1674801794
How to Parse and Validate JSON Web Tokens (JWTs) in Python
Learn how to verify, parse and prepare for errors with JWTs Python using the most popular JWT library: PyJWT
If you use APIs you probably heard of JWTs before and you are trying to parse and verify the JWTs you just received. This compact way to carry information can be used in a number of scenarios and is important to be able to verify and parse your tokens. In this video, you'll see how you can verify, parse and prepare for errors with JWTs Python using the most popular JWT library: PyJWT
Links:
- A very complete blog post on "How to Handle JWTs in Python": https://auth0.com/blog/how-to-handle-jwt-in-python/
- Auth0's page on JWTs: https://auth0.com/learn/json-web-tokens/
- PyJWT source code: https://github.com/jpadilla/pyjwt/
- Auth0's free ebook on JWTs: https://auth0.com/resources/ebooks/jwt-handbook
- Documentation on Python virtual environments: https://docs.python.org/3/library/venv.html#creating-virtual-environments
#python #jwt #security
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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
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
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
1593251880
JSON Parsing in Android - Step by Step Implementation
JSON Structures in Android
JSON uses two types of brackets that are as follows:
- [] – To declare the elements of Array in JSON, they’re written in square brackets.
- {} – To create JSON objects, the elements are written in curly brackets.
JSON has the following types of structures that are:
1. JSON Objects
The elements inside the curly brackets are known as Objects.
2. JSON Array
A list of values, known as Arrays.
3. JSON Key-Value
This data is stored as a pair of keys and values. Here the keys can be a name, a number for which the values can be Seema, 98767586 etc.
Why JSON Parsing in Android over XML?
Let us see some reasons for why to choose JSON over XML:
- It is much easier and quicker with high performance
- It can use arrays
- Its libraries do not depend on other libraries
- The codes written in JSON are short, clean and easy to understand
- It is free to open use and open-source tool
- In JSON value retrieval is easy
- It has a fully automated way of serializing/deserializing JavaScript.
- It is supported by many Ajax toolkits and most of the backend technologies.
Examples of XML and JSON
Let us see the code difference of JSON and XML files:
XML Example:
<?xml version= “1.0” encoding= “” ?>
<student>
<student>
<name> Sia Sharma</name>
<city> Chandigarh</city>
</student>
<student>
<name>Dimple D’souza</name>
<city> Nagpur</city>
</student>
<student>
<name>Anna Jones</name>
<city> Mumbai</city>
</student>
</student>
JSON Example:
{ “students”: [
{ “name”: “Sia Sharma”, “city”: “Chandigarh”},
{ “name”: “Prachi D’Souza”, “city”: “Nagpur”},
{ “name”: “Annas Jones”, “city”: “Mumbai”}
]}
I hope the difference is all clear in front of you. This is how simple JSON is and how easily it could be understood.
#android tutorials #json parsing in android #json parsing in android example #json parsing in android step by step #json parsing with android #read json file android
1618217374
Hire Python Developer | Python web development company india
Are you looking to hire Python developers online? ValueCoders provide dedicated and certified Python engineers who are proficient in building robust, secure & scalable web applications utilizing the best Python development strategies.
Visit Website - https://bit.ly/3td9l9Y
#python web development #hire python developers #hiring python developers #hire python developer #web-development #python
1597751700
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