Have you been struggling lately with your design-development workflow? Are you experiencing the handoff problem resulting in poor product decisions? Looking for ways to significantly improve it? Well, you need a Design Systems. It will help you work better, faster and improve your team collaboration. But what really is a Design System?
Well, a Design System is a fairly new idea in the digital transformation landscape. But one that has stirred up a lot of emotions and interest lately.
Known by many names such as Atomic Design Methodology, Component Design, and Design Language, the idea behind a design system is creating a series of design components that can be reused by you and your team.
Airbnb and Uber have fundamentally changed how digital products are designed by implementing their own unique design systems. By using a series of repeatable components and a set of standards that facilitate the use of these components, these companies were able to drastically change the pace of innovation and production within their teams.
What are Design Systems?
When too many people work on the same project and face the same challenges in a design team, each person finding a unique way to solve the problem can result in an incoherent experience for the user when they use the product. The fundamentals of a Design Systems is to manage design at scale.
The definition of a Design System is a series of elements that can be combined and reused on a product by the whole team. It includes colors, designs, components and character styles. These series of components can be reused in different combinations.
Product Design has always been about consistency and predictability. With a unified Design System, you can build products better, faster and it results in a cohesive experience for the user.
A Design System helps companies render exceptional UX and strengthen their brand.
The Handoff Problem:
Previously, Designers and Developers faced a lot of problems. Due to iterations, requirement changes and siloed nature of design and development, handoff posed a lot of challenges. More often than not, it resulted in developers being blocked by designers and poor product decisions.
By focusing on commonly used components, there has been greater collaboration between designers and developers and previously siloed teams are now working off the same mental model. Seeing already existing design system components eliminates a great deal of duplicated effort.
The component-based design model is a great step. It has significantly reduced the need for handoff.
Design System is a consistent approach to product development, one that encompasses guidelines, principles, philosophies, and code. A design system is a perfect tool for scaling the design practice, eliminating the need for hand-off and facilitating greater collaboration.
Difference Between a Design System, Pattern Library and Style Guide
Design Systems are a comprehensive guide on how to design a product. It is not just the classification of components but a whole process. It is a collection of rules, principles and best practices. The main element of a Design System is a library of UI components.
More often than not, a Design System is interchangeably used with a Style Guide or a Component Library. However, these are sub-components of a Design System.
A Design System is far more complex than simple style guides. It includes everything from colors to documentation. What a Design System really does is, it defines a common visual language for the product teams.
It speeds up the design process. A System Design bridges the gap between the teams involved in building a final product with consistent graphics standards, making it super easy to create websites from components. It is like a rulebook for the design and development teams and can be broken down into:
Design System – The entire set of design standards along with principles, patterns, and components on how to achieve them.
Pattern Library- A sub-component of Design System, a pattern library is a repository of reusable components and user interface design elements. Essentially, a pattern library is a collection of design elements that surface multiple times on a site.
Style Guide- Another sub-component of the Design System, a Style Guide emphasizes the visual presentation and determines how products should look. It includes colours, fonts, brand attributes and logos.
Why should you use a Design System?
There are many benefits of this System. It helps the entire company deliver better and more consistent design solutions efficiently. A Design System eases out the process of designing delightful experiences for end-users.
1. Facilitates Consistency-
Building a System begins with classifying all the visual components within a product. This helps in highlighting the biggest inconsistencies within the product and helps the team decide the product’s relevant and most commonly used elements and components. Consistency in Design is the most crucial Design Principle.
2. Better communication-
For the team involved in product development, Design Systems are often referred to as the single source of truth. It helps the team to plan, develop and maintain product quality.
Single source of truth (SSOT) is a concept that organizations apply as part of their information architecture to ensure that everyone uses the same data when making business decisions.
Since it is a single source of truth, this implies it also includes the vocabulary that may be used in the project. Gone are the days when a developer referred to a button as the red colored one. This leads to better discussions between the developers and designers and allows them to talk in the same naming convention.
3. Clarity to Developers-
With a design system in place, developers have a clear vision of how to build the required components while maintaining the unified styles.
4. Iterate Faster-
By implementing a Design System, teams can iterate a lot faster. You can release new designs with lesser resources in small chunks and with shorter feedback loops. It helps you stay organized and up to date with all the design changes your team makes.
5. Leveraging Each Other’s work–
Since Design Systems can be shared across multiple teams, efficiencies can be extended across teams and products. It has become easy to leverage other people’s work, use each other’s innovation without reinventing the wheel.
Operating at scale and improving efficiency and consistency are the main advantages of using and maintaining a Design System. Since you are reusing components in a Design System, the time and effort spent on building one really pays off in the long run. Your design and development team can just tweak the existing products, enhance the experience or focus on building other products.
Examples of Design System
With a staggering rise in the number of devices, environments, and browsers, there is an ever-increasing need to develop thoughtful interface design systems.
Design Systems are an industry standard. Not only do they provide the best team collaboration and keep your project organized, it also provides design guidance which is especially important in larger design teams. In recent years, leading tech firms have shared their design concepts and conventions, and here’s a list of the best design systems:
1. Material Design
Material Design System is widely known for its simplicity of navigation. It is a design language developed by Google in 2014 to create consistency across all Android design and devices and is widely adopted by Android and Web App developers.
2. Atlassian
Atlassian Design System is quite exhaustive and is widely used to create straightforward and beautiful experiences.
3. Polaris
Polaris from Shopify is widely popular for simplifying the designer-developer workflow.
4. Carbon
Carbon Design System is IBM’s open-source design system for products and experiences, with the IBM design language as its foundation.
5. Human Interface Guidelines
Human Interface Guidelines is a Design System prepared by Apple for all their platforms which provides in-depth UI resources and practical information.
6. Grommet
Created by Hewlett- Packard, Grommet is a design system that can help you embrace atomic design methods and build a library that meets your needs.
7. Mailchimp
Mailchimp’s design system is all about bold and creative designs with a focus to provide a consistent structure to the design language.
8. Digital Telepathy
Digital Telepathy is a Digital Design agency. Over the years they have refined a results-driven design methodology to iteratively improve the experience of customers.
9. Sushi
Since the initial design system was not scalable, Zomato recently came up with a new design system called Sushi. It provides a new and enhanced experience to its users with the Zomato app.
How can Design System benefit designers?
Now that you know what is a design system in UX and UX review, and the many benefits of having one, a design system benefits designers and simplifies the tasks for them. As a leading mobile app design company, we noticed that for Designers it has become easy to break down the UI into small parts rather than consider the whole webpage as one entity. You can think of a particular page as a set of components and quickly find and use the right component, pattern or style option( color, icons, fonts, etc.) from the Design System.
Conclusion–
Instead of re-thinking the foundation of each new experience for your products, a Design System keeps designers, developers, product managers as well as multiple stakeholders aligned with the design vision of the company and allows the team to easily focus on pixel-perfect development.
Mobile phones have contributed immensely to the progression of technological advancements. They’re no longer simple communication devices; they’re serving a pivotal role in business, entertainment, communication, and routine tasks of daily life. All this is possible because of mobile application. In the current era, we can easily find an app for every purpose – business, medical assistance, booking a ticket, paying online, games, education, cooking, shopping, or anything. You name it, and they have it. These apps help users from managing daily tasks to planning significant events; they also help promote business and ease communication between sellers and consumers.
The real problem
The real problem here is that users often don’t know what exactly they want. They are not aware of the concept of good application design, except the ones having slight knowledge of designing. One would never hear users praising the excellent design of an application; however, a poorly designed or poorly performing app would stick out like a sore thumb. So for a designer and a developer, the goal is to come up with an “unnoticeable design.”
On that note, let’s take a look at some of the most common mobile app design mistakes. That designers make, which causes an app to become negatively noticed by users.
Top mobile app design mistakes
1. A Poor First Impression
The first look and appeal of an app are critical to attracting a potential user. A user makes a perception about the features and working of an application with his first experience of using it. If something seems confusing or dull, the user might not even give it a second try. Thus, the App Development Company must create an engaging first impression with a user-friendly UI.
Displaying relevant information on the first screen is very important. All the necessary icons like login, logout, the home page, help section, contact information, or any other important features should have their icons on the very first screen. Whatever the app is related to, its key functionalities should be reachable without any complexity.
