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Key Difference Between Python and C++

Python code runs through an interpreter while C++ code is pre-compiled

Python supports Garbage Collection whereas C++ does not support Garbage Collection

Python is slower, on the other hand, C++ is faster than Python

In Python, Rapid Prototyping is possible because of the small size of the code while in C++, Rapid Prototyping not possible because of larger code size

Python is easy to learn language whereas C++ has a stiff learning curve as it has lots of predefined syntaxes and structure

What is C++?

C++ is widely used in general-purpose programming languages. The language allows you to encapsulates high and low-level language features. So, it is seen as an intermediate-level language. It also used to develop complex systems where the hardware level coding requires.

What is Python?

Python is a high-level object-oriented programming language. It has built-in data structures, combined with dynamic binding and typing, which makes it an ideal choice for rapid application development. Python also offers support for modules and packages, which allows system modularity and code reuse.

It is one of the fastest programming languages as it requires very few lines of code. Its emphasis is on readability and simplicity, which make it a great choice for beginners.

Stack Overflow Questions c++ VS. Python

Why Python?

Here, are reasons for using Python language:

Very simple syntax compared to Java, C, and C++ languages.

It is used for Machine Learning, Deep Learning, and the general overarching AI field.

Very useful in data analysis and visualization.

Extensive library and handy tools for developers/programmer

Python is cross-compatible

Python has its auto-installed shell

Compared with the code of other languages, python code is easy to write and debug. Therefore, its source code is relatively easy to maintain.

Python is a portable language so that it can run on a wide variety of Operating systems and platforms.

Python comes with many prebuilt libraries, which makes your development task easy.

Python helps you to make complex programming simpler. As it internally deals with memory addresses, garbage collection.

Python provides an interactive shell that helps you to test the things before it’s actual implementation.

Python offers database interfaces to all major commercial DBMS systems.

Supports imperative and functional programming

Python is famous for its use in IoT.

Why C++?

Here, are reasons for using C++

C++ is multi-paradigm means it follows three paradigms Generic, Imperative, and Object-Oriented.

C++ provides performance and memory efficiency.

It provides high-level abstraction.

C++ is compatible with C.

The language allows the reusability of code.

Features of C++

Here, are important features of C++

The program should be simple, object-oriented and easy to understand

Development should be conducted in a robust and secure environment.

Code should follow the specific architecture and must be portable.

Code should be easily “interpreted and dynamic “

Features of Python

Here, are important features of Python

Easy to learn, read, and maintain

It can run on various hardware platforms using the same interface.

You can include low-level modules to the Python interpreter.

Python offers an ideal structure and support for large programs.

Python offers support for automatic garbage collection.

It supports an interactive mode of testing and debugging.

It offers high-level dynamic data types and also supports dynamic type checking.

Python language can be integrated with Java, C, and C++ programming code

Applications of C++

Here, are important applications of C++:

C++ is used to develop all kinds of embedded systems like smartwatches, multimedia systems in automobiles, lot devices, etc.

C++ also allows you to develop the servers and the high-performance microcontroller programs

Game development is the key to C++. That’s why C++ is becoming more popular among game developers.

Applications of Python

Here, are some important Applications of Python

Python is widely used in machine learning

The language allows you to manage a huge amount of data with an easy and cost-effective way.

Data analysts use Python to analyze the data and statistical information.

It is also useful in big data technologies. In fact, most of the significant data functions can be performed using python programming.

Web developers use python language for developing the complex web application; that’s because Python offers the Django framework, which helps you to create the entire sites using Python.

Python vs. C++: Differences Between Python and C++

Here, are the major difference between Python and C++

Python C++

Supports Garbage Collection Does not support Garbage Collection

Python programs are easier to write Not easy in contrast to Python because of its complex syntax.

Run through interpreter C++ is pre-compiled

Rapid Prototyping is possible because of the small size of the code Rapid Prototyping not possible because of larger code size

Python is difficult to be installed on a windows box Not have an issue while installing in the windows system.

Python is nearer to plain English language. Therefore, it is easy to learn language. C++ has a stiff learning curve as it has lots of predefined syntaxes and structure

Python is slower. C++ is faster than Python

Python has more English like syntax, so readability is very high. C++ code readability is weak when compared with Python code.

