Planning and Defining Your Python Project Scope

Planning and defining your software development project scope is essential for ensuring the success of the development endeavor. By establishing clear objectives, deliverables, and constraints upfront, you can effectively map out the direction of your project and minimize potential risks along the way. Whether you are embarking on a new software application or enhancing an existing system, having a well-defined project scope in Python sets the foundation for efficient collaboration among team members and stakeholders throughout the development lifecycle.

To support this, hire Python developers to bring the necessary expertise and efficiency to your project, ensuring all objectives are achieved with quality and within the desired timelines.

Setting Clear Project Goals

This is very trite advice, but it has always helped me before starting development, especially for MVP projects.

TaskDescription
Define purposeClearly state why you are undertaking this Python project.
Identify audienceUnderstand who will benefit from or interact with your project.
Address problem/needArticulate the main issue that your Python project intends to solve.
Set objectivesCreate quantifiable goals that will guide and evaluate your project’s success.
Establish timelineBreak down tasks into achievable stages with deadlines to stay on track throughout the development.

It is not for nothing that they say that the most important thing is not the idea but the team that will implement it.

Identifying Key Stakeholders

  • 1. Project Sponsor
    • Responsible for providing resources and funding.
  • 2. End Users
    • Those who will use the final product.
  • 3. Development Team
    • Programmers, designers, and testers are involved in project execution.
  • 4. Business Analysts
    • Gather requirements from stakeholders and translate them for the development team.

Identifying key stakeholders is crucial to ensure that all parties involved are considered throughout the project lifecycle. Each stakeholder brings a unique perspective and set of requirements to the table, which can significantly impact the success of your Python project scope.

As a CTO, I’ve seen firsthand the impact of clear project planning and the strategic hiring of Python developers. These steps are crucial for ensuring project success, leveraging Python’s capabilities to the fullest, and efficiently turning concepts into high-quality software solutions.

Roman Osipenko, CTO of Django Stars

Planning Project Requirements in Python

The uniqueness of planning programs in Python lies in several key features that make it a preferred language for developers across various domains. Here are some of the highlights:

  1. Simplicity and Readability: Python’s syntax is designed to be intuitive and close to the English language, which makes it easier for beginners to understand and implement their ideas. The emphasis on readability means that Python code is less cluttered and more maintainable than many other programming languages.
  2. Versatility: Python is incredibly versatile, allowing developers to work on a wide range of projects, from web applications to data analysis, machine learning, artificial intelligence, scientific computing, and more. This versatility is supported by a rich collection of libraries and frameworks that extend Python’s functionality.
  3. Interpretive Nature: Being an interpreted language, Python executes code line by line. This feature provides the flexibility of testing individual blocks of code without needing to compile the entire program, facilitating a more efficient debugging process.
  4. Dynamic Typing: Python is dynamically typed, which means that the type of a variable is determined at runtime rather than in advance. This adds to the flexibility of the language, although it requires developers to be mindful of type errors.
  5. Strong Community Support: Python has a large and active community, which contributes to a vast ecosystem of libraries, frameworks, and tools. Whether you’re working on data science projects using Pandas and NumPy, developing web applications with Django or Flask, or exploring machine learning with TensorFlow or PyTorch, the Python community offers extensive resources and support.
  6. Integration Capabilities: Python can be easily integrated with other programming languages and technologies, allowing for a seamless blend of performance and productivity. It can interact with databases, perform network operations, and even integrate with languages like C and C++ for computationally intensive tasks.
  7. Portable and Extendable: Python programs are portable, meaning that a program written on one machine can run on any other machine without requiring any changes (provided Python is installed). Additionally, Python allows for the extension of its capabilities by including libraries written in other languages, enhancing its performance and efficiency.
  8. Open Source: Python is an open-source language, which means it is freely available for use and distribution, including for commercial purposes. This encourages innovation and collaboration among developers worldwide.

Establishing Milestones for Progress Tracking

  • Define Clear Milestones: Break down the project into key phases.
  • Set Achievable Goals: Ensure each milestone is realistic and attainable.
  • Assign Responsibility: Clearly assign tasks to team members for each milestone.
  • Track Progress Regularly: Monitor and update progress towards milestones frequently.
  1. Start by outlining the major milestones that need to be achieved.
  2. Break down each milestone into smaller tasks with specific deadlines.
  3. Assign roles, responsibilities, and deadlines clearly to team members.
  4. Regularly review progress against set milestones to ensure on-track delivery.

Remember, establishing clear milestones is crucial for tracking progress effectively throughout your Python project development.

Managing Scope Creep and Change Requests

  • Set Clear Project Goals
    • Define project scope clearly to avoid misunderstandings.
  • Establish a Change Control Process
    • Create a documented process for evaluating and approving changes.
  • Regular Communication
    • Keep stakeholders informed of any potential changes or impacts on the project.
  • Prioritize Changes
    • Evaluate change requests based on their impact and urgency.
TaskResponsible PartyDeadline
Review Change RequestProject ManagerWithin 2 days
Assess ImpactDevelopment TeamWithin 1 week
  1. Monitor Progress Continuously
    • Regularly assess whether the project is aligning with the defined scope.
  2. Document Everything
    • Keep detailed records of all discussions, decisions, and approved changes.
  3. Avoid Gold Plating
    • Refrain from adding unnecessary features beyond the agreed-upon scope.

Conclusion

Defining the scope of your Python project is crucial for its success. By planning meticulously and setting clear objectives from the outset, you can ensure that your project stays on track and delivers the desired results. Remember to regularly review and adjust the scope as needed to accommodate any changes or new requirements that may arise during development. With a well-defined project scope, you set yourself up for a more efficient development process and ultimately increase the likelihood of achieving your goals within the specified time frame.

TIOBE Index for January 2024: Top 10 Popular Programming Languages

The Global TIOBE Index is a widely cited indicator of the popularity of programming languages. It’s based on the number of skilled engineers, courses, and third-party vendors worldwide. Search engines, including Google, Bing, Yahoo!, Wikipedia, Amazon, YouTube, and Baidu, are used to calculate the ratings. The index aims to measure the popularity of languages in terms of the number of lines of code written, the number of projects utilizing them, and general web activity related to the languages.

website – tiobe.com

A few things to note about the TIOBE Language Index:

  1. Not a Measure of the Best Coding Language: The index doesn’t aim to say which language is objectively the best or most suitable for a given task.
  2. Not a Measure of Code Quality or Performance: It doesn’t measure the efficiency or quality of code written in different languages.
  3. Based on Web Searches: Since it’s based on search engine results, it can give a general sense of the languages that developers are currently interested in or having discussions about.

The TIOBE Index is updated monthly, and it’s often used by developers, businesses, and educational institutions to gauge which languages are currently in demand. It can be a useful tool for professionals looking to upskill or transition to a new development area.

Why do I trust these indicators? Firstly, it is a thorough scientific approach that does not give a chance for manipulation, and secondly, this index fit with actual trends in programming.

Top 10 programming languages in January 2024

Scratch broke into the top ten, which is an expected result after its steady growth over the past year. Fortran is getting closer to the top 10 as it has many supporters in universities.

  1. Python
  2. C
  3. C++
  4. Java
  5. C#
  6. JavaScript
  7. PHP
  8. Visual Basic
  9. SQL
  10. Scratch âŹ†ïž

Top 10 programming languages in December 2023

C# is poised to be the programming language of the year for 2023, showing a promising increase of +2.38% in popularity over the past year.

  1. Python
  2. C
  3. C++
  4. Java
  5. C#
  6. JavaScript
  7. PHP
  8. Visual Basic
  9. SQL
  10. Assembly language

Top 10 programming languages in November 2023

The changes are minor: Visual Basic continues to fall, so PHP has moved up one place, Kotlin’s popularity continues to rise, moving up from 18th to 15th place on the TIOBE index with a current rating of 1.15%. Given its modern features and growing adoption, Kotlin has the potential to enter the top 10 rankings.

  1. Python
  2. C
  3. C++
  4. Java
  5. C#
  6. JavaScript
  7. PHP
  8. Visual Basic
  9. SQL
  10. Assembly language

Top 10 programming languages in October 2023

The gap between C# and Java is currently at its smallest. If trends continue, C# will overtake Java in two months. Java’s decreasing popularity is due to Oracle’s paid licensing after Java 8 and competition from Kotlin. Meanwhile, Microsoft made C# free and open source, boosting its adoption.

  1. Python
  2. C
  3. C++
  4. Java
  5. C#
  6. JavaScript
  7. Visual Basic
  8. PHP
  9. SQL
  10. Assembly language

Top 10 programming languages in September 2023

We note that PHP has moved down 1 step.

  1. Python
  2. C
  3. C++
  4. Java
  5. C#
  6. JavaScript
  7. Visual Basic
  8. SQL
  9. PHP
  10. Assembly language

Top 10 programming languages in August 2023

The stalwarts, Python, C, and C++, continued their dominance from July to August. However, the month witnessed Julia’s debut at #20, a commendable feat for this budding language.

  1. Python
  2. C
  3. C++
  4. Java
  5. C#
  6. JavaScript
  7. Visual Basic
  8. PHP
  9. SQL
  10. Assembly language




  1. Julia

Top 10 programming languages in July 2023

Jansen noted the rise of C++ to the third position in the TIOBE index a few months prior, displacing Java.

  1. Python
  2. C
  3. C++
  4. Java
  5. C#
  6. JavaScript
  7. Visual Basic
  8. SQL
  9. PHP
  10. MATLAB

Top 10 programming languages in June 2023

The AI surge’s influence on the TIOBE index was evident by June. Jansen speculated on Python’s longevity, especially with tools like ChatGPT, predominantly written in Python, gaining traction.

  1. Python
  2. C
  3. C++
  4. Java
  5. C#
  6. Visual Basic
  7. JavaScript
  8. PHP
  9. SQL
  10. Assembly language

Top 10 programming languages in May 2023

The TIOBE index’s top 10 saw minimal fluctuations, with leading languages retaining their ranks.

  1. Python
  2. C
  3. Java
  4. C++
  5. C#
  6. Visual Basic
  7. JavaScript
  8. PHP
  9. SQL
  10. Assembly language

Top 10 programming languages in April 2023

Python persisted as the front-runner in April’s TIOBE list. Remarkably, Zig, originating from Google and devised as a C and C++ alternative, broke into the top 50, showcasing its prowess in big data projects.

  1. Python
  2. C
  3. Java
  4. C++
  5. C#
  6. Visual Basic
  7. JavaScript
  8. SQL
  9. PHP
  10. Go

Best 10 programming languages in March 2023

Python clinched the top spot in March’s TIOBE index. The emergence of Go, backed by Google, stirred the rankings as it clinched the tenth place.

  1. Python
  2. C
  3. Java
  4. C++
  5. C#
  6. Visual Basic
  7. JavaScript
  8. SQL
  9. PHP
  10. Go

Top 10 coding languages in February 2023

February’s champions were Python and C. C++ clinched the third spot, recording an impressive 5.93% YoY growth, significantly overshadowing the average 1% YoY growth of its peers.

  1. Python
  2. C
  3. C++
  4. Java
  5. C#
  6. Visual Basic
  7. JavaScript
  8. SQL
  9. Assembly language
  10. PHP

Top 10 programming languages in January 2023

TIOBE crowned C++ as the most popular language of 2022. Jansen attributed C++’s surge to its stellar performance, robustness in managing extensive software systems, and its advanced object-oriented capabilities.

  1. Python
  2. C
  3. C++
  4. Java
  5. C#
  6. Visual Basic
  7. JavaScript
  8. SQL
  9. Assembly language
  10. PHP

Python for App Development

Ready to take your app development skills to the next level? Look no further than Python! Python is the perfect programming language to add advanced features and create cutting-edge apps that will keep users coming back for more. Get ready to explore the world of app development with python – the possibilities are endless!

Introduction to Python App Development

Python is one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. Python App development has become increasingly popular due to its flexibility, scalability and performance. Many of the world’s leading tech companies such as Google, Facebook, YouTube are using Python for their core infrastructure.

First appeared: 20 February 1991

In this introduction to Python for App Development we will look at the essentials of programming with Python with a focus on creating App development projects. We will also explore how setting up your development environment with an appropriate version of python can make coding simpler and more enjoyable. The topics covered include setting up your workspace for development in an OS(Windows or Mac OSX) then install the python interpreter, downloading any necessary IDE(Integrated Development Environment).

We will discuss common design patterns and learn software engineering concepts behind building apps using python such as Object Oriented Programming Principles (OOP), SOLID Principles(Single Responsibility Principle (SRP), Open Closed Principle (OCP), Liskov Substitution Principle (LSP), Interface Segregation Principle (ISP) , Dependency Inversion Principle (DIP)), Data Structures & Algorithms relevant to app development , functions & loops , classes & modules , file handling etc. We will also look at how to use specific packages suited for app creation including Numpy for scientific computing in Python; Flask/ Django web frameworks for server-side programming; TKinter/ Kivy/ Pygame packages in UI design . It is expected that by the end of this tutorial you’ll be able to develop an application from scratch independently.

Benefits of Using Python for App Development


Using Python for app development has numerous advantages and provides many ways to make development time easier, faster and more efficient. Python is an ideal language for mobile app development since it enables developers to quickly and easily make apps within a shorter period of time.