Other than that, one prime factor that contributes to an excellent first impression is an app’s loading time. If it takes too much time to open the app or load any key feature, users get bored and lose interest. Thirdly, the colour scheme of an app should also align with its purpose. For example, an app used for professional purposes should not have a funky colour scheme, and entertainment-related apps should not be dull or boring. Colours should be bright and solid, or the users might get bored and have a terrible first experience.
2. Poor Information Architecture (IA)
Most designers don’t spend enough time to design a proper information infrastructure for their app. That means the app should have easy access to information; this involves analyzing the most used or required features by users and making them visible in front. This concept is called “Prioritizing based on popularity.”
If you are developing an app with an already existing idea, it would be easier for you to identify the user’s priority by doing a little research. But if you are developing an app for a new business idea, you might not be aware of what users like most. So a designer should be capable of identifying this through his wisdom and experience, or they can release a prototype of the app and collect feedback from users. After that, they can implement the changes in their next release or update.
3. Lack of Design Consistency
Having a consistent design is a significant factor in designing an app’s UI. That means the font type should be the same within the whole app, the layout should be subtle, all icons should be placed correctly, and changing screens should change the visuals. Also, the text should be readable throughout the application.
Maintaining consistency throughout the app is the real trick for a designer. If needed, a little bit of inconsistency can be entertained if appropriately done; for example, highlighting some text or image, placing a great animation or advertisement. But these changes should align with the context of the app. Having a consistent design prevents users from getting confused and help in enhancing their experience.
4. Ambiguous CTA Positioning
“Call To Action” buttons are placed on websites and apps to help and prompt users to take the next step. The positioning of CTAs on webpages not only affects lead capture for businesses but also directly impacts the user experience. To take full advantage of these buttons, designers must ensure that they correctly place them on the screen, and all their aspects are clearly defined. The action of these buttons is mostly mentioned through text placed strategically on them. Care should be taken to make the CTA text as clear and understandable for the user as possible.
5. Too Many Features
Having too many features within a single app is also not a suggested practice. It could make your app slow and congested, and it affects the overall performance of your app. It causes:
Complexity
A slow loading UI
Both of these issues could cause you the loss of potential users instantly. So it is best to have fewer features and serve them correctly. If having too many features is the requirement of your business, you can primarily offer a version with basic and primary functionality to gain the trust of users, and later, you can include new features in future updates.
6. Absence of Default Values
Default values can save noteworthy client exertion in dull assignments, for example, filling in a similar form multiple times. Recognizing key values for form fields can build profitability and decrease annoyance. Your analytics can assist you with the comprehension if there is a most frequently picked choice for a particular field.
Specifically, dropdown menus profit by a relevant default. Numerous applications give “Choose One” as the default decision, compelling each client to communicate with the dropdown and select a value. On the contrary, if you preselect one value (the most used one), probably a few clients won’t need to associate with that dropdown at all.
7. Excessive use of Modals
Numerous applications utilize modal windows to execute communications with information — altering a current thing, including another item, erasing, or in any event, perusing extra insights regarding an item. Modals show up over the current page and the background content is normally darkened (under the presumption that diminishing will decrease interruptions and assist clients with concentrating on the current task). Sadly, this design lessens the options for clients by concealing data that they may wish to allude to while filling the form. (Note that, regardless of whether the concealed window doesn’t contain data required for the editing, clients frequently endeavour to use the work they’ve done beforehand, by copying and pasting past sources of info.)
8. Irrelevant Information
Long series of letters and digits, for example, consequently produced IDs in a database are as often used to exceptionally distinguish an item in an application. These strings are totally insignificant to clients, yet they are frequently shown as the primary section of a table, compelling individuals to check past that first segment to discover the data that they care about. While these good for nothing lists are significant towards the backend, they aren’t supposed to be shown to the users. Particularly in high–data density screens, give some comprehensible data as the primary stay point and push the IDs to a less visible position.
Why do users uninstall mobile apps?
According to statistics, more than 91 billion apps were downloaded from Android and iOS app stores in 2017. It counts 13 apps per person on the entire planet. These stats have only increased since then, and users are getting dependent on these automated solutions. But it does not end here; research also shows that on average, users delete and app within 90 days of its download. Most apps are not opened more than two or three times within 30 days of downloading and are deleted without serving their purpose. The reason behind this is not the user. Users don’t download apps with the intention of not using them. Other factors frustrate them, and they get rid of apps. These factors mostly include poor performance and intricate app design. When an app doesn’t meet the user’s expectations, they switch to another one. And that’s because all that matters is comfort and ease for them.
That is why, while developing an application, it is essential to pay ample attention to its UI design. The goal should be to keep it as simple as possible, the colours should be soft and pleasant to the eyes, and the performance should be up to the mark. That would make an app popular among its users.
CONCLUSION
Despite the fact that the field of mobile application designing has progressed significantly from its initial arrangement, 2020 is expected to see an extraordinary increase in the number of both great and terrible applications. Indeed, even the apps which make it in 2020, there’s no assurance they will cut in 2021. It’s all about steady change. Designers need to continue updating their knowledge about user patterns and the user-psychology that drives these practices. The most important thing to be taken care of while designing an app is to think from a user’s perspective. Don’t choose or reject a colour, font, or design because you like or dislike it. Instead, research and go for what is trending. You can experiment by adding new things to your app to avoid mobile app design mistakes, but changing the whole designing rules is not recommended. It confuses users as they might have got along with the traditional practices, and your experiment could prove to be a big disaster. What works for others will undoubtedly work for you too.
Imagining Artificial Intelligence in situations and use cases where there are a massive number of data in picture makes perfect sense. But what happens when the situation is entirely based on human discretion? Will an artificial intelligence user experience design would also be able to do what AI did to several other industry verticals?
Designing, almost in all its different forms is driven by keeping the human part of process at a much higher ground than the analytical and data driven side. While there are some domains like CAD design or Product Design that leaves some space open for machine learning to enter, when the design form in question is mobile app design, the gap seems to become negligible.
However, Artificial Intelligence, like a number of other industries have found a place in the Mobile App Design vertical as well, giving birth to the concept of artificial intelligence user interface design. A concept that is ought to bring a new level to the relationship between artificial intelligence and customer experience.
While, the answer to whether machine would replace designers is next to impossible, there are ways that the designer community has started taking AI user experience together in their journey to designing memorable mobile apps in multiple ways, like –
Getting time-taking manual works like image resizing automated
Making designs localized by taking help of AI based translation
Bring system consistency between users and products
Give insights into which elements are users interacting with, which needs attention
This participation that the deisgning industry is witnessing coming in from the AI driven UI domain is something that is showing to have a huge impact on the industry’s present, while paving the way to a world where AI and the future of design is much better linked.
Now that we have seen the impact that AI carries on Mobile app Design and how it is soon becoming one of the proven tips to enhance mobile app design, the next step is to look at the principles that guide their unison in the domain of designing AI experiences
The Guiding Principles that Combine Mobile App Design with Machine Learning
Develop a Shared Language
Elements like user experience review, product vision, and business goals are something that needs to be understood and shared by the complete team. You would only be able to create a meaningful and truly intelligent user experience if the mobile app design and machine learning development methods complement each other through shared concepts and common language. The machine learning experts and user experience designers should come together to develop a common blueprint which includes data pipelines and user interfaces, with the aim to set a blueprint that grounds the team’s product planning with the users’ reality.
Focus on Use Case
The important thing when developing a consumer facing app, as the top software designers would tell you, is not the technology that backs it but the business goal and the user experience that you plan on achieving. And so, it is extremely important that you crystallize the use case. With a separate focus on the use case, you can then put your intricate attention on the user flow, which then allows the team to identify the main points where machine learning can be added to enhance the experience.
A clear understanding of the use case also enable teams of the mobile app design company to determine the right KPI for the development of user experience program, which in turn is aligned with machine learning metrics.
Mix Quantitative and Qualitative Data
In order to understand the true impact of combining the machine learning solution and user experience design, it is important that both qualitative and quantitative data is considered. You should make use of qualitative research methods like questionnaires, interviews, etc to measure how the users are experiencing your app.
