Developing a Chatbot using Python Language: Tutorial

Hands up, If you want to learn how to build an AI Chatbot with Python. This article will walk you through using a Python language library to develop a simple chatbot that determines the value and responds to user input.

Before we get started, there are some points which you need to know before creating artificial intelligence using Python.

What Other Languages Are Used For Building AI?

One of the most known languages for creating AI is LISP (an acronym for list processing).  Its key features consist of, dynamic typing, garbage collection, interactive environment, and uniform syntax. The codes written in LISP are s-expressions which consist of lists.

Prolog is also one of the most popular AI programming languages. It has a built-in unifier, which makes it different from others. The main drawback of this language is that it is very difficult to learn. Therefore, people have to think twice before actually going for it. Another language which is best suitable, if you want to build a simple AI in a short period of time is C/C++.  Its portability and built-in types make this language a priority choice for some developers.

Last but not the least, we introduce you Python. It’s quite similar to Lisp and is one of the most popular languages amongst the other AI languages. But what makes it so popular? Let’s find out.

Why People Opt For Python?

Python has a clean grammar and syntax; it is natural and fluent, explicit than implicit. It has a playful approach to many tutorials and other materials.

Python offers some really efficient features such as, thought out syntax, language interoperability, holistic design, low-level and high-level programming, documentation generation system, testing frameworks and numerous libraries, which are often enjoyed by the developers. When compared to other OOP (Object Oriented Programming) languages Python is comparatively much easier to learn.

Proceeding on Towards Building AI Based Chatbot Using Python

STEP 1 Build AI with Python

Building AI using Python is time-consuming. In fact, it certainly depends on your motivation, skills and the level of experience in programming.  You must have a basic understanding of this language, in order to build AI with Python. First of all, install Python. You may do that installing Anaconda or any other open source analytics platform. The next step is to gain knowledge of machine learning. I understand that it’s quite impossible to reach the ultimate understanding of machine learning in such a short period of time. Hence, start with basic knowledge.

Python libraries are very useful when you build AI. Pandas, an open source library that provides developers with convenient data structures analytic tools is another important tool for Python. Scikit-learn is an efficient tool for data analysis. It is amongst the most popular general purpose machine learning library.

After working with scikit-learn, explore k-means clustering. To learn more about Python in AI, you can read about a deep learning framework caffee and a Python library Theano.

By above paragraphs, it can be concluded that Python is quite important for AI. Any machine learning project can take benefit from using Python. AI indeed demands a lot of research. Use of Python in AI makes its programming efficient like no other.

How To Develop a Chatbot Using Python?

A chatbot is a computer program, which is designed to simulate a conversation with human users, especially over the internet. They are online assistants that offer different services through chatting. For example, there is Lyft whom you can request a ride via chat (Facebook Messenger and Slack) or voice (Amazon Echo) or Starbucks with which you can easily place an order using voice commands or text messaging. Cool right?

A chatbot can be used in any department, business and every environment. They are artificial narrow intelligence (ANI). Thus, are not as clever as humans. Additionally, chatbots only carry out a limited amount of task i.e. as per their design. However, these chatbots make our lives easier and convenient.

The trend of Chatbots is growing rapidly between businesses and entrepreneurs, and are willing to bring chatbots to their sites. There are various ways to do that such as by using different languages and approach or you may ask a professional software development company to do that for you. You might also create it yourself using Python.

To build artificial intelligence chatbots through Python, you will require ATML package (Artificial Intelligence Markup Language).

First, create a standard startup file without any pattern and load aiml b. Add random responses that would make a dialogue interesting.

Now, to code your own AIML files, look for some files which are available beforehand. For example, browse among files from the Alice Bot website.

The startup file you will be creating will act as a separate entity. As a result of which, you will have more AIML files without a source code modification.  The program will start running when there are enough AIML files.  This was an introduction to how to make AI using Python. Now, let’s proceed further and see which particular library can be implemented for building a Chatbot.

Chatbots in Relation to NLP (Natural Language Processing)

Nowadays, Natural Language Processing or to be precise, its component Language Understanding (NLU) has allowed bots to possess a greater understanding of language and context.

They are advancing at an unprecedented rate and are becoming more intelligent in understanding the meaning of the search. They are now capable of responding in a more specific, accurate and context-based information.

Social media platforms such as Facebook Messenger, WhatsApp, Slack etc. are progressively being used by businesses.  Websites-interface is being replaced by Bots. From the numerous choices available for building a chatbot, the implementation below uses the RASA-NLU in Python.

How To Install RASA?

Rasa can be installed on a standalone machine. Steps are as follows:

  • It can be done by pip install rasa_nlu
  • Latest documents can be seen here

RASA-NLU is made up of separate components, where here every component does its own specific work. Each component has its own province. Options such as MITIE, Spacy, and Skelearn are available. We will be using Spacy and Sklearn here.

Flask is simple to code. Use pip install flask and follow along to understand the basics of the framework.

Server

A RASA-NLU platform needs to be practiced before actually initiating it. We must transfer few sentences and mention the intents and entities in it. For those who don’t know, Intents are sentences that contain actions and categories, and entities are compulsory variables required to fulfill the actions.

Below is a simple example, showing that it contains many entries:

The explanation is as stated below:

  • Text: the input sentence.
  • Intent: “restaurant_search”. Call-back function.
  • Entities: one is ‘location’ consisting value as ‘centre’. Second is ‘cuisine’ with value as ‘Italian’. ‘start’ and ‘end’ in the above context is the beginning and ending indication of the words.

These are Some Steps To Create a Server Side of the GST Chatbot Application-

  • Build a new directory and navigate to it.
  • Create a data/demo_gst.json.
  • Train the project in python.

This will create a model_YYYYMMDD-HHMMSS folder.

GST Bot is just a small example, revealing the potential to develop something which is completely functional and useful.

7 Kick-ass Games Built Using Python Language

Python is an unimaginably compelling and valuable PC programming language that a significant number of the famous games depend on for their establishment. Programmers picked Python for the game development activities since it is an easy language to begin with, and is fun and simple to learn.

From one perspective, it consolidates the profundity and resources of utilizing C/C ++ libraries, and on the other hand the simplicity of utilizing Flash, with a normal execution between the two. In this way, commonly it is a decent language to program complex things rapidly, however, clearly giving up execution, being games interpreted and not gathered.

Here is a list of the most popular game programs that are written in Python language and what they do.

1. Civilization IV

Civilization IV, otherwise called Sid Meier’s Civilization IV is a turn-based methodology PC game and the fourth version of the Civilization game series. It was developed by Soren Johnson under the management of Sid Meier and his computer game development studio Firaxis Games. It was launched between October 25 and November 4, 2005, in Europe, North America, and Australia.

The map editor of this game version supports Python.

2. Battlefield 2

Battlefield 2 was designed by Digital Illusions CE in the year 2005. It is a military simulator first-person shooter video game. It was developed with contributions by Trauma Studios, and distributed by Electronic Arts only for Microsoft Windows as the third version in the Battlefield game series.

Battlefield Heroes handles some portion of the game logic involving game modes, scoring with cleartext Python scripts.

3. Sims 4

The Sims 4 is the 4th significant version in the series of the life simulation video game – The Sims. The Sims 4 is similar to its predecessors. It is created by Maxis and The Sims Studio and distributed by Electronic Arts. Players design a Sim character and manage their life to examine different personalities which transform the way in which the game plays out.

Mod support for The Sims 4 is prepared through Python including the application of Python for coding.