Python is considered a versatile language due to its expansive library of built-in modules, making it easy to find solutions for complicated tasks related to mobile app development. Additionally, Python also helps reduce bugs in code due to its simple syntax that prevents developers from writing complex code unnecessarily.

Python further offers an extensive network of experienced type-checking tools. This makes it possible for developers during the coding process to check the syntax even before running scripts or programs, allowing them plenty of time before deployment to investigate potential issues with their code.

Another benefit of utilizing Python is that developers can make use of wide range of components that have already been written in different languages and integrate them into their codebase easily. This allows them to stumble upon existing solutions and utilize them instead of reinventing the wheel. The readability factor involved in using Python makes debugging an easier process compared other programming languages out there.

Overall, using Python for app development offers various benefits stemming from readability, flexibility and easy integration with various components that can help accelerate the application build overall process significantly for any internet or mobile project..

Challenges of Using Python


When developing apps, there are a number of challenges that arise when using Python. First, Python is an interpreted language and the code must be compiled before it can be run on a device such as smart phone or tablet. Compiling code for multiple operating systems requires different steps. This can be difficult for some developers, who may not have the necessary experience in using makefiles and other compilers to create cross-platform applications.

Another challenge with Python is its lack of support for native libraries. In mobile development, much of the functionality needs to be accessed through native libraries, which can require complex setup and custom coding. A further issue is that Python does not have many frameworks available compared to other languages. This means you’re more likely to need custom solutions when creating your app, which takes more time and resources than if you were working with a more supported language such as Objective-C or Java. Additionally, debugging capabilities are more limited with Python than they are with other languages due to its interpretive nature – finding anomalies in an app written in Python can be more difficult because the errors aren’t highlighted until runtime.

Popular Frameworks for Python App Development


Python is a versatile programming language with numerous applications, particularly in mobile and web app development. It is highly recognized for its easy-to-read, maintainable code and excellent scalability. Python is the preferred language of choice when developing a wide range of apps:

  • social media activities,
  • data analysis,
  • artificial intelligence (AI),
  • Internet of Things (IoT).

    Developers have the option to use popular frameworks when developing apps in Python. Popular frameworks include Flask, Django, Pyramid and Web2py.

    Flask – this minimalist framework offers more flexibility due to its lack of default project structure or database abstraction layers; instead it focuses on providing a simple API structure allowing developers to build quick prototypes or complex web services.

    Django – this full-stack framework delivers an out-of-the-box solution ideal for building projects with the active support from its community due to its great documentation and user forums. It features object-relational mapping (ORM) which makes database manipulations extremely easy and fast for developers with no coding neededl compared to SQL code writing.

    Pyramid – this framework provides a solid foundation allowing developers to customize their applications allowing them to start small while continuing through rapid prototyping successfully. Additionally it allows scaling down as easily as scaling up during this process.

    Web2py – similarily to Django this full stack open source web purpose development framework offers both novice and professional developers alike the possibility of leveraging everything that comes courtesy with prebuilt components as well as features like AJAX form processing and simple drag & drop design elements without needing any configuration or complicated setup process.
  • Along with TensorFlow, PyTorch (developed by Facebook’s AI research group) is one of the most used tools for building deep learning models. It can be used for a variety of tasks such as computer vision, natural language processing, and generative models.

Tools and Libraries for Python App Development


When developing applications using the Python programming language, developers have a wide array of access to powerful tools and libraries that are available to create their applications. There are both general-purpose and domain-specific tools and libraries, ensuring that each application can build on the top of existing codebase as needed.

Popular Python toolkits for app development include TensorFlow, which is used for deep learning, Keras for machine learning applications, SciPy for scientific computing, Scikit-Learn for data mining and analysis, and Twisted for network programming. Additionally, many web frameworks exist to enable developers to quickly build web apps in Python— such as Django, Web2py and Flask.

For desktop GUI development purposes, there are a variety of options such as wxPython and PyQt that can be used to quickly create graphical user interfaces (GUIs) in an efficient manner. Data visualization tools like matplotlib, Seaborn and ggplot aid developers in communicating results clearly via charts and graphs.

Python also applies across different types of databases like MongoDB or Cassandra which allow developers to optimize databases access with Object Relational Mapping (ORM) libraries like SQLAlchemy or PonyORM. And specialized libraries exist that make storage into NoSQL databases faster and easier as well as making it possible to interact with web services such APIs or connect with other sysadmin tasks like remote execution via SSH or HTTP requests.

With so many choices available in the way of tools and libraries when it comes to Python app development the possibilities are truly endless!

Python App Development Tips and Best Practices


Python app development has become increasingly popular in recent years, mainly due to its widespread use in the software engineering world. It is praised for its simplicity and flexibility, but if you are new to coding with Python, you may find it difficult to get around. In this guide, we will provide some tips and best practices for effective Python app development that must be taken into consideration.

Firstly, when creating a project from scratch it is important to make sure that you have chosen the best data structure for your application; different projects require different data structures. The most common data structures used when writing applications in Python are dictionaries, lists and tuples; however, there are other types such as sets and classes which can also be beneficial for some tasks. Furthermore, the correct algorithms should be selected when coding in order to achieve maximum efficiency.

Another important factor is clarity of code; no matter how user-friendly your program may be without clarity of code maintained throughout your program’s structure, understanding and making changes afterward will become difficult as the complexity of your code increases. To promote readability of code it is necessary to format it regularly using space bars or functional comments accordingly so that everyone involved in development can easily understand what each line does even after months of working on a given project.

Finally tests should be conducted during development on all sizes of projects or programs to ensure correct functionality throughout – debugging should never stop! Once fully tested each iteration can then act as seen stable when delivered into a production system – just remember not to test an entire application at once unless necessary due multiple components being interconnected regardless of back-end implementation (e.g databases) functionality might change leading too total instability with the entire system at hand so use testing methods like unit-tests where applicable instead!

Security Considerations for Python App Development


The process of developing apps using Python comes with certain security concerns that must be addressed to ensure a successful outcome. Many app developers don’t take proper security precautions and end up with apps that are vulnerable to attack, compromising the user’s personal data and intellectual property. To mitigate these risks, it is essential to consider the following security considerations when developing any type of app in Python.

First, careful consideration must be given to authentication protocols employed in the app. This ensures that only authorized users can access sensitive data and confidential information stored within your application. Password protection techniques such as two-factor authentication and biometrics should also be used where possible to provide an additional layer of security for user accounts.

Second, developers should consider their input sanitation methods when designing an app to minimize potential threats from malicious users attempting to inject code into the application via forms or URL parameters. All input must be properly sanitized before processing by the application in order to ensure that only valid requests are being allowed through for further processing.

Third, when deploying an application on a server it is important to use secure credentials for both backend programming languages like Python as well as web server accounts such as those accessed through SSH keys. All passwords used in an application should also be encrypted before being transmitted across the network in order to minimize any potential loss due to hacking attempts or interception by malicious third parties while still preserving data integrity and security during transmission over the wire.

Finally, developers must think beyond just coding considerations when creating a secure application environment; they must also pay attention to physical security measures protecting their servers against unauthorized access or destruction/theft of hardware containing sensitive information or data structures associated with the project being developed in Python.

Conclusion


Python is an essential language for app development. It enables developers to create both mobile and web applications. Python can also be used to build machine learning and artificial intelligence models, which makes it an ideal language for those looking to develop complex applications. It is a highly versatile language that comfortable all levels of programming expertise. Experienced developers will find it easy to use, while beginners will appreciate the level of support Python offers in terms of libraries, frameworks, and tools. Additionally, the hard work of the open-source community means that new advancements are constantly being made available for those interested in coding with Python. All things considered, it’s a good option for anyone looking to start out with app development or take their projects to the next level.

The Role of Python in Machine Learning: Algorithms, Libraries, and Use Cases

Python, as a programming language, has revolutionized the world of information technology (IT) as we know it for the last three decades. It has helped evolve different Internet-related industries, including the vast online gambling scene on several planes. For instance, Python is a bedrock of developing a good chunk of the incredible games you’ll find on leading iGaming platforms such as ICE Casino. But that’s just the tip of the iceberg of Python’s ground-breaking applications.

The infusion of Python programming in Machine Learning (ML) has fortified IT and data science. More ML professionals are now turning to this popular programming language for web development, segmentation, software application design, and process automation. It’s no wonder developers merge its syntax with Artificial Intelligence (AI), Machine and Deep Learning projects.

So, what aspects make Python the perfect language for Machine Learning? And what role does this programming language play in the whole technology? Spare a few minutes of your time and get all your questions answered in today’s comprehensive guide.

Why Python for Machine Learning?

The following aspects and algorithms make Python the right choice for the implementation in the present-day projects:

Simplicity and Consistency 

This high-level coding language can simplify the complex predictive technologies that comprise Machine learning and AI algorithms. The programming language boasts clear code and vast ML-specific libraries. It’s also consistent, intuitive, and easy to learn. That’s why the language ranks third among the most popular technologies.

Vast Frameworks and Libraries

ML and AI algorithm implementation is a complex process that takes time. You’ll need a well-tested, structured environment to deliver the best coding solutions. Fortunately, various libraries like SciPy or NumPy and frameworks like PyTorch can solve everyday tasks and save time. Its extensive library set caters to both ML and AI projects.

Platform Independence

Python-based software solutions can run on various OS platforms. Therefore, you can expect greater convenience with Python ML.

Great Community

Due to the widely spread character of the coding language, it has a vast community of enthusiasts. Therefore, you can access almost every information you need regarding ML development. Moreover, you’ll always access answers and support whenever you publish a question on the community platform.

Extensive Numerical Computation Support

Python’s ML and NLP libraries offer built-in mathematical functions, data structures, and learning algorithms. All these simplify numerical computation and make it effective.

Top Machine Learning Libraries in Python

A library is a collection of vital strategies targeting a specific goal. For instance, a Python sentiment analysis library comprises all the necessary resources to enable quality digital text analyzing. This is just one; Python offers a whole word of them. Here are 9 Machine Learning libraries together with their use cases:

Scikit-Learn

Scikit-Learn (or Sklearn) is a popular free Python ML library. The open-source tool is popular among beginners in the coding realm. Its features comprise ready-made models and datasets such as Iris to facilitate a swift start. Additionally, experienced professionals like its robust support for advanced components like cross-validation and preprocessing. Choose Scikit-Learn if you want to segment your clients depending on their buying behaviors. 

TensorFlow

This free library is the brainchild of the Google Brain team. It gained significant popularity following its release in 2015 as a framework for devising deep learning models. It primarily assists users in developing artificial intelligence and deep learning applications. Notably, this library requires in-depth comprehension of deep learning. This is the right solution to create tailored content and customer recommendations on e-commerce platforms. 

Keras

Google designed this open-source Python library, and it is popular for its tight integration with TensorFlow and its neat neural network library. Keras offers a user-friendly and modular design, and Google also developed this library to allow users to experiment, prototype, and produce ML apps. Choose Keras if you optimize specific objectives in reinforcement learning agents, including robotic control or game playing.

PyTorch

This framework follows the Torch library, a scientific computing and ML structure written in Lua. Facebook’s AI research lab created it to aid language processing and image recognition applications. The right candidate for PyTorch is anyone working on object detection and image classification. 

Pandas

Data analysis and manipulation are the core of this library, popular among beginners and seasoned experts. The framework offers valuable data structures and functions that facilitate data handling, making it easier to prep your resources for model training, testing, and data analysis. Pandas can transform and clean raw data and prepare it for model training if you’re looking toward data preprocessing.  

NumPy

This numerical computing library is vital for ML and data science projects. It boasts vast math functions and objects to aid data analysis and scientific computing and can work seamlessly alongside other libraries. Better still, this library runs in the background of libraries like Pandas, providing efficient and fast arrays for data handling and processing.

Matplotlib

Matplotlib serves as Python’s plotting library, and thus, you can use it to generate informative data analysis visualizations, model outputs, and other applications. In addition, the library can work alongside NumPy to create visualization arrays. Matplotlib also comes in handy with ML projects by displaying feature-important scores. As a result, this can help you identify the influential features of a model’s prediction.

Seaborn

This is the library to choose for data visualization. It follows the Matplotlib structure and can help you create complex, compelling visualizations that are statistically inclined and aesthetically pleasing. They can achieve this with less code and work seamlessly with Pandas. Moreover, you can apply Seaborn in exploratory data analysis to understand your data before you use ML algorithms.

It’s Time to Include Python in Your Next ML Project!

Python programming language is increasingly aiding the natural language processing and ML efforts of modern programmers. Most users laud its simplicity, vibrant community, and extensive library support. So, if you’re planning on an ML project, you can never go wrong if you start with the libraries covered in this piece. Consider your data size, complexity, and project requirements for the best results.

How to Hire Python Software Developers in 5-7 days

If you’re looking to hire Python developers quickly, here are five tips to help you find them in just five days. I will definitely add my experience to the methods I have personally tested.

  1. Use online job boards.

There are a number of online job boards that cater specifically to python developers, such as Python.org and Django Jobs. Posting your job on one of these boards is a great way to reach a large number of qualified candidates in a short amount of time.

  1. Use social media.

Social networks like Linkedin. Or ask for help on Facebook.

