Python for Mobile App Development Sumeet Shah November 23, 2022

What is Python?

Python is a major scripting language that includes compelling semantic features. Its clear, easy-to-learn syntax emphasizes readability, lowering the program’s maintenance costs. And the syntax is nearly identical to that of English. Guido van Rossum, a Dutch programmer, designed Python and released it in 1991. Python 2 is the most extensively used as compared to its latest version, Python 3. The language codes are written in a text editor or an integrated development environment, such as Thonny, Netbeans, or Pycharm (computer programs). So what does Python do?

  1. It can handle massive data and perform complex calculations
  2. It can connect to database systems and read or modify the files
  3. When used alongside a software application, it can create workflows
  4. If used on a server, it establishes web applications
  5. It is also used in the development of software prototypes

Did you know: Python has been a crucial part of Google since its establishment as a search engine?

 

Why use Python coding in mobile app development?

Python is an outstanding language for mobile app development because:

  1. It is straightforward, easy to read and write, and powerful when solving complex problems. 
  2. Its huge standard library allows you to integrate the language with third-party APIs or modules.
  3. It can be used on various platforms, including iOS, Windows phones, and desktop computers.
  4. It also works on Windows, Linux, Macintosh, and Unix and has been ported to Java and virtual machines (.NET)
  5. Although Android does not support native Python, it can be used in mobile app development. It is possible by using various tools that convert Python apps into Android Packages that run on Android devices.
  6. Python frameworks aid in the development of mobile apps in a shorter time.
  7. You only need a capable device, such as a laptop/desktop computer running Ubuntu, macOS, or Fedora. Alternatively, you can use mobile phones, such as the Galaxy S4, Nexus 5, etc., for Python coding.

Did you know?: Python is used in developing applications like YouTube, Instagram, Spotify, Quora, Dropbox, Pinterest, Reddit, and many others.

Frameworks to build mobile apps with Python:

Python does not support the interpreted languages by iOS or Android. In fact, Python apps cannot run natively. And at this point, various frameworks emerge to bridge the gap, allowing these apps to run on mobile devices with a native appearance and functionality. 

The preferred implementation language for Android is always Java. So, to write an Android application in Python, you need a way to run its code on a Java virtual machine. The steps for creating an app for iOS are comparatively more complex than those for Android.

So which frameworks can help you to develop an actual application on your device? Let’s take a look-

VOC

VOC (Vestigial Output Compiler) is a component of the BeeWare suite that allows you to access Java native objects and implement Java interfaces in Python classes. It takes Python’s source code, compiles it to CPython bytecode, and then transpile it into Java-compatible bytecode (machine code). The result is that your Python source code files are compiled directly into a Java .class file, which is then packaged into an Android application. It will allow you to write Android applications now to the native API of Android. Once you’ve registered your native Android application, you can use Briefcase for packaging your Python code as an Android application.

Python-for-Android

It is a tool for integrating Python with Android. Its primary function is to create Android APKs that can be installed or uploaded to marketplaces such as Play Store. The first function of the tool is to compile the Python interpreter, its dependencies, backend libraries, and Python code for Android devices. By totally customizing this stage, you can install whatever components you like. This results in a standalone Android project used for generating any number of different APKs, even with other names, icons, Python code, etc. The second function of Python-for-Android is to give a simple interface to these distributions.

Kivy

Kivy is a cross-platform framework that lets you create apps and games for Windows, Linux, iOS, and Android. Kivy has an extensive Python library with many features, such as multitouch events and so on. These multitouch gestures aid in developing rich user experiences (UX) with less effort. Kivy also supports the use of native libraries on various platforms. You can directly call functions from its central platform and also access features that Python does not offer.

PyJNIus 

PyJNIus allows you to create Android apps without any prior knowledge of Java. It gives access to Java classes and methods using Python, making it a powerful tool for mobile app development. Its framework even allows Python to interact with the Android API. Developers use this API to obtain information from various parts of their mobile devices through pause, vibration, etc., functions.