4. Toontown Online

Disney’s Toontown Online is generally also famous as Toontown or Toontown Online. It is a 3D massively multiplayer online role-playing (MMORPGs) game designed on a cartoon animal world. The game series is developed by Disney’s Virtual Reality Studio and Schell Games. It is published by the Walt Disney Company. Players could build characters named “Toons”. Players are also capable to customize their Toons character in different shapes, clothes, colors, and sizes, as well as their species.

It is utilizing Python for writing codes and panda3D for graphics. Python has pulled out for this game as it is almost lightweight, efficient, and balances properly. It consists of a syntax that is simple to learn and debug, as well as the documentation is great.

5. World of Tanks

World of Tanks or WoT is also an MMORPGs created by the Belarusian-Cypriot organization Wargaming. The game features the mid-20th century i.e. 1930s-1960s era war battle vehicles. It is developed upon a freemium business form where the game is free-to-play, although members also have the alternative of paying a fee for using its “premium” features.

World of Tanks has additionally, ported to many gaming consoles. Wargaming West studio developed an Xbox 360 variant, called World of Tanks: Xbox 360 Edition. The PlayStation 4 adaption was launched in the in 2016. WoT has further recently developed to mobile platforms with the title World of Tanks Blitz.

The game has Python at its focus as a scripting language for user-side logic.

6. EVE Online

EVE Online is an online space-oriented, steadfast world MMORPGs created and distributed both by CCP Games. The players in this game can partake in diverse in-game tasks and activities, such as trading, mining, manufacturing, piracy, investigation, and combat (both player versus player and player versus environment).

Both the server and the client program for Eve Online are developed using Stackless Python, a variation of the Python programming language. Stackless Python permits a generally huge number of players to execute duties without the overhead of utilizing the call stack utilized as a part of the regular Python distribution. This liberates the game designers from playing out some regular work and enables them to apply transitions to the game universe with no need of resetting the server. In any case, the Eve cluster is taken offline every day for server and database support.

7. Frets on Fire

Frets on Fire or FoF is a free and open-source Finnish music video game developed by Unreal Voodoo. Players utilize the console to play alongside markers which show up on screen, with the plan to score points, accomplish a high point multiplier, and finish a tune.

The game is written using the Python programming language and is authorized under the GNU General Public License, despite the fact that the game fuses other free and open-source code under different licenses. The game’s incorporated song files and some inner text styles are restrictive, and their redistribution isn’t allowed outside of the Frets On Fire executable.

Conclusion

What influences Python to emerge among different programming languages for game development is its readable and clean syntax structure. Relatively every developer will approve that Python code is more comprehensible than that of Java or C language. And keep in mind that development speed may change from one project to another, it is broadly accepted that developing a game in Python is 5-10 times speedier than making it in Java, not to state of C/C++.

Python vs PHP? Which Language is Better for Web Development

Before exploring the reasons that construe Python better than PHP, let’s first understand what is web development?

It is a wide term used for the work in developing a website for the Internet or an intranet. It includes web designing, web content development, network security configuration etc. It ranges from creating text pages to complex web applications.

Web designing is done in following hierarchy:-

  • Client-side coding
  • Server-side coding
  • Database technology

For developing websites we need programming languages. The two most prominent programming languages used for web development are Python & PHP.

In the following sections, we are going to discuss two programming languages and will also try to find out how Python is better than PHP.

PHP (Hypertext Pre-processor):-

It is a scripting language designed for web development which is used to create dynamic and interactive HTML Web pages; it is also used as a general-purpose programming language. It is introduced by Rasmus Lerdorf in the year 1994. The full form of PHP is Personal Home Page but now it is known as Hypertext Preprocessor.

It is an HTML-embedded Web scripting language; which means PHP code can be easily inserted into the HTML of a Web page. It is the fastest source to create database-enabled dynamic websites.

PHP supports main web and enterprise servers like Apache, Netscape, Microsoft IIS, etc. And it also works on the operating systems like Linux, Windows, UNIX and Mac OS.

The Key Features of PHP include:

  • Open Source:-

It is the open source of programming which means you don’t need to pay to use it. You can download for free and use the PHP language.

  • Simple:-

It is very easy to use as compared to other scripting languages. It is very simple and easy and widely used all over the world.

  • Interpreted:-

There is no need for compilation as it is an interpreted language.

  • Platform Independent:-

It is a platform independent language as PHP code can be run on every platform like Linux, UNIX, Mac OS X, and Windows etc.

  • Speed:-

It is comparatively faster than another scripting language since it uses much system resources.

  • Error reporting:-

PHP has a function to generate warning or error notice so that one can easily find the errors & can fix it on time.

But with all these advantages, come certain disadvantages which are discussed as follows.

  • Security:-

As we have discussed that it is an open source. All the people using it can access the source code and if there are bugs in the source code, it can be used to explore the weakness of PHP

  • Unfit for large applications:-

It is hard to maintain as it is not very modular.

Post this critical analysis of PHP, let us discuss the essential features of Python and see how these two languages compare.

Python is a high-level programming language used for general-purpose programming, designed by Guido van Rossum. It started in 1991 and has a design philosophy that stresses on code readability, notably using remarkable whitespace.

It is used for: – web development, software development, mathematics and system scripting. There are 2 major versions of Python programming language i.e. Python 2 and Python 3.

Python code has a natural style which makes it is easy to read and understand. Hence, making it easy to learn. Some of the key reasons why one should learn and use Python programming language include:

  • Beginner friendly:-

It is a beginner friendly language because it is easy to understand and fun to use. That is one of the reasons that python has gained popularity to be a beginner friendly language.

  • High-level language:-

As it is a high-level programming language so while using the python you not need to worry about low-level details such as managing the memory used by the program.

  • Shorter codes:-

Another advantage of python language is that its coding is quite shorter than other programming languages.

  • Clear syntax:-

Python does not consist of curly braces; it has a very clear, brief and orthogonal syntax.

  • Object-oriented:-

Python supports both procedure oriented and project-oriented programming as well.  It has a very powerful but easy way of performing object-oriented programming as compared to other programming languages.

Now, let’s look at some reasons for why to prefer using python over PHP

  • If we talk about the readability of both the languages PHP is not much maintainable as compared to Python.
  • Python consists of more security features as compared to PHP.
  • In PHP, the functional programming is not provided but in python, functional programming and techniques are possible.
  • PHP was designed as a ‘web development’ language while Python was designed as a ‘general purpose’ language.
  • Python has more united and commanding standard library, including library much better than PHP’s.
  • Python has more dense and clean syntax that helps developers in web development.

Below are some areas where Python proves its domination over PHP. Thereby, also stating that why it is a rising star in the field of web development

  • Better designed:-

Python has a construction that helps make it carefully considered, well designed and robust language. PHP, on the other hand, seems not to be so well thought out. It is much easier to use Python to write great code.

  • Better in long-term:-

From the point of view of a developer, one should consider what is likely to create the maximum value for them in the long term. However PHP has a short learning curve but if we talk about the long-term, python is more productive than PHP.

  • Better web framework:-

The most suitable framework for Python is Django framework, whereas PHP works on Kohana, Symfony, CodeIgnitor, and Zend.

  • Readability:-

Python is more readable than PHP and other programming languages. Python is easy to read and easy to learn as well.

  • Simpler syntax:-

The coding in python is comparatively simpler than PHP; it has very clear, brief and orthogonal syntax. The codes are easier to understand and write in python. When we write something in python, it is so simple and effective that you want to show it to others.