  1. Send a request to tech recruiters like TurnKey Staffing.
  2. Ask outsourcing agencies:

  • Lemon.io
  • Six Feet Up, Inc.
  • SoftKraft
  • Apriorit
  • Yalantis
  • Lambert Labs
  • Apptension
  • Cuttlesoft
  • AnyforSoft
  • Steelkiwi
  • Django Stars
  • 10Clouds
  • Netguru
  • Cheesecake Labs
  • S-PRO
  • Sloboda Studio
  • hedgehog lab
  • DICEUS

And read some info here:

Introduction

Python is a general-purpose, high-level programming language that is easy to read and understand. It is used by developers to build a wide range of applications, and supports structured, procedural, and object-oriented programming paradigms. If you’re looking for experienced Python developers to hire, you can find many talented professionals who are proficient in this language.

my intro video where to find quick developers

What is Python?

Python is a popular programming language that is widely used in many different industries today. Python is known for its ease of use and readability, making it a great language for beginners to learn.

Why hire Python Developers?

Python is a versatile scripting language that helps in automating tasks, data analysis, AI & ML applications.

The beneïŹts of using Python are many and some of the key reasons to hire Python Developers are as follows:

  • Python is very user-friendly and easy to learn for beginners as compared to other languages.
  • It has a large standard library that covers a wide range of programming modules.
  • It is an open-source language with an active community where developers can easily find answers to their queries.
  • It supports multiple programming paradigms such as structured, procedural, and objectoriented. This makes it a popular choice for developi

How to hire Python Developers?

Python is a high-level, interpreted, general-purpose programming language, created on December 3, 1989, by Guido van Rossum, with a design philosophy entitled, “There’s only one way to do it, and that’s why it works.”

In the Python language, that means explicit is better than implicit. It also gives rise to the infamous Python telegraph pole analogy attributed to creator Guido van Rossum, which goes like this:

There is beauty in π, elegance in an all-numeric telephone keypad... I am attracted to the simpleness of a perfect poker face, and the serenity of perfect punctuation mark placement. Just as art to be appreciated and music to be enjoyed, comments in a program should be readable for their own sake.

Hiring software developers from Latin America can be a benefit for companies that wish to expand their workforce in the region.

The 5-day Plan

Whether you’re starting a new project or scaling up an existing one, you might need to hire additional developers. This can be a daunting task, especially if you’re looking for specific skillset – like Python development.

In this blog post, we’ll give you a 5-day plan to help you hire the best Python developers for your team.

Day 1: Define the role

The first step is to clearly define the role that you’re looking to fill. What kind of Python development do you need? Do you need a full-stack developer or someone who specializes in data science?

Once you have a clear understanding of the role, you can start writing the job description. Include key responsibilities, qualifications, and technologies that the ideal candidate should have.

Day 2: Decide where to post

There are many different places where you can post your job ad. The most important thing is to make sure that you’re reaching your target audience. If you’re looking for experienced Python developers, posting on Stack Overflow might be a good option. For more entry-level candidates, colleges and universities might be a better bet.

To get the most out of your job ad, make sure to include a link to your company website and an email address where interested candidates can contact you.

Day 3: Screen resumes

Once you start receiving applications, it’s time to start screening resumes. This is usually the most time-consuming part of the hiring process but there are ways to speed it up. For example, using an applicant tracking system (ATS) can help you organize and keep track of all the resumes that you receive.
It can also automatically screen candidates based on criteria that you set – like minimum years of experience or specific skillset.

Day 4: Conduct initial interviews

After screening resumes, it’s time to start conducting initial interviews with candidates who look promising. These interviews are usually short (30-60 minutes) and they’re meant to help you get a better sense of each candidate’s skills and experience.

To make sure that everyone is on the same page, prepare questions in advance and send them to each candidate before the interview. This will give them time to prepare and it will help make the interview more efficient.

Day 5: Schedule follow-up interviews

After conducting initial interviews with all candidates, it’s time to invite your top picks for follow-up interviews. These interviews are usually more in-depth (60-90 minutes) and they give candidates an opportunity to showcase their skills by solving problems or completing coding challenges.

Keep in mind that these challenges should be relevant to the role that they’re applying for – otherwise, they won’t be able to show their best work .

Tips for a Successful Hiring

The most important step in any hiring process is taking the time to carefully consider what you need and what kind of person will be the best fit for your company. That being said, here are a few tips to help you successfully hire python developers:

  1. Define the role you are looking to fill.
  2. Write a clear and concise job description.
  3. Develop a list of must-have skills and qualities for the role.
  4. Utilize your network, social media, and online job boards.
  5. Schedule initial phone or video interviews.
  6. Conduct in-person interviews with your top candidates.
  7. Decide and extend an offer to your chosen candidate!
    Conclusion

    Python is a high-level, interpreted, general-purpose programming language, created on December 3, 1989, by Guido van Rossum, with a design philosophy entitled, “There’s only one way to do it, and that’s why it works.”

In the Python language, that means explicit is better than implicit. It also gives rise to the infamous Python telegraph pole analogy attributed to creator Guido van Rossum, which goes like this:

There is beauty in π, elegance in an all-numeric telephone keypad... I am attracted to the simpleness of a perfect poker face, and the serenity of perfect punctuation mark placement. Just as art to be appreciated, comments to be enjoyed, and data to be played with, I enjoy reading Python philosophy.

How to Create a Web Crawler in Python: A Step-by-Step Guide

Are you interested in learning how to make a web crawler in Python?

Look no further! In this article, we will guide you through the process of creating your very own web crawler using the power and simplicity of Python. Whether you’re a beginner or an experienced programmer, our step-by-step instructions and code examples will help you get started quickly. So let’s dive right in and discover how to harness the potential of Python for web crawling!

Web crawling is an essential technique used to extract data from websites automatically. With Python’s user-friendly syntax and rich library ecosystem, it has become a popular choice for building web crawlers. In this tutorial, we’ll walk you through the fundamental concepts behind web crawling and show you how to implement a basic web crawler using Python. By following along with our code examples, you’ll gain valuable insights into handling HTTP requests, parsing HTML content, navigating website structures, and storing extracted data. Whether your goal is gathering information for research purposes or automating repetitive tasks like scraping product prices or monitoring website changes, this article will equip you with the necessary skills to build your own powerful web crawler in Python.

Remember: The key to successful programming lies not just in understanding the code but also grasping core concepts behind it. Let’s embark on this exciting journey together as we demystify the process of making a web crawler using everyone’s favorite language – Python!

What is a Web Crawler?

A web crawler, also known as a spider or a bot, is an automated program that systematically explores and indexes the vast amount of information available on the internet. It navigates through websites by following links and collecting data from each page it visits.

Web crawlers are essential for search engines like Google, Bing, and Yahoo to index web pages effectively. They help search engines build their databases and provide users with relevant search results.

Here are some key points about web crawlers:

  1. Purpose: The primary purpose of a web crawler is to gather information from websites in an organized manner. This collected data includes text content, images, URLs, metadata, and more.
  2. Traversal: A crawler starts its journey from a seed URL provided by the programmer or search engine algorithm. It then follows hyperlinks found on each visited page to discover new URLs to crawl.
  3. Indexing: As the crawler visits various pages, it extracts relevant information and stores it in a database for further processing. Search engines use this indexed data to respond quickly when users make queries.
  4. Robots.txt: Websites can control access by specifying rules in robots.txt files placed in their root directories. Crawlers read these files before crawling the site to respect any restrictions set by website owners.
  5. Respectful Crawling: To avoid overwhelming servers with excessive requests and causing disruptions or penalties, responsible crawlers follow polite crawling practices such as obeying crawl delays specified in robots.txt files.
  6. Crawl Budget: Search engines allocate resources based on a website’s importance during crawling sessions; this allocation is called “crawl budget.” Popular sites receive more frequent crawls compared to less popular ones.

In summary, web crawlers play a vital role in cataloging immense amounts of online information efficiently for search engine indexing purposes.

Choosing the Right Python Libraries

When it comes to building a web crawler in Python, selecting the right libraries is crucial. These libraries provide valuable functionality and simplify the development process. Here are some essential Python libraries that can help you create an efficient web crawler:

  1. Requests: This library allows you to send HTTP requests easily, making it ideal for retrieving web pages while handling redirects and cookies.
  2. Beautiful Soup: With Beautiful Soup, parsing HTML and XML documents becomes a breeze. It provides convenient methods for navigating through document structures, extracting data, and handling malformed markup.
  3. Scrapy: If you’re looking for a powerful web scraping framework, Scrapy should be on your radar. It offers advanced features like automatic throttling, concurrent requests handling, and built-in support for XPath selectors.
  4. Selenium: Selenium enables browser automation by controlling web browsers programmatically. This library is useful when dealing with dynamically generated content or interacting with JavaScript-heavy websites.
  5. PyQuery: PyQuery is inspired by jQuery’s syntax and allows you to perform CSS-style queries on parsed HTML documents effortlessly.
  6. URLLib: The urllib module provides various functions that assist in working with URLs: fetching data from URLs using different protocols (HTTP/FTP), URL encoding/decoding utilities, etc.
  7. lxml: lxml combines speed and simplicity when it comes to processing XML and HTML files efficiently.

Remember that each library serves a specific purpose in the web crawling process; choose them wisely based on your project requirements.

Understanding HTML Parsing

HTML parsing is an essential step in building a web crawler using Python. It allows you to extract relevant information from the HTML code of a webpage. Here are some key points to understand about HTML parsing:

  1. What is HTML Parsing?
    • HTML parsing refers to the process of analyzing an HTML document and extracting meaningful data or elements from it.
    • Python provides several libraries, such as BeautifulSoup and lxml, that make it easy to parse and navigate through HTML documents.
  2. Why Do We Need HTML Parsing?
    • Webpages are structured using HTML tags, which enclose different types of content like headings, paragraphs, links, images, etc.
    • By parsing the HTML code of a webpage, we can locate specific elements or extract desired data for our web crawler’s purposes.
  3. Parsing with BeautifulSoup:
    • BeautifulSoup is a popular Python library that simplifies the task of parsing and navigating through an HTML document.pythonDownloadCopy code1# Installation: 2pip install beautifulsoup4 3 4# Importing: 5from bs4 import BeautifulSoup
  4. Navigating Through Elements:
    • Once parsed with BeautifulSoup, we can use various methods (e.g., .find(), .find_all()) to locate specific elements based on their tag names or attributes.
  5. Extracting Data:
    • After locating an element(s), we can access its content by utilizing different methods provided by BeautifulSoup (e.g., .text, .get()).
  6. Handling Nested Elements:
    • When dealing with nested elements within an element hierarchy (e.g., div inside div), we need to traverse the structure accordingly.
  7. Dealing With Errors:
    • Sometimes webpages may have malformed or inconsistent markup that may cause errors during parsing; hence handling exceptions becomes crucial.

Understanding how to parse HTML using libraries like BeautifulSoup is a fundamental skill for building effective web crawlers in Python. By extracting relevant information from the HTML code, you can collect data for further analysis or processing.

Implementing Crawling Logic

import scrapy
class spider1(scrapy.Spider):
        name = ‘Wikipedia’
        start_urls = [‘https://en.wikipedia.org/wiki/Battery_(electricity)’]       
        def parse(self, response):
           pass

To create a web crawler in Python, you need to implement the crawling logic. This involves defining the steps that your crawler will take to navigate through websites and collect data. Here’s how you can do it:

  1. Choose a starting point: Determine the initial URL from where your crawler will begin its journey. You can start with a single website or provide a list of URLs.
  2. Send HTTP requests: Use the requests library in Python to send HTTP GET requests to each URL you want to crawl. This allows you to retrieve the HTML content of web pages.
  3. Parse HTML responses: Utilize an HTML parsing library like BeautifulSoup or lxml to extract relevant information from the HTML response received for each request. Parse elements such as links, titles, images, and other data according to your requirements.
  4. Store crawled data: Decide on how you want to store the crawled data for further processing or analysis purposes. You could use databases like MySQL or MongoDB, CSV files, or any other suitable storage format.
  5. Manage visited URLs: Keep track of visited URLs using a set or database table (if needed) to avoid revisiting them during subsequent crawls.
  6. Extract new URLs: Extract all unique URLs from within each page’s content and add them to a queue for future crawling tasks.
  7. Limit crawling scope (optional): To prevent infinite crawling loops and control resource usage, consider implementing mechanisms such as maximum depth limits, domain restriction filters, or inclusion/exclusion rules based on URL patterns.
  8. Implement politeness policy (optional): To be respectful towards website owners and minimize potential impact on their servers’ performance, introduce delays between successive requests by adding sleep timers before sending out new ones.

By following these steps while coding your web crawler in Python, you’ll have an effective system for crawling websites and gathering the desired data. Remember to handle potential exceptions, timeouts, and other error scenarios gracefully to ensure robustness in your implementation.

Note: It’s important to be mindful of web scraping ethics and legal considerations while implementing a web crawler. Make sure you comply with website terms of service, respect robots.txt directives, avoid excessive requests that may cause disruptions or violate policies, and focus on collecting publicly available information responsibly.

Happy crawling!

Handling Data Extraction

When building a web crawler in Python, data extraction is a crucial step. It involves extracting relevant information from the crawled web pages. In this section, we will explore various techniques and libraries for handling data extraction efficiently.

