Python is widely regarded as an easy language for beginners. But did you know that there’s a much easier language, one that has far greater capabilities? It’s called Pharo, a modern variant of Smalltalk. Let’s compare the two…
Simplicity, Conciseness, and Elegance
Pharo is much, much simpler than Python. It has all of six reserved words. The complete syntax fits on a post card!
You sure as hell can’t do that with Python!
You can learn the entire language in 15 minutes: Learn Smalltalk with ProfStef. You sure as hell can’t do that with Python!
Pharo is astonishingly concise and elegant. Here’s a sampling of wonderful one-liners:
"Compute difference in days between two dates" ('2014-07-01' asDate - '2013/2/1' asDate) days "Set up an HTTP server that returns the current timestamp" (ZnServer startDefaultOn: 8080) onRequestRespond: [ :request | ZnResponse ok: (ZnEntity with: DateAndTime now printString) ] "Split a string on dashes, reverse the order of the elements and join them using slashes" $/ join: ($- split: '1969-07-20') reverse "Sum of the primes up to 64" (Integer primesUpTo: 64) sum "Extract a Unix format timestamp from the 5th to 8th byte of a byte array given in hex" DateAndTime fromUnixTime: ((ByteArray readHexFrom: 'CAFEBABE4422334400FF') copyFrom: 5 to: 8) asInteger "Return the weekday of a date" '2013/5/7' asDate dayOfWeekName "Save the HTML source of a web page to a file" 'http://www.pharo.org' asUrl saveContentsToFile: 'page.html' "Count the number of, or show the leap years between two years" (1914 to: 1945) count: [ :each | Year isLeapYear: each ]. (1895 to: 1915) select: [ :each | Year isLeapYear: each ]. "Encode the same string using Latin1, UTF-8 and UTF-16" #(latin1 utf8 utf16) collect: [ :each | (ZnCharacterEncoder newForEncoding: each) encodeString: 'Les élèves Français' ]
In Python, it’s almost impossible to do anything in one line.
Python’s use of indentation as syntax is highly controversial. It’s the main reason why so many developers hate Python. One issue is that an accidental misalignment of code can cause a very subtle and difficult-to-find bug. Who can claim that accidents never happen?
Pharo doesn’t suffer from this malady.
Pharo is purely object-oriented from top to bottom. Its clarity and consistency in this regard are unmatched by any other language.
Python, on the other hand, has a makeshift implementation of OOP that feels bolted on. For example, there is no true encapsulation in Python: instance variables and methods are “hidden” or made “private” by prefixing their names with underscores. This is extremely kludgy.
Python requires you to explicitly pass “self” as the first argument to all instance methods. This is unbelievably hokey.
Python objects don’t always have the attribute that you expect. For example, the length property is almost always an external function called len().
Pharo has a lovely implementation of lambdas in its “blocks.” This provides Pharo with a nice functional programming capability. In fact, Pharo’s class library contains many functional constructs.
Python can also do functional programming after a fashion. However, its lambdas are restricted to a single expression, rather than allowing for multiple lines of code. No other programming language in the world has this restriction! I hesitate to call this hokey and kludgy. (Okay, I lied: it’s hokey and kludgy.)
IDE (integrated development environment)
Pharo has a lovely built-in live coding IDE that’s every bit as simple and easy to use as the language itself. Live coding allows you to inspect and modify the code and data in your program while it’s running! This powerful technique practically eliminates the traditional edit-compile-test-debug cycle that has hampered developers for over half a century. This is the main reason why Pharo (Smalltalk) is the most productive general-purpose programming language in the world, according to a study conducted by Namcook Analytics.
Python’s best IDE is PyCharm. While it’s a nice IDE to be sure, there’s no question that it’s much, much larger and more complex than Pharo’s IDE. It would take a long time to master this program.
And PyCharm doesn’t support live coding.
Productivity and Ease of Development
Python has a reputation for being productive. Namcook Analytics tell us that Pharo (Smalltalk) is twice as productive as Python. This is on average. In many cases, Pharo will be much more productive, sometimes by a factor of five!
Plain and simple, Pharo is just much easier to use for programming. The language and its development environment present virtually no cognitive load on the developer.
Python has an enviable ecosystem of libraries. This is a weak point for Pharo. Despite this, Pharo is incredibly versatile. It’s used for many different kinds of applications. For example, Pharo is very good for web development, thanks to the Seaside web framework and the Teapot micro framework.
Pharo is very good for front-end development, thanks to Amber and PharoJS.
Pharo is good for data science, thanks to PolyMath and Roassal.
Pharo is good for virtual reality:
Pharo is good for Internet of Things and embedded programming. See Learn How To Program.
Pharo is used to script the Unreal game engine:
Pharo is being used to fight Ebola!
Pharo is used in wide-scale data visualization for medicines in 16 countries.
Pharo is used for natural language processing.
Pharo is used for machine learning and neural network processing.
Smalltalk, in general, is versatile. The U.S. joint military used Smalltalk to write a million-line battle simulator called JWARS. It actually outperformed a simular program called STORM written in C++ by the U.S. Air Force. Whoa! That’s mind-blowing!
Smalltalk was used by JP Morgan to write their massive financial risk management system called Kapital.
Orient Overseas Container Lines used Smalltalk to develop their IRIS-2 shipping management system.
If Pharo is disadvantaged by its ecosystem, it certainly doesn’t seem to slow it down. In fact, I think it’s fair to say that Pharo is more versatile than Python.
Both Pharo and Python can do multithreading, but Python is hampered by the GIL (global interpreter lock), long a complaint of most programmers.
(First published at Code.)
No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas.
By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities.
Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly.
Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.
Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions.
Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events.
Simple to read and compose
Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building.
The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties.
Utilized by the best
Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player.
Massive community support
Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions.
Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking.
Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.
The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.
Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential.
The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.
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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.
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')
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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.
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
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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.
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
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
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At the end of 2019, Python is one of the fastest-growing programming languages. More than 10% of developers have opted for Python development.
In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.
Table of Contents hide
III Built-in data types in Python
The Size and declared value and its sequence of the object can able to be modified called mutable objects.
Mutable Data Types are list, dict, set, byte array
The Size and declared value and its sequence of the object can able to be modified.
Immutable data types are int, float, complex, String, tuples, bytes, and frozen sets.
id() and type() is used to know the Identity and data type of the object
a**=str(“Hello python world”)****#str**
Numbers are stored in numeric Types. when a number is assigned to a variable, Python creates Number objects.
Python supports 3 types of numeric data.
int (signed integers like 20, 2, 225, etc.)
float (float is used to store floating-point numbers like 9.8, 3.1444, 89.52, etc.)
complex (complex numbers like 8.94j, 4.0 + 7.3j, etc.)
A complex number contains an ordered pair, i.e., a + ib where a and b denote the real and imaginary parts respectively).
The string can be represented as the sequence of characters in the quotation marks. In python, to define strings we can use single, double, or triple quotes.
# String Handling
#single (') Quoted String
# Double (") Quoted String
# triple (‘’') (“”") Quoted String
In python, string handling is a straightforward task, and python provides various built-in functions and operators for representing strings.
The operator “+” is used to concatenate strings and “*” is used to repeat the string.
'Output : Python python ’
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