  • Simpler debugging tools:-

In case of bug you need to use several debugging tools in PHP but in case of python, only fewer debugging tools are required such as pdb 26.2, pdb 27.3 etc. Most of the times the debugging tools in the Python downloader package are quite sufficient.

  • Better package management:-

As compared to PHP, Python has a better package management. With the help of package management, one can write, build and share packages in such a way that developers can easily plug into other applications.

By considering all the above-mentioned points and facts we can safely draw the conclusion that Python is much better than PHP in web development. If we think from the point of view of a developer, Python has more advantages over PHP in the long run.

Tutorial: Python Database Programming For SQLite3

The advancement in technology leads to the development of many software which can be utilized for accessing various information from the server. Thus this server needs a system which can be accessed from anywhere and anytime, making it simpler for the user to access the information.

What is a Database Management System?

This system can be referred to as DBMS (Database Management System). DBMS is used to store data in an organized way which can be retrieved or modified easily by a user through a query. Dbase, libreOffice base, Microsoft Access or Foxpro are often used to retrieve data from the server. DBMS was introduced to access information easier and efficiently.

Another system was introduced so as to make the complexity of database more simpler and efficient which can be referred as Relational Database Management System or RDBMS. In RDBMS the data is stored as Files. Whereas, in RDBMS the data is stored in a table form containing the data in a more structured way. Oracle, MySQL, SQLite, MariaDB are often used in this system to access the data from RDBMS.

Every organization whether it be offices or banks, they all need a large database system, which can store the data which is relatable to each other in many different entities, in various columns and rows, therefore RDBMS makes it easier and simpler to manipulate this data and access them.

In programming Languages, Data needs to be stored, modified or retrieved easily, thus RDBMS plays a huge role in programming languages.  Programming languages like Python, C, C++, PHP and Java needs a library where the data can be stored and used. These libraries are referred to as a Database. To access these, a Structured Query Language or SQL is used.

What is SQL?

SQL is used in programming which is a specific language used for modifying and accessing the data in RDBMS. In RDMS there is a set of relations between data in a structured way and through SQL this set of Data entries can be easily modified through a single query.

Why Python?

In a programming language like python, there is a strong need for database handling and manipulation. There are various databases like MySQL, SQLite, Oracle etc, which python supports. Python language is more efficient and mainly used for web programming, python generally works on a larger database system, as it comprises of web development. That is the main reason why python supports various platforms to access the RDBMS.

SQLite system is Relational Database Management System basically for embedded systems which were introduced by D. Richard Hipp. Use of SQLite RDBMS in python would play a major role in handling the database, As SQLite is commonly used database for web programming processes. Python programming language is used for web development and use of SQLite would not be a bad idea, as it will make it faster for the python language to access the information. The SQLite is fast and light weighted database. SQLite is not a client-server based system, thus it does not process on its own and through linking to a program, the SQLite library becomes a part of that application.

Python can be used for Database programming which can be very beneficial and is very fast and efficient compared to other programming languages.  Handling a larger database system more effectively and easily, python programming also provides a platform where the different databases can be interfaced and manipulated. To perform operations in database Python Database Application Programming interface or python DB-API is needed. It is used to interface with the database system, python DB- API is a set of the procedure used to create applications which allow the platform to interface with other services such as database system.

How to Install SQLite3?

SQLite3 can be unsegregated with Python using SQ3 lite3 module, written by Gerhard Haring.

One does need to install this module separately as it is shipped by default along with Python version 2.5.x and above.

In order to use Sqlite3, it is essential to first create a connection object that represents the database and after as per your choice you can build a cursor object, which will help you perform and execute all the SQL statements.

Database Connection using Python Coding

The Python code below shows how to connect to an existing database. In case, the database does not exist, it will be created and a database object will eventually return.

You can also supply database Memory to create a database in RAM. Let’s run the above program to create database test.db in the current directory. Your path can be changed as per your need. A successful database creation will give the following message.

Table Creation

The program below will be used to create a table in the already created database.

The execution of the above program will create the SCHOOL table in your test.db and will display the result below:

What a day today!Table created successfully

Inserting Operations

Following Python program shows how to create records in the SCHOOL table created above.

Once the above program is executed, it will show the following result.

Selecting Operations

Following Python program shows how to get and display records from the SCHOOL table and created in the above example.

The program above will give the following results.

Updating Operation

The Python code below shows how to use UPDATE statement to update any record and then get and display the updated records from the SCHOOL table.

When the above program is executed, it will produce the following result.

Deleting Operations

Following program shows how to use DELETE statement to delete any record and get the remaining records to display them from the SCHOOL table.

When the above program is executed, it will produce the following result.

Python -The Most Trusted Language in Data Science

Without no doubt Python is the most famous Programming Language at the moment. Stack Overflow has recently published a survey in which it has been clearly mentioned that Python has surpassed the fame of c# and PHP and has been named as the fastest growing language of this time.

But what makes Python so much in demand especially when it comes to Data Science?

  • Python’s simple syntax makes it easy to use
  • Owing to its versatility the language is considered as a Swiss Army Knife in data science
  • Python has impeccable packages such as Numpy, Pandas, Scipy, Scikit-learn, PyBrain, Tensorflow, Cython, PyMySQL etc.
  • For interactive programming there is an iPython notebook.
  • For Data visualization purposes Python has packages such as, Plotly, Matpolib, ggplot, Pygal. Networkx etc.
  • Learning curve of Python is comparatively low compared to others.
  • Python is compatible with open-source data platform Hadoop
  • Anaconda platform of Python is fast when it comes to data processing.

Let’s have a look at an infographic for a clear idea and some valuable suggestion regarding learning Python for Data science related purposes.

How to integrate Python and HTML in different ways?

The web application is slowly but gradually spreading all over the internet world and is slowly turning out to be the new face of businesses. Initially, Hypertext Mark-up Language (HTML) was used for the process of web development. Well, that changed with the introduction of many platforms which made the process easier. However, the use of HTML in web development never ceased.

Let’s see how Python and HTML dependant on each other.

Low-Level View

The user makes a request with the server when they enter any website. The server will search for the particular request and will revert the answer to the browser that will display it to the user known as a response. Well, this is a common way in which HTTP works for the user. However, dynamic websites have a different way to work as they depend on the programs to fulfill their request and generate the solution for the user. This includes many things such as showing email, posting bulletin board, software configuring, and displaying time.

neural networks python

Since there are many servers that support python, hence these codes are usually written on that platform only for the dynamic sites. Subsequently, HTML use C, C++ which make python execution difficult. A developer needs to create a bridge like structure between the two to help in easy interactions. Also, it is important to know that interfaces can be rejected by the server. The only newer server can easily support the change without much problem.

CGI: Common Gateway Interface

It is the oldest and most supported interfaced used by web servers. CGI is used to make a request to the server and since the server started the python interpreter, the load situations seem to go out of hand. The python takes some time to load off the content and get started to work. The best thing is that Python with CGI only needs a total of three line of code (LOC) to bridge the gap. Well, it doesn’t help much to the developer. However, you don’t have to write CGI programs. However, you can use the simple CGI code to get started with:

enable debugging
Import cgitb
Cgitb.enable()
print “Content-Type: text/plain;charset=utf-8”
print “Hello World!”