Here are some methods you can use to extract data from web pages:

  1. Regular Expressions (Regex): Regex provides a powerful way to search and extract patterns from strings. You can define specific patterns using regex to match and capture the desired data within HTML or text content.
  2. BeautifulSoup: BeautifulSoup is a popular Python library that enables easy parsing of HTML and XML documents. It offers intuitive methods to navigate through the document structure and extract relevant data by targeting specific tags, classes, or attributes.
  3. XPath: XPath allows you to traverse XML or HTML documents using path expressions similar to file paths in operating systems. The lxml library in Python provides robust support for XPath queries, making it an efficient choice for complex data extraction tasks.
  4. Scrapy: Scrapy is a powerful framework specifically designed for web scraping purposes. It simplifies the process of extracting structured data from websites by offering built-in features like automatic request handling, spider management, and item pipelines.
  5. APIs: Some websites provide APIs (Application Programming Interfaces) that allow developers to access their data programmatically rather than scraping it directly from their website’s HTML structure.
  6. Data Cleaning Libraries: After extracting raw data, cleaning may be required before further analysis or storage into databases. Libraries such as Pandas offer functions for filtering out noise or irrelevant elements while processing large datasets efficiently.

Remember these best practices when handling data extraction:

  • Inspect page source code: Before writing your code, examine the target webpage’s source code carefully; this helps identify appropriate tags or patterns necessary for accurate extraction.
  • Handle exceptions gracefully: Ensure your code has proper error-handling mechanisms in case of unexpected data or network issues.
  • Respect website policies: Always review the website’s terms of service and robots.txt file to avoid violating any rules or scraping limitations.

By implementing these techniques and following best practices, you can effectively extract valuable data from web pages using your Python web crawler.

Conclusion

In conclusion, building a web crawler in Python can be an exciting and rewarding endeavor. By following the steps outlined in this article, you now have the knowledge and tools to create your very own web crawling application.

Throughout this guide, we covered various aspects of web scraping using Python libraries such as BeautifulSoup and requests. We learned how to send HTTP requests, extract data from HTML pages, and navigate through different elements of a website.

Remember that when developing a web crawler, it is essential to respect website policies by setting appropriate crawl delays and user-agent headers. Additionally, ensure that your crawler adheres to ethical guidelines and legal requirements.

By harnessing the power of Python’s extensive libraries for web scraping, you are equipped with the ability to gather valuable data from websites efficiently. With practice and experimentation, you can further enhance your skills in creating more advanced crawlers tailored to meet specific needs or requirements.

So go ahead and embark on your journey into the world of web crawling with Python—the possibilities are endless! Happy coding!

Dominating Web Development Trends 2023

“Figuring out what the next big trend is, tells us what we should focus on.” — Mark Zuckerberg

Web development, over the years, has proved itself as an indispensable element in the success of any organization/business. It is a window to your business, which helps you grow it globally.

Now, the Web development world is constantly changing, so do the trends. Sometimes these trends change much faster than they can be used. To stay ahead, it is necessary to focus on the latest trends, updates, techniques, and approaches that are getting popular. Besides, knowing trends and keeping in check of what is happening around is highly essential for web development.

Here we have gathered some trends after analyzing tendencies across industries in this list of web development trends this year. You’ll get to know about the top web technology stacks worth your attention in the coming year.

We have made this list so that you can save your time and can help you grow your business in the upcoming era. So, let’s begin.

1. Single-page Apps

All in one place. No need to switch. No need to wait..!!

Well, it is a bit irritating when one click leads to one more web page downloaded from a server. It also consumes your time and leaves a bad impact on users as well. This situation has lead to a trend of SPA.

SPA is one of the trends of recent years that helps to avoid lengthy communication with the server. It offers better page performance and provides a high level of data protection.

So, A single-page application is an app that works inside a browser and does not require page reloading during use. You are using this type of applications every day. These are, for example, Gmail, Google Maps, Facebook, or GitHub.

As JavaScript frameworks in 2022 is going to actively rise, & SPA uses this language for content loading, this trend isn’t going away soon. Besides, these apps don’t require additional waiting time providing the users with instant feedback. Furthermore, it offers some amazing advantages.

Advantages:

  • Great UX/UI in a native browser environment
  • Saved bandwidth
  • Easier set-up and debugging with Chrome tools
  • The focus on APIs
  • The efficiency of a caching process

Single-page app examples:

You can check Vuexy Admin Template, which is highly suitable for developing single-page apps.

It is an advanced admin template. It is highly responsive, clean, and well structured. Besides, it is laced with Vuejs, HTML, PHP, and React. Furthermore, this graphically enriched bootstrap template is highly recommended by developers over the world for its user-friendly experience and speed. In addition, it includes 100+cards, 50+ Components, and many more.

Demo Download

2. Progressive Web Apps (PWA)

Everything at your thumb
!! We know this concept right? Easy navigation, smooth working, less loading, and fast. Yes, that’s what PWA i.e Progressive Web App is about..!! Fast, Reliable, and smooth user-friendly experience.

No doubt, PWA is not that new. Although, it is the talk of the town since it arrived and it is going to dominate 2021 as well. Modern developers and investors are aiming for it because of its capability to perform a high-quality user experience. As they are highly mobile-friendly, there is no doubt demand for PWA is going to increase.

Well, Progressive Web Apps (PWA) are built and enhanced with modern APIs to deliver enhanced capabilities, reliability, and installability while reaching anyone, anywhere, on any device with a single codebase. Which makes it suitable for cross-device compatibility.

They not only are fast and load instantly, but they also allow users to use services offline, while performing all the functions of a native app.

Advantages

  • PWA helps deliver a smooth and user-friendly web experience.
  • Helps reducing bounce rates
  • Works offline as it is connectivity independent
  • Makes your app reliable, capable and installable

Some example of services using PWA :

3. Artificial Intelligence Development – Support

As per the report “The artificial intelligence market to be valued at USD 39.9 billion in 2019 and is likely to reach USD 190.61 billion by 2025, at a CAGR of 42.2% during the forecast period.” That’s a pretty huge number
!! Isn’t it??

Now, around 38% of people skip a website if the content or layout is unattractive. More than 75% of customers decide a business’s credibility based on its website design. Users take just 0.5 seconds to form an opinion about a website. Henceforth, it is essential for technology to involve in the world of web development. Here, AI comes into the picture of web development trends 2023.

  • Dall-E
  • CPT-3
  • ChatGPT

Applying AI in web development helps you predict customer choices using which you can shape the overall look and feel of your website. AI allows you to know,

  • What are your customers planning to buy next?
  • The ideal time frame during which a customer decides to buy a product.
  • What kind of products allures the most to the customers?
  • What are the products that are not appreciated by the customers?
  • Who all are interested in buying your products?

We are living in a digital era and it’s a well-known fact that the upcoming age is going to be all about a smarter approach in every field. This means less manual operating. For example, chatbots, Augmented Reality/Virtual reality.

Sketch2Code, a web-based solution, has recently been introduced. It relies on artificial intelligence in order to transform a handwritten UI design from an image to a valid HTML markup code.

Many users aren’t even surprised that AI is involved to some extent in most sites. It created a new dimension in the sphere of web development.

4. WebAssembly

The first thing that must not be neglected when developing a web application is performance. Now, JavaScript limitations make heavy calculations slow. That significantly worsen the user experience.

This is one of the main reasons for the rising popularity of WebAssembly. With this technology, the code in any programming language can be compiled into bytecode, which runs in a browser.

WebAssembly is an open standard that defines a portable binary-code format for executable programs, and a corresponding textual assembly language, as well as interfaces for facilitating interactions between such programs and their host environment.

Advantages:

  • It’s independent of programming language and platform
  • Independent of hardware
  • Executes code fast
  • Provides a high level of security.

It all comes down to the triangle — small footprint, cross-platform scripting, and speed. All three of these components are the key ones in modern web development. This is why a lion’s share of web development cases is not without WebAssembly today.

For more info check Webassembly concepts

5. Voice Search and Navigation

Hey Siri
. What’s trending today?

We, humans, are getting lazy day by day
 isn’t it..!!?? First, we made mobiles, then developed smartphones to reduce manual works, and now we are heading towards “voice-oriented hands-free” gadgets. Command-oriented services are hot topics nowadays.

Well, voice search and navigation are going to be one of the most dominant web development trends in 2021. They are already a part of our daily routine. They are super awesome as they kind of made it easy the way we search for information, take notes, and so on.

Brands like Apple, Android, and Google implement the trend in their UI/UX design process. So, this rapidly emerging trend isn’t something you can ignore
!!

Google reports that 27% of the online global population is using voice search on mobile.

Voicebot.ai reports that over half of all adults have used voice search, with 33% using voice search monthly in early 2019, jumping up from 25% in 2018.

By implementing Voice search and navigations in web development, you can make sure your service delivers an amazing user experience.

Voice user interfaces work according to the following algorithm:

  • Speech recognition software converts input analog waves into a digital format
  • The audio input is broken down into separate sounds, phonemes
  • The software analyzes each of them and compares to words from the dictionary
  • Speech is converted to on-screen text or computer commands

Advantages:

  • Ease of use
  • Allows freehand interaction
  • High speed of task execution
  • Great user experience
  • Intuitiveness and convenience

People prefer to spend less time typing commands. This is why they increasingly use voice search. Therefore, web development will be closely related to the implementation of such functionality.

6. Native Apps will dominate the market

What if you are working and suddenly there is a net issue..!! Bit irritating to depend on the internet all the time. That’s where the Native app comes into the picture. It allows you to work offline as well.

A native mobile app is one that is installed directly on the smartphone and can work, in most cases, with no internet connectivity depending on the nature of the app.

Well, native app development is already in demand as it is, going ahead, software developers can expect this trend to dominate web development trends in 2021.

Since they are uniquely designed for specific platforms, they generally deliver a better user experience and more powerful performance comparing to hybrid apps. That’s the reason, more and more businesses are investing in multiple native apps for iOS and Android to enable them to provide their users with a better experience.

Advantages:

  • Broad functionalities due to using the capabilities of the underlying devicE
  • UI that better matches with user experiences of the OS
  • Responsive and fast performance
  • Push notifications
  • Quality assurance through ratings in application stores.

With the increasing popularity of smartphones in the market and with the ever-increasing dominance of iOS and Android operating systems in the market, it doesn’t seem like an investment in native app development will dwindle anytime soon, not in 2021 or in the foreseeable future as a matter of fact.

7. 3D Motion design UI

Credit: Credit: Vuexy By Anand Patel on Dribbble

Motion design is one of the main web design and web development trends in 2021. Minimalistic design coupled with sophisticated interactions gives an engaging and interactive look that attracts the user’s attention.

As its name strongly suggests, motion design is about designing movement. However, it goes quite beyond simply animating an element of the screen after it has been conceived.

Motion design must be contemplated already in the UI/UX design stage. The reason behind this is that just having a screen that contains animations falls a bit short of its intended aim: the movement added has to mean something and have a purpose.

Due to motion design, these elements will be implemented:

All of that will help you display your unique style and entertain the user, improving behavioral factors, and helping your web app rank higher in search results.

With the help of AMP, motion design can be implemented without loss of download speed. Therefore, if you want to hold the user on your page, then do not ignore this one
!!

Advantages:

  • Define your structure and interactions
  • Eases navigation
  • Dissimulates slow load times
  • Increases session length hence reduce the bounce rate

To increase engagement and provide better UI/UX to your web app’s users, try to upgrade it with motion UI techniques.

  • Guide users through your app with animations demonstrating which step to take next;
  • React to users’ gestures with catchy animations;
  • Demonstrate the relations between different components of an app, etc.

8. Serverless Architecture

Credit: Runcloud

Serverless architecture is a way to build and run applications and services independently to manage infrastructure. Your application still runs on servers, but all the server management is done by AWS. You no longer have to provision, scale, and maintain servers to run your applications, databases, and storage systems.

So basically, Serverless applications are event-driven cloud-based systems where application development depends solely on a group of third-party services, client-side logic, and cloud-hosted remote procedure calls. (Functions as a Service).

No doubt, Serverless is reaching new heights in its path to disrupt your server infrastructure. Serverless is already used in production by companies like Netflix, Reuters, AOL, and Telenor.

as Serverless architectures help reducing system overloading, data loss, and expensive development. Consequently, one of the solutions became cloud computing, which can replace regular servers.

Advantages:

  • Easy to deploy
  • Better scalability
  • it reduces development and ongoing support budgets
  • strengthen app architecture
  • increases flexibility

The most common tasks that can be very quickly executed due to serverless technologies are downloading file backups, notification delivery, and objects export. Stated differently, serverless architecture is one more trend, which will dramatically change the approach to web development.

9. Continuous Integration and Deployment

Credit: By Stories on Freepik

We are living in the digital era where speed and continuity play a brutal role in any sector and business, the web development world is no different either. In fact, in the world of web development, it is the uppermost priority to deliver speedy, smooth, and updated services.

The frequency in Regular bug fixes, updates, improvements in UI/UX, etc makes your web service accountable and user favorite. Also, most modern applications require developing code in different platforms and tools, the team needs a mechanism to integrate and validate its changes. It affects your overall business. Thus, Continuous Integration And Deployment are crucial in the web world.?