In a nutshell:

Python has become one of the most eminent programming languages. It’s easy to learn, and there are lots of free online tutorials available to learn Python. You can use Python to write programs for almost any application, including web applications, mobile app development, desktop apps, games, scientific computing, and much more.

Is Python worth learning in 2022 Sumeet Shah July 20, 2022

What Is Python Used For? A step-by-step guide for Beginners

What is Python?

Python is a dynamically semantic, interpreted, object-oriented high-level programming language. Python is a general-purpose programming language, which means it can be used for a variety of tasks such as data research, software and web development, automation, and just getting crap done in context. Python’s concise, easy-to-learn syntax prioritizes readability, which lowers software maintenance costs. Modules and packages are supported by Python, which fosters program modularity and code reuse. Guido van Rossum created Python, and it was published in 1991.

What is Python used for?

1. Web Development:

Python is a popular choice for complicated web development projects because of its versatility, which allows for the creation of sophisticated online utilities with ease. Web developers that use it save a lot of time and energy because of its straightforward syntax, which is quite comparable to the English language. Python is a very flexible backend language. Backend or server-side functionality can be handled more easily using Python-based web frameworks like Django. Python’s prominence in web development is largely due to frameworks and libraries such as Django and Flask, which enhance the language’s capabilities.

2. Data Analytics/Data Science:

Python is used to create several of the most popular data mining tools. As a result, it’s a fantastic data science tool. Data scientists and analysts alter data using coding languages like Python and R for reporting, predictive analysis, and other purposes. The Pandas library is a major advance forward from the outdated Excel files that have been used for so long for financial research. NumPy also allows you to perform linear algebra, scientific computing, and a variety of other specialized tasks. Python’s features enable programmers to distinguish between crucial and relevant data. Organizations may learn more about themselves by interpreting big data well.

3. AI and ML:

These days, artificial intelligence and machine learning are buzzwords, but the fact is that it all boils down to algorithms, code, and logic. Machine learning is the process of teaching computers to learn on their own using algorithms that are continually updated based on incoming data. Python is often regarded as the greatest programming language for Artificial Intelligence (AI) due to its clear syntax and ease of learning. Given the diversity and capability, it’s no wonder that some genuinely world-class tools for producing intelligent behavior exist in Python.

4. Financial Analysis:

When recruiting engineers, the most popular programming language considered by FinTech organizations is Python. Python is gaining popularity as a result of its potential financial services. Python’s utility in applications such as data regulation, analytics, risk management, and quantitative rate difficulties is the reason for its appeal. More than only FinTech companies use Python programming. Python is widely used everywhere in the financial industry due to its data processing skills and various third-party financial analysis tools.

5. Scripting:

The script language generates code and is very easy to learn, even for newbies. Python is widely used in programming and is an interpreted language that occurs during runtime. It becomes more flexible and adaptable than many other scripting languages since it translates to code. In a program, a script is used to automate particular operations. It can run on its own and requires less code, but modules in Python are referred to as libraries that cannot run on their own. It must be imported before it may be used. Python is classified as a scripting language since it is an interpreted language and its popularity in scripting relates to its simple scripting interface.

Frequently-asked Question

What is Pandas Python?

Pandas is a widely used open-source Python library for data science, data analysis, and machine learning activities. It is developed on top of NumPy, a library that supports multi-dimensional arrays. It provides quick, simple, and adaptable data structures for working with structured (table form, multivariate, possibly heterogeneous) and time-series data. Pandas is a Python data science module. It works well with many other Python data science modules and is normally included in every Python installation. Among other things, Pandas supports re-indexing, repetition, filtering, data analytics, sequences, and representations.

Python — A Better Scripting Language Marketing November 29, 2021

One of the most used scripting languages, Python is popular among developers due to its ease of use and versatility. It is simple to comprehend and get used to and as we know, a coder will use any programming language with which they are most accustomed and which gets the task done most successfully. Python is widely used in both academia and the industry, and it has a global following. Python is regarded as one of the most powerful strong computer languages available. Python has a great number of libraries and modules, according to experts. Libraries store code for common functions so developers shouldn’t have to develop them from the start.