Save the code as per your configuration with the extension – .py or .cgi. Also, you need to save the file in the folder named as cgi-bin for security.The cgitbwill allow displayingtraceback instead of crashing the request or“Internal server error”. However, it can risk in reliving important data during debugging. If you are using production code then avoid using cgitb. There are other methods like exceptions that could be used.

mod_python

People that are from the PHP or JS background usually find it difficult to understand python. To overcome this, they simply use mod_python as it is similar to mod_php. Well, there are many things that make them different. mod_python is used to embed the translator in a process and speed the request process without calling out the interpreter of python to load. However, it cannot be used with Python incorporation with HTML, the same way it might work with PHP with HTML.

As a matter of fact, it can create extra problems in the code. However, it can imitate CGI to work in the python server page which has a publisher to select a file to receive requests. But, python interpreter depends on cache for the file execution. If a file is changed then you need to restart the server. Another issue that might be faced by using mod_python is that a child process is used to receive and handle the request which needs the whole interpreter to load at once all over again. This results in slowing down the server. In some cases, it is better to use mod_python like in the WSGI programs.

mod_wsgi

With the help of mod_wsgi, you can easily get rid of the low-level gateways. However, WSGI applications are usually deployed with the help of mod_python, SUGI, and FastCGI. WSGI applications were directly embedded in the Apache server by using mod_wsgi that is precisely planned as per the host. This helps in deployment making it easier than any other methods. Also, you won’t need glue code if you are using it. However, it may limit the server.

WSGI Server

The WSGI server is the code that connects the gateways such as mod_python and CGI. The most commonly used server is flup supported by SCGI and FastCGI including AJP. The server is written in the python language but also be translated to another platform including C to use as a replacement method. The main advantage python has over other is that it can be deployed on nearly any platform.

Templates

There are few libraries that made it possible to mix python and HTML together. However, it is easy but it can be difficult to maintain and hence you will require templates. They are like the placeholders for the HTML files.

>>> template = “<html><body><h1>Hello %s!</h1></body></html>

>>> print template % “Reader”

<html><body><h1>Hello Reader!</h1></body></html>

>>> from string import Template

>>> template = Template(“<html><body><h1>Hello ${name}</h1></body></html>”)

>>>print template.substiture(dict(name=’Dinsdale’))

<html><body><h1>Hello Dinsdale!</h1></body></html>

 

In order to generate HTML with a complex solution that is based on model data, looping constructs or conditional like python if and forwill be needed. However, it is well supported by the template engines.

probytes

Templates are available as per user requirement without or with the framework. If you are looking for learning purpose then you can adopt plain text programmingand other most popular is XML.

There are many frameworks available in the market that is extremely used by the developers. You can select any one of them as per your requirement and server techniques. It is simply a way to save money, time and enhance the rate of production.

Learn How To Use Python For Building Your Own Neural Network

In simple terms, the neural networks is a computer simulation model that is designed according to the human nervous system and brain. However, neural network python could easily be described without using the human analogies. You can also take them as a mathematical function to give out perfect explanation.

python

However, you might have certain doubts that why to build Neural Network from the scratch?

There are neural network  python libraries available such as PyBrain that could be used. However, implementing a network is essential to get a better understanding of the working process of the neural network.

Before getting started, let us tell you that the codes used here are simply for the understanding point of view. Now, get the work started.

1. Generating A Dataset

You need to generate a dataset before starting the neural network building using python. You can generate it yourself or you can simply take help from some online software that offers inbuilt dataset. Take two different type of sets on the x and y-axis.  Basically, you need to plot the data. It can be medical data or business related data.

We are mainly focusing on the Machine Learning Classifiers that can easily predict the class of the data spread out on the x and y coordinates. However, the data cannot be separated by a line that will limit the use of linear classifier. This simply means that you cannot use Logistic Regression without non-linear features.

This is the plus point of using neural networks as there is no need to worry about features like polynomials. The neural network has some hidden layer that can easily remember features.

2. Training A Neural Network

Then you need to create the neural network 3-layers such as input layer, an output layer and a hidden layer. Since the dimension of the data taken is x and y hence the input layer will have 2 nodes in total (if you have more dimensions then you need to take the number of nodes accordingly).

The classes will determine the number of nodes that will be held in the output layer. Since our predicting class has two values (1,0) hence the number of nodes will be 2 as well. You can extend the classes and network as per your wish.

However, the hidden layer dimensionality is in your hand. You can take as many nodes as you want to take. You need to understand that more nodes give you a chance to fit more complex functions. The two things that you will face with higher nodes are:

  • To make predictions you will need more computation and need to learn network parameters efficiently.
  • You will become disposed to overfit the data with the higher number of nodes.

Then, you will need an activation function that will transform the input data to the output layer. The most commonly used activation functions are a sigmoid function, tanh, and ReLUs.

Creating a class:

class NeuralNetwork:

def _init_(self, x, y);

self.input = x

self.weights1 = np.random.rand(self.input.shape[1],4)

self.weights2 = np.random.rand(4,1)

self.y = y

self.output = np.zeros(y,shape)

Here x is the input layer with randomly hidden layer and ŷ as the output layer. The weights and biases are denoted by their first letter that is W and b respectively. The sigmoid function will be the activation function.

The output of the neural network will become:

Ŷ = σ(W2σ(W1x+b1)+b2)

Since you can see that in the equation, W and b are affecting the output layer. Logically, the correct value of W and b are required in order to define the strong point of the predictions. This fine-tuning of W and b are the main functioning of the data known as training a neural network.

The main work of this aspect is:

  • Feedforward: Through this, you are calculating the Ŷ that is the predicted value.
  • Backpropagation: it is simply the value update of W and b.

In the above code you need to add the feedforward code to come in sequence;

def feedforward(self):

self.layer1 = sigmoid(np.dot(self.input, self.weights1))

self.output = sigmoid(np.dot(self.layer1, self.weights2))

After this, you need to check out the best of the prediction you have done, to do you will need a loss function. The main thing to keep in mind is that you need to minimize the value of loss function to get the result. Use sum-of-square error as the loss function to dictate the problem.

probytes

The sum of square error is mainly the basic square of the difference between the predicted and actual value.

Gradient Descent:

Then comes the back propagation, once you are done with finding the loss error then you need to propagate the loss back in order to update the b and W value. Simply, derivative the loss function with W and b to get the result.

But you won’t be able to derivative the functions directly hence you will need a chain rule that can help out in easy calculations.

Loss (y, ŷ) = S i=1-n (y-ŷ)square

dLoss(y,ŷ) = dLoss(y,ŷ) *dŷ *dz

————–    ————–   —–  —

dw                      dŷ             dz    dW

=   2(y-ŷ) *derivate of sigmoid function *x

=   2(y-ŷ) *z(1-z) *x

Now simply add the code to the main python code to get the proper result.

This looks complicated, however, when you will start to write the code, you will start to understand the terms and the basis. Don’t be worried if your prediction is not the same as your output. There can be a slight variation to avoid overfitting. This will generalize the data in a better way by giving the desired output.

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Python Development Trends 2018 – [Infographic]

The growth of Python language over the course of 5 years has been tremendous. It would not be an exaggeration to name this language as the fastest growing language now.

newone

Why Python programming is so much in demand nowadays

1. First of all, Data science is booming nowadays. For related development, Python is put to use the most. Reason?

  • Availability of numerous libraries such as NumPy, ScikitLearn, SciPy, PyBrain, etc
  • Python comes with a data analytics tool, Pandas which is of great use to data scientist and developers
  • Machine learning algorithm is easy to obtain in Python e.g.: Scikit-Learn and TensorFlow
  • Presence of Third party module which makes it compatible with all other programming languages and platform. Due to it’s increased speed and productivity, Python is the top prior option for developers in creating complex multi-protocol network application

2. Apart from the development of artificial intelligence and Data Science application and programs. Python is extensively used for web, mobile, and desktop-based software development. Reason? The language is so much simpler to use.