The reason why we are emphasizing on using a combination of quantitative and qualitative data is because when designing a new app, it is possible that you meet unexpected factors that affect machine learning developmant and user experience. Factors like: Effectiveness of feedback loop, ability of data point capturing intention and user behaviour, which are must to know parts of Artificial Intelligence app design can best be answered only after a deep consideration of both the data types.
Bring Your Combined Data to Real Life Setting
How do you make sure that machine learning is actually used to develop comprehensible and fluent user experience? By setting up an end to end solution that shows how machine learning and user experience fit together in real world. An MVP that includes the working data pipeline along with the machine learning models makes it easy to iterate the AI assisted design together and helps in getting a direct feedback from the users via beta or user testing.
When both UX designers and Machine Learning experts of your partnered AI app development company share the understanding of product design issues, iteration is productive and fast. While on the other hand, user experience designers become aware of possibilities that surrounds machine learning: when it can be used to improve the user experience and how.
Be Transparent About Collecting Data
Designing for AI and with it, needs a constant effort and for it to be absolutely on point, it is important that you give a special focus to the data you have collected. It is very important to consider the end user side in this cycle of collect data – convert data into information – iterate design. Tell users that their data is being used to feed the AI and give them the option to alter the collected information in a way that the best context comes through. In addition to giving users the option to change what data is collected by the AI, you should also give them the option to change what the AI learns – to ensure that the predictions are what the users desire.
While these principles that we just saw help in giving some clarity into how the combined AI and UX design should function, let us look at how some of the famous designing and editing tools that are backed by the developers community across the globe are using the technology to offer better mobile app user experience.
Tools That Use Artificial Intelligence for Design
Tailor Brands
The Tailor Brands logo maker is a famous product used by businesses to get professional logo in a small budget. The AI designs are built upon with your input coming in form of information that would be entered in logo.
Adobe Photoshop
The Select Subject functionality that Photoshop offers make use of AI for memorizing the shape, and then shifting, changing, and editing them with much ease. The tool works on an internal AI system known as Sensei that enables changing backgroungds by recognizing the different subjects in the image.
Prisma and Deepart
Both the famous image editing tools/AI design software make use of artificial intelligence for identify the different aspects of your video and photo and transforming them in a style of your choosing. They give you the option to work around filters and colours among other things.
Let’s Enhance
One of the most frequently arising issues in the designing industry is low quality images. Let’s enhance, powered by AI improves the quality of images using three filters. Anti-JPEF filter converts image to high quality PNG while Boring filter scales up image to around 4 times without any compromise on the image quality. Magic, the third filter allows you to add detailing inside the image. Making Artificial Intelligence a primary part of the Mobile App Design process is something that comes packaged with several add on factors that have to be considered to ensure that that User Interface and User Experience is intact.
And this in turn is not an easy process.
Packaging your app’s user experience with Artificial Intelligence in a way that the whole process gets translated into Artificial Intelligence design patterns calls for a lot of homework, which in itself is heavily dependent on the information that the users provide with consent.
If you are just starting with making your designs smarter, there are some UI patterns that would help you start on the intelligent journey.
A. Criteria Sliders
A number of apps use machine learning algorithms to predict an outcome or pass recommendations. A criteria slider comes in handy here for it helps userss adjust and then fine tune recommendations on the basis of criteria that is meaningful to them. Here, you will have to ensure that the criteria that the users are manipulating with is mapped correctly to data which the machine is using in algorithms.
B. Like and Dislike Button
A simple like and dislike button help better the user experience that someone shares inside the application. Wwhen you ask users to feed in their experience even through a simple like and dislike button, you give them the option to not just build upon the recommendation system but also give feedback on what they don’t like and why.
C. Confidence Inducing Tips
More often than not, users not just not know how the whole prediction and artificial system works, but also they don’t know how much confidence they can place in the system. When you ask users to feed in their data or answer questions in return of something – better matched clothes choice, next show to follow option, etc. The confidence quotient increases even more when you give users the result and let them approve or disapprove it. Doing this makes your users in charge of the charge – something that automatically instills confidence in the app.
D. Give them an In and Out Option
Not all users would want to feed in data for you to fetch and feed in the artificial intelligent system or even want to take the smart route. So, give them the option to opt in and out of the smart options as and when it suits them. Doing this, they would not just have a more positive outlook towards your app but also, knowing that they have an out option, they will be more willing to add in their data in the future.
Now that you have seen the ways AI powered UX is impacting the app design industry, the guiding principles of designing for AI, tools that are already using AI, and the UI patterns that you should add in your design manifesto to make your users open to the idea of AI, there is only one last thing left to do.
And that last thing is to make AI an active part of your mobile app design process. Let our team of UI/UX designers help you with that.
When we talk about the present, we don’t realize that we are actually talking about yesterday’s future. And one such futuristic technology to talk about is how to implement ML and how to add AI to your app. Your next seven minutes will be spent on learning what is the role of Machine learning and Artificial intelligence in the mobile app development industry and what you can do to take advantage of it.
The time of generic services and simpler technologies is long gone and today we’re living in a highly machine-driven world. Machines which are capable of learning our behaviors and making our daily lives easier than we ever imagined possible, all the way, making it necessary for us to understand the process of integrating Machine Learning and Artificial Intelligence into apps.
Technological realm today is fast-paced enough to quickly switch between Brands and Apps and technologies if one happens to not justify their needs in the first five minutes of using it. This is also a reflection upon the competition this fast pace has led to. Mobile app development companies simply cannot afford to be left behind in the race of forever evolving technologies.
Today, if we see, there is Artificial Intelligence and Machine Learning incorporated in almost every mobile application we choose to use. Which makes it all the more important to know How to integrate machine learning and artificial intelligence in mobile apps.
For instance, our food delivery app will show us the restaurants which deliver the kind of food we like to order, our on-demand taxi applications show us the real-time location of our rides, time management applications tell us what is the most suitable time to complete a task and how to prioritize our work.
In fact, Artificial Intelligence and Machine Learning that were once considered top complicated technology to work on or even comprehend is something that has become an everyday part of our lives without even use realizing of its presence. A proof of which is the following functionalities offered by the top brand apps.
The wide inclusion of the two related technologies has made the need for worrying over simple, even complicated things cease to exist because our mobile applications and our smartphone devices are doing that for us.
The below provided stats will show us that ML and AI powered mobile apps are a leading category among funded startups and businesses.
Allied Market Research has predicted that the market for ML will reach $5,537 million in 2023 further demonstrating its growing prevalence.
According to the 2019 CIO Survey by Gartner, the number of companies implementing AI technologies in some form has grown by 270% in the past years.
According to Microsoft, 44% of organisations fear they’ll lose out to startups if they’re too slow to implement AI.
Research by Fortune Business Insights predicts that $117.19 billion is the expected value of the global machine learning market by 2027 at a CAGR of 39.2% during the forecast period.
The Wall Street Journal, states that the advancements in AI and machine learning have the potential to increase global GDP by 14% from, now until 2030.
The idea behind any kind of business is to make profits and that can only be done when they gain new users and retain their old users. The difficult task can be made easy through AI as it comes as one of the benefits or advantages of integrating machine learning and artificial intelligence in apps.
Ways To Implement AI and ML
There are three primal ways through which the power of Machine Learning and Artificial Intelligence can be incorporated in mobile apps to make the application more efficient, sound, and intelligent. The ways which are also the answer to how to add AI and ML to your app.
Reasoning
AI and ML are two proficient technologies that imbibe the power of reasoning for solving problems. Applications like Uber or Google Maps that are used by individuals to travel to different areas, many times change the course or route based on the traffic conditions. This is where AI works – by harnessing its thinking capacities. This facility is what makes AI beat a human at chess and how Uber makes use of automated reasoning for optimizing routes to get the users to reach their destination faster.
Hence, real-time quick decisions are presently being controlled by AI to provide the best customer service.
Recommendation
As you are familiar with OTT platforms like Netflix, Amazon, and others; the streaming features of these platforms acquire a large number of customers with high rates of user trust and retention. Both Netflix and Amazon have implemented AI and ML into their applications that examine the customer’s decision based on age, gender, location, and their preferences. The technology based on the customer’s choices then suggests the most popular alternatives in their watch playlist or that individuals with similar tastes have watched.