Is Python a Programming language?

Is Python considered to be a programming language? Is it possible that it’s a scripting language? To set the record straight, Python is a programming language that may also be used for scripting. It is a popular programming language that is also an interpreted language that executes at runtime. It is much more flexible and adaptive than most scripting languages as it converts code. Python is a scripting language because it interprets source code. Python is well-liked for its clean and simple syntax and coding in Python requires far less typing than other languages.

Is Python a Scripting language? 

In the natural world, all scripting languages are considered programming languages. The only difference is that the scripting language may be easily interpreted without the need for compilation. Python is a programming and scripting language that is considered to be one of the most popular computer languages. An interpreter is used to translate and execute its code. Python’s use as a scripting language is thus justified. A scripting language is indeed a programming language that automates a repetitive process involving more or less the same types of steps while running a process or application. It will help to decrease human efforts, save time, and lower expenses even further. To run the program in scripting languages, a separate runtime execution is required. The majority of scripting languages are interpreted instead of constructed. Scripting language refers to a language that is interpreted. Python is a scripting language. Python’s code is translated and executed using an interpreter. It is therefore a scripting language.

Is Python the best Scripting language?

Python is unquestionably a leading scripting language on par with JavaScript or C++, and it is among the most widely utilized by firms and companies. Python remains relevant, despite being nearly thirty years old, because of its convenience of use, thriving community, and numerous applications. It’s adaptable and provides everything software developers require. Python is a worthwhile investment of time and effort. It’s advantageous on numerous levels. It is a tough and powerful programming language. Python has something for everyone, even if you’re a beginner or a seasoned coder.

Why has Python become so popular?

One of the languages that continue to rise in popularity year after year, is Python. Python is used in web programming, artificial intelligence (AI), machine learning (ML), data analysis, operating systems, mobile application development, and gameplay creation. Python’s popularity among developers can be attributed to several factors, including:

  • Supportive Community:

 Positive community involvement benefits a coding language in a variety of ways, particularly whenever the language is open-source. Python is a free programming language that comes with several essential libraries, tools, as well as online documentation. There is a wealth of material, guidelines, and tutorial videos accessible for the Scripting language that learners and developers of all skill ages and levels can use to improve their understanding of the language.

  • Easy to learn:

For newbies and novices, this language is relatively straightforward to understand. Python is amongst the most approachable scripting languages today since it has a simple syntax and so is not overly technical, allowing natural language to take hold. Python codes can be produced and performed way quicker than other scripting languages due to their ease of understanding and use. It is also said to be more clear than most other computer languages by many developers. When numerous programmers are involved, it is suited for a shared execution.

  • Abundance of libraries and frameworks:

Python includes good libraries that you may use to pick and save time and effort on the original production cycle, thanks to its corporate backing and large network of support. It is made up of many frameworks and libraries. These can assist a developer in simplifying and speeding up the process. Python enables developers to make the most of these packages and frameworks. Many cloud media providers also provide cross-platform access through library-like services, which can be incredibly useful.

  • Highly secure:

Do you want to choose Python for your startup but are confused about it? Are you worried if it is a secure option or not? Python is often regarded as one of the safest computer languages. White box testing, unit testing, integration testing, and other security aspects are used. It has the ability to withstand a wide range of strikes.

  • Super efficient:

Python applications may be developed and deployed in almost any environment, with next to no performance loss regardless of platform. Another advantage of the Python language’s adaptability is that it may be implemented in a wide range of situations, including mobile apps, desktop apps, web development, hardware coding, etc. Python’s adaptability makes it more appealing to use because of its wide variety of uses. 

Conclusion:

Python has become one of the most popular coding languages among the developers’ community, be it for programming or scripting. It is indeed a very good scripting language. 