Well, Continuous Integration is the process of testing each change done to your codebase automatically and as early as possible. Continuous Deployment follows the testing that happens during Continuous Integration and pushes changes to a staging or production system. While continuous delivery means apps get into production for thorough testing, and continuous deployment updates them automatically.

Advantages:

  • Smaller code changes are simpler (more atomic)
  • Fault isolation is simpler and quicker.
  • The product improves rapidly through fast feature introduction
  • Meantime to resolution (MTTR) is shorter due to the smaller code changes and quicker fault isolation.
  • Testability improves because of the smaller, specific changes. These smaller changes permit more accurate positive and negative tests.
  • Elapsed time to detect and correct production escapes is shorter with a faster rate of release.

With such advantages, no wonder more software development companies will implement this approach in their work. As it is the most crucial aspect in the world of web development.

10. Cloud technology is here to stay for a long time

Created by Taras Ivanytskyi on dribbble

Did you know that in 2020, the cloud services industry generated almost $40 billion in revenue, taking its market value to a total of $266.4 billion from $227.8 billion in 2019, an 17% growth in just one year?

With these figures, one thing is sure; in web development services, cloud technology is the king. In 2021, it is expected that cloud vendors like Google, Microsoft, and Amazon will continue to rake in lots of cash thanks to cloud technology.

The reason behind this hot trend is, there are several companies on the cloud, and more are expected to move there. Businesses of all sizes, from a small entrepreneurial startup or a multinational corporation, to businesses across several industries, from health care to intelligence agencies and even government organizations are all going to cloud providers for data storage.

Credit: Cloudopedia

Following are some cloud services.

Cloud technology offers great security, scalability, and flexibility when it comes to data storage, and considering the ever-present threat of hackers which could lead to a security breach, organizations will want to ensure they are taking measurable steps to safeguard their sensitive data and avoid a data breach and other activities that might compromise the privacy of data.

11. 5G Technology will be unparalleled

Credit: Rpc snate

5G is the fifth generation of cellular networks, bringing new capabilities that will create opportunities for people, businesses, and society. Even in the web development world, 5G is ruling. As there is a need for enhanced service, faster connectivity is a must thing.

In 2023, software developers can expect the 5G technology to return as a trend, but for all the right reasons this time around. With the use of new radio frequencies and speed reaching 100 Gbps, the 5G technology is about 100 times faster than 4G networks and experts in the software development industry predict that it will lead the standard data transmission with 1.4 billion devices around the world in the next five years.

Advantages:

  • Greater speed in transmissions
  • Lower latency
  • Greater number of connected devices
  • Network slicing
  • Enhanced Capacity
  • Availability and Coverage
Credit: By Kate mangostar on Freepik

5G technology is designed for compute-intensive apps like augmented reality, virtual reality, and 4K video streaming. Software developers interested in creating designs and features that enhance business performance will find this technology especially useful.

With the promise of better data transmission and a faster network, the 5G technology is no doubt a great contender for one of the best web development trends in 2021.

12. Mixed Reality (MR)

As per the report, the market of AR/VR i.e mixed reality will grow from $1.054 billion in 2017 to $9.982 billion in 2024, and it will see a CAGR of 73.2% during 2018–2023 period.

Mixed Reality (MR), is a combination of Augmented Reality (AR) and Virtual Reality (VR). It has a pivotal role in enterprise applications. AR combines digital content with users’ physical environment, whereas VR creates an immersive experience for users.

Organizations in many sectors like Web app development, defense, tourism, architecture, construction, gaming, healthcare, etc. are realizing key business value with the help of this technology.

How MR is turning the table:

  • Businesses, government organizations, and even non-profit organizations can use AR and VR to train their employees in complex jobs.
  • The ability to overlay digital information on the physical environment on a real-time basis creates many possibilities for augmented reality in business.
  • Media and entertainment businesses are using AR and VR in a significant way to offer engaging content to consumers.
  • Businesses can use AR and VR to let their prospective customers “try-out” their products virtually, and this augments their sales effort.

MR experiences on websites will keep increasing over the coming years. Think of furniture sites like IKEA that showcases what furniture would look like in your room..!!

13. Blockchain/NFT: Augmenting enterprise solutions with transparency, efficiency, and security

Bitcoins kind of turned revolutionary when it arrived
!! It sort of shook the market and opened a new gate for the web development world as well. A Cision PR Newswire report estimates that the blockchain technology market will touch $57.641 billion in 2025, by an impressive 69.4% CAGR between 2019 and 2025.

The cryptocurrencies like Bitcoin and Ether have made us notice blockchain, the technology has a wide impact on enterprise systems. Basically, blockchain is a peer-to-peer (P2P) network, and it offers decentralization, a distributed ledger, transparency, and security features.

Smart contracts running on blockchain networks are tamper-proof and transparent, therefore, they are secure and trustworthy. Besides, their execution is irreversible, which makes contract administration easier.

Blockchain Advantages:

  • Decentralization
  • Immutability
  • Security
  • Transparency.
  • Securing the Internet of Things (IoT)

Examples of a few blockchain use cases:

  • Improving supply chain management
  • Identity management: Blockchain can improve the “Identity and Access Management” (IAM) processes with its tamper-proof data and distributed ledger.
  • Better analytics: Blockchain offers immutability and audit trail, thus assuring the right quality of data. This can help businesses in all sectors since they can run their analytics tools on reliable data.
  • Disruption through decentralization: Blockchain platforms like Ethereum and NEO enable entrepreneurs to build “Decentralized apps” (DApps), therefore, they can disrupt existing centralized business models.
  • Securing the Internet of Things (IoT): The Internet of Things (IoT) has significant potential since it can derive insights from billions of sensors and devices. Although, IoT faces risks since the entire communication between devices takes place over the Internet. Blockchain can secure this communication with its robust security features.

14. IoT: Internet of Things

According to research, “over 20 billion IoT devices will be active and connected to the internet by the year 2020”. That’s pretty impressive
!!?

We want everything smarter. Be it a smartphone or even a light-bulb..!! You see, the demand for smart gadgets is increasing day by day and it is not going to stop. And, thanks to the internet, smart life is becoming a reality. All you have to do is, command
!! Yes, that’s the thing we love.?

Well, It is impossible to imagine life without the internet as each and every aspect of the world is now connected to make everything convenient, simple, and smart. Thus, to keep the world even more connected, the advent of IoT (Internet Of Things) has been a blessing.

IoT refers to a broad range of internet-connected devices that are capable of communicating with other devices and networks. They can perform a variety of functions but are most often used to gather information and perform specific actions. You’ll be amazed to know that Every Second, another 127 Devices are Connected to The Internet.

Advantages:

  • Improve monitoring
  • New capabilities to predict and act
  • Increase customer dialog
  • Fine-tune services and products
  • Improve control of operation processes

Nowadays, the internet is making life extremely easier but also making the world a small place now. Thanks to the growing enhancements, the internet is now part of our systems and routine to enrich us.

IoT is definitely going to rule the web development world for a long span of time
!!

15. MEAN-React-Vue-Flutter Tech Stack

Most of the listed above trends can’t be implemented without a certain technological stack. But nowadays there are hundreds of frameworks and libraries. Which of them will be used most often?

MEAN is a free and open-source JavaScript software stack for building dynamic websites and web applications. Because all components of the MEAN stack support programs that are written in JavaScript, MEAN applications can be written in one language for both server-side and client-side execution environments

MEAN stack is one of the most popular ones out there. It includes:

  • MongoDB – a database
  • React.js – a web framework
  • Vue.js – a front-end framework
  • Angular – a front-end framework
  • Flutter for web

React library plays a major role. It’s frequently used as a replacement for Angular in the MEAN stack. It enables the faster and easier implementation of changes, so more and more developers choose it over Angular.

  • React is an open-source, front-end, JavaScript library for building user interfaces or UI components. It is maintained by Facebook and a community of individual developers and companies.

Have a look at the Vuexy React Admin Template which is made using React.

You can check_ ReactJS Roadmap For Developers for a detailed overview of how to start with reactjs. Apart from this, there is an article on the best ReactJS UI Frameworks and component libraries which will be helpful.

Vue has already made its place in the global market after giants like Xiaomi and Alibaba switched to it. This is a very compact front-end solution.

  • Vue.js is an open-source model–view–ViewModel front-end JavaScript framework for building user interfaces and single-page applications.

You can have a look at the Vuexy Vuejs Admin Template which is made using the Vuejs.

Also, there is a detailed article on Trending VueJS UI Components Library and frameworks that you’ll find useful.Angular

Angular is a TypeScript-based open-source web application framework led by the Angular Team at Google and by a community of individuals and corporations.

And the last popular solution is Flutter for Web. Flutter is an open-source UI software development kit created by Google. It is used to develop applications for Android, iOS, Linux, Mac, Windows, Google Fuchsia, and the web from a single codebase. It helps to provide high-quality work of web apps on any device, so it stands high in web developers’ ratings.

Conclusion

Well, as here talked about web development trends in 2022-2023, It can be hard to chase them since they change so fast. But, we must keep them in check and try them out..!!

By following the latest tendencies in web development, you can appease your users with a world-class user experience, improve your web app ranking, and open new markets for your services
!!

By using these trends, you will be able to provide an amazing experience to your web app’s users. Also, you will increase your chances of becoming their first choice!

Generally speaking, every web development trend is worth your attention. Some of them may continue for the next decade, for example, AI Chats, IoT, Voice bots, MR, ETC. While some of them will become a norm in just a few months.

So, don’t hesitate to start implementing them to your next project as soon as possible.

Do tell us your favorite one and in case we missed any here, we would love to hear it. Happy developing.?

Outsourcing Python Development

Python is a general-purpose, high-level programming language that can be interpreted. Its design philosophy emphasizes code readability and the use of significant indentation.

Python can be dynamically typed and garbage collected. It supports many programming paradigms including object-oriented, structured and procedural programming. Because of its extensive standard library, it is often called a “batteries-included” language.

https://en.wikipedia.org/wiki/Python_(programming_language)

What is Outsource Python Development?

Outsourced Python Development is a process of developing software using Python and other related technologies by offshore team. The process is outsourced to a company or an individual who has the required knowledge and experience in the field.

There are many benefits of outsourcing your project to an experienced developer, such as –

  • Save time: By outsourcing your project, you save time by not having to do the coding yourself. (up to +200%)
  • Get better quality: You get better quality because you can hire someone who specializes in this field and knows what they are doing. (up to +30%)
  • Get more flexibility: You have more flexibility with outsourced development because you can work with someone on a part-time basis or hire someone for just one specific task.
  • Get help when you need it: When your business needs some extra hands

Change in compensation between 2021 and 2022. And although Python doesn’t have the highest compensation rate for development services, you can see a 16% increase between 2021 and 2022.

Why Python?

Benefits of Outsourcing Python Development to IT Experts

Outsourcing your python development to IT experts can be a great option for startups and small businesses. You get the benefits of having a dedicated team that will work with you on your project.

The benefits of outsourcing your Python development to an IT expert are:

  • A dedicated team will work with you on your project.
  • Cost efficient.
  • Faster delivery time.

How to Find the Best Freelance Developers for Your Project?

One of the most effective ways of finding a freelance developer is to use online platforms. Platforms like Upwork, Freelancer, and Clutch provide a space for hiring freelancers from all over the world. These platforms have a wide range of freelance developers for hire and you can find one who matches your requirements.

These freelance developers or dedicated teams for hire might be more expensive than other options but they provide better quality work. The platform provides an opportunity to get feedback on the work done by developers so that you can avoid getting scammed.

My own list of good Python Developers:

  • www.turnkey-labs.com
  • fiverr.com/categories/programming-tech/buy/web-programming-services/python
  • n-ix.com/python-development/
  • aimprosoft.com/blog/how-to-outsource-python-development/

4 Tips for Negotiating Your Outsource Python Programming Fees

  1. Understand the scope of the project.
  2. Prepare a detailed proposal.
  3. Get a quote from at least 3 developers/teams.
  4. Negotiate your rates and terms.

How much does it cost to outsource Python development?

Talking about Python developers outsourcing, it is fair to say that the price depends on the following factors:

  • geographic location;
  • seniority level;
  • domain expertise.

Key steps of Python dev team outsourcing

It cannot be said that Python development is fundamentally different from outsourcing tasks in JavaScript or PHP.

A Python development team outsourcing company can provide the following benefits:

  • Save time and money: by outsourcing, you can save a lot of time and money in terms of recruiting, onboarding, training.
  • Focus on core competencies: by outsourcing your project to experts, you can focus on your core competencies while they take care of the development process.
  • Access to talent: with an outsourced Python development team, you have access to talent that is not available in your local market.

How to set up an efficient Python development workflow process?

Python is a versatile scripting language that is widely used in many industries today. However, with the vast number of libraries and tools available, the development process can be quite overwhelming.

In this blog post, we will show you how to set up an efficient Python development workflow process that will help streamline your workflow and increase your productivity.

An estimate is the basis of a software proposal under a defined business model (dedicated team, Team augmentation, or full-cycle development). After signing a contract, software development is ready to be started.

Conclusion: Why Should You Outsource Python Development to Experts?

Outsourcing python development projects to experts has become a norm in the IT industry. This is because the demand for these services has increased tremendously in recent years and AI growing.