In Python, variables are accessible outside the loop. The scope of the C++ variables is limited within the loops.

Famous companies using Python are Google, Lyft, Twitch, Telegram. Famous companies using C++ are Uber technologies, Netflix, Spotify, Instagram.

TIOBE rating is 3 TIOBE rating is 4

The average salary for a Python Developer is $120,359 per year in the United States of America. The average salary for a C++ Developer is $108,809 per year in the United States.

Here, are cons/drawbacks of using C++ language

It offers no security for your code

Complex language to use in a very large high-level program.

It is used for platform-specific applications commonly.

When C++ used for web applications it is complex and difficult to debug.

C++ can’t support garbage collection.

C++ is not as portable as other high-level programming languages. So, when you want to compile the C++ code, you need to run it on another machine.

If the same operation has to be executed more than one time, the same sequence has to copy at some places, which increases code redundancy.

Here, are cons/drawbacks of using Python language

Used in fewer platforms.

Weak in mobile computing, hence not used in app development

As Python is dynamic, so it shows more errors at run-time

Under-developed and primitive database access layer

Absence of commercial support

Google Trends C++ vs. Python

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Difference Between C++ And Java

What is the C++ language?

C++ is a computer programming language that contains the feature of C programming language as well as Simula67 (first object Oriented language). C++ introduced the concept of Class and Objects.

It encapsulates high and low-level language features. So, it is seen as an intermediate level language. Earlier it was called “C with classes” as it had all the properties of the C language.

What is the Java language?

Java is programming language developed by Sun Microsystems. A small software development team developed this language. They were known as the Green Team, who initiated Java language in the year 1991.

History of C++

C++ language was developed by Bjarne Stroustrup at AT & T Bell Laboratories. Stroustrup was a strong supporter of C and an admirer of Simula67. He wanted to combine the best of both the languages. He was aiming to create a language which supports object-oriented programming features and still retains the power of C. This resulted in C++.

History of Java

Later, in 2009, Oracle Corporation acquired Sun Microsystems and took ownership of two key Sun software assets: Java and Solaris.


C++ uses only compiler, whereas Java uses compiler and interpreter both.

C++ supports both operator overloading & method overloading whereas Java only supports method overloading.

C++ supports manual object management with the help of new and delete keywords whereas Java has built-in automatic garbage collection.

C++ supports structures whereas Java doesn’t supports structures.

C++ supports unions while Java doesn’t support unions.

C++ Vs Java

C++ Vs. Java

Parameter C++ Java

Relationship No strict relationship between class names and filenames. In C++, header files and implementation files are used for specific class. The strict relationship is enforced, e.g., the source code for class PayRoll has to be in

Input mechanism I/O statements use in and cout, e.g., in » x; cout« y;

Compiler and Interpreter C++ only support compiler Java supports both compiler and interpreter

Compatibility with other languages Compatible with C source code, except some exceptional cases. No backward compatibility with any previous language. The syntax is influenced by C/C++.

Access control and object protection Flexible model with constant protection available The cumbersome model encourages weak encapsulation.

Concept Write once compile anywhere Write once run anywhere everywhere

Support for programming type Allows both procedural programming and object-oriented programming. Support object-oriented programming model.

Interface Allows direct calls to native system libraries. Only call through the Java Native Interface and recently Java Native Access

Memory management Accessible to programmer System controlled

Root hierarchy C++ there is no such root hierarchy. C++ supports both procedural and object-oriented programming; therefore, it is called a hybrid language. Java is a pure object-oriented programming language. That’s. Why It follows single root hierarchy.

Best features C++ supports Object-oriented features Procedural programming features. Java support automatic garbage collection. It does not support destructors as C++ does.

Goto Statement C++ has a goto statement. Although, it is not ideal to a use a goto statement. Java has no goto statement. The keywords got, and const are reserved even if they are not used.

Multiple inheritance C++ provide multipleInheritance. The keyword virtual is used to resolveproblems during multipleinheritance if there is any. Java doesn’t provide multiple inheritance.

Scope resolution operator C++ has scope resolution operator (: 🙂 which is used to define a method outside of a class and to access a global variable within from the scope where a local variable also exists with the same name. No scope resolution operator (: 🙂 in Java. The method definitions have to occur within a class, so there is no need for scope resolution.

