Types, Effects and Attributes

HTML Button Tag – Types, Effects and Attributes

In this article, we are going to learn HTML Button Tags. So let’s start!!!

HTML Button

HTML Button

The

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Types, Effects and Attributes
Arvel  Parker

Arvel Parker

1593156510

Basic Data Types in Python | Python Web Development For Beginners

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

I Mutable objects

II Immutable objects

III Built-in data types in Python

Mutable objects

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

Immutable objects

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**=25+**85j

type**(a)**

output**:<class’complex’>**

b**={1:10,2:“Pinky”****}**

id**(b)**

output**:**238989244168

Built-in data types in Python

a**=str(“Hello python world”)****#str**

b**=int(18)****#int**

c**=float(20482.5)****#float**

d**=complex(5+85j)****#complex**

e**=list((“python”,“fast”,“growing”,“in”,2018))****#list**

f**=tuple((“python”,“easy”,“learning”))****#tuple**

g**=range(10)****#range**

h**=dict(name=“Vidu”,age=36)****#dict**

i**=set((“python”,“fast”,“growing”,“in”,2018))****#set**

j**=frozenset((“python”,“fast”,“growing”,“in”,2018))****#frozenset**

k**=bool(18)****#bool**

l**=bytes(8)****#bytes**

m**=bytearray(8)****#bytearray**

n**=memoryview(bytes(18))****#memoryview**

Numbers (int,Float,Complex)

Numbers are stored in numeric Types. when a number is assigned to a variable, Python creates Number objects.

#signed interger

age**=**18

print**(age)**

Output**:**18

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).

String

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

‘Hello Python’

#single (') Quoted String

“Hello Python”

# Double (") Quoted String

“”“Hello Python”“”

‘’‘Hello Python’‘’

# 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.

“Hello”+“python”

output**:****‘Hello python’**

"python "*****2

'Output : Python python ’

#python web development #data types in python #list of all python data types #python data types #python datatypes #python types #python variable type

Ray  Patel

Ray Patel

1623121920

Python typing and validation with mypy and pydantic.

Python is a dynamically typed programming language, which means the types are only checked at runtime and a variable is allowed to change its type over its lifetime, whereas a statically typed language like Java checks the types at compile-time, and a variable is not allowed to change its type over its lifetime. On the other hand, Python is a strongly typed language because the types cannot be automatically converted at runtime. For example, you cannot have an addition calculation on integer 1 and string "2", while in a weakly typed language such as JavaScript such calculation is allowed.

Even though dynamic typing can make it faster to write Python code in the development stage, it is also very easy to introduce bugs and errors which can only be identified at runtime. Besides, with no type definitions, the code can be more difficult to read and maintain. For example, you need to read through a function to get to know what type of data would be returned by it. However, with type hints or type annotations, the return type of a function can be known immediately. Once a program is developed, you would rarely need to rewrite or redesign it. However, it is much more common that you or your colleagues need to read or maintain it after some time. Therefore, making the code easier to read would be very important, especially if you work in a team where people have to review each other’s code.

Typing has become more and more important in Python and the type hint standards introduced in PEP484 make it possible and easy to add type annotations to your Python code. After type hints have been added to a Python file, the mypy library can be used to do static type checking before it is run. Besides, pydantic, a data validation library using Python type annotations, can enforce type hints at runtime and provide user-friendly errors when data is invalid.

#python #mypy #pydantic #typing #type-hints #python typing and validation with mypy and pydantic.

What is “effect” or “effectful” mean in Functional Programming?

A lot of the time, when we discuss the effect, we usually talk about side-effect. However, as I study more and more into functional programming and reading more and more functional programming books, I noticed many times “Effect” or “Effectful” had been widely said in the FP community when describing abstract things.

I dig a little deeper into what an “Effect” or “Effectful” means and put that in this blog post for a note to my future self.

It is not Side Effect

Usually, what they meant for “Effect” or “Effectful” is no side effect (sometimes it does). It is Main Effect.

It has something to do with Type Category

A type category is a Math Structure to abstract out representation for all the different fields in Math. When designing a program, we can think in the properties of that program before writing code instead of the other way around. For example, a function sum can be empty (identity law), has the property of combined operation and needs to be associative. (1+2 is equal to 2+1). We can characterize them as and restrict input function to be a Monoid. This way, we can create a solution in a systematic approach that generates fewer bugs.