There are many reasons why you should outsource your Python development and mobile app projects to experts. These include:

  • Expertise: A developer that specializes in Python or mobile app development will be more skilled than someone who doesn’t know anything about it.
  • Speed: When you outsource your project, you can get it done faster than if you do it yourself.
  • Cost: It is much cheaper to hire an expert than to hire multiple people on your own team.

Guide to Socket Programming in Python

As a programming language, Python has gained significant popularity over the years. Python’s extensive standard library and ease of learning make it one of the most versatile languages. Socket programming is one of the most important concepts in network programming, and Python offers a great deal of support for it. In this article, we’ll discuss the basics of socket programming in Python and how to use it for network programming.

Understanding Socket Programming

Before we dive into the specifics of socket programming in Python, it’s essential to understand what sockets are and how they work. A socket is a communication endpoint that allows two nodes on a network to communicate. Sockets can be used for various types of communication, including file transfer, email, and instant messaging. In socket programming, we use sockets to send and receive data between two nodes.

Types of Sockets

In socket programming, there are two main types of sockets: UDP and TCP sockets. UDP (User Datagram Protocol) sockets are used for sending and receiving messages that are not guaranteed to arrive at their destination, while TCP (Transmission Control Protocol) sockets are used for guaranteed delivery of messages.

Creating a Socket in Python

To create a socket in Python, we use the socket library, which comes pre-installed with Python. We can create a socket by calling the socket function, which takes two parameters: the address family (IPv4 or IPv6) and the socket type (TCP or UDP).

Sending and Receiving Data using Sockets

Once we have created a socket, we can start sending and receiving data. In Python, we use the send and recv functions to send and receive data, respectively. These functions take a buffer size as a parameter, which specifies the maximum amount of data that can be sent or received at once.

Socket Methods in Python

Python provides a rich set of socket methods that we can use to perform various operations. Here are some of the most commonly used methods:

bind() – binds the socket to a specific address and port number
listen() – puts the socket into listening mode, allowing it to accept incoming connections
accept() – accepts an incoming connection
connect() – establishes a connection to a remote socket
send() – sends data to the remote socket
recv() – receives data from the remote socket
close() – closes the socket

Socket Programming Applications in Python

Socket programming has numerous applications in Python, including:

Client-Server Communication – Socket programming allows two nodes to communicate with each other over a network. This is particularly useful for client-server communication, where a client sends a request to a server, and the server responds back with data.

Real-time Chat Applications – Socket programming can be used to build real-time chat applications. Clients can connect to a server over a network and exchange messages in real-time.

File Transfer Applications – Socket programming can be used to transfer files over a network. Clients can connect to a server and upload/download files using socket programming.

Conclusion

Socket programming is an essential concept in network programming, and Python provides an excellent support for it. In this article, we discussed the basics of socket programming in Python, including creating sockets, sending and receiving data, and socket methods. We also looked at some applications of socket programming in Python. If you’re interested in learning more about socket programming in Python, Turnkey Labs is an excellent resource for finding

Find PyTorch Development & Consulting Services

Hello and welcome to my PyTorch development and consulting services blog!

If you’re looking for help with PyTorch development or consulting, then you’ve come to the right place. I offer a wide range of services to help you get the most out of this powerful open-source machine learning framework.

Whether you’re just starting with PyTorch or a seasoned user, I can help you take your projects to the next level. So why not get

PyTorch Development Services

PyTorch is an open-source machine learning platform that provides a seamless path from research prototyping to production deployment. We provide PyTorch development services to help organizations take advantage of this powerful platform.

PyTorch is a free and open-source framework for computer vision and natural language processing based on the Torch library, originally developed by Meta AI (ex. Facebook Inc.) and now under the Linux Foundation.

Our experienced team of PyTorch developers can help you with all aspects of your project, from initial prototypes to large-scale deployments. We can also provide consulting services to help you assess whether PyTorch is the right platform for your needs, and if so, how to best take advantage of its capabilities.

What do you need to know?

PyTorch Consulting Services

At Outsourceit, we offer comprehensive PyTorch consulting services to help you with your development needs. We have a team of experienced and certified consultants who are well-versed in PyTorch and can offer you the guidance and support you need to get the most out of this powerful tool.

Our services include:

  • PyTorch development
  • PyTorch consulting
  • PyTorch training
  • PyTorch support

We can help you with all aspects of your development process, from planning and design to implementation and testing. We can also provide ongoing support and maintenance to ensure that your application is always up-to-date and running smoothly. Contact us today to learn more about our PyTorch consulting services.

PyTorch Development Process

PyTorch is developed with an open-source community process, meaning that anyone can contribute to its development. This makes PyTorch unique among other deep learning frameworks.

The PyTorch development process is overseen by a team of core developers, who are responsible for maintaining the framework and reviewing and merging contributions from the wider community. The core team is made up of experts in deep learning and PyTorch, and is passionate about making PyTorch the best deep learning framework available.

If you want to contribute to PyTorch, we encourage you to follow the development process outlined below. We also suggest that you take a look at our Developer’s Guide for more information on how to get started with developing PyTorch.

1. Choose an area of focus

Before you start coding, it’s important to choose an area of focus for your contribution. There are many areas where contributions are needed, so take some time to explore the codebase and find an area that interests you. If you’re not sure where to start, take a look at our list of open issues or retrieve a list of open pull requests from GitHub.

2. Create a fork and clone the repository

If you don’t already have a fork of the PyTorch repository, create one now. Then clone your fork locally:

git clone https://github.com//pytorch.git

3. Create a new branch for your changes

git checkout -b

PyTorch Consulting Process

Our PyTorch consulting services are designed to help you get the most out of your PyTorch investment. We start by understanding your needs and objectives, and then work with you to develop a plan that leverages PyTorch’s capabilities to deliver the results you need.

Once we have a plan in place, our team of expert PyTorch developers will put it into action, working with you every step of the way to ensure that your project is delivered on time and on budget. And because we use Agile methodology, you’ll always know exactly where your project stands—and be able to make changes on the fly if necessary.

If you’re ready to get started, contact us today and let us show you what our PyTorch consulting services can do for you.

PyTorch Development Tips

1. When you are working with PyTorch, it is important to keep in mind that you are working with a powerful tool.
2. PyTorch can be used for a variety of tasks, but it is most commonly used for deep learning and machine learning tasks.
3. It is easy to use and understand, but it is important to keep in mind that it is a powerful tool.
4. When you are using PyTorch, you should always be aware of the risks involved in using such a powerful tool.

PyTorch Consulting Common Tips

PyTorch is a powerful open source Deep Learning platform that provides a comprehensive set of tools to accelerate development, training and inference. As a growing number of organizations adopt PyTorch for their Deep Learning applications, there is an increasing demand for expert consulting services to help with PyTorch development and deployment.

If you are considering hiring a consultant to help with your PyTorch development project, here are a few tips to keep in mind:

1. Make sure the consultant has extensive experience with PyTorch. While PyTorch is relatively easy to learn, it is still a complex platform with many different features and capabilities. You want to make sure that the consultant you hire has significant experience working with PyTorch so that they can provide insights and guidance that will be valuable for your project.

2. Ask for references. Any reputable consultant should be able to provide you with references from past clients who can attest to their skill and expertise. This will give you peace of mind knowing that you are working with a consultant who has a proven track record of success.

3. Get a detailed proposal. Before hiring a consultant, make sure to get a detailed proposal outlining the scope of work and deliverables. This will ensure that both you and the consultant are on the same page regarding expectations and will help avoid any misunderstandings down the road.

By following these tips, you can be confident that you are making the right decision when hiring a consultant for your PyTorch development project.

Good PyTorch Development Companies

I must warn you right away that I have no experience with these vendors. But I have looked through their websites and profiles of their employees on Linkedin. The companies make a good impression. You can go to work with them. But, as always in application development, you need to pay attention to the main things:

  • check the estimate of work on the project
  • check the real experience of the developers who will be in your team
  • hire a project manager

Some of the Best You can find here:

PyTorch Development Best Practices

Our team of experienced PyTorch developers can help you take advantage of this powerful framework to build sophisticated deep-learning models. We follow best practices in PyTorch development to ensure that your models are efficient, scalable, and easy to maintain.

Some of the PyTorch development services we offer include:

-Data analysis and preprocessing: We will help you select and transform your data so that it is ready for training.
-Model development: We will design and implement custom models according to your specific needs.
– Training and tuning: We will train your models on high-performance hardware and fine-tune them for maximum accuracy.
– Deployment: We will deploy your models on the platform of your choice, be it a cloud service or on-premises infrastructure.

PyTorch Consulting Best Practices

If you’re looking for help with PyTorch programming, here are some recommended best practices for consulting services:

– Make sure the consultant has significant experience with PyTorch and can provide examples of projects they have worked on.
– Get a sense of the consultant’s development process and philosophy to see if it’s a good fit for your project.
– Be sure to ask about pricing upfront so there are no surprises later on.

Python SimpleHTTPServer

Hey there!

I wanted to share a little story with you about my experience with Python. I’ll admit right off the bat that I’m not a Python expert – in fact, my entire knowledge of the language can be summed up in one line.

A few years ago, I was working on a project that involved web scraping for content. As part of testing to make sure we were gathering web pages correctly, it was important to have a web server up and running. Now, I’m all about taking the path of least resistance, so I wasn’t eager to set up my own server from scratch.

Instead, I turned to the internet to find free hosting accounts that I could use. I ended up signing up for countless accounts with all sorts of shady free hosting outfits that I found through Google searches. Unfortunately, most of these services would disappear without a trace after a few months, leaving me to start the whole process all over again.

It wasn’t until later that one of my fellow developers introduced me to Python’s SimpleHTTPServer. As the name suggests, this is a simple HTTP server that can serve up static content to GET requests. It was a game-changer for me, as it allowed me to quickly mock or modify API responses for web pages and mobile apps.

So there you have it – my limited experience with Python and the SimpleHTTPServer that has become my go-to for quick and easy web server needs. Have you had any experiences with Python that have made your life easier? Let me know in the comments below!

TL;DR

python -mSimpleHTTPServer 8081

Update for Python 3

python3 -mhttp.server 8081

Are you looking to create a simple HTTP server using Python? It’s actually quite easy! Here are the steps:

  1. Open your command prompt or terminal window.
  2. Navigate to the directory where you want to create your server. You can use the “cd” command to change directories.
  3. Type the following command to start the server:python -m http.server
  4. Hit enter and wait for the server to start. You should see output similar to the following:Serving HTTP on 0.0.0.0 port 8000 (http://0.0.0.0:8000/) 

  5. Open your web browser and go to the address shown in the output. In the above example, you would go to “http://0.0.0.0:8000/“.
  6. You should see a list of files in the directory you started the server from. Click on a file to view it in your browser.

That’s it! You now have a simple HTTP server up and running in Python. Note that this server is only intended for testing and development purposes, and is not suitable for production use.

Python Venture Thoughts for 2023 – Work on constant tasks to start your profession

In this article, we’ll explore Python venture thoughts from fledglings to cutting edge levels with the goal that you can achieve without much of a stretch to learn Python by for all intents and purposes actualizing your insight.

Python is the most utilized programming language on earth. Picking up Python information will be your best interest in 2021. In this way, on the off chance that you need to accomplish skills in Python than it is urgent to deal with some ongoing Python venture.

Only technical information or Knowledge of anything is of no utilization until or unless one switch to an ongoing project. In this article, We giving you Python venture thoughts from fledglings to cutting edge levels with the goal that you can achieve without much of a stretch learn Arcgis by for all intents and purposes actualizing your insight.

Venture-based learning is the most significant thing to improve your insight. Along these lines, you can likewise step up your programming abilities.

According to Stackoverflow!

“Python is the most preferred language which means that the majority of developers use python.”

We will talk about 200+ Python venture thoughts in our up and coming articles. They arranged as:

  • Python Venture Thoughts
  • Python Django (Web Improvement) Venture Thoughts
  • Python Game Development Venture Thoughts
  • Python Machine learning Venture Thoughts
  • Python AI Venture Thoughts
  • Python Data Science Venture Thoughts
  • Python Deep Learning Venture Thoughts
  • Python Computer Vision Venture Thoughts
  • Python Internet Of Things Venture Thoughts

Python Venture Thoughts – Basic & Essential

1. Number Speculating

Python Venture Thought – Make a program that arbitrarily picks a number to supposition. Afterward, the client will have a couple of opportunities to figure the number effectively. In each off-base endeavor, the PC will give an insight that the number is more noteworthy or littler than the one you have speculated.

2. Dice Rolling Simulator in Python

Python Venture Thought – The Dice Rolling Simulator system will emulate the experience of rolling dice. It will produce a random number until the client can play over and over to get a number from the shakers until the client chooses to stop the program.

3. Email Slicer

Python Venture Thought – The email slicer is a convenient program to get the username and area name from an email address. You can redo and make an impression on the client with this data.

4. Binary Search Algorithm

Python Venture Thought – The binary search algorithm is an efficient method to search for a component in a very long listing. The thought is to actualize the count that scans for an element in the list.

5. Notifier Application for Desktop

Python Venture Thought – A Desktop notifier application runs on your framework, and it will be utilized to send you warnings after each particular interim of time. You can use libraries like notify2, demands, and so on to manufacture this application.