Supporting method C++ supports both method overloading & operator overloading Java only supports method overloading. It does not provide support for operator overloading.

Portability The source must be recompiled for the platform; hence the code is not portable. Bytecode classes are transferrable to platform-specific JVM’s.

Type semantics Consistent between primitive and object types. Differ for primitive and object types.

Libraries Predominantly low-level functionality Massive, classes for high-level services.

Runtime error detection Programmer responsibility. System Responsibility.

Functions & Data Functions and data may exist external to any class, global and namespace scopes are available. All function and data exist within classes; package scope are available.

Platform C++ programs are platform dependent. They need to be compiled for a particular platform. Java programs are platform independent. Java programs are written for Java Virtual Machine (JVM). It will run without needing recompilation.

Runtime error detection In C++, It is Programmer responsibility to check the errors. It is system responsibility to check error in the program.

Pointer C++ support pointers. Java offers only limited support for pointers.

Structure It supports structures. It does not any support for structures.

Unions C++ supports unions. Java does not support unions.

Object management C++ supports manual object management with the help of new and delete keywords. Java is heavy depend on automatic garbage collection. It does not support destructors.

C++ Vs Python: Which Programming Language Will Takeover Tiobe Index In 2023?

C++ vs Python: C++ is now aiming for Python’s first place on the Tiobe index in 2023

C++ vs Python are two different languages that have different features and different behavior. Both these languages have one thing in common i.e., strong support for object-oriented programming. This article features the difference between two world-famous programming languages, C++ and Python, and also we will discuss which programming language will take over Tiobe Index in 2023.

C++ vs Python: Which Programming Language Will Take over Tiobe Index?

First, let us dive into the efficiencies and effectiveness of Python. It is a high-level language and one of the top programming languages that are taught and used by institutes around the world. Developers can build robust applications with the help of Python due to its English-like syntax. There are several quantum professionals without any prior exposure to coding or programming, hence, using Python programming might ease up their doubts and guide them toward executing complex problems quite quickly. The primary characteristic of Python that makes it so desirable among developers and coders is its accessibility. Python is absolutely free to use and anybody can use and download the source code, modify it, and conduct programming and coding capabilities, without any prior training.

C++ on the other hand is a high-level, general-purpose programming language created by Bjarne Stroustrup in 1979 as an extension of the C programming language, or “C with Classes”. The concept of object-oriented programming was first introduced in the C++ language. C++ is also known as an object-oriented programming language. It was designed for system programming and embedded systems, but later on, it was used in developing various applications such as desktop applications, video games, servers such as e-commerce, Web search or SQL servers, and performance-critical applications such as telephone switches. Many of the technologies as libraries in Python have underlying C++ code.

C++ is faster than a python programming language. Python is written in the C programming language, so memory management is very difficult in python. In C++, we can allocate the memory to the variables and can deallocate the memory when the variable is no longer used in the code.

According to the Tiobe programming languages index, C++ has already overtaken Java in popularity and is now aiming for Python as it is in first place on the Tiobe index. Java is currently ranked fourth in the TIOBE index after C++ overtook Java for the first time.

The Tiobe programming language index indicates that Python is in the first position. According to Paul Jansen, CEO of Tiobe Software, a Dutch company that performs software quality testing, this is the first time C++ has surpassed Java in the Tiobe index and it’s the first time since 2001 that Java hasn’t been in the top three.

What is the Tiobe index?

The Netherlands-based TIOBE Software BV, which is based in Eindhoven, devised and maintains the TIOBE programming community index as a metric for programming language popularity. The index is determined by counting how many times the name of the language appears in search engine results. The index includes Wikipedia, YouTube, MSN, Yahoo!, Baidu, Google Blogs, and Google. Once every month, the index is updated. The long-term statistical data is for sale, while the current information is available for free. The index creators claim that it might be helpful while deciding on various strategic options. TIOBE does not offer data on, for example, the popularity of HTML because it concentrates on Turing complete languages.

C++ vs Python: Which one is better to learn?

It ideally depends on the programmer as to what he/she wants to learn. Secondly, it also depends on the current requirements. Suppose you want to learn system programming or any such low-level programming, C++ is your ideal choice.