Giving the users insight into what they would require next has turned out to be the secret of success of some of the top brands in the world – Amazon, Flipkart, Netflix, amongst others have been using the Artificial Intelligence backed power for a very long time now. This is an amazingly popular technology for streaming services and is currently being executed into numerous other applications.
Behavioral
Learning how the user behaves in the app can help Artificial Intelligence set a new border in the world of security. Every time someone tries to take your data and try to impersonate any online transaction without your knowledge, the AI system can track the uncommon behavior and stop the transaction there and then.
These three primal bases that answer what are the best ways to incorporate machine learning and AI in application development can be used in multiple capacities to enable your app to offer a lot better customer experience.
And now that we have looked at how to integrate AI in android apps along with integration of ML, let us answer the why?
Why should you integrate machine learning and AI into your mobile app?
Why to Integrate Machine Learning and AI Into Your Mobile App?
Personalization
Any AI algorithm attached to your simpleton mobile application can analyze various sources of information from social media activities to credit ratings and provide recommendations to every user device. Machine learning application development can be used to learn:
Who are your customers?
What do they like?
What can they afford?
What words they’re using to talk about different products?
Based on all of this information, you can classify your customer behaviors and use that classification for target marketing. To put simply, ML will allow you to provide your customers and potential customers with more relevant and enticing content and put up an impression that your mobile app technologies with AI are customized especially for them.
To look at a few AI ML examples of big brands who are setting standards on how to implement Machine Learning in apps?
Taco Bell as a TacBot that takes orders, answers questions and recommends menu items based on your preferences.
Uber uses ML to provide an estimated time of arrival and cost to its users.
ImprompDo is a Time management app that employs ML to find a suitable time for you to complete your tasks and to prioritize your to-do list
Migraine Buddy is a great healthcare app which adopts ML to forecast the possibility of a headache and recommends ways to prevent it.
Optimize fitness is a sports app which incorporates an available sensor and genetic data to customize a highly individual workout program.
Advanced search
Through the AI and Machine learning based app development process, you will get an app that lets you optimize search options in your mobile applications. AI and Machine Learning makes the search results more intuitive and contextual for its users. The algorithms learn from the different queries put by customers and prioritize the results based on those queries.
In fact, not only search algorithms, modern mobile applications allow you to gather all the user data including search histories and typical actions. This data can be used along with the behavioral data and search requests to rank your products and services and show the best applicable outcomes.
Upgrades, such as voice search or gestural search can be incorporated for a better performing application.
Predicting user behavior
The biggest advantage of AI based machine learning app development for marketers is that they get an understanding of users’ preferences and behavior patterns by inspection of different kinds of data concerning the age, gender, location, search histories, app usage frequency, etc. This data is the key to improving the effectiveness of your application and marketing efforts.
Amazon’s suggestion mechanism and Netflix’s recommendation works on the same principle that ML aids in creating customized recommendations for each individual.
And not only Amazon and Netflix but mobile apps such as Youbox, JJ food service, and Qloo entertainment adopt ML to predict the user preferences and build the user profile according to that.
More relevant ads
Many industry experts have exerted on this point that the only way to move forward in this never-ending consumer market can be achieved by personalizing every experience for every customer.
According to a report by The Relevancy group, 38% of executives are already using machine learning for mobile apps as a part of their Data Management Platform (DMP) for advertising.
With the help of integrating machine learning in mobile apps, you can avoid debilitating your customers by approaching them with products and services that they have no interest in. Rather you can concentrate all your energy towards generating ads that cater to each user’s unique fancies and whims.
Machine Learning app development companies today can easily consolidate data intelligently that will in return save time and money went into inappropriate advertising and improve the brand reputation of any company.
For instance, Coca-Cola is known for customizing its ads as per the demographic. It does so by having information about what situations prompt customers to talk about the brand and has, hence, defined the best way to serve advertisements.
Improved security level
Besides making a very effective marketing tool, Artificial Intelligence and machine learning for mobile apps can also streamline and secure app authentication. Features such as Image recognition or Audio recognition makes it possible for users to set up their biometric data as a security authentication step in their mobile devices. ML also aids you in establishing access rights for your customers as well.
Apps such as ZoOm Login and BioID have invested in ML and AI application development to allow users to use their fingerprints and Face IDs to set up security locks to various websites and apps. In fact, BioID even offers a periocular eye recognition for partially visible faces.
Now that we have looked at the different areas in which application of AI and ML can be incorporated in the mobile app, it is now time to look at the platforms which will make it possible, which we in our capacity has experienced AI app development company have been relying on, before we head on to the strategy that a business should devise to ensure a smooth implementation.
User engagement
The AI development services and solutions engage organizations to offer balanced customer support and a span of features. Few apps provide small incentives to the customers so that they utilize the application consistently. Also just for entertainment purposes, chatty AI assistants are there to help the users and hold a discussion at any hour.
Data mining
Data mining, also known as data discovery, includes analyzing the vast set of data to gather helpful information and collect it in different areas, including data warehouses and others. ML offers data algorithms that will generally improve automatically through experience based on information. It follows the way of learning new algorithms that make it quite simple to find associations inside the data sets and gather the data effortlessly.
Fraud detection
The cases of fraud are a worry for every industry, particularly banking and finance. To solve this problem, ML utilizes data analysis to limit loan defaults, fraud checks, credit card fraud, and more.
It also assists you with determining an individual’s capability to take care of a loan and the danger related with giving the loan. E-commerce apps frequently exploit ML to discover promotional discounts and offers.
Object and facial recognition
Facial recognition is the most loved and latest feature for the mobile apps. Facial recognition can help improve the security of your application while additionally making it faster to login. It also helps in securing the data from unknown sources.
With the improved security, facial recognition can be utilized by medical professionals to evaluate the health of patients by examining a patient’s face.
Best Platforms to Develop a Mobile App with Machine Learning?
1. Azure
Azure is a Microsoft cloud solution. Azure has a very large support community, and high-quality multilingual documents, and a high number of accessible tutorials. The programming languages of this platform are R and Python. Because of an advanced analytical mechanism, the AI app developers can create mobile applications with accurate forecasting capabilities.
2. IBM Watson
The main characteristic of using IBM Watson, is that it allows the developers to process user requests comprehensively regardless of the format. Any kind of data. Including voice notes, images or printed formats is analyzed quickly with the help of multiple approaches. This search method is not provided by any other platform than IBM Watson. Other platforms involve complex logical chains of ANN for search properties. The multitasking in IBM Watson places an upper hand in the majority of the cases since it determines the factor of minimum risk.
3. Tensorflow
Google’s open-source library, Tensor, allows AI application development companies to create multiple solutions depending upon deep machine learning which is deemed necessary to solve nonlinear problems. Tensorflow applications work by using the communication experience with users in their environment and gradually finding correct answers as per the requests by users. Although, this open library is not the best choice for beginners.
4. Api.ai
It is a platform that is created by the Google development team which is known to use contextual dependencies. This platform can be very successfully used to create AI based virtual assistants for Android and iOS. The two fundamental concepts that Api.ai depends on are – Entities and Roles. Entities are the central objects and Roles are accompanying objects that determine the central object’s activity. Furthermore, the creators of Api.ai have created a highly powerful database that strengthened their algorithms.
5. Wit.ai
Api.ai and Wit.ai have largely similar platforms. Another prominent characteristic of Wit.ai is that it converts speech files into printed texts. Wit.ai also enables a “history” feature which can analyze context-sensitive data and therefore, can generate highly accurate answers to user requests and this is especially the case of chatbots for commercial websites. This is a good platform for the creation of Windows, iOS or Android mobile applications with machine learning.
6. Amazon AI
The famous AI based platform is used to identify human speech, visual objects with the help of deep machine learning processes. The solution is completely adapted for the purpose of cloud deployment and thus allowing you to develop low complexity AI-powered mobile apps.
7. Clarifai
The solution based on AI analyzes information with the help of complicated and capacitive algorithms. The apps made using the platform (which can be integrated in-app using REST API) – can adapt to individual user experience – which makes it the most preferred choice for the developers who wish to invest in Artificial intelligence for app development to enter the world of intelligent assistants.
