Vernie  Heller

Vernie Heller

1595728680

How Julia Uses Multiple Dispatch to Beat Python

Julia

Julia is a new language. It’s simple to learn, and extremely fast. (Almost as fast as C.) Many people believe that Julia will become a dominant programming language, especially for machine learning and scientific computing.

There is a lot of hype about Julia. Beyond speed, Meta-programming and multiple dispatch are a few of Julia’s useful programming tools that make the language exciting.

But a word of caution. If you learn Julia and then program in other languages you will find yourself thinking: **This would be so much simpler in Julia. **This happens to me when I code in Python. I love Python, but for certain things, like the effectiveness of multiple dispatch, Julia gives Python a beatdown.

How Multiple Dispatch Beats Python

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Photo by Anastase Maragos on Unsplash

What is Multiple Dispatch

Multiple dispatch is a simple concept: Functions can have multiple definitions as long as each definition accepts a different combination of arguments. It is perhaps one of the best features of the Julia language.

Surprisingly, it is not clear that Julia creators anticipated its usefulness. Years after Julia’s release, one of them gave a presentation called “The Unreasonable Effectiveness of Multiple Dispatch” [1]. (The talk presents how the Julia community used multiple dispatch with surprising results.)

As a simple example of multiple dispatch, consider the following:

function sort(x::Array{String, 1})
    ...
end

function sort(x::Array{Int, 1})
    ...
end
function sort(x::Array{Bool, 1})
    ...
end

The notation x::Array{String, 1} means that x is required to be a 1 dimensional array of strings. If each of these definitions had an implementation, it would leave us with a single functionsort, that we could call on arrays of strings, integers or bools and it would** treat each case differently**. (Integers might be sorted smallest to largest, strings might be sorted alphabetically and booleans might be returned with the false values first.) Which implementation to call is determined at runtime with a lookup table. This is how most functions work in the Julia base.

#julialang #python

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How Julia Uses Multiple Dispatch to Beat Python
Ray  Patel

Ray Patel

1619518440

top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

#python #python hacks tricks #python learning tips #python programming tricks #python tips #python tips and tricks #python tips and tricks advanced #python tips and tricks for beginners #python tips tricks and techniques #python tutorial #tips and tricks in python #tips to learn python #top 30 python tips and tricks for beginners

Ray  Patel

Ray Patel

1619510796

Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

How To Compare Tesla and Ford Company By Using Magic Methods in Python

Magic Methods are the special methods which gives us the ability to access built in syntactical features such as ‘<’, ‘>’, ‘==’, ‘+’ etc…

You must have worked with such methods without knowing them to be as magic methods. Magic methods can be identified with their names which start with __ and ends with __ like init, call, str etc. These methods are also called Dunder Methods, because of their name starting and ending with Double Underscore (Dunder).

Now there are a number of such special methods, which you might have come across too, in Python. We will just be taking an example of a few of them to understand how they work and how we can use them.

1. init

class AnyClass:
    def __init__():
        print("Init called on its own")
obj = AnyClass()

The first example is _init, _and as the name suggests, it is used for initializing objects. Init method is called on its own, ie. whenever an object is created for the class, the init method is called on its own.

The output of the above code will be given below. Note how we did not call the init method and it got invoked as we created an object for class AnyClass.

Init called on its own

2. add

Let’s move to some other example, add gives us the ability to access the built in syntax feature of the character +. Let’s see how,

class AnyClass:
    def __init__(self, var):
        self.some_var = var
    def __add__(self, other_obj):
        print("Calling the add method")
        return self.some_var + other_obj.some_var
obj1 = AnyClass(5)
obj2 = AnyClass(6)
obj1 + obj2

#python3 #python #python-programming #python-web-development #python-tutorials #python-top-story #python-tips #learn-python

Art  Lind

Art Lind

1602968400

Python Tricks Every Developer Should Know

Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?

In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.

Let’s get started

Swapping value in Python

Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead

>>> FirstName = "kalebu"
>>> LastName = "Jordan"
>>> FirstName, LastName = LastName, FirstName 
>>> print(FirstName, LastName)
('Jordan', 'kalebu')

#python #python-programming #python3 #python-tutorials #learn-python #python-tips #python-skills #python-development

Art  Lind

Art Lind

1602666000

How to Remove all Duplicate Files on your Drive via Python

Today you’re going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates.

Intro

In many situations you may find yourself having duplicates files on your disk and but when it comes to tracking and checking them manually it can tedious.

Heres a solution

Instead of tracking throughout your disk to see if there is a duplicate, you can automate the process using coding, by writing a program to recursively track through the disk and remove all the found duplicates and that’s what this article is about.

But How do we do it?

If we were to read the whole file and then compare it to the rest of the files recursively through the given directory it will take a very long time, then how do we do it?

The answer is hashing, with hashing can generate a given string of letters and numbers which act as the identity of a given file and if we find any other file with the same identity we gonna delete it.

There’s a variety of hashing algorithms out there such as

  • md5
  • sha1
  • sha224, sha256, sha384 and sha512

#python-programming #python-tutorials #learn-python #python-project #python3 #python #python-skills #python-tips