But if you want some machine learning knowledge and put it to practice, then you should go for Python. Alternatively, if you want to make yourself comfortable in web programming, then you could opt for Ruby or JavaScript or angular JS, etc.

Sas Vs R: What Is Difference Between R And Sas?

What is SAS?

SAS stands for Statistical Analysis Software which is used for Data Analytics. It helps you to use qualitative techniques and processes which allows you to enhance employee productivity and business profits. SAS is pronounced as SaaS.

What is mean by R?

R is a programming language is widely used by data scientists and major corporations like Google, Airbnb, Facebook etc. for data analysis.

R language offers a wide range of functions for every data manipulation, statistical model, or chart which is needed by the data analyst. R offers inbuilt mechanisms for organizing data, running calculations on the given information and creating graphical representations of that data sets.

Google Trend SAS vs R


SAS is commercial software, so it needs a financial investment, whereas R is open source software, So, anyone can use it.

SAS is the easiest tool to learn. So, people with limited knowledge of SQL can learn it easily; on the other hand, R programmers need to write tedious and lengthy codes.

SAS is relatively less frequently updated, whereas R is an open-source tool, continuously updated.

SAS has good graphical support, whereas the Graphical support of the R tool is poor.

SAS provides dedicated customer support, whereas R has the biggest online communities but no customer service support.

Why use SAS?

Access raw data files and data in an external database

Analyze data using statics, descriptive, multivariate techniques, forecasting, modeling, and linear programming

Advanced analytics feature allows you to make changes and improvements in business practices.

Helps businesses to know about their historical data

Why use R?

R offers a useful programming constructs for data analytics like conditionals, loops, input and output facilities, user-defined recursive functions, etc.

R has a rich and expanding ecosystem and plenty of documentation available over the internet.

You can run this tool on a variety of platforms including Windows, Unix, and MacOS.

Good graphics capabilities Supported by an extensive user network.

R Vs Sas Stackoverflow Questions

History of SAS

SAS was developed by Jim Goodnight and John Shall in 1970 at N.C. University

Initially, it was developed for Agricultural Research.

Later, it expanded to a gamut of tools to include Predictive Analytics, Data Management, BI, among others.

Today 98 of the world’s top companies in fortune 400 uses SAS data analytical tool for Data analysis.

History of R

1993- R is a programming language developed by Ross Ihaka and Robert Gentleman

1995: R first distributed as an open-source tool under GPL2 license

1997: R core group and CRAN founded

1999: The R website, chúng tôi launched

2000: R 1.0.0 released

2004: R 2.0.0 released

2009: First edition of the R Journal

2013: R 3.0.0 released

2024: New R logo adopted

SAS Vs. R: Key Differences

Differences between SAS and R

Parameters SAS R

Availability / Cost SAS is commercial software, so it needs a financial investment. R is open source software, So, anyone can use it.

Ease of Learning SAS is the easiest tool to learn. So, people with limited knowledge of SQL can learn it easily. R programmers need to write tedious and lengthy codes.

Statistical Abilities SAS offers a powerful package which offers all types of statistical analysis and techniques. R is an open source tool which allows users to submit their own packages/libraries. The latest technologies are often released in R first.

File Sharing You can’t share SAS generated files with another user who does not use SAS. Since anyone uses r, it is much easier to share files with another user.

Updates SAS relatively less frequently updated. R is an open source tool, so it is continuously updated.

Market Share Currently, SAS is facing stiff competition from R, and other Data analytical tool as a result market share of SAS is gradually declining. R has seen exponential growth in the last past five years with its increasing popularity. That is why its market share is increasing rapidly.

Graphical Capabilities SAS has good graphical support. However, it does not offer any customization. Graphical support of R tool is poor.

Customer Support SAS provides dedicated customer support. R has the biggest online communities but no customer service support.

Support for Deep learning Deep Learning in SAS is still in its early stages, and there’s a lot to work for before it matures.

Job Scenario SAS analytic tool is still the market leader as far as corporate jobs are concerned. Many big companies still work on SAS. Jobs on R have been reported to increase over the last few years.

Salary Range The average salary for any SAS programmer is $81,560 per year in the U.S.A. The average salary for an “R” programmer” ranges from approximately $127,937 per year for Data scientists to $147,189 per year.