With this, you now know that the ways your mobile app can become an AI app and the tools that will help with Machine learning and AI app development. The next and the last and the most important part that we are going to discuss now is how to get started.
How to Start Implementation of AI into Apps?
Implementation of Artificial or Machine Learning in an application calls in for a monumental shift in the operation of an application that works sans intelligence.
This shift that is asked for by AI is what demands to look at pointers that are very different from what is needed when investing in the usual mobile app development process.
Here are the things that you will have to keep into consideration when managing an AI project:
Identify the issue to solve through AI
What works in case of applying AI in a mobile app, as we saw in the first illustration of the article is applying the technology in one process instead of multiple. When the technology is applied in a single feature of the application, it is much easier to not just manage but also to exploit to the best extent. So, identify which is that part of your application that would benefit from intelligence – is it recommendation? Would the technology help in giving a better ETA? – And then collect data specifically from that field.
Know your data
Before you look forward to AI app development, it is important to first get an understanding of where the data would come from. At the stage of data fetching and refinement, it would help to identify the platforms where the information would come from in the first place. Next, you will have to look at the refinement of the data – ensuring that the data you are planning to feed in your AI module is clean, non-duplicated, and truly informative.
Understand that APIs are not enough
The next big thing, when it comes to implementing AI in a mobile app is understanding that the more extensively you use it, the more unsound Application Programming Interfaces (APIs) would prove to be. While the APIs that we mentioned above are enough to convert your app into an AI app, they are not enough to support a heavy, full-fledged AI solution. The point is, the more you want a model to be intelligent, the more you will have to work towards data modeling – something that APIs solely cannot solve.
Set metrics that would help gauge AI’s effectiveness
There is hardly a point of having an AI or Machine Learning feature implemented in your mobile app until you also have the mechanism to measure its effectiveness – something which can only be drawn after getting an understanding of what exactly do you want it to solve. So, before you head out to implement AI or even ML in your mobile app, understand what you would like it to achieve.
Employ data scientists
The last most important point to consider is employing data scientists on either your payroll or invest in a mobile app development agency that has data scientists in their team. Data scientists will help you with all your data refining and management needs, basically, everything that is needed on a must-have level to stand and excel your Artificial Intelligence game.
This is the stage where you are now ready to implement the intelligence in your mobile application. Since we talked about data a lot in the last segment and because data is an inherent part of Artificial Intelligence, let us look at the solution of problems that can arise out of data as the parting note.
Feasibility and practical changes to make
Now that you have known the which, why and how about the implementation of AI and Machine Learning apps, you might have an idea regarding a plan in mind like what steps should be taken as a top priority and how your application would work/appear, once the changes are made. Along these lines, it is an ideal opportunity to perform a couple of checks prior to moving ahead, for example, –
Perform a quick possibility test to know if your future execution will profit your business, improve user experience and increase engagement. A fruitful upgrade is the one which could make the existing users and customers happy and attract more individual towards your product. If an update is not expanding your efficiency, then there is no reason for putting in effort and money for it.
Analyze if your current group can deliver what is required. If there is less or no internal team capacity then you need to hire new employees or outsource the work to a reliable and expert artificial intelligence development company.
Data integration and security
While implementing Machine Learning projects for mobile applications, your app will require a better information configuration model. Old data, which is composed in a different way, may influence the effectiveness of your ML deployment.
When it is decided what abilities and features will be added in the application, it is important to focus on data sets. Efficient and well organized data along with careful integration will help in providing your app with high-quality performance in the long run.
Security is another basic issue, which can’t be overlooked. To keep your application strong and secure, you need to think of the correct arrangement to integrate security implications, clinging to standards and the needs of your product.
Use strong supporting technological aids
You need to pick the right technology and digital solutions to back your application. Your data storing space, security tools, backup software, optimizing services, and so on should be strong and secure, to keep your app consistent. Without this, the drastic decrease in performance may occur.
Solutions to the Most Common Challenges in AI Technology?
Like any other technology, there is always a series of challenges attached to AI as well. The basic working principle behind machine learning is the availability of enough resource data as a training sample. And as a benchmark of learning, the size of training sample data should be large enough so as to ensure a fundamental perfection in the AI algorithm.
In order to avoid the risks of misinterpretation of visual cues or any other digital information by the machine or mobile application, the following are the various methods which can be used:
1. Hard sample mining
When a subject consists of several objects similar to the main object, the machine is ought to confuse between those objects if the sample size provided for analysis as the example if not big enough. Differentiating between different objects with the help of multiple examples is how the machine learns to analyze which object is the central object.
2. Data augmentation
When there is an image in question in which the machine or mobile application is required to identify a central image, there should be modifications made to the entire image keeping the subject unchanged, thereby enabling the app to register the main object in a variety of environments.
3. Data addition imitation
In this method, some of the data is nullified keeping only the information about the central object. This is done so that the machine memory only contains the data regarding the main subject image and not about the surrounding objects.
Concluding Thoughts
Now that you know the reasons and how to implement mobile apps, it is time to apply the top-notch performance and quality for AI and ML together to bring out the best in the application. AI and ML together are the future of advancement of mobile app development.
If you are still confused and want to clear your doubts, you can contact us. If you are looking to develop an app that is advancing with the time and technology and want to update your existing app with all the latest technology features, then you should partner with ML and AI development company that is well-adapted with the changing market needs. You can also opt for professional development providers in your area like AI development services USA or other regions. But make sure you choose the best to get quality results.
Not many people are familiar with the benefits of mobile app deep linking but the truth is there are benefits.
The technique not only provides better user engagement but also helps in tracking the most effective campaigns.
In this blog, we will talk all about deep linking in mobile apps and much more. Let us begin with a general idea about deep linking in mobile apps and then move on to further segments.
What is deep linking?
Technically, a deep link is any link that takes a user to any specific content. Deep links are used within mobile applications to locate specific content. Almost all the web links are deep links. Deep links will not only open your app but also will use the information in the link to perform a specific action.
For instance, if the link to your Facebook profile is fb://profile/, then the Facebook app will be launched and will open your profile. This is how deep linking functions. It does more than just launching an app when a link is clicked.
What are the different methods of deep linking in mobile apps?
Deep linking apps may have more than just one method. Deep links with apps provide a solution to the problem that has been bugging the users for a long time now. So basically, web links didn’t work with native apps and whenever the link to a certain product from an app was clicked, the web browser was launched. But when mobile deep linking is done then the link straight away launches the app on the specific page.
Here are some different ways mobile app deep linking is done:
1. Traditional deep linking
Traditional deep links work as long as the app is already installed when the link is clicked. When a user clicks on the link, the device will open the app and not the web browser. If a user does not have the app installed already then the result will either show error or an alternative page.
2. Deferred deep linking
As the word ‘deferred’ suggests, this method of mobile app deep linking directs the users even when the app is not installed. With deferred deep linking when users without the app, click on the link, they will be directed to the app in the Play Store or App Store. Once the app is installed then the user will be taken to the specific content immediately post the first launch.
3. Contextual deep linking
Contextual deep links have all the functionality of deferred deep linking and more. In this method of deep linking app, information about the users’ desired actions is stored. Information like where the user wants to go next, who was the original sender of the link and many other custom information is stored.
This type of linking is great for both users and developers. The developers can build amazing content with personalized messages and the users get better user experience.
4. Custom deep links
Custom deep links or custom URI schemes were the original way of deep linking. These links act as a private internet for the app, giving users a better experience. The advantages of using URI schemes is that they are easy to set up and most of the apps already have it.
URI scheme deep linking is still used for deep linking Android but for iOS app deep linking is no more done with this method. Apple blocked this method in 2015 when it launched the Universal Links for deep linking iOS apps.
5. Apple iOS Universal links
The custom URI schemes had a lack of proper fallback functionality which is why Apple blocked in 2015. With iOS 9, Apple launched Universal Links that locate the content on a web page or in the app. What iOS does when a link is clicked is that it checks for any apps associated with the link. If yes, then it launches the app and if no, then the link is opened in Safari. In a study, it was found that Universal Links have increased the conversion to open by 40%.
6. Android links
Google also created App Links to match the iOS Universal Links and has somewhat the same functionality. The link leads to both webpages and apps depending on the presence of an app in the device. But since Android still has URI schemes running quite well, developers aren’t adopting the App Links that much.
