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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Python Tutorial for Beginners (2019) - Learn Python for Machine Learning and Web Development

TABLE OF CONTENT

00:00:00 Introduction

00:01:49 Installing Python

00:06:10 Your First Python Program

00:08:11 How Python Code Gets Executed

00:11:24 How Long It Takes To Learn Python

00:13:03 Variables

00:18:21 Receiving Input

00:22:16 Python Cheat Sheet

00:22:46 Type Conversion

00:29:31 Strings

00:37:36 Formatted Strings

00:40:50 String Methods

00:48:33 Arithmetic Operations

00:51:33 Operator Precedence

00:55:04 Math Functions

00:58:17 If Statements

01:06:32 Logical Operators

01:11:25 Comparison Operators

01:16:17 Weight Converter Program

01:20:43 While Loops

01:24:07 Building a Guessing Game

01:30:51 Building the Car Game

01:41:48 For Loops

01:47:46 Nested Loops

01:55:50 Lists

02:01:45 2D Lists

02:05:11 My Complete Python Course

02:06:00 List Methods

02:13:25 Tuples

02:15:34 Unpacking

02:18:21 Dictionaries

02:26:21 Emoji Converter

02:30:31 Functions

02:35:21 Parameters

02:39:24 Keyword Arguments

02:44:45 Return Statement

02:48:55 Creating a Reusable Function

02:53:42 Exceptions

02:59:14 Comments

03:01:46 Classes

03:07:46 Constructors

03:14:41 Inheritance

03:19:33 Modules

03:30:12 Packages

03:36:22 Generating Random Values

03:44:37 Working with Directories

03:50:47 Pypi and Pip

03:55:34 Project 1: Automation with Python

04:10:22 Project 2: Machine Learning with Python

04:58:37 Project 3: Building a Website with Django

Thanks for reading ❤

If you liked this post, share it with all of your programming buddies!

Top 10 Python Frameworks for Web Development In 2019

In this article, we are going to share our list of the top 10 Python frameworks for web development which we believe will help you to develop awesome applications and your technical abilities.

Given how dynamic web development has become, the popularity of Python frameworks seems to be only increasing. This object-oriented, powerfully composed, interpreted, and interactive programming language is easy to **learn **and effectively lessens the development time with its easy-to-read syntax and simple compilation feature. That’s reason enough why it is continuously gaining popularity.

Also, it has a vast number of Python libraries that support data analysis, visualization, and manipulation. Consequently, it has advanced as the most favored programming language and is now considered the “Next Big Thing” for professionals.

Since **Python **does not accompany the built-in features required to accelerate custom web application development, many developers choose Python’s robust collection of frameworks to deal with the subtleties of execution.

**Python **gives a wide scope of frameworks to developers. There are two types of Python frameworks – **Full Stack Framework **and Non-Full Stack Framework. The full-stack frameworks give full support to Python developers including basic components like form generators, form validation, and template layouts.

There is a cluster of full stack options when we talk of Python frameworks. Listed below are the top 10 full-stack web frameworks for **Python **that you should be using in 2019 valuable for enhancing your technical abilities.

Django

Django is a free and open-source Python framework that enables developers to develop complex code and applications effectively and quickly. This high-level framework streamlines web application development by giving different vigorous features. It has a colossal assortment of libraries and underscores effectiveness, less need for coding, and reusability of components.

A few of the key features of Django, such as authentication mechanism, URL routing, template engine, and database schema migration implements ORM (Object Relational Mapper) for mapping its objects to database tables. The framework underpins numerous **databases **including PostgreSQL, MySQL, Oracle, and SQLite, which implies that a similar coding works with various databases.

Django’s cutting-edge features help developers in achieving basic web development tasks like user authentication, RSS feeds, content services, and sitemap. Due to its incredible features, Django framework is extensively used in several high-traffic sites, which include Pinterest, Instagram, Bitbucket, Mozilla, Disqus, and The Washington Times.

CherryPy

**CherryPy **is an open source Python web development framework that implants its very own multi-strung server. It can keep running on any working framework that supports Python. **CherryPy **features incorporate thread-pooled web server, setup framework, and module framework.

A moderate web framework enables you to utilize any sort of technology for data access, templating, etc. Yet, it can do everything that a web framework can, for instance, handling sessions, static, file uploads, cookies, and so on.

Regardless of the accessible features and advantages like running on multiple platforms, built-in support for profiling, reporting, and testing, some developers may imagine that there is a requirement for easy and enhanced documentation. It doesn’t constrain you to use a specific template engine, ORM, so that you can use anything you wish to use.

Pyramid

**Pyramid **is a Python framework that underpins validation and directing. It is incredible for growing huge web applications, as CMSs, and it is valuable for prototyping an idea and for developers chipping away at API projects. Pyramid is adaptable and can be utilized for both easy as well as difficult projects.