Owing to obvious reasons career opportunity of Python is also in an all-time rise. The major share of the traffic that websites that deal with Python share are owing to this high demand.

It has to be noted that 22% of the Python developers are either 1-2 years of experience cementing the fact that there is a large requirement of new developers.

Different Python related jobs include,

  • Python Developer
  • Research Analyst
  • Data Analyst:
  • Data Scientist
  • DevOps Engineer

Moreover Big Shots like

  • YouTube
  • Quora
  • Google
  • Survey Monkey
  • Dropbox
  • Yahoo!
  • Survey Monkey
  • Spotify
  • Instagram
  • Bitly etc has relied Python for the development of their websites, various platforms etc.

Since the importance of this Language has been evidently proved, let’s have a look at the python development trends that’s already happening or going to happen this year.

python development trends

Python Programming: All You Need To know About It

What Is Python?

Named after Monty Python, Python first came into existence in 1991, and since then it was a relatively new language to most of the programmers. Right after its advent, it was used for a multitude of tasks including testing microchips at Intel to building video games.

One of the reasons why Python gained popularity is due to the reason that it was most similar to the English language. Thus, Python emerged as a first-class programming language in the modern software development world.

Why Choose Python?

 

 

Python programming

 

There are many reasons why Python became a success across the world. We have listed the significant reasons why developers personally choose Python and recommend it to as many people as possible.

Readability:

As stated earlier, Python very closely resembles the English language and uses the words like ‘not’ and ‘in’ to build a script. Thus, when reading out a program or script aloud to an average person, the developer wouldn’t appear like an alien speaking an unknown language. Again, Python features strict punctuation rules which mean that the codes wouldn’t be filled with curly braces.

probytes

Python also has got a set of rules known as PEP 8 that gives information to the users on how to format the codes. Thus, whenever working with Python, the user knows where to put new lines, and whether written by a professional or novice, the script would still look the same.

Libraries:

It has almost been around 20 years since Python was first used. Thus, a lot of code written in Python by developers has eventually built up forming a vast library. Being an open source programming language, a lot of these codes have been released for others to use.

All these codes are collected on https://pypi.python.org/ which is pronounced as “pie-pee-eye”, and it is most commonly referred to as the “CheeseShop”. The software could be installed on any system and could be used when working on personal projects.

On the other hand, if you are a developer who would wish to use Python to build scripts with command-line arguments, you would have to install the “click” library to import your scripts into it and use it. Thus, there are libraries for almost every case that a developer can come up with from scientific calculations to image manipulation.

Community:

Python holds major conferences on every continent except for Antarctica and has user groups called PUG’s. The largest Python conference in North America is called Pycon NA and sells 2,500 tickets every year. Most importantly, Python supports women environment, and it has had over 30% women speakers.

Python came up with yet another innovative event in 2013, where Pycon NA started offering “Young Coder” workshops where attendees are brought to teach Python to kids between 9 to 16 years of age. The program helps children grow familiar with the language and eventually help them to hack and modify certain games on the Raspberry Pis that would be given to them. Being part of such a positive community helps in keeping you motivated.

Popularity:

Python is broadly used and supported among the web developers. Being highly rated in surveys held by Tiobe Index, Python runs on almost all major operating systems and platforms. Python is written in modest language thus it is much easier to grasp when you are a complete novice at web programming.

 

What Is Python Used For?

What is Python used for? This would be the most frequent question that you must be asking yourself if you are a beginner trying to step foot into the Python world of programming.

Python, as it is known, is a programming language that is mainly used for scripting and automation. Nonetheless, Python isn’t just a replacement for batch files and shell scripts. It is also used to automate interactions with web browsers, application GUIs, system provisioning, and configuration in tools.

For General Application Programming:

Python can build both CLI and cross-platform GUI applications. However, Python isn’t capable of generating a standalone binary from a script. Nonetheless, third-party packages such as cx_Freeze or PyInstaller could be used to accomplish these tasks.

For Data Science and Machine Learning:

Sophisticated data analysis has become one of the major and dynamic progressing areas in the IT sector. The vast libraries used in data science and machine learning use Python interfaces, making the language reach a certain height of popularity.

For Web Services and RESTful APIs:

As mentioned earlier, Python features native libraries and third-party web frameworks. They provide the quick and convenient way to weave everything from a simple REST API with just a few lines of codes to a full-blown, data-driven site. Furthermore, the latest version of Python features powerful support for asynchronous operations which allows sites to handle tens and thousands of requests every second.

For Meta-programming:

When it comes to Python, every aspect of the language is an object including the libraries and modules themselves. This very ability aids Python to function as a highly efficient code generator. Generating codes means Python is capable of writing applications that could manipulate their functions and have a kind of extensibility. This particular ability of Python is hard to the point of being impossible to achieve with other languages.

For Glue Code:

Python is often referred to as the “glue language”. Glue language means that it allows different codes to interoperate. These codes are in turn the elements that help Python execute data science and machine learning.

Again, Python is a high-level language. Thus, it is unsuitable for system-level programming. It is also not efficient at situations that call for cross-platform standalone binaries. Standalone apps could be built for Windows, Mac, and Linux using Python. However, the apps wouldn’t appear elegant or simple. Python is again not the best choice when speed is given the ultimate priority.

Python Codes

When writing a program using Python, there are two ways in which you can do it.

Functional programming

Object-oriented programming (OOP)

Functional programming involves using functions whereas object-oriented programming is all about the involvement of classes. Now you may ask, what is the difference between a class and a function?

A function is a collection of codes ought to perform a single operation. The operation of the function can only be acquired when the function’s name is used. And the class includes a group of functions that can be retrieved using an object. Another difference that may appear to be quite absurd would be the usage of “def” to begin a function and “class” to begin a class.  Usually, class names are written in capital letters whereas methods don’t follow the capitalisation.

Python is an object-oriented programming language; thus anyone writing a program in Python is given the ability to come up with new classes of objects and utilise them. Thus the programmer is not forced to work with just the built-in classes of objects.

Loop

There are two types of a loop on python. The for loop and the while loop. First, let us take a look at the “For Loop”.

For Loop

The general format used for a loop is as follows.

for variable in sequence:

#some commands

#other commands after the loop

The loop starts from the colon, and the indents and new lines are what administers the end of the For loop. Now using the general format, let us weave a loop that could be used when programming.

#The following code demonstrates a list with strings

Ingredientslist = [“Rice”, “Water”, “Jelly”]

for i in ingredientslist:

print i

print “No longer in the loop”

Here, ‘i’ is the variable which moves along the string list becoming each string in turn. The above-written code brings in the following output.

  • Rice
  • Water
  • Jelly
  • No longer in the loop
While Loop

The while loop is similar to the For loop in many ways. But what makes them different is the fact that the while loop continues to loop until the specifically mentioned condition cease to become true. The while loop, unlike the For loop, isn’t asked to work along with any specific sequences.

i = 3

while i <= 15:

    # some commands

    i = i + 1 # a command that will eventually end the loop is naturally required

# other commands after while loop

When using loops, For loops are always simple and easy to use. However, while loops come handy if the number of iterations before the loop needs to end is unknown.