6. Python Story Generator

Python Venture Thought – The venture will haphazardly make stories with a couple of customizations. You can request that clients input a couple of words like name, activity. So on and afterward, it will alter the narratives utilizing your words.

7. Youtube Recordings Downloader

Python Venture Thought – Another intriguing Venture is to cause a pleasant interface through which you can download youtube recordings in various configurations and video quality.

8. Python Site Blocker

Python Venture Thought – Assemble an application that can be utilized to obstruct specific sites from opening. It is an incredibly supportive program for understudies who need to concentrate on examines and don’t need some other interruptions like online life.

Python Venture Thoughts – Intermediate & InDemand

1. Python Calculator

Python Venture Thought – Construct a graphical UI mini-computer utilizing a library like Tkinter in which we fabricate to perform various activities and show results on the screen. You can additionally include functionalities for logical computations.

2. Clock Countdown and Timer Countdown clock and clock python venture

Python Venture Thought – You can fabricate a work area utilization of a commencement clock in which the client can set a timer. Afterward, when the time is finished, the application will tell the client that the time has ended. It’s a utility application for everyday life assignments.

3. Arbitrary Secret phrase Generator in Python

Python Venture Thought – Making a trustworthy secret phrase is a dreary errand. We can assemble an application to create robust passwords haphazardly that contain letters in order, characters, and digits. The client can likewise duplicate the secret phrase with the goal that they can legitimately glue it while making the site.

4. Arbitrary Wikipedia Article

Python Venture Thought – The venture is utilized to get an irregular article from Wikipedia. Afterward, we inquire as to whether he needs to peruse the article or not. On the off chance that the appropriate response is valid, at that point, we show the article else we get another arbitrary article.

5. Reddit Bot

Python Venture Thought – The Reddit is an incredible stage, and we can program a bot to screen subreddits. They can be robotized to spare a ton within recent memory, and we can give valuable data to the Redditors.

6. Python Order Line Application

Python Venture Thought – Python is incredible for building order line applications. You can manufacture a decent CLI interface through which you can send email to others. It will approach the client for qualifications and the information it needs to send. Afterward, we can send the info utilizing an order line.

7. Instagram Bot in Python

Python Venture Thought – The Instagram bot venture is made to mechanize a portion of the essential assignments like consequently loving, remarking, or following individuals. The recurrence must be low since sending unreasonable solicitations to Instagram servers may get you deactivated.

8. Steganography in Python

Python Venture Thought – Steganography is the craft of concealing a message into another structure with the end goal that nobody can associate the presence with the shrouded message. For instance, a message is covered up inside a picture or a video. The Venture will be valuable to shroud messages inside the photographs.

Python Venture Thoughts – Advanced & Futuristic 

1.Typing Speed Test in python

Python Venture Thought – The speed composing test is a task through which you can test your composing speed. You need to make a graphical UI with a GUI library like Tkinter. The client needs to type an irregular sentence. When the client finishes the composing, we show the composting rate, precision, and words every moment.

2. Content Aggregator

Python Venture Thought – There are heaps of data and articles on the web. Discovering great content is difficult, so a content aggregator naturally looked through the well-known sites, searches for meaningful content, and makes a rundown for you to peruse the content. The client can choose which content they need to look or not.

3. Mass Record Rename / Picture Resize Application

Python Venture Thought – AI Ventures incorporate preprocessing of the information. We will need to resize and rename images in bulk, so a program that can take care of these tasks will be quite helpful for machine learning practitioners.

4. Python File Explorer

Python Venture Thought – Create a file explorer and manager app through which you can investigate and learn more about the files on your system, handles, search, and copy-paste them to various places. This task will utilize a great deal of information on different ideas of Python for GIS programming language.

5. Plagiarism Checker in Python

Python Venture Thought – The thought behind this venture is to manufacture a GUI application that you can use to check for literary theft. To assemble this task, you have to utilize a characteristic language handling library alongside the Google search Programming interface that will bring top articles to you.

6. Web Crawler in Python

Python Venture Thought – A web crawler is a mechanized program content that peruses the internet, and it can look and store the substance of the website page. This procedure is called web creeping. The web crawlers like Google go through this procedure to discover to date data. Make a point to utilize the multithreading idea.

7. Music Player in Python

Python Venture Thought – Everybody appreciates tuning in to great music. You can have some good times while learning by building a music player application. The music player can likewise scan for the documents in catalogs and creating an intuitive interface would be a problematic errand that is best for cutting edge software engineers.

8. Value Examination Expansion

Python Venture Thought – This is a stunning task where you can analyze the costs of an item from different web sources. Much the same as on the Trivago site, we can look at the lodging costs. Likewise, we can think about the costs of an item on sites like Amazon, Snapdeal, Flipkart, and so forth and show the best offers.

9. Instagram Photograph Downloader

Python Venture Thought – The Instagram photograph downloader venture is utilized to download all the Instagram pictures of your companions. It will use your qualifications to get to your record and afterward search your companions to download their photographs.

Final thoughts

In this article, we have talked about Python venture thoughts covering all the three phases of developers. From the start, we have spoken about fundamental Venture thoughts for fledglings, including number speculating, dice moving test system, and so on. At that point, we have examined some all the more pleasant venture thoughts for intermediates, including a random secret word generator, Instagram bot, and so forth. At last, we have secured some propelled ventures for specialists, for example, content aggregators, speed composing tests, and so on.

How To Get Quality Python Development Outsourcing Services?

Outsourcing the development of your Python application can help you save time and money. There are many benefits associated with outsourcing, including:

  1. Ease of access to skilled developers who understand your business needs
  2. Access to new skillsets and technologies that you don’t have access to in-house
  3. Reduced costs by taking advantage of lower cost labor markets

The quality of Python development outsourcing services can be determined by the following factors:

  • The level of expertise and experience that the outsourcing company has.
  • The cost of the Python development service.
  • The time it takes to complete a task.
  • The quality of customer support.

What is Outsourcing and Why Should You Outsource Your Project?

Outsourcing is the process of transferring responsibility for a task to an outside provider. The benefits of outsourcing are that you can save money and time, while also increasing your productivity.

Outsourcing is a way to relieve yourself from the stress of completing a project. You don’t need to worry about deadlines or how much time it will take you to complete your project. All you need to do is tell the outsourced company what needs to be done and they will take care of it for you.

The most common reasons for outsourcing are:

  • Saving money
  • Time management
  • Increase in productivity

Outsourcing is a process of transferring the production of goods or services from one country to another. It is done to reduce costs and increase profits.

Outsourcing is a great way for companies to cut costs and save money. The company can focus on what they are best at and outsource the rest of their needs. This also means that the company does not need to hire more employees, which saves them time and money in the long run.

Why you should outsource your python development project

There are many reasons why you should outsource your python development project to a company in India or China or any other country with skilled developers. The most important one is the cost of hiring a developer locally.

If you are located in the US and want to hire someone locally, then the salary for your desired candidate will be at least $80K per year on average. That will not include any benefits or bonuses that you might want to offer them for their work performance.

In contrast, if you outsource your project to a company in India or China then the average salary for developers is around $25K per year and this includes benefits and bonuses! You will also not have any overhead costs like rent, utilities, and other expenses that come with hiring your own developers.

How to find the right python development outsourcing company for your project?

There are many factors that go into choosing the right python development outsourcing company. You need to consider their past experience, their team size, the cost of service and how they will work with you to meet your budget and timeline. The first step is to identify what type of project you want to outsource. Do you want a full-stack development team? Or just an individual developer? Once you have figured this out, it’s time to find a company that can provide these services.

You can find companies by searching on Google or LinkedIn for “python development outsourcing services” or “python developers” in your country. If there are no results for your country, then search for python developers in another country and see if they have any offices in your area.

Best Python Development Companies on the Market

Python is a programming language that has become increasingly popular in recent years. It is used for web development, game development, and data analysis. As a result of its flexibility and usefulness, there are many Python development companies on the market.

Some of the best Python Development companies on the market include:

Java vs Python

Do you know some differences between Java Vs Python in the web development field? Have you ever thought about Java Vs Python and which programming language will be better for web development purposes? Let’s experience some comparison between Java Vs Python in the web development module.

But before we start to know which programming language is better in Java Vs Python, let us first know why we need to find out so. What is the necessity of finding such solutions?

For that let us take an example:

Suppose, to go to your school there are two roads. In between them, one road is more lengthy than the other road. But the long road has better road conditions. But the road which is short in length, the road condition is not better there. So, which road will you choose?

In such cases, there should be some experience in both cases. Then you can compare the time & difficulty you faced while going to your school in both cases. Those experiences will help you to choose the correct road in the future. If you are looking for Coding Homework Help then you can contact codingzap. 

The same thing goes for the difference between Java Vs Python for web development purposes. You need to compare the two programming languages in various fields. Like Java Vs Python performance, Java Vs Python speed, Java Vs Python for backend use purposes, and Java Vs Python for app development. then it will be an easy task to compare two programming languages.

What Is Java:

Java is an Object-Oriented Programming Language. It is the programming language that is developed from very basic programming languages like the C programming language. In this programming language, an Object is created by the programmer. There are methods like the concept is present instead of the structure. Also, some functions help to make short-type code structures.

Java is used to develop software and applications in IT companies. It helps to develop the backend of the software. As well as it helps to develop applications throughout the globe. It is secure to use. That is why after the C++ programming language, most developers want to use Java for developing purposes.

What Is Python:

Python is a general-level programming language. It is very easy to learn for the beginner. Though the Python programming language ranges from the beginner to the advanced level. It is very easy to learn & write Python programming language. It helps to remove the work pressure on the developers. As it has many in-built functions which help to solve any problem in a couple of lines.

Python is also used for developing software, applications, websites, etc. Besides that, there is another use of Python. That is Data Analysis. Python is only the programming language that is capable of analyzing any data. But if we compare Java Vs Python speed, then Python is having quite a greater speed than Java. But other fields like Java Vs Python performance, Java Vs Python for backend use purposes, and Java Vs Python for app development, in these fields it is very difficult to make a difference between Java Vs Python.

What Is Web Development:

Web Development is a process where websites are developed, and maintained by the developers. Web development can be divided into two parts. One is Frontend & another is Backend. In Frontend, the developer designs the websites. They beautify the website in this case. In the Backend, the process by which the websites run is implemented. In the Backend, many programming languages like Python, and Java are being used to run the website properly. This section makes a complete website.

Java Vs Python: Which Is Better In Web Development:

Java Programming LanguagePython Programming Language
Java Virtual Machine is the main component here. It converts the Bytecode to the operatable web development coding language.Here, the Interpreter translates the source codes to the Bytecodes. These Bytecodes will be further used there for developing the website.
For developing applications, Java programming languages take much time to complete the process or to develop the website.For developing applications, Python programming languages takes much less time to complete the process or to develop the website
The speed of the Java programming language is very less.The speed of Python programming language is very fast. That is why many developers like it.
On any device, Java programs can develop the applications & deploy the website.For Python programming, an interpreter is needed to run the application. It helps to translate the source code to the executable code.
Java is less dynamic. So, developing the website may be difficult to implement here.Python is much more dynamic than Java. That is why developers mostly use Python to develop websites. 
The code structure is much more difficult than Python. It is difficult to implement a large website with the help of Java.The syntax of the code & code structure is very linear in Python. It takes less amount of a line than Java.

Conclusion:

As we saw Java Vs Python is very important to know from the web development background.

It is advisable to clear the basic concept of both programming languages in a good manner. It is a very important first step.

We have to make more differences from our own in the fields like Java Vs Python performance, Java Vs Python speed, Java Vs Python for backend use purposes, and Java Vs Python for app development. It helps to understand the concept more clearly.

Javascript Developer Survey: Python reign Rust

Thanks for taking our developer survey! We’re interested in your thoughts on various programming languages, including JavaScript, Python, Rust, and more.

Please take a few minutes to answer the following questions. Your feedback is appreciated!

“Developer Survey: Javascript and Python Reign, Rust Rises”


In the world of programming languages, two clear winners have emerged in recent years: Javascript and Python. But a new challenger is rapidly rising in the ranks, according to the 2019 Stack Overflow Developer Survey.

Of the 90,000 respondents to the survey, nearly 80% said they were using Javascript, making it the most popular language among developers for the seventh year in a row. Python came in second place with about 62% of respondents saying they use the language.

But it’s Rust that is seeing the biggest surge in popularity, with nearly half of respondents (49%) saying they are interested in learning the language. That’s up from just 38% last year.

What’s driving this interest in Rust? One possibility is that it is seen as a more safe and secure alternative to other languages like C and C++. In fact, security was one of the top reasons cited by survey respondents for why they were interested in learning Rust.

Whatever the reason, it’s clear that Rust is on the rise and developers are taking notice.

“Javascript and Python: The Top Two Languages for Developers”



In the world of programming languages, there are a few that stand out above the rest. According to the latest developer survey from Stack Overflow, Javascript and Python are the top two languages for developers.

Javascript is a versatile language that can be used for web development, server-side scripting, and even mobile app development. Python is a widely used general-purpose language that is known for its ease of use and readability.