Pyramid is enhanced with features without driving a specific method for completing things, lightweight without abandoning you all alone as your app develops. It is a most valued web framework among experienced Python developers by virtue of its transparency and measured quality. It has been used by a moderate team and tech giants like Mozilla, Yelp, Dropbox, and SurveyMonkey.

The pyramid is reliably known for its security arrangements, which makes it easy to set up and check access control records. Another inventive functionality worth uncovering is Pyramid’s Traversal framework for mapping URLs to code, which makes it simple to develop RESTful APIs.

TurboGears

**TurboGears **is an open-source, free, and data-driven full-stack web application Python framework. It is designed to overcome the inadequacies of various extensively used web development frameworks. It empowers software engineers to begin developing web applications with an insignificant setup.

**TurboGears **enables web developers to streamline web application development utilizing diverse JavaScript development tools. You can develop web applications with the help of elements such as SQLAlchemy, Repoze, WebOb, and Genshi, much faster than other existing frameworks. It supports different **databases **and web servers like Pylons.

The framework pursues an MVC (Model-View-Controller) design and incorporates vigorous formats, an incredible Object Relational Mapper (ORM) and Ajax for the server and program. Organizations using TurboGears incorporate Bisque, ShowMeDo, and SourceForge.

Web2Py

**Web2py **is a free, open source Python framework for web application development. The framework accompanies a debugger, code editor as well as a deployment tool to enable you to build and debug the code, as well as test and keep up web applications.

It’s a cross platform framework that underpins Windows, Unix/Linux, Mac, Google App Engine, and different other platforms. It pursues the MVC (Model-View-Controller) design. The framework streamlines web application development procedure via a web server, SQL database, and an online interface. It enables clients to build, revise, deploy, and manage web applications via web browsers.

The key component of Web2py is a ticketing framework, which issues a ticket when a mistake occurs. This encourages the client to follow the mistake and its status. Also, it has in-built components to manage HTTP requests, reactions, sessions, and cookies.

Bottle

Another interesting Python web framework is Bottle, which falls under the class of small-scale frameworks. Originally, it was developed for building web APIs. Also, Bottle tries to execute everything in a single document, which should give you a short perspective on how small it is designed to be.

The out-of-the-box functionalities include templating, utilities, directing, and some fundamental abstraction over the WSGI standard. Like Flask, you will be coding significantly closer to the metal than with a full-stack framework. Regardless of their, Bottle has been used by Netflix to create web interfaces.

Tornado

Tornado is a Python web framework and offbeat framework library. It utilizes a non-blocking framework I/O and unravels the C10k issue (which means that, whenever configured properly, it can deal with 10,000+ simultaneous connections).

Tornado’s main features comprise of built-in support for user confirmation, superior quality, real-time services, non-blocking HTTP customer, Python-based web templating language, and support for interpretation and localization.

This makes it an extraordinary tool for building applications that require superior and a huge number of simultaneous clients.

Flask

Flask is a Python framework accessible under the BSD license, which is inspired by the Sinatra Ruby framework. Flask relies upon the Werkzeug WSGI toolbox and Jinja2 template. The main purpose is to help develop a strong web application base.

**Developers **can **develop backend frameworks **any way they need, however, it was designed for applications that are open-ended. Flask has been used by big companies, which include LinkedIn and Pinterest. As compared to Django, Flask is best suited for small and easy projects. Thus, you can expect a web server development, **support **for Google App Engine as well as in-built unit testing.

Grok

**Grok framework **has been created, depending on Zope toolbox for giving an agile development experience to developers by concentrating on convention over configuration and DRY (Don’t Repeat Yourself). It is an open-source framework, developed to speed up the application development process.

Developers can choose from a wide scope of network and independent libraries as indicated by the task needs. Grok’s UI (user interface) is like other full-stack frameworks such as **Pylons **and TurboGears.

The Grok component architecture helps developers lessen the unpredictability of development by availing views, content objects, and controller. Grok, likewise, provides the building blocks and other essential assets required to develop custom web applications for business needs.

BlueBream

**BlueBream **is also an open source web application framework, server, and library for website developers. It has been developed by the Zope team which was formerly known as Zope 3.

This framework is best suited for both medium and substantial activities apportioned into various re-usable and well-suited segments.

**BlueBream **relies upon Zoop Toolkit (ZTK). It holds extensive periods of experience ensuring that it meets the main essential for enduring, relentless, and adaptable programming.

Conclusion

Though there are many python web development frameworks that will be popular and in-demand in the coming years, especially in 2019, every framework has its own pros and cons. Every developer has different coding styles and preferences. They will assess every framework as per the requirements of an individual task. In this way, the choice of python web development framework will change from one developer onto the next.

The above-listed are some of the Python frameworks that are widely used as a full-stack backend web application development. Which one are you picking for your next project? Do let us know in the comments section given below.