There are innumerable benefits of using deep linking for your app and by now you might have already figured out some of them. Even though the adoption of deep links was quite slow in the past because of its unknown benefits yet it was still being used. And today the benefits are said to be the reason why deep linking is even considered for mobile apps. Here, we will lay down some benefits of deep linking app.
Why use Deep Linking for your app?
1. Enhancing the user experience
It wouldn’t be a surprise to know that deep linking plays a part in enhancing the overall user experience of an app. As much as the UI is important for an app, deep linking is an integral part of it. Users have the freedom to access content via deep links on the app or the web page.
2. User retention, usage, and engagement
What is a deep link to an app? Speaking non-technically, it is a way to bring in more engagement, ensuring high retention and high usage. As seen in the graph above, apps having deep links have more activation rate and more app visits. When compared to apps without any deep links, users are less active and the app has a low engagement rate.
3. User onboarding
Deep links with apps help developers in personalizing the onboard experience. If we take the case of contextual deep links, a developer can easily create personalized application invitations or may as well include some incentives in the user onboarding flow.
4. Re-engaging users
It is very important for an app to have active users but sometimes there are inactive users. With deep linking, you can direct those inactive users to specific content or page on your app which will result in more active users. Sending deep links with push notifications is a great way to do that.
5. Marketing benefits
Deep linking can help in increasing the sales and revenue of a company. The thing with deep links is that they can direct users to any page of content from the app and that is why this can be strategically used to generate more sales. An e-commerce app can use deep links to send notifications about the latest deals and offers and direct users to the offers section.
6. Effectiveness of campaigns
As we saw earlier that contextual deep linking stores custom data about users and their behavior on the app. This information can be used to see which campaign and sources are most fruitful for driving audience or increasing engagement and sales.
When you shouldn’t go for deep linking apps?
Is deep link service for everybody to go with? Well, the benefits are compelling enough to go for it. But it does not mean you should always go where the benefits have an edge. Deep linking may not be the wisest choice for many app owners.
The reason why deep linking apps may not be the right choice for you depends on the app you have. If your native app has poor UI/UX or has a lot of glitches, you can spare your users the trouble of going through such an experience.
The only reason you should be using deep linking in your app is if the app experience is better than the web experience. If not, then it will not be the best decision.
Apps that are totally focused on the industry it is in and has the need to push notifications, filtering search results, etc. should have deep linking. It will be of great use if users find more comfort in shifting from a webpage to an app and that can only happen if the app is worth it.
So, how to use deep linking in mobile app?
Deep linking can be used in both iOS and Android apps. The condition for iOS apps is that deep links are supported in iOS 9.0 and above versions whereas all versions of Android support deep links.
Let us show you the different ways deep linking is done.
1. Mapping out URLs from the website for the app
The first step is to map out the URLs you will be using in your app. You have to make a match of which specific URLs of your website will represent what pages in your app. Also, keep in mind that not every link needs to be mapped.
For instance, if your website has a Blog section then you don’t need to direct users to app for reading a blog. Whereas, you can direct users to your app if they search for any products. It is very important to understand here that users should not be forced to visit the app.
One thing to keep in mind is that the users should only be directed to the app if you can show what they have been looking for. There is nothing worse than an annoyed user who may never return.
2. Universal Links for iOS
By now you know that Apple uses Universal Links for deep linking iOS for version 9.0 and above. The Universal Links not only provide a better user experience but also has good compatibility with the iOS 9.0.
It is recommended that you don’t implement the support for iOS 8.0 and below since it’s not going to be worth the effort. This clearly means that deep linking won’t work for any user having iOS 8.0 or below. However, Apple reported that 83% of iOS users have upgraded their iOS to 12.0 so it shouldn’t be much of a loss. In fact, this number is growing rapidly in the US and Europe.
To implement the iOS Universal Links, follow the steps:
Decide what links will launch the iOS app and represent what products on it. For this, you have to create a file on your website such as https://www.example.com/.well-known/apple-app-site-association. This basically informs Apple that the app is yours and therefore it should intercept all the links to products and pages.
The second stage will be updating your iOS app so that it can respond to all the changes being made and can receive the links.
And voila! Your iOS deep linking into the app is done.
3. Android App Links
Android has been using the deferred deep linking Android for a long time. But they launched the App Links in Android Marshmallow 6.0. To implement the same in your follow these steps:
To get your website verified by Android, update your AndroidManifest.xml file.
Create a file on the website such as https://www.example.com/.well-known/assetlinks.json which will prove to Google that the app is yours.
And the deep linking for Android is done!
The last and most important step is to promote your app as much as you can. Users will be directed to your website if they don’t have the app therefore, promoting the app becomes the primary job once deep linking is done.
This is our take on deep linking mobile apps as an app development company. Contact our team of developers at Anteelo to know more.
All the different app development processes take their individual development time.
Although research stages take up around 2 to 3 weeks of development time, when done right, they can not just save time on a later stage but also aid the smooth sailing of processes.
Factors that slow down the mobile app development timeline are changes made mid-project inexperienced developers and use of complex technologies
RFPs, MVPs, and Cross-platform development tend to speed up the app development process.
There is no doubt about the fact that with 350 billion app downloads worldwide, businesses are looking to get the same attention. It’s very normal for a business to inquire about the app development process and the mobile app development cost.
Usually, businesses and clients are interested in knowing how long does it take to create an app, the cost of app development, and all the efforts involved. As soon as they learn the benefits of having a mobile application for their business, they wish to get on with it. Hence, the question how long does it take to develop an app.
{Also read our article on – How much Does it Cost to Develop an App Like Careem & Uber}
Now, usually, the average time to develop an app looks like the below image. But there is no definite time as it depend on person to person and company to company
But there is no definitive-ness. And thus this article.
In this blog, we will not only look at the mobile app development process, factors affecting the average time to build an app but also will determine how long it takes to mobile app development.
Key Stages of The Mobile App Development Process
The app development process has different stages and all of these stages require different time slots. From the planning process until the launch of the application, the entire process is interdependent on each other and requires proper attendance. It is quite obvious that apps with different sizes and different features have different app development time.
Each development stage is discussed below to answer the question ‘how much time does it take to build an app?’
This is one of the main documents that entrepreneurs and app developers often miss out on. Ideally, the better the brief the lesser time it would take to understand the software project and the requirements. In fact, this one step can have a HUGE impact on the time required to develop an app.
There are some things that you have to include in the brief which you are working with such as the company information. But to help give your app development agency a detailed understanding of the project and the mobile app development services they will have to deploy.
The outcome of this stage is usually: The Brief of an App Development Before we look into the different design and development related phases, let us first look into the time it takes to set the basis of all the design and development processes that follow.
Project
Project goals and the success metrics
RFP
NDA
The budget range
Delivery date
Stage 1: Forming ideas and research
It’s easy to get great ideas but it’s not necessary that everyone will agree to it being great. The idea formation and research part very much affect how long it takes to build an app. This stage involves starting with an idea and then researching it for more improvements.
Even if the idea of the app seems right, a test must be run to keep things as real as possible. This can prove to be a very important step taken in the initial stage. Testing application ideas also ensure that when the app is launched in the market, the users are going to love it.
Another thing that this stage involves is targeting the right audience. It is in this initial stage that the right audience is targeted for the app. Defining the target audience not only helps in boosting the app after its launch but also in shaping the app in the right direction.
Different apps have different size and ages of the target audience. For instance, Facebook has all ages of people on its platform whereas Tinder has a younger target audience. Targeting has made these apps so successful therefore is suggested that proper targeting and research should be done.
Analyzing the competitiveness of the market and the app is also necessary. During the research about the app, one should also gather information about the competitors and potential threats. This will prepare the app owners for any difficulties after the app launch.
The entire research takes several weeks. By the end of the research, you should know all the strengths and weaknesses of the competitors, the app strategies and defined target audience.
By the end of this stage, you should get these outcomes:
Minimum Viable Product
User Stories
App Prototypes
Stage 2: Planning it all out
The next stage is the planning stage. Once you know all about your market, its time to plan out the app development process. The planning stage involves decisions regarding the configuration of the app. These decisions include making a choice between iOS and Android, native or hybrid, cross-platform or not, web-based app or mobile app, etc.
