5 common mistakes made by beginner Python programmers

Python is a relatively easy language to get started in where there’s … Here are 5 common Python programming mistakes most beginners find …

During the initial days as python programmer, all of us face some or other type of weird bug in our code which, after spending multiple painful hours on StackOverflow, turns out to be not a bug but python feature. That’s how things work in python. So below are the 5 most common mistakes most of the beginner python programmers make. Let’s know a bit about them so that we can save a few hours of asking questions on Facebook pages and groups.

Creating a copy of dictionary or lists.

Whenever you need to make a copy of a dictionary or list, do not simply use the assignment operator.

Wrong:

>>> dict_a = {"name": "John", "address":"221B Baker street"}
>>> dict_b = dict_a

Now if you edit/update the dict_b, dict_a will also be updated because by using assignment operator, you are trying to say that dict_b will point to the same object to which dict_a is pointing.

>>> dict_b["age"] = 26
>>> dict_b
{'address': '221B Baker street', 'name': 'John', 'age': 26}
>>> dict_a
{'address': '221B Baker street', 'name': 'John', 'age': 26}
>>> 

Correct:

Use the copy() or deepcopy() method.

>>> dict_c = dict_b.copy()
>>> dict_c["location"] = "somewhere"
>>> dict_c
{'address': '221B Baker street', 'name': 'John', 'age': 26, 'location': 'somewhere'}
>>> dict_b
{'address': '221B Baker street', 'name': 'John', 'age': 26}
>>> dict_a
{'address': '221B Baker street', 'name': 'John', 'age': 26}
>>> 

See the difference between copy and deepcopy.

Dictionary keys.

Let’s say we put the below values in a dictionary.

>>> dict_a = dict()
>>> dict_a
{}
>>> dict_a[1] = "apple"
>>> dict_a[True] = "mango"
>>> dict_a[2] = "melon"

If we try to print the dictionary, what will be the output. Let’s see.

>>> dict_a
{1: 'mango', 2: 'melon'}

What just happened? where is the key True?

Remember Boolean class is the subclass of Integer. Integer equivalent of True is 1 and that of False is 0. Hence the value of key 1 is overwritten.

>>> isinstance(True, int)
True
>>> isinstance(False, int)
True
>>> True == 1
True
>>> False == 0
True
>>> 

Updating lists or dictionaries.

Let’s say you want to append an item to the list.

>>> list_a = [1,2,3,4,5]
>>> list_a = list_a.append(6)
>>> list_a
>>> # prints nothing

Try to update a dictionary.

>>> dict_a = {"a" : "b"}
>>> dict_a = dict_a.update({"c" : "d"})
>>> dict_a
>>> # prints nothing

Ok, let’s try to sort a list.

>>> list_b = [2,5,3,1,7]
>>> list_b = list_b.sort()
>>> list_b
>>> # prints nothing

Why nothing is being printed? What are we doing wrong?

Most the sequence object methods like sort, update, append, add, etc works in place to increase performance by avoiding to create a separate copy un-necessarily.

Do not try to assign the output of such methods to the variable.

Right way:

>>> list_a = [1,2,3,4,5]
>>> list_a.append(6)
>>> dict_a = {"a" : "b"}
>>> dict_a.update({"c" : "d"})
>>> dict_a
{'c': 'd', 'a': 'b'}
>>> list_a.sort()
>>> list_a
[1, 2, 3, 4, 5, 6]

Interned Strings.

In some cases, python tries to reuse the existing immutable objects. String interning is one such case.

>>> a = "gmail"
>>> b = "gmail"
>>> a is b
True

Here we tried to create two different string objects. But when checked if both the objects are same, it returned True. This is because python didn’t create another object b but pointed the b to the first value “gmail”.

All strings of length 1 are interned. A string having anything except ASCII characters, digits and underscore in them are not interned.

Let’s see.

>>> a = "@gmail"
>>> b = "@gmail"
>>> a is b
False
>>> 

Also, remember == is different than is operator. == checks if values are equal or not while is checks if both the variable are pointing to the same object.

>>> a = "@gmail"
>>> b = "@gmail"
>>> a is b
False
>>> a == b
True
>>> 

So keep the above point in mind while using immutable strings or == or isoperator.

Default arguments are evaluated only once.

Consider the below example.

def func(a, lst=[]):
    lst.append(a)
    return lst

print(func(1))
print(func(2))

What do you think will be the output of the above two print statements?

Let’s try to run it.

>>> def func(a, lst=[]):
...     lst.append(a)
...     return lst
... 
>>> print(func(1))
[1]
>>> print(func(2))
[1, 2]
>>> 

Why the output is [1,2] in the second case. Shouldn’t it be just [2]?

So the catch here is, default arguments of a function are evaluated just once. On first call i.e func(1), list lst is evaluated and is found empty hence 1 is appended to it. But on the second call, the list is already having one element hence output is [1,2]

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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.

…

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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:

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Learn Python - Full Course for Beginners [Tutorial]

This course will give you a full introduction into all of the core concepts in python. Follow along with the videos and you’ll be a python programmer in no time!
⭐️ Contents ⭐
⌨️ (0:00) Introduction
⌨️ (1:45) Installing Python & PyCharm
⌨️ (6:40) Setup & Hello World
⌨️ (10:23) Drawing a Shape
⌨️ (15:06) Variables & Data Types
⌨️ (27:03) Working With Strings
⌨️ (38:18) Working With Numbers
⌨️ (48:26) Getting Input From Users
⌨️ (52:37) Building a Basic Calculator
⌨️ (58:27) Mad Libs Game
⌨️ (1:03:10) Lists
⌨️ (1:10:44) List Functions
⌨️ (1:18:57) Tuples
⌨️ (1:24:15) Functions
⌨️ (1:34:11) Return Statement
⌨️ (1:40:06) If Statements
⌨️ (1:54:07) If Statements & Comparisons
⌨️ (2:00:37) Building a better Calculator
⌨️ (2:07:17) Dictionaries
⌨️ (2:14:13) While Loop
⌨️ (2:20:21) Building a Guessing Game
⌨️ (2:32:44) For Loops
⌨️ (2:41:20) Exponent Function
⌨️ (2:47:13) 2D Lists & Nested Loops
⌨️ (2:52:41) Building a Translator
⌨️ (3:00:18) Comments
⌨️ (3:04:17) Try / Except
⌨️ (3:12:41) Reading Files
⌨️ (3:21:26) Writing to Files
⌨️ (3:28:13) Modules & Pip
⌨️ (3:43:56) Classes & Objects
⌨️ (3:57:37) Building a Multiple Choice Quiz
⌨️ (4:08:28) Object Functions
⌨️ (4:12:37) Inheritance
⌨️ (4:20:43) Python Interpreter
📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=rfscVS0vtbw&list=PLWKjhJtqVAblfum5WiQblKPwIbqYXkDoC&index=3

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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.

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Every Java Junior does it: Common Java mistakes made by newcomers

Everyone makes mistakes, not just beginners, but even professionals. This article goes over a dozen common mistakes that Java newbies and newcomers make and how to avoid them. Have you or your colleagues made any of these common Java mistakes early in your career?

Everyone makes mistakes, not only learners or beginners, but professionals. As a programming course, CodeGym team often collects mistakes of newbies to improve our auto validator. This time we decided to interview experienced programmers about mistakes in Java they made closer to their careers start or noticed them among their young colleagues.

We collected their answers and compiled this list of dozen popular mistakes Java beginners make. The order of errors is random and does not carry any special meaning.

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