If Statement

If statements work the same way as the loops mentioned earlier. However, when using if statements, the key identifier used is a colon while starting and ending the statements. As an alternative of “if”, “else” can also be used after the loops and it gives out the same result.

If   j  intestlist:

     # some commands

elif  j == 5:

    # some commands

else:

    # some commands

Array Types

Lists

As we all know, a list is a sequence of variables collected together as a group. The range function is commonly used when creating lists of integers with the general format of range. 0 acts as a default for start and 1 as the default for the first step.

>>>  range (3,8)

[3, 4 , 5, 6, 7]

A long side integers, lists can even accommodate strings in them with a mix of integers and floats. They can generally be created by a loop or by explicit creation. Nonetheless, it should be noted that the print statement would display a string/ variable/ list to the user.

>>> a = [5, 8, “pt”]

>>> print a

[5, 8, ‘pt’]

>>> print a [Ө]

5

Tuples

Tuples resemble the list, but on the negative side, they can’t be modified after their creation. So whatever changes you have got to make, you ought to do it when creating them. Tuples are assigned using the below mentioned code.

>>> x = (4, 1, 8, “string”, [1,Ө], [“j”, 4, “o”), 14)

Tuples give the programmer complete freedom of including any strings, other tuples, number, lists, objects, and functions in them. Another important thing to note when creating tuples is that the first element of any tuple is numbered as element “zero”. The data can be retrieved using the following code.

>>>x [Ө]

4

>>>x [3]

“string”

Dictionaries

A dictionary includes a list of reference keys each associated with a particular data. The important fact about a dictionary is that its operation isn’t affected by the order. When using dictionaries, the keys are not just consecutive integers as in a list. Instead, the keys could be floats, strings, or integers. You may get a better idea once you go through the below code.

>>> x = {} # creates a new empty dictionary – note the curly brackets denoting the creation of a dictionary

>>>  x[4] = “programming” # the string “programming” is added to the dictionary x, with “4” as it’s reference

>>>x[“games”] = 12

>>>print x[“games”]

12

The reference keys and the stored values present in the dictionary can be of any type. Alongside, the new dictionary elements are additionally inserted as when they are created. In a list, this isn’t possible, because the user cannot access the list that exceeds the initially defined list dimensions. Let us take a look at the below program.

costs = {“CHICKEN”: 1.3, “BEEF”: 0.8, “MUTTON”: 12}

print “Cost of Meats”

for i in costs:

print i

print costs[i]

costs[“LAMB”] = 5

print “Updated Costs of Meats”

for i in costs:

print i

print costs[i]

This program would give the output as shown below.

Cost of Meats

  • CHICKEN
  • 3
  • MUTTON
  • 12
  • BEEF
  • 8

Updated Costs of Meats

  • LAMB

  • 5

  • CHICKEN

  • 3

  • MUTTON

  • 12

  • BEEF

  • 8

In the example given, you would find the use of curly brackets and colons that represent the assignment of data to the specific dictionary keys. While the variable i is allotted to the keys in the exact way it is done in case of the list. The dictionary can then be called using this key, and it would return the data saved under that specific key name. These kinds of loops are highly useful in crafting PuLP to model LPs.

Notes onThe Syntax Of List, Tuple, and Dictionary

Though you are familiar with the codes, there are specific fundamental factors to take care of when writing a program using Python. A few of the point to keep in mind when creating lists, tuples and dictionaries are listed below.

  • Square brackets are used when creating lists
  • Tuples are inserted using round brackets and a comma
  • Parentheses work when creating dictionaries

No matter what kind of brackets the user use while programming after the user is done with the creation, the operations are always performed using square brackets to access the elements in the list, tuple, or dictionary. Nonetheless, the data retrieved would also change when using the square brackets. When the user is performing the function on a list or tuple, the data stored in the fourth element would be returned, whereas, if the same is performed on the dictionary, the data stored under the reference key of 3 would be restored.

List Comprehensions – The Fastest Way To Create Lists

List comprehensions are one of the fastest ways in which a user could create lists using Python. It saves time by banishing the use of multiple lines. They are apparently easy to understand and simple to use when programming.

For a better understanding, we would break up the program to snippets and go through each part.

>>> a = [i for i in range(5)]

>>>a

[0, 1, 2, 3, 4]

The program will create a list as is understood from the code and allocate it to the variable “a”. Whereas, the program given below make use of the if statement and the modulus operator. It is done to remove all the even numbers for only the odd numbers to be included in the list. Here modulus calculator does the function of calculating the remainder from an integer division.

>>>odds = [i for i in range(25) if i%2==1]

>>>odds

[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23]

The next program is created to form a list with every fifth value as in 0, 5, 10, and so on. At this point, it is to be noted that an existing list can be put to use in the creation of new lists.

>>>fifths = [i for i in range(25) if i%5==0]

>>>fifths

[0, 5, 10, 15, 20]

Now, let us look at this program.

>>> a = [i for i in range(25) if (i in odds and i not in fifths)]

This same program could have been done using a single step and that too right from scratch which is given below.

>>> a = [i for i in range(25) if (i%2==1 and i%5==0)]

Being a programmer or developer, the user needs to understand the importance of time and should adapt to the latest methodologies that save time. Because, time is indeed of the essence.

Functions

Functions and class is yet another important feature of Python, and it is a must that every developer knows about it. Firstly, let us talk about functions. Functions, as mentioned earlier, begins with the term “def” which is the abbreviation for define. Functions are generally inserted into the program using the below format.

def name(inputparameter1, inputparameter2, . . .):

#function body

When an input is allotted a value in the function, the value will only be put to use if no other value is passed in. This, in turn, means that the order of the input parameters isn’t of concern at all. Once the function is retrieved, the positional parameters are entered in the equivalent order. Again, the order of parameter doesn’t matter when keywords are used in the functions.

defstring_appender(head=’begin’, tail=’end’, end_message=’EOL’):

result = head + tail + end_message

return result

>>>string_appender(‘newbegin’, end_message = ‘StringOver’)

newbeginendStringOver

If you would take a look at the program given above, then you would come to know that here, the output function call is printed. The input of “newbegin” was used in place of the default value “begin” for the head. Nonetheless, the default value for the tail – “end” was used correctly. When writing programs, it should be kept in mind that no value is given for tail and thus, the end_message must be defined as a keyword.

Classes

Classes begin with the term “class”. To see how class work in Python, let us take a look at its structure.

class Pattern:

“””

Information on a specific pattern in the SpongeRoll Problem

“””

cost = 1

trimValue = 0.04

totalRollLength = 20

lenOpts = [5, 7, 9]

def __init__(self,name,lengths = None):

self.name = name

self.lengthsdict = dict(zip(self.lenOpts,lengths))

def __str__(self):

return self.name

def trim(self):

returnPattern.totalRollLength – sum([int(i)*self.lengthsdict[i] for i in self.lengthsdict])

The class would be as follows.

>>>Pattern.cost # The class attributes can be accessed without making an instance of the class

1

>>> a = Pattern(“PatternA”,[1,0,1])

>>>a.cost # a is now an instance of the Pattern class and is associated with Pattern class variables

1

>>> print a # This calls the Pattern.__str__() function “PatternA”

>>>a.trim() # This calls the Pattern.trim() function. Note that no input is required.

The class name used in the program is Pattern, and several variables come under the class. The variables are appropriate to any instance of the pattern class. And the functions used are

__init__

It is the function that creates an instance of the pattern class. It also allocates the attributes of lengths and name.

__str__

This function is solely responsible for deciding what to return if the class instance gets printed.