Once these plans are made, its time to add on the features. Now the features of an app should be such that neither does it complicate the app nor slows it down. There are many basic features that an app should have such as search bar, social media sharing buttons, profile building, login option, etc. These features make a basic app much convenient for users.
As the app size increases, the features are more and more directed towards the type of app. For instance, any e-commerce app will have the ‘Add to cart’ feature. Similarly, social media apps have the option of media sharing and various other features for engagement on the app.
All these planning is quite complex and will require a month or so.
Stage 3: Design Sprints and Idea Validation
Design sprints processes are being used for testing different aspects of an application. It takes around a week to complete the whole design sprint. The idea of the stage is to test different aspects of the idea and get them validated by a pool of prospective users.
Design Sprint helps businesses understand if users value a feature, how they use it, when they would be using it, how easy or difficult do they think it is to navigate the application, etc.
Stage 4: Development stage
In the development stage, there are three elements that need to be built: the UI, Front End and Back End. Once all the planning is done, the developers and designers will work their magic and start building the app. So how long does it take to build an app? Well, the development and designing stage takes about six weeks.
The UI of an app is taken care of by graphic designers. This gives the apps an appearance to enhance the user experience. UI is important for any app to flourish in the market because the users seem to like visually appealing apps more.
The Frontend and the Backend are also very important components of the app development process. The Front End is what users see and how they act in an app but nothing will make sense until the Back End is developed. The Backend connects the UI with the system and allows the proper functioning of the app. So, how to make a mobile app without either of these? Well, you cannot.
Let us deep dive a little to know what both the engineering processes consist of:
Picking the best development team is never simple, even when you have the best team you are in constant search of more. To help you with the hunt, you can either look for them locally, which is quite difficult or outsource the task to either app development companies or to freelancers that will turn into a team under your influence. Or if you want, you can opt for companies in your area like mobile app development company in USA if you live in the US or any other area where you reside.
Obviously, the most ideal alternative is to find a current development team with demonstrated experience in the industry and direct all the requirements to them. There are a few reasons behind that:
Having a team means that they know each other and are strong as a group.
As the developers know each other thus, their work timings and pace are similar minimizing any sort of delays.
Having a strong team with a project manager will help you to place all your requests to an individual (project lead/manager).
Another incredible benefit of selecting a ready to work development team is that, they will give you the end result and will handle all the application development stages themselves. In addition, proficient groups can provide you with a good understanding of the process of developing apps, guide on improving the work process, and assist you with picking a native or a hybrid app, based on your objectives.
Stage 6: Testing
What does it take to run an app? To know whether the app is even going to run after the development is finished, we need to do test runs. We cannot deny the fact that the app will have some or the other bugs that need to be fixed before the final launch. These bugs can be identified with the help of tests.
There are many ways to test a mobile app’s performance and functioning. We, at Anteelo, have our own strategies for testing mobile apps. The quality assurance tests are run so that users don’t find any issues when they first use the app making the app more likable.
Alpha and Beta testing are done on the app to make the app error-free. After the testing, the app is launched. Post-launch whatever feedback is gathered from the users, the necessary changes are made.
Stage 7: Deployment on Stores
The time that it takes to deploy the app can be divided in two sections: submission & review. When you submit an application, either on the Apple App Store or on the Google Play Store, there are some guidelines you will have to follow, such as:
Screenshots
App Descriptions
Icons
Video or Image demonstration
App Store Optimization
The time stores take for deploying your applications.
When you compare the time it takes to launch apps on App Store compared to publishing them on Play Store, Apple follows a very detailed reviewing process – which increases the launch time to some extent. On the other hand, Google makes use of algorithms for pre-analyzing your apps, thus lowering the app launch time.
What Slows Down The App Development Process?
As seen in the section before, the app development process usually takes about 2-3 months. But there are some things that delay the overall process and the answer of how long it takes to create a mobile app.
Mid-project changes
Developing apps is a continuous process where all the stages are connected to each other in some ways. If there are sudden changes in the plan in the middle then the process is bound to get slower. These mid-project changes can also affect the app’s performance since too many changes in an already built code base can do that to the app.
Unexperienced developers
What does it take to build an app that is successful? Great ideas, proper budget and a good developer, for sure. Often business especially start-ups make the mistake of hiring developers that aren’t up to the mark with the work. This results in slowing down the process as well as a poor app for the business. Our team of app developers is highly skilled with good experience at hand which has allowed us to launch high performing apps one after another. We also have helped our clients with their app ideas so that they get the best outcome for their business.
Complex technologies
Technologies like machine learning, artificial intelligence, VR, AR, etc. cause the slow down of the mobile app development process. There’s no doubt that these technologies make the app a better experience but everything good comes at a price. And the price of using the latest technology is that they might slow down the app development process.
The reason why this happens is that the technologies are a bit complex and takes time to fit in the app.
Industry-wise difference
The industry for which the app is being built also plays an important role in the average app development time. The answer to the question of how long does it take to make a social media app is 1-2 month(s). Whereas on-demand apps take more time to be developed. Therefore, the industry is another factor that affects the time required to make an app.
How to Speed Up The Time of Application Development?
With the fast growth of mobile apps, one cannot afford to slow down in the development process. Businesses, be it startups or enterprises, are looking for mobile app developers who can develop apps faster without compromising the quality of the app.
There are no problems without solutions and the same goes with time required to develop an app. When it comes to startups, then gathering a massive crowd is a survival goal and for that mobile apps are the solution.
By now we know how to create an app and what does it take to make an app? We have also known what factors affect the time to make an app. It’s time to see how we can reduce the time of application development.
MVPs or prototypes are a great way to save time. They can be built easily and resemble the original idea of the application. Once the MVPs are out in public, the actual app can be built by adding features and making improvements. Many businesses like Airbnb, MailChimp, etc. started as MVPs before the actual implementation.
Go for cross-platform
Android vs iOS is the biggest debate of all times and sometimes people get so confused that they don’t know which to choose. The timeline and cost of app development of both the platforms individually are relatively high. But cross-platform app development is a solution for this. With tools like Xamarin and PhoneGap, great multi-platform apps can be built which take less time.
Hire a professional developer
A professional app developer for your app is the best you can do. Not only will the app have amazing UI/UX design but also will take less time to develop. In fact, the hours will only lower if you choose to outsource. Being one of the top reasons why you should outsource, when you choose a professional app development company off-shore, you’ll not just get a good experience but will basically make your work easier. Appinventiv is also a professional app development company that has developed several successful apps for clients.
Agile development
There are numerous app development organizations that follow agile development as it accelerates the development cycle. The main purpose behind agile app development is that the organizations can’t face the challenge of starting all over again. It has a flexible and adaptable programming structure that is ideal for open-ended communication between app owners and developers. To put it plainly, it speeds up the development process and guarantees that the application is developed on time.
White label solutions
White label solutions are products that were produced by one company and then is rebranded and made to look like other company’s. This will save a lot of time since there will be no need to build anything from scratch. However, this will not result in a good application especially not the one that generates huge traffic or sales.
Automated testing
Automated testing, although it sounds a quite obvious thing but this is ignored by many. This type of testing is one of the significant periods of development that reduces the mobile app development cycle. The best thing about automated testing is that it can run a whole set of tests all at once. This decreases the time spent on manual testing and helps in improving the security of the application. Automated testing involves several testing methods that are applied to save time. As the testing process becomes quicker, the development process also aces its speed. Executing more than one testing strategy can offer error free code.
This was our take on the mobile app development process timelines and some ways to reduce app development timeframe. Feel free to contact our app developers at Anteelo for any further queries on how to reduce yours.
Twitter is known for giving a strong voice to people from all corners of the world. The layout and smooth functioning have also made it easy for users to spend more time on the app.
Twitter survived in the world where Instagram, Snapchat and Facebook were ruling and the reason was having honest opinions of the users on the latest topics. However, there are still some issues that need attention for further growth of the platform.
In order to attract more audience, Twitter needs to make some serious changes. The company is going to make some changes by launching Twitter’s new app in beta mode.