Best features



Nested rules



Data analysis

Graphics and data Flexible statistical analysis

Highly interactive

Famous companies using Airbnb, StacShare, Asana, Hubspot Instacart, Adroll, Opbandit, Custora

TIOBE Rating 22 16

Feature of R

R helps you to connect to many databases and data types

A large number of algorithms and packages for statistics flexible

Offers effective data handling and storage facility

Collect and analyze social media data

Train machines to make predictions

Scrape data from websites

A comprehensive and integrated collection of intermediate tools for data analysis

Interface with other languages and scripting capabilities

Flexible, extensible, and comprehensive for productivity

Ideal platform for data visualization

Features of SAS

Operations Research and Project Management

Report formation with standard graphics

Data updating and modification

Powerful Data handling language

Read and write almost any data format

Best data cleansing functions

Allows you to Interact with multiple host systems

The Final Verdict: R vs SAS

After comparing some main differences between both these tools, we can say that both have their own set of users. There are many companies, who prefer SAS because of data security issues, which show despite a drop in a recent year, there is still a huge demand for SAS certified professionals.

On the other hand, R is an ideal tool for those professionals who want to do deep cost-effective Data analytics jobs. The numbers of startup companies are increasing all over the world. Therefore, the demand for R-certified developers is also increasing. Currently, both have equal potential for growth in the market, and both are equally popular tools.

Topological Sort: Python, C++ Algorithm Example

What is Topological Sort Algorithm?

Topological Sorting is also known as Kahn’s algorithm and is a popular Sorting Algorithm. Using a directed graph as input, Topological Sort sorts the nodes so that each appears before the one it points to.

This algorithm is applied on a DAG (Directed Acyclic Graph) so that each node appears in the ordered array before all other nodes are pointed to it. This algorithm follows some rules repeatedly until the sort is completed.

To simplify, look at the following example:

Directed Graph

Here, we can see that “A” has no indegree. It means the edge that points to a node. “B” and “C” have a pre-requisite of “A”, then “E” has a pre-requisite of “D” and “F” nodes. Some of the nodes are dependent on other nodes.

Here’s another representation of the above Graph:

Dependency of each node (Linear Ordering)

So, when we pass the DAG (Directed Acyclic Graph) to the topological sort, it will give us an array with linear ordering, where the first element has no dependency.

This example shows a graph with a cycle:

Here’re the steps to do this:

Step 1) Find the node with zero incoming edges, a node with zero degrees.

Step 2) Store that zeroes in-degree node in a Queue or Stack and removes the node from the Graph.

Step 3) Then delete the outgoing edge from that node.

This will decrement the in-degree count for the next node.

Topological ordering requires that the graph data structure will not have any cycle.

A graph will be considered a DAG if it follows these requirements:

One or more nodes with an indegree value of zero.

Graph doesn’t contain any cycle

As long as there’re nodes in the Graph and the Graph is still DAG, we will run the above three steps. Otherwise, the algorithm will fall into the cyclic dependency, and Kahn’s Algorithm won’t be able to find a node with zero in-degree.

How Topological Sort Works

Here, we will use “Kahn’s Algorithm” for the topological sort. Let’s say we have the following Graph:

Here’re the steps for Kahn’s Algorithm:

Step 1) Calculate the indegree or incoming edge of all nodes in the Graph.


Indegree means the directed edges pointing to the node.

Outdegree means the directed edges that come from a node.

Here’s the indegree and outdegree of the above Graph:

Step 2) Find the node with zero indegrees or zero incoming edges.

The node with zero indegree means no edges are coming toward that node. Node “A” has zero indegrees, meaning there’s no edge pointing to node “A”.

So, we will do the following actions:

Remove this node and its outdegree edges (outgoing edges)

Place the node in the Queue for ordering.

Update the in-degree count of the neighbor node of “A.”

Step 3) We need to find a node with an indegree value of zero. In this example, “B” and “C” have zero indegree.

Here, we can take either of these two. Let’s take “B” and delete it from the Graph.

Then update the indegree values of other nodes.

After performing these operations, our Graph and Queue will look like the following:

Step 4) Node “C” has no incoming edge. So, we will remove node “C” from the Graph and push it into the Queue.