Trim

This function looks normal like any other function, if not for the class functions that it works. The function must be put in the input brackets.

 

Disadvantages of Python

 

Speed:

Speed is something that every developer or programmer would want on his device. After all, no person this world would love to sit and wait every time for their device to perform a particular task. If you are a developer looking for something that could save your time, then Python is not the programming language for you.

As a matter of fact, Python is way too slow. In fact, it is slower than C and C++. However, everything in this world comes with both a positive and negative side. Python is a high-level language, unlike C and C+. Thus, it is evident that Python may work slower than expected.

Mobile Development:

More than half of the world depends on their mobile phone to get most of the information that they want every day. While travelling or having a day off, most people won’t usually bother opening their PC to search for the smallest information or maybe to check their social media accounts.

Due to this reason, most of the developers are trying to come up with programs that would work the same on both PC and mobile devices. However, unlike the other programming languages, Python is not a great language for mobile development. Mobile computing through Python tends to be weaker, and this is the reason why a very few developers take up the challenge of programming mobile applications using Python.

Memory Consumption:

Now with all the tasks up to your sleeves, the last thing that you would want to see happening would be your memory running out of space.  And once your system runs out of space, it takes a tedious amount of work to bring it back to normal.

You would already know that Python is flexible with data types if you have worked with it before. However, due to this reason, Python consumes a whole lot of memory. Thus, Python won’t be a better option when working in memory intensive tasks.

Database Access:

Python’s database layer was recently found to be a bit underdeveloped and unrefined when compared to other popular technologies such as JDBC and ODBC. Thus enterprises looking out for smooth interaction and complex legacy data ought to stay away from the Python because it has limitations with the database access. Nonetheless, you could still use Python if you have got sufficient skills to pull off any task.

Runtime Errors:

Python, as mentioned earlier, is easy to learn and program. The language is similar to the English language, and thus every novice can find their way through it with ease. However, Python programmers recently came up with several issues related to the design of the language. The reason that they gave for the mishap was that the language was dynamically typed.

These issues don’t show up while creating the applications. The errors show up only at the runtime. The developers demanded that the language should be tested more thoroughly to eliminate the mistakes because they aren’t ready to give up on Python.

FAQ

What is known as a docstring in Python?

Docstring in Python stand as an abbreviation of documentation strings. Docstring or documentation strings provide an amble way to link documentation with Python modules, classes, functions, and methods. Docstring was initially introduced to remove the unpleasant feeling that the use of comments gives when documenting a function using comments. Docstring being a multi-line string isn’t connected to anything and thus doesn’t require the need of comments to make the screen appear cluttered and clumsy.

The conventional source code comments usually describe how the function performs a particular task. Whereas, docstring does the opposite and describe what a function does rather than how it does.

In most of the prominent cases, one-line docstrings are put to use. An example of using a docstring is given below.

def sum(x, y):

“””Returns arg1 value add to arg2 value.”””

returna+b

printsum.__doc__

Output:

Returns arg1 value add to arg2 value.

It is better to give more information about a function when writing larger and more complex projects.

What is the purpose of pass statement in Python?

As the name suggests, the pass statement does not act in particular. Instead, it serves as a placeholder when a statement is necessary, but no action is to be performed. When the Python interpreter comes across the pass statement, it continues executing the same way as it was doing before. However, if the pass statement isn’t added in the test_method one of the given program, then a pop-up box would show Indentation Error.

classtest_class(object):

def test_method_1(self):

pass

deftest_method_2(self):

print “calling…me…”

In short, the pass statement does nothing but pass the statement to the next one. But on the other hand, the Python interpreter reads it, and if accidentally placed in if statements or functions, the pass statement is considered as a statement too.

How to achieve web scraping with Python?

Before proceeding with the question, it is important to mention what web scraping is. Web scraping is nothing but software that performs the technique of deriving information from different websites. The process is mainly focused on transforming unstructured data on the web to structures data. To achieve this transformation with Python, Python provides you with several options.

Beautiful Shop

The first method includes using the Python library for extracting data out of the HTML and XML files. Beautiful ship lets you squeeze out specific information from the webpage by removing HTML markup. On the upper hand, it even saves the information that is extracted. Professional developers can even scrape information from web pages in the form of paragraphs, lists, and tables.

A long side Beautiful Shop, Urllib 2 is another library that could be used to achieve the same tasks. Urllib even offers the feature of adding extra filters when in need of extracting particulate information from the web pages.

Mechanize

Unlike Beauty Shop, Mechanize is a Python module that is used to navigate through web forms. It acts like any standard browser but to scrape information.

Scrapemark

Scrapemark is super easy to use when extracting information from a web page as it utilises an HTML-like markup language. The results though are retrieved as Python lists and dictionaries.

Scrapy

What makes Scrapy attractive is it is a free and open source web scraping framework. It features all the tools necessary for extracting data from web pages, processing them, and storing them as per your requirement.

How does ternary operator work in Python?

Ternary operators are most commonly referred to as conditional expressions. They analyse something based on a given condition being true or false. Furthermore, the tests are done using a single line rather than the multiline if-else.

The syntax is given below.

[true] if [expression] else [false]

The result given would read “True” if the condition is satisfied, or else it reads “False”. Ternary operators are the quickest way to test a condition while using multiline statements would put hours of hard work to waste. It makes the code appear compact and maintainable.

x=20

y=10

res = “x greater” if x>y else “y greater”

print(res)

What is the purpose of self in Python?

class Student:

def __init__(self, name, age):

self.name = name

self.age = age

defstudent_info(self):

print(“Name : “, self.name, ” Age : “,self.age)

The self in Python usually refers to the instance of the class. People often mistake self for a keyword as it is used as a keyword in C++. However, in Python, self is a coding convention. Mostly, the first argument of any method is termed as self. Self makes it easier to differentiate between instance attributes and local variables.

When variables are declared within a class without using the self-reference, then it means that the variables would be shared by all instances grouped under that particular class.

How to debug a program in Python?

Python comes with an inbuilt debugger which is only available as a module called PDB. It allows setting conditional breakpoints, stacking information, running through the source code etc.

importpdb

msg = “this is a test”

pdb.set_trace()

print(msg)

As in the example, pdb.set_trace ( ) should be inserted wherever you would want it o function as a breakpoint. However, spending time in debuggers can be a bit hectic; thus you can dump execution trace and analyse it a bit later.

What are literals in Python?

The easily visible method to write a value is known as literal. Literals most commonly represent the primitive forms of language and are often integers, Booleans, floating point, and character strings.

What does ‘Yield’ do in Python?

When a compiler comes across the yield keyword anywhere in a function, it makes the function no longer return through the return statement. What it does instead is return a ‘pending list’ object referred to as a generator. The generator is repeatable and includes a built-in protocol to visit each element in a particular order.

In other words, a function called yield becomes a generator and no longer remains a standard function.

defmakeSqure(n):

i = 1

while i < n:

yield i * i

i += 1

print(list(makeSqure(5)))

In short, the above-given code generates the following output.

[1, 4, 9, 16]

The example demonstrates how the yield statement debars the function’s execution and sends the value back to the caller during each repetition.

What is meant by Accessor and Mutator methods in Python?

 

classMyClass():

def __init__(self):

self.__my_attr = 3

defset_my_attr(self,val):

self.__my_attr = val

defget_my_attr(self):

return self.__my_attr

obj1 = MyClass()

print (obj1.get_my_attr())

obj1.set_my_attr(7)

print (obj1.get_my_attr())

It is always a better idea to keep the internal data within an object private. Thus we still need specific methods to allow the user to access the data in a controlled way. The method defined by the class to bring about this change can either be an Accessor or a Mutator method.