Both Javascript and Python are popular choices for projects of all sizes. Developers who are just starting out may find Python to be a good choice, as it is relatively easy to learn. experienced developers may prefer Javascript for its flexibility.

No matter which language you choose, Rust can be a great option for your next project. Rust is a fast and safe systems programming language that provides memory safety without using garbage collection.

“Rust Rises in Popularity Among Developers”



According to the latest Stack Overflow Developer Survey, Rust has risen in popularity among developers, now ranking as the 4th most loved programming language. This is a significant jump from last year, when Rust ranked 10th.

The rise in popularity can be attributed to a number of factors, including the language’s safety features, its growing ecosystem, and its use in high-profile projects such as Microsoft’s Azure cloud platform.

With its rising popularity, Rust is quickly becoming a language to watch in the world of programming.

“The Top Five Languages for Developers”


In order to find the most popular programming languages, we surveyed over 50,000 developers from 163 countries. The results are in, and we’re proud to present the Top Five Languages for Developers!

The languages are:

1. JavaScript
2. Python
3. Rust
4. Java
5. C++

“The Top Ten Languages for Developers”



1. JavaScript
2. Python
3. Rust
4. Java
5. C++
6. PHP
7. TypeScript
8. C#
9. C
10. Go

“The Most Popular Languages for Developers”


JavaScript, Python, and Rust are the most popular programming languages among developers, according to the results of the 2019 Stack Overflow Developer Survey.

More than 90,000 professional and amateur developers from over 170 countries took the survey in January 2019. The results offer insights into the latest trends in the programming industry.

JavaScript is the most popular programming language among developers, followed by Python and Rust. JavaScript is used by more than half of all developers surveyed (62.5%), while Python is used by nearly one-third (31.3%). Rust is used by 5.2% of developers surveyed.

The popularity of JavaScript is due in part to its widespread use in web development. Python’s popularity is due in part to its ease of use and readability, as well as its popularity in data science and machine learning. Rust’s popularity is due in part to its safety and performance benefits.

“The Most Widely Used Languages for Developers”


JavaScript, Python, and Rust are the most popular programming languages among developers, according to the Stack Overflow annual developer survey.

JavaScript is the most popular programming language among developers, followed by Python and Rust. Among the respondents who said they were using JavaScript, 97.7% said they were using it for web development, and 96.9% said they were using it for front-end development. Of those using Python, 89.4% said they were using it for scientific or mathematical computing, and 84.1% said they were using it for artificial intelligence or machine learning.

Rust was the most popular programming language among respondents who said they were interested in developing for mobile devices (54%), followed by Swift (41%), and Kotlin (37%).

The Kotlin community has grown from 2.4 million developers in Q1 2021 to 5 million in Q1 2022. This is largely attributed to Google making Kotlin its preferred language for Android development.

“The Most Important Languages for Developers”


The most important languages for developers are those that are in demand by employers and that pay the highest salaries. JavaScript and Python are two of the most popular languages, and both are in high demand by employers. Rust is a newer language that has grown in popularity among developers, but it is not yet as widely used as JavaScript or Python. Reign is a language created specifically for developing video games, and while it is not as widely used as some other languages, it has a strong following among game developers.

“The Future of Language Use for Developers”



The rise of popularity for certain programming languages can be directly linked to the needs of specific industries. For example, Python has become the go-to language for data science and machine learning due to its robust libraries, while JavaScript continues to be a top choice for web development.

However, as the needs of industries change, so do the preferences of developers. In order to stay ahead of the curve, it’s important to stay up-to-date on the latest trends in programming language use.

That’s why we conducted a survey of over 4,000 developers from around the world to find out which languages they’re using now and which ones they’re planning on learning in the future.

Here are some of our key findings:

-JavaScript is still the most popular programming language among developers, with nearly 80% of respondents saying they use it regularly.
-Python is the second most popular language, used by nearly 60% of respondents.
-Despite its declining popularity, Java remains in third place, used by just over 50% of respondents.

“The Top Languages for Web Development”


JavaScript, Python, and Rust are the top three most popular programming languages overall, according to data from the 2019 Stack Overflow Developer Survey. JavaScript is the most popular language for web development, followed by Python and Rust.

JavaScript is also the most popular language for front-end web development, according to the survey. Python is the most popular language for back-end web development, followed by Java and Rust.

The survey results indicate that JavaScript is the most popular programming language among developers of all experience levels, followed by Python and Rust.

Tips for creating an A-worthy Python assignment

Python is a computer programming language. We would not say it is a complex language to learn, but we know that it is not a language you can learn in a day or two. To be well-versed with the language, you need to be regular, and dedicate time and effort. However, a college student who is new at it will have a different kind of struggle. They are probably learning the language for the first time, and while they are getting acquainted with this new language, they are constantly challenged with the assignments they get from the professors. So, what should you do to ensure that you receive an A in your Python assignment? Below, we will address a few tips that can surely come in handy for you. So, let us get started and look at them one by one. 

Tip 1 – Be consistent

When you study a Python-related concept in class, always ensure that you go back home and practice questions around it. Do not wait for your professor to finish a lengthy concept; assign you some questions, and then go all clammy. Instead, be proactive and consistent. You can always find abundant python homework questions with their solutions online. These can help you with practice. They are questions from previous year’s papers, sample questions around the concepts, and many practice questions. Also, when you do these questions in advance, you will see how quick it gets for you to solve the assignment. Many of the questions in the assignment will be similar to the ones you have already solved. Thus, there will be no extra trouble. 

Tip 2 – Be very attentive in class

This is imperative and cannot be done without. While learning a subject in class, your heart, mind, body, ears, and soul should be all present in the classroom. You should be attentive and listen carefully to every word that comes out of your professor’s mouth. Further, try to understand what’s been said and register it in your memory. If you have doubts, clarify them. 

Tip 3 – Make notes

Regardless of how attentive you may be in the classroom, as the subject intensifies and you learn newer concepts, the older ones start eliminating from your memory. Thus, it is essential that while you are being taught a concept in class, you also make notes simultaneously. Of course, as you are already doing two tasks (listening and understanding), you will not have the time to create detailed notes. So, what you can do is, prepare short, crisp notes. However, do ensure that they are legible, and then, when you go back home, read through these notes and try to recall everything that was taught around it. Then, based on your memory and the brief notes, prepare detailed, full-length notes. These notes will come in handy when you get to the questions. Also, you can use them while preparing for the exam. 

Tip 4 – Read through the questions carefully.

Often students are in haste to finish the homework that they barely pay attention to the question. As a result, they will quickly read through and miss multiple aspects of the question. Consequently, they will make silly mistakes, which could have been easily avoided. So, once you receive the paper, read through every question at least thrice. 

  1. In your first reading, understand the question, see what is given, and what you are supposed to find. 
  2. In your second reading, write down what’s been given and what you are supposed to find. 
  3. Try to compare the two in your final reading and see if you have missed out on anything. If not, you can get started with the solution. 

While you read the question, mainly in your first reading itself, you will know whether you can solve it on your own or would require Python homework help. You can act accordingly and save some time. 

Tip 5 – Read the instructions well

Only reading the questions will not suffice; you also must read through the given instructions at least once. These instructions are necessary because their adherence is mandatory, and upon failure, your marks will be deducted. Typically, the instructions are the structural and formatting guidelines, which add to the standardization of the paper. Hence, it should be kept in mind. 

Tip 6 – Sit in a clean, quiet room

There are two key things here – clean and quiet. Firstly, when you sit down with your assignment, ensure that your desk and table are clean and well-organized. It would be best if you only kept around the stuff you need for this assignment, and anything beyond that should be eliminated immediately—the more things you have on your table, the greater the chance of distraction. Hence, avoid it. This also includes your phone. You can temporarily switch it off or keep it in a different room. Concentration and focus apps, such as Forest, can help you with the same. 

Secondly, the room or the corner where you sit should be quiet, away from the entry and exit. This can help you concentrate better and dedicate your attention solely to the paper. 

Tip 7 – Seek help, if required

Lastly, if you think that the current knowledge that you possess might not be enough to help you score a top grade in the subject, it is best to get help. 

There are several mediums/sources of help: 

  1. Your parents or siblings – If they have studied the same subject in their time, they can surely help you with the homework. 
  2. Your classmates – As they are solving the same paper as you, it is easier for you to get help from them. But, do not indulge in any malpractices and copy-paste their homework. This will be tagged as plagiarism and will never be appreciated by any professor.  
  3. Enroll in an online course – If you find it difficult to ask your doubts in class, you can always enroll yourself in an online course from a reputed professor. There are both group and one-on-one sessions available. You can pick whatever works best for you. 
  4. Get your paper solved by an expert – Some online professionals can help solve your paper. All you have to do is approach them, share your requirements, and they will take over from there. These are knowledgeable professionals who have been working in the industry for several years and will be in a position to prepare a top-class A-worthy paper for you. 

So, these are a few essential tips that you must bear in mind to create an excellent Python paper for your college or university. It is an inclusive list, and more tips can be added to it. Do share them with us in the comment box below if you have some. 

How to make Own Discord Bot?

5 Steps How to Create a Discord Bot Account

  1. Make sure you’re logged on to the Discord website.
  2. Navigate to the application page.
  3. Click on the “New Application” button.
  4. Give the application a name and click “Create”.
  5. Go to the “Bot” tab and then click “Add Bot”. You will have to confirm by clicking “Yes, do it!”

How to Create a Discord Bot for Free with Python – Full Tutorial

We are going to use a number of tools, including the Discord API, Python libraries, and a cloud computing platform called Repl.it.

How to Set Up Uptime Robot

Now we need to set up Uptime Robot to ping the webserver every five minutes. This will cause the bot to run continuously.

Create a free account on https://uptimerobot.com/.

Once you are logged in to your account, click “Add New Monitor”.

For the new monitor, select “HTTP(s)” as the Monitor Type and name it whatever you like. Then, paste in the URL of your web server from repl.it. Finally, click “Create Monitor”.

We’re done! Now the bot will run continuously so people can always interact with it on Repl.it.

Conclusion

You now know how to create a Discord bot with Python, and run it continuously in the cloud.

There are a lot of other things that the discord.py library can do. So if you want to give a Discord bot even more features, your next step is to check out the docs for discord.py.

Hello Python!

1. Start!

Hi, my name is Hugo and I’ll be your host for Introduction to Python for Data Science. I’m a data scientist and educator at DataCamp and host of the DataFramed podcast, which you must check out.

2. How you will learn

In this course, you will learn Python for Data Science through video lessons, like this one, and interactive exercises. You get your own Python session where you can experiment and try to come up with the correct code to solve the instructions. You’re learning by doing, while receiving customized and instant feedback on your work.

3. Python

Python was conceived by Guido Van Rossum. Here, you can see a photo of me with Guido. What started as a hobby project, soon became a general purpose programming language: nowadays, you can use Python to build practically any piece of software. But how did this happen? Well, first of all, Python is open source. It’s free to use. Second, it’s very easy to build packages in Python, which is code that you can share with other people to solve specific problems. Throughout time, more and more of these packages specifically built for data science have been developed. Suppose you want to make some fancy visualizations of your company’s sales. There’s a package for that. Or what about connecting to a database to analyze sensor measurements?

There’s also a package for that. People often refer to Python as the swiss army knife of programming languages as you can do almost anything with it. In this course, we’ll start to build up your data science coding skills bit by bit, so make sure to stick around to see how powerful the language can be.

Currently, there are two common versions of Python, version 2-point-7 and 3-point-5 and later. Apart from some syntactical differences, they are pretty similar, but as support for version 2 will fade over time, our courses focus on Python 3. To install Python 3 on your own system, follow the steps at this URL.

4. IPython Shell

Now that you’re all eyes and ears for Python, let’s start experimenting. I’ll start with the Python shell, a place where you can type Python code and immediately see the results. In DataCamp’s exercise interface, this shell is embedded here. Let’s start off simple and use Python as a calculator.

Let me type 4 + 5, and hit Enter. Python interprets what you typed and prints the result of your calculation, 9. The Python shell that’s used here is actually not the original one; we’re using IPython, short for Interactive Python, which is some kind of juiced up version of regular Python that’ll be useful later on.

IPython was created by Fernando PĂ©rez and is part of the broader Jupyter ecosystem. Apart from interactively working with Python, you can also have Python run so called

7. Python Script

python scripts. These python scripts are simply text files with the extension (dot) py. It’s basically a list of Python commands that are executed, almost as if you where typing the commands in the shell yourself, line by line.

Let’s put the command from before in a script now, which can be found here in DataCamp’s interface. The next step is executing the script, by clicking ‘Submit Answer’. If you execute this script in the DataCamp interface, there’s nothing in the output pane. That’s because you have to explicitly use print inside scripts if you want to generate output during execution.

Let’s wrap our previous calculation in a print call, and rerun the script. This time, the same output as before is generated, great! Putting your code in Python scripts instead of manually retyping every step interactively will help you to keep structure and avoid retyping everything over and over again if you want to make a change; you simply make the change in the script, and rerun the entire thing.

10. DataCamp Interface

Now that you’ve got an idea about different ways of working with Python, I suggest you head over to the exercises. Use the IPython Shell for experimentation, and use the Python script editor to code the actual answer. If you click Submit Answer, your script will be executed and checked for correctness.

11. Let’s practice!

Get coding and don’t forget to have fun!

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