Should I use python for data analysis? Marketing February 26, 2021

 

Should I use python for data analysis

Python programming is internationally one of the fastest-growing languages. Python is used to handle data in an efficient manner. It was designed by Guido van Rossum and first appeared in 1991 in the Netherlands. Data scientists use it frequently to handle their data better because of its high potential in the data science sector. It can be used for scripting applications or building web applications also. 

In this era of technology, we have to store, maintain and process data with a lot of data with accuracy. Incorrect handling of this data can be expensive and time-consuming. Many programming languages offer the same and Python is one of them. All of them are unique in their way. But some features of Python make it different from any other language. First of all, it has an amazing robust ecosystem which makes it easier to read and learn. Secondly, it has a set of data-oriented feature packages. That makes programming easy and speedy for the programmers. Programmers must consider Python for data analysis due to its capability and ongoing improvement it is great for mathematical computations and algorithms.

DATA ANALYSIS

Data analysis refers to collecting raw data and converting it into logical and statistically meaningful data. It is helpful to draw conclusions, generate insights and make better decisions for the company. Nowadays, businesses need to maintain and manage large volumes of the data generated. That helps them to extract useful information. There are many tools through which data analysis can take place. For example- Python, Java, SQL, etc.

IMPORTANCE OF DATA ANALYSIS

1. Through data analysis, we can obtain accurate data for our business strategies. You can get to know about the target set or actual outcome and can make plans accordingly.

2. We can get to know about areas which are overfunded and help to cut down our cost.

3. Data analysis also gives us an idea of future consumer behavioral patterns. It enables us to make future inventions in our products.

4. Through sentiment analysis, we can analyze customer reviews online. This will help us to know about negative or positive reviews about our products. We can make changes in our products accordingly.

5. Data analysis can anchor your graphic design and digital marketing strategies.

6. Data analysis can be used to take action to enhance productivity and business gain.

7. Also, we can collect information about our customer’s demographics. Through which we can target the consumer group accordingly.

WHAT MAKES PYTHON A SOUND OPTION FOR DATA ANALYSIS?

Python is a data-centric programming language. It offers a lot of facilities and tools to programmers. These tools and features make data analysis easy and cost-effective. Let’s take a look at some of its features that make it a sound option for data analysis

1. Libraries Collection It has a huge collection of tools as libraries. These libraries are available free of cost to any user. These tools save a lot of time and can fix most problems. Some of these libraries are Pandas, NumPy, SciPy, Matplotlib, seaborn, etc.

2. Scalability Python is one of the best languages to scale rapidly. There are many approaches to fix the same issue. One can handle all from a few records to billions of rows of data using python.

3. Flexibility It is highly flexible which makes it one of the most requested languages among programmers. We can build data models, web services, can apply data mining, etc using python. Many new models and algorithms can be built on it.

4. Python Community Python has great community support. It is open-source that means it’s available freely and as a result has a large community. It employs a community-based development model. 

5. Easy to learn It is one of the easiest languages to start with. It has a smooth learning curve. Its ecosystem makes it very understandable and readable and a great first programming language to start learning.

6. Data handling capacities We can easily install well-tested packages for data analysis in python. We can also handle data available in bulk. It also contains several libraries with renowned algorithms. NumPy and Pandas are some of the mainly used libraries for data analysis in Python.

ECOSYSTEM OF PYTHON FOR DATA ANALYSIS

Python has one of the best ecosystems among all the languages for data analysis. It has a robust ecosystem that makes it one of the easiest languages also. It is growing gradually which makes Python a better platform to work on. It makes it understandable and readable which helps a newbie to learn Python. It has a simple syntax and its commands mimic the English language. It is great for building a data science pipeline and machine learning. It is a general programming language that we can use for production as well as for research & development. Python is easy to write and easily interpretable.

CONCLUSION

Python is a well-structured programming language that is very helpful for any business. Also, it is very easy to learn and understand Python. There are many reasons to select Python as we discussed all the features above in this article. Its tools and features make it more efficient and unique. It gives us various solutions to the same problem which makes it flexible and scalable. It has community support as well as it is open-source. Most programmers prefer Python nowadays. Python is a base for any data scientist, especially for data analysis.