Through the accessor method, the function is made to return a copy of an internal variable or computed value. While a mutator modifies the value of the internal data variable, the most straightforward way in which a mutator functions is by adding a variable directly to a new value.

What are the different files processing modes supported by Python?

A file as mentioned here can be any amount of information or data stored in the computer storage. And Python can manipulate these files by default. A significant part of the manipulation can be done using a file object, and Python language supports two types of files, namely text file, and binary file.

As the name suggests, text file store data in the form of text readable by humans whereas, the binary file contains data stored in binary numbers which can only be read by a computer. Python comes with a built-in function called open() to open a file.

open(file_name , [access_mode],[buffer_size],[encoding])

The access mode by default is set to read-only. Alongside there are several other modes to open a file too. It includes ‘w’ which open the file for writing, and all the data from the file would be cleared from it. ‘x’ open for the exclusive creation and fail to open the file if it already exists. ‘a’ is again used to open the file for writing, and ‘b’ opens the file in binary mode.

Python is fantastic programming in itself. It does take a bit of time to master the language but compared to the other programming language, as it is ample to learn. And once you have mastered the language, there is nothing else that you would require because it is time to start weaving beautiful creations.

Advantages and Disadvantages of Python | ProBytes from ProBytes

52 Best Websites to Learn Python language ASAP!

Python without any doubt is one of the most popular programming languages that are being put to use at present. This high-level programming language is asy to use and can be learned within a short span of time.  But the question is from where?

Listed here are 52 websites that can help you in learning Python language within a short span of time.

  • Code Academy

Code academy is where the newest people to coding get their start. The website revolves around interactive training. You read a bit, type your code directly into the browser, and see results instantly.

Intended for intermediate to professional Python developers, every post on the website is in the form of a tutorial that incorporates a specific focus, like using Python decorators, integrating Node.js with Python, and more.

Similar to Code Academy, Tutorials Point will teach you on how to write basic syntax, set up a Python development environment, work with operators, variables, and loops, and a lot more.

In case you love challenges and want to put a little pressure to improve your learning ability, PythonChallenge is made for you. The lessons and challenges you will partake in it are really productive to learn Python.

What’s better decision to choose the official documentation for a language?

Python.org is the official platform for the Python developers. So, you can discover plenty of materials, references, and resources on managing with the language.

You’ll begin with the “Hello World,” tutorial and progress towards high-level topics with their courses. This platform is best for beginner to intermediate level code learners. It permits you to engage in interactive tutorials.

It is properly written eBook which clearly illustrates different concepts of Python, but it’s more about programming theory as compared to its practical application. So, you won’t get any step-by-step tutorials to test out various snippets of code.

A free eBook which you can read in full that’s absolutely worth your time.

The driving idea behind the Invent with Python eBook is to gain knowledge while having fun and enjoying the learning.

The online versions can always be obtained for free, though there are alternatives to buy them for offline access.

A great channel for coding and amateur video tutorials on a diverse range of subjects.

The material is for intermediate to professional level Python developers to learn an advanced Python magic method concept.

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It’s basically an online guide; you can additionally download a PDF version for offline access.

The site is perfect for Python developers of all skill levels. You’ll get a large list of Python coding snippets and guides which you can utilize in your projects.

An online book that comprises the distinction between working with Python 3, as compared to Python 2.

  • Code School’s Try Python

The kind of hard worker that wouldn’t like to mess with dealing with an abundance of content-based instructional guides and tutorials.

Gamification is really big these days. CheckiO takes the method of programming learning and changes it into a fun learning game.

It is a famous training crew, known for their in-depth YouTube video tutorials.

Runestone Interactive gives a plenty of open-source, online reading material for novice and middle-level coding classes.

  • Python Crash Course

The course includes a range of presentation slides and documents, that are intended to serve as a teaching assistant.

  • Learning to Program Version 3

The site offers beginner tutorials centered on Python version 3 to introduce programming beginners to basic of coding.

The video tutorials are elegantly composed, easy to follow, and cover a scope of essential themes identified with Python.

Offers individual free courses that train you for specific careers like front-end web developers. You’ll learn how to build your own search engine, web crawler, and social network employing Python.

Free online courses by Rice University. It’s a 7-course sequence in separate two parts. It can be understood over the course of several weeks after registering for the course.

It commences with some simple and fundamental concepts and progress to advanced topics. The tutorials feature a native code simulator permitting you to write and use code from the browser.

It happens to be one of the most accurate and informative guides along with clarification on the natural order of the Python. But it isn’t free.

Python Tutor is a platform to learn the programming basics and get familiar with a collection of languages like Python, C++, Ruby, Java, JavaScript, etc.

  • Real Python

A premium online course with various subscription levels. You’ll gain access to over 9 hours of video, 1,300 pages of content, sample files, exercises, and course assignments after purchase.

Mostly comes in a written form with some tutorials on databases, game development etc.

When you would like some extra guidance, it is for you.You’ll be accredited individual projects to develop like building a certain kind of website demo, web app, or module.

Composed by professors at Harvey Mudd College, it explores the framework of computer science by the use of Python.

If you are familiar with the concept of informatics, PythonLearn is a resource portal you might be interested in.

A framework actually makes a developer’s work easier by executing a more modular pattern of a language with video series.

A great portal to discover information on Python topics. There’s a segment dedicated to what you ought to do after finishing the tutorial.

Free online book for novices. One can pick to download it as a PDF for free or spend in the hard copy.

A niche blog channel that gives Python snippets, scripts, and tutorials to be practiced in the business world.

This book is a collection of training notes for tips from Anand Chitipothu, a famous Python enthusiast. The book is recommended for beginners as it came along while he practiced every key point amid his Python classes.

An online podcast that emphasizes discussions and tips from devs and thought influencers who actually spend their time working with Python.

Learn by creating games like Hangman, Tic Tac Toe, and Reversi. This is the coolest Python guide ever.

The eBook essentially strives to teach newbie’s computer science basics and programming fundamentals.

It helps to set a community model that all developers would do well to follow style guides. This is a helpful resource for everyone.

Even though this isn’t a course, it has an abundance of activities for learners to practice Python skills.

A compilation of resources and articles. Everything in the collection is regarded as a “must read”.

A free downloadable list that exposes a ton of frameworks, software, and libraries you can operate with.

A free, email newsletter that consistently grips you on all the Python events and current affairs. You’ll get news about new videos, tutorials, potential projects, and much more.

Already understand how to use Python and just searching for any tips and tricks for later use? Python Tips is a solution for this.

A massive source to the language along with fundamental guides about the Python dev community.

Free Udacity course made by one of Reddit’s founders, Steve Huffman. It takes you into basic web development theories and guides you how to develop web applications.

It commences with the basics and gradually evolves to more complicated topics.

Each tutorial examines a bizarre project that you can build using the language e.g. sending selfies without servers using Python.

Tons of subjects to learn even for young kids, mostly on computer programming.

They have a series of tutorials on Python 3.4 Basics for design and game development that are unique, particularly for rookies.

An open-source higher education program governed by Harvard and MIT. Provides 107 courses on various programming languages including Python

Matt Makai composed a beneficial personal blog for Learning Python as a novice. Most significantly, it tells about the best place to begin when you have no prior programming experience and offers certain relevant resources.

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