We can also delete the edge that is outgoing from “C”.

Now, our Graph will look like this:

Step 5) We can see that nodes “D” and “F” have the indegree of zero. We will take a node and put it in the Queue.

Let’s take out “D” first. Then the indegree count for node “E” will be 1. Now, there’ll be no node from D to E.

We need to do the same for node “F”, our result will be like the following:

Step 6) The indegree (ingoing edges) and outdegree (outgoing edges) of node “E” became zero. So, we have met all the pre-requisite for node “E”.

Here, we l put “E” at the end of the Queue. So, we don’t have any nodes left, so the algorithm ends here.

Pseudo Code for Topological Sorting

Here’s the pseudo-code for the topological sort while using Kahn’s Algorithm.

function TopologicalSort( Graph G ): for each node in G: calculate the indegree start = Node with 0 indegree G.remove(start) topological_list = [start] While node with O indegree present: topological_list.append(node) G.remove(node) Update Indegree of present nodes Return topological_list

Topological sort can also be implemented using the DFS (Depth First Search) method. However, that approach is the recursive method. Kahn’s algorithm is more efficient than the DFS approach.

C++ Implementation of Topological Sorting

using namespace std; class graph{ int vertices; public: graph(int vertices){ } void createEdge(int u, int v){ adjecentList[u].push_back(v); } void TopologicalSort(){

for(int i=0;i<vertices;i++){ for(itr=adjecentList[i].begin(); itr!=adjecentList[i].end();itr++){ indegree_count[*itr]++; } } for(int i=0; i<vertices;i++){ if(indegree_count[i]==0){ Q.push(i); } } int visited_node = 0; while(!Q.empty()){ int u = Q.front(); Q.pop(); order.push_back(u);

for(itr=adjecentList[u].begin(); itr!=adjecentList[u].end();itr++){ if(–indegree_count[*itr]==0){ Q.push(*itr); } } visited_node++; } if(visited_node!=vertices){ cout<<“There’s a cycle present in the Graph.nGiven graph is not DAG”<<endl; return; } for(int i=0; i<order.size();i++){ cout<<order[i]<<“t”; } } }; int main(){ graph G(6); G.createEdge(0,1); G.createEdge(0,2); G.createEdge(1,3); G.createEdge(1,5); G.createEdge(2,3); G.createEdge(2,5); G.createEdge(3,4); G.createEdge(5,4); G.TopologicalSort(); }

Output: 0 1 2 3 5 4 Python Implementation of Topological Sorting from collections import defaultdict class graph: def __init__(self, vertices): self.adjacencyList = defaultdict(list) self.Vertices = vertices # No. of vertices # function to add an edge to adjacencyList def createEdge(self, u, v): self.adjacencyList[u].append(v) # The function to do Topological Sort. def topologicalSort(self): total_indegree = [0]*(self.Vertices) for i in self.adjacencyList: for j in self.adjacencyList[i]: total_indegree[j] += 1 queue = [] for i in range(self.Vertices): if total_indegree[i] == 0: queue.append(i) visited_node = 0 order = [] while queue: u = queue.pop(0) order.append(u) for i in self.adjacencyList[u]: total_indegree[i] -= 1 if total_indegree[i] == 0: queue.append(i) visited_node += 1 if visited_node != self.Vertices: print("There's a cycle present in the Graph.nGiven graph is not DAG") else: print(order) G = graph(6) G.createEdge(0,1) G.createEdge(0,2) G.createEdge(1,3) G.createEdge(1,5) G.createEdge(2,3) G.createEdge(2,5) G.createEdge(3,4) G.createEdge(5,4) G.topologicalSort() Output: [0, 1, 2, 3, 5, 4] Cyclic Graphs of Topological Sort Algorithm

A graph containing a cycle can’t be topologically ordered. As the cyclic Graph has the dependency in a cyclic manner.

For example, check this Graph:

This Graph is not DAG (Directed Acyclic Graph) because A, B, and C create a cycle. If you notice, there’s no node with zero in-degree value.

According to Kahn’s Algorithm, if we analyze the above Graph:

Find a node with zero indegrees (no incoming edges).

However, in the above Graph, there’s no node with zero in degrees. Every node has an in-degree value greater than 0.