Within Type Category is a fancy word for a wrapper that produces an “effect” on a given type. I will quote the statement that Alvin Alexander mentioned in Functional and Reactive Domain Modeling:

  1. Option models the effects of optionality
  2. Future models latency as an effect
  3. Try abstract the consequences of failures

Those statements can be rewritten as:

  1. Option is a monad that models the effect of optionality (of being something optional)
  2. Future is a monad that models the impact of latency
  3. Try is a monad that models the impact of failures (manages exception as an effect)

Similarly:

  1. Reader is a monad that models the effect of composting operations based on some input.
  2. Writer is a monad that models the impact of logging
  3. State is a monad that models the impact of State
  4. Sync in Cats-effect is a monad that models the effects of synchronous lazy execution.

It is an F[A] instead of A

An effect can be said of what the monad handles.

Quoting from Rob Norris in Functional Programming with Effects — an effectual function returns F[A] rather than A.

#scala #programming #functional-programming #effect #side-effects

Gerhard  Brink

Gerhard Brink

1624825860

What are the Best Steps to Effective Data Classification?

Data protection is not only a legal necessity. It is essential for an organization’s survival and profitability. Nowadays, storage has become cheap, and organizations have become data hoarders. And even one day will come when they’ll get around mining all of those data and look for something useful.

But, again, data hoarding causes serious issues. And most of what is collected may become redundant, old, or when it is not touched for years.

Moreover, storage might be cheap, but it is not free. And storing a huge amount of data might cost you and, more importantly, increases your risk.

So, suppose your sensitive data is stored digitally, which includes intellectual property, personally identifiable data on the customers or employees, protected health information or financial account information, and credit card details. In that case, these needs are to be properly secured.

So how to protect your data?

What is data classification?

Here are the seven effective steps to Data Classification

#big data #latest news #what are the best steps to effective data classification? #effective data classification #best #effective

Ari  Bogisich

Ari Bogisich

1595762400

Stretching the Reach of Implicitly Typed Variables in C#

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Type inference is a common feature among mainstream programming languages. The functional ones, like ML and Haskell, are pioneers in exploring this programming paradigm where the declaration of a variable or a function may omit a type annotation. Today, even classic imperative languages such as C++ offer, to a certain extent, a kind of type inference.

C# is not an exception to the ever-increasing popularity of inference-enabled languages: since C# 3.0, developers may declare implicitly typed variables with the var keyword (in C++ 11, a similar feature was introduced — re-targeting the then-existing auto keyword). This functionality, however, falls under a provision: a declaration must be accompanied by an initializer.

Although one would not expect to see ML and Haskell’s “whole-program type inference” in C#, could this initializer requirement be relaxed? Why does it exist, altogether?

  • Is it due to any limitation or just a matter of taste?
  • Could the variable’s type be inferred from arbitrary expressions?
  • If yes, what are trade-offs from a language-design perspective?

In this article, I will describe the foundation of a standard type inference technique and ramble about the questions above.

Non-initializing Declarations

What do you answer when someone asks: why is it necessary, in C#, that a local var-declared variable is accompanied with an _initializer? _The accurate reply to this question is: because the language specification says so; it is not because the type would not be inferable otherwise. Consider function f.

The two statements above (a declaration- and an expression-statement) are not fundamentally different from the single statement var num = 42;. In fact, if permitted, the _Intermediate Language _(IL) code produced for the former would probably be equal to that produced for the latter. Also, one may easily observe that int is a valid replacement for var in f.

To set the stage for our discussion, let us quote — with minor adjustments for pedagogical reasons — the relevant fragment of the C# specification to which var is subject:

“When the local variable type is specified as var… the declaration is an implicitly typed local variable declaration, whose type is inferred from the type of the associated initializer expression.”

Another characteristic of C# is that a variable must be definitely assigned before we attempt to obtain its value. Let us also quote the language specification fragment that states such mandatory assignment.

“For an initially unassigned variable to be considered definitely assigned… , an assignment to the variable must occur in every possible execution path…”

It is not my intent to enter the pedantic realm of language specifications. Yet, based on our (informal) observation that var num; num = 42; is equivalent to var num = 42;; and the fact that a variable must be assigned before being used, could we slightly stretch the functionality provided by var?

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#type-systems #hindley-milner #type-theory #type-inference #csharp #programming-c