passing one value at a time in a loop to C from Python, computing and sending it back and in another case, you pass a list to C, do your computation there and send the result back. You will be able to get the best results by reducing the number of trips from C to Python as data passing between them is a costly operation. Python’s Ctypes library is a prime example that is compatible with Python runtime and leverages the benefits of C.

They are faster and more efficient than their respective Python libraries. Python libraries are not as efficient as Cones and hence if you have a choice or get an opportunity to use a C library, always go for the C library one. A similar concept can be applied to other libraries and functions as well. Use Numpy for all Mathematical OperationsĪs you have already seen the use of NumPy along with C libraries and how powerful it can be.

For example maybe the most recently retrieved items over the past 24 hours or a value which will be called multiple times for the next 24 hours.ģ. This is used to store values that are frequently repeated within a stipulated frame of time. You can set a custom value to the LRU Cache or set it to ‘None’ to store all.

Shocking isn’t it? This is the power of LRU_Cache in the functools library. T1 = timeit.Timer('fib(40)', 'from _main_ import fib')Īdd the following two lines of code : from functools import : (In my local machine) These special functionalities of python are known as decorators and you can use them in your code to speed up your code. Python provides you with the option of a cache that will give you the ability to instantly fetch results of functions that have been previously computed.

Memoization is a process where you do not repeat the same work over and over again even if it is a function whose value has already been calculated previously.

Python program closes instantly