Return an empty queue, as it could not find any node with zero in degrees.

We can detect cycles using the topological ordering with the following steps:

Step 1) Perform topological Sorting.

Step 2) Calculate the total number of elements in the topologically sorted list.

Step 3) If the number of elements equals the total number of vertex, then there’s no cycle.

Step 4) If it’s not equal to the number of vertices, then there’s at least one cycle in the given graph data structure.

Complexity Analysis of Topological Sort

There are two types of complexity in algorithms. They’re

Time Complexity

Space Complexity

These complexities are represented with a function that provides a general complexity.

Time Complexity: All time complexity is the same for Topological Sorting. There are worst, average, and best-case scenarios for time complexity.

The time complexity for topological Sorting is O(E + V), here, E means the number of Edges in the Graph, and V means the number of vertices in the Graph.

Let’s break through this complexity:

Step 1) At the beginning, we will calculate all the indegrees. To do that, we need to go through all the edges, and initially, we will assign all V vertex indegrees to zero. So, the incremental steps we complete will be O(V+E).

Step 2) We will find the node with zero indegree value. We need to search from the V number of the vertex. So, the steps completed will be O(V).

Step 3) For each node with zero indegrees, we will remove that node and decrement the indegree. Performing this operation for all the nodes will take O(E).

Step 4) Finally, we will check if there is any cycle or not. We will check whether the total number of elements in the sorted array is equal to the total number of nodes. It will take O(1).

So, these were the individual time complexity for each step of the topological Sorting or topological ordering. We can say that the time complexity from the above calculation will be O( V + E ); here, O means the complexity function.

Space Complexity: We needed O(V) spaces for running the topological sorting algorithm.

Here are the steps where we needed the space for the program:

We had to calculate all the indegrees of nodes present in the Graph. As the Graph has a total of V nodes, we need to create an array of size V. So, the space required was O(V).

A Queue data structure was used to store the node with zero indegree. We removed the nodes with zero indegree from the original Graph and placed them in the Queue. For this, the required space was O(V).

The array is named “order.” That stored the nodes in topological order. That also required O(V) spaces.

These were the individual space complexity. So, we need to maximize these spaces in the run time.

Space complexity stands for O(V), where V means the number of the vertex in the Graph.

Application of Topological Sort

There’s a huge use for Topological Sorting. Here are some of them:

It is used when Operating system needs to perform the resource allocation.

Finding a cycle in the Graph. We can validate if the Graph is DAG or not with topological sort.

Sentence ordering in the auto-completion apps.

It is use for detecting deadlocks.

Different type of Scheduling or course scheduling uses the topological sort.

Resolving dependencies. For example, if you try to install a package, that package might also need other packages. Topological ordering finds out all the necessary packages to install the current package.

Linux uses the topological sort in the “apt” to check the dependency of the packages.

Difference Between Acetone And Non

Acetone and non-acetone are two common solvents used for various applications, including cleaning, painting, and cosmetics. While they share some similarities, they also have several differences that make them suitable for different purposes. In this essay, we will explore the difference between acetone vs. non-acetone in terms of their properties, uses, and safety.

What is Acetone?

Acetone is a clear, colorless, and highly flammable liquid that has a strong odor. It is a type of organic solvent that can dissolve many substances, including plastic, rubber, and paint. Acetone is also highly volatile, meaning it evaporates quickly, leaving no residue behind. Due to its properties, acetone is widely used in industrial processes, including manufacturing, cleaning, and degreasing.

Formation − In industry, the acetone can be made by a process known as the cumene hydroperoxide method. Acetone is also made in the human body as a byproduct of the breakdown of fats and conversion to ketone bodies. It is formed in large amounts in people who have uncontrolled diabetes with ketoacidosis.

Uses of Acetone − Acetone is a substance that is often used in the cosmetics industry to remove nail polish and it is used to also strip paint. Acetone is used as a solvent to remove lacquers and inks, and it is often used to make artificial fibers. It has also been shown to inhibit the growth of bacteria such as Aerobacter aerogenes, and so can be used as a bacteriostatic agent.

