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.

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Python typing and validation with mypy and pydantic.
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.

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

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

Shardul Bhatt

Shardul Bhatt

1626775355

Why use Python for Software Development

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. 

5 Reasons to Utilize Python for Programming Web Apps 

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.

Robust frameworks 

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. 

Progressive applications 

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.

Summary

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.

#python development services #python development company #python app development #python development #python in web development #python software development

August  Larson

August Larson

1624934525

Python I: Data Types and Operators, variable assignment, and print()

Learn the Python basics so that you can use it for your data science projects.

This blog is part of a series of tutorials called Data in Day. Follow these tutorials to create your first end-to-end data science project in just one day. This is a fun easy project that will teach you the basics of setting up your computer for a data science project and introduce you to some of the most popular tools available. It is a great way to get acquainted with the data science workflow.

I. About Python 🐍

Created by Dutch programmer Guido van Rossum at Centrum Wiskunde & Informatica, Python made its debut in 1991. Over thirty years it has gained popularity earned a reputation of being the “Swiss army knife of programming languages.” Here are a few reasons why:

In emerging fields like data science, artificial intelligence, and machine learning, a robust community, plenty of packages, paradigm flexibility, and syntactical simplicity, allow beginners and professionals to focus on insights and innovation.

#python3 #variables-in-python #data-types-in-python #operators-in-python #python #python i: data types and operators, variable assignment, and print()