Safety − Acetone is relatively safe to use provided that sufficient and adequate precautions are taken when using it and it is used in very small amounts. This is because the vapors that are given off can be very irritating to both the eyes and various mucus membranes. If spilled on the skin it can cause some irritation and dermatitis. It is also important to remember that it is a flammable substance so care should be taken not to use it near an ignition source.

What is Non-Acetone?

Non-acetone is the name most commonly used to refer to the chemical ethyl acetate which has the formula C4H8O2 and is used as an alternative instead of acetone in nail polish remover.

Properties − The molecular weight of ethyl-acetate is 88.106g/mol, and it is a clear liquid that has no color. It does also have a distinctive sweet smell to it that has been described as being like that of a pineapple and it is a flammable substance. Ethyl acetate is a type of molecule that is known as an ester, and it is also a flammable liquid.

Formation − Ethyl acetate can be manufactured commercially by a method that is called the Tischenko condensation reaction. It can also be made by the esterification of acetic acid and ethanol and is formed by several different microbes including the yeast Saccharomyces cerevisiae and the bacterium Staphylococcus.

Uses − There are many uses for ethyl acetate including use as nail polish remover. It is also used by entomologists to kill insects for pinning purposes since it keeps the insect body reasonably pliable and easy to manipulate. It is also used in the alcoholic beverage industry but can spoil wine if the concentrations of the ethyl acetate are too high. This substance is also used to remove the caffeine from tea and coffee. Non-acetone (ethyl acetate) is a useful solvent that is also found in many adhesive products.

Safety − Ethyl acetate can be dangerous if people are not careful and are exposed to large amounts. The substance can cause irritation to the eye and can result in actual eye damage. It can cause irritation to the breathing passages and can cause a headache. This is also a very flammable liquid that should not be exposed to any type of ignition source.

Differences: Acetone vs. Non-acetone

One of the main differences between acetone and non-acetone is their effectiveness in dissolving certain substances. Acetone is a more potent solvent than non-acetone and can dissolve a wider range of substances, including plastic and rubber. However, this property also makes acetone unsuitable for use on some materials, such as painted surfaces, as it can strip the paint. Non-acetone, on the other hand, is less aggressive and can be used on more delicate surfaces without causing damage.

Another difference between acetone and non-acetone is their evaporation rate. Acetone evaporates much faster than non-acetone, which means it dries more quickly. This property makes acetone ideal for use in applications where a quick-drying solvent is required, such as in manufacturing or cleaning. Non-acetone, on the other hand, evaporates more slowly, which means it stays wetter for longer. This property makes it more suitable for use in applications where a longer working time is required, such as in nail polish remover or cosmetic products.

In terms of safety, both acetone and non-acetone have some risks associated with their use. Acetone is highly flammable and can ignite easily, so it should be handled with care and kept away from heat sources. Acetone can also be harmful if ingested or inhaled, and prolonged exposure can cause skin irritation or dermatitis. Non-acetone is generally considered safer than acetone, as it is less flammable and less aggressive. However, it can still be harmful if ingested or inhaled, and prolonged exposure can cause skin irritation or dryness.





Acetone is the substance that is also known as dimethyl ketone that has the molecular formula of CH3COCH3 or C3H6O.

Non-acetone is the substance that is also known as ethyl acetate that has the molecular formula C4H8O.

Molecular weight

The molecular weight of acetone is 58.07 g/mol.

The molecular weight of non-acetone is 88.106g/mol.

Type of molecule

Acetone is a molecule known as a ketone.

Non-acetone is a molecule known as an ester.

Formation in industry

The cumene hydroperoxide process is used to form acetone in industry.

The Tischenko condensation process is used to form non-acetone (ethyl acetate) in industry.

Formation in nature

Acetone is formed in the human body during times when fats are broken down to produce ketone bodies.

Ethyl acetate (non-acetone) is produced by microbes such as yeasts and certain bacteria.


The odor of acetone is usually described as fruity.

The odor of non-acetone is described as sweet.


Acetone can be used as a nail polish remover, to remove inks, paints, and lacquers; to manufacture fibers and for use as a bacteriostatic agent.

Non-acetone can be used as a nail polish remover, in alcoholic beverages, adhesives, for the decaffeination of tea and coffee, and to kill insects for pinning.


In conclusion, acetone and non-acetone are two types of organic solvents that have different properties, uses, and safety considerations.

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