How is Twitter’s new beta app going to work? Well, Twitter will have a selected group of people to test the new features in the beta app. These users will have a full-fledged discussion on various new features just like any user can have on any trending topic.
From the discussions, Twitter will pick up all the data and use that to make decisions. The decisions will be regarding the features and whether it should be launched for the entire user base in general.
The app is scheduled to be launched in this week and we will see Twitter’s first look quite soon. Twitter said, “only a few thousand users will be able to get the beta version and not everyone who applies for it”. The users that will be allowed to test the Twitter beta app will be allowed to have an open discussion about the features of the app.
This programme will not be supervised by the NDA unlike other experiment programmes conducted by Twitter. There is more to it than just a basic beta testing app.
Unlike other beta apps, the Twitter beta app will not have final features. The discussion panel will control which features to be built further or which features should not be.
Twitter’s director of product management, Sara Haider, told Techcrunch, “Unlike a traditional beta that is the last step before launch, we’re bringing people in super early,”. The first version of the beta app will have features that will improve the conversations on Twitter. There will be different colour schemes and visual cues to mark important discussions.
Haider believes that there are going to be a lot of significant changes and it should not be dropped on users all at once. This is why Twitter will be slowly launching new additions and making changes in a way that the entire user base can adapt to it easily.
Expected Features in The New Twitter Beta App
1. Colour Coded Replies
The new app will have colour-coded replies. The colours will be different for the poster of the tweet, people you follow and people whom you don’t follow. This will make a clear distinction in a long Twitter conversation. These conversations will also have visual cues to help users find the best and most relevant tweet in the thread.
2. New Algorithms
Twitter is going to have a new algorithm for all the tweet replies. Earlier, the problem was that users couldn’t find the tweets that they wanted to keep updated about. To do so they had to either ‘heart’ it or had to use the ‘Tweets & Replies’ section to find the tweets. With the new update, all the replies will be arranged as per a user’s interest.
In the future, Twitter may also have a ‘highlight’ feature for the tweet replies.
3. Removing Engagement Icons
Twitter users ‘heart’ and ‘retweet’ as a way of engagement. In the new update, there is no heart or retweet icon under every reply. The reason behind this is a simplified view for users who do not wish to engage with the thread. However, this does not mean others can’t engage with the tweets in a thread. By clicking on the particular tweet, the icons will appear just like in the current version.
Twitter was not originally built the way it is today. The platform was updated depending on how the users were using it. The features such as retweet, hashtags, @mentions, and many more were not originally in the app but were added later on seeing the users behavior. The same is being followed with the beta app and we shall see some changes in Twitter soon.
Unless you are living under the rocks, it is likely that you would be familiar with what is Blockchain and what is its potential when it comes to reforming the tech world. The technology, that have been the driving force of Cryptocurrencies, has taken the front seat and come up with a myriad of options to mitigate the traditional challenges that a myriad of industries face, helping them grab better opportunities. It has proven to hold the potential to revamp the whole economy – be it healthcare, travel, education, or legal domain.A ripple impact of which is that today, both startups and Fortune 500 companies like IBM, and Accenture are putting efforts towards making their presence known in the Blockchain arena.
Because of this, rather sudden, mass adoption, the number of Blockchain jobs are increasing in the market exponentially. A clear indication of which is that a 517% rise is predicted in the number of Blockchain jobs in 2019, compared to 2018.
And, behind the curtains, the type of blockchain development platforms and programming languages are also evolving. While many traditional ones are proving to be undisputed leaders, many new entrants are bringing radical changes in the development environment.
This, as a whole, is making it necessary for all Blockchain enthusiasts to be familiar with the best Blockchain programming languages to headstart with. Something we will cover in this article.
But, before that, you will be able to earn brownie points if to go through a blockchain development guide to have a clarity of concepts, and to get familiar with the challenges developers come across while starting their journey in this innovative technology.
Challenges You Might Face While Entering the Blockchain Development World
A. Resource Management
In the Blockchain arena, it is imperative for developers to ensure that they are familiar with real-time network demands and that they are well-versed with opportunities to handle remote and local queries. This, in turn, can be challenging for them to manage their resources efficiently and effectively.
B. Isolation
Another issue faced by Blockchain developers is that all the hash functions operate in a deterministic manner. Meaning, they do not act in two different ways depending on the circumstances.
In such a scenario, the development team has to opt Isolation mechanism to bring non-deterministic nature into their blockchain solution.
C. Lower Performance
Last but not least, Lower performance is also one of the challenges of Blockchain programming that developers often have to deal with. Especially when choosing the right Blockchain development language.
This is because some of the Blockchain operations are parallelizable, while others are not. Meaning, it becomes important for them to bring a language on table that is versatile in nature.
Now that you know what Blockchain programming problems you might encounter while heading your journey to Blockchain development, let’s jump to the core part of this article, i.e, unveiling of the top Blockchain programming languages.
15 Programming Languages to Consider for Developing Blockchain Applications
1. Solidity
Influenced from JavaScript, Powershell, and C++, Solidity is the first blockchain programming language that one must learn. Especially when they have to develop dApps or are looking to get into the ICO development game.
The Solidity programming language was developed by Vitalik Buterin, the mastermind behind Ethereum, and serves blockchain development firm with a myriad of benefits, such as:-
Developer-friendliness,
Accessibility to JavaScript infrastructures, debuggers, and other tools,
Statically typed programming,
Possibility of inheritance properties in smart contracts,
Precise accuracy, etc.
2. Java
Java, the official language of Android mobile app development and a preferred option for backend development, is also considered a great programming language used for Blockchain development.
The language is derived from C-syntax and is widely chosen for building sophisticated Smart contracts and dApps because of its following properties:-
Robust support for OOP (Object-Oriented Programming) methodology,
Ease of memory cleaning,
Availability of ample of libraries.
Some of the best examples of Blockchain solutions developed using Java are NEM, IOTA, NEO, and Hyperledger Fabric.
3. Python
Python has not only ruled the world of app development, IoT app development, and network servers’ development, but is also proving to be an asset in Blockchain-as-a-service arena.
The language, created in 1991, is widely used for dApps and Smart Contracts development because of ample of features it avails. Some of those features and functionalities are:-
Easy to learn,
Access to dynamic architecture,
Perfect for both base and scripting approaches,
Open-source support,
Efficient for Prototyping, etc.
Steem, Hyperledger Fabric, and NEO are a few popular Python based Blockchain projects that are prevailing the industry.
4. JavaScript
Considered for a wide range of app and game development needs, JavaScript is also one of the best Blockchain programming languages to keep an eye on.
The language, in the form of frameworks like Node.js framework, offers developers ample of benefits like:-
Easier and earlier entry to market,
Enhanced Scalability,
Availability of multiple JavaScript frameworks,
No hassle of integration of respective resources, and more.
5. PHP
Released in 1995, PHP (Hypertext Preprocessor) is another programming language that every reputed mobile app development company recommend for creating Blockchain solutions.
The language, though considered as a backend development tech stack in the form of best PHP frameworks, is often used to develop blockchain solutions of different complexity range. Something that is a ripple effect of its huge open-source community and object-oriented features.
6. C++
C++, introduced back in 1985 by Bjarne Stroustrup, is the best programming language for cryptocurrency development.
The language follows OOPs methodology and is highly used for developing cryptocurrencies and Blockchain Projects like Bitcoin, Litecoin, Ripple, Stellar, and EOS. Something that is a direct result of the following set of features and functionalities it offers:-
Efficient CPU management and memory control,
Ease of running parallel/non-parallel threads,
Option to move semantics for copying data effectively,
Compile-time polymorphism for enhanced performance,
Code isolation for different data structures, and more.
7. C#
Created by Microsoft as a substitute of Java, the OOP language offer a huge number of features for enterprise-powered apps, cloud, and cross-platform development. The language comes loaded with features of C, SQL, and .NET frameworks, and is highly favored for Blockchain development because:-
It is open source.
Its syntax is easy to understand and learn – thanks to its identicality with C++ and Java.
It empowers developers to write portable code across devices.
It is cost-effective to use because of BizSpark program.
The programming language is majorly considered for building dApps, Smart Contracts, and infrastructure in Blockchain environment.
8. Go
Go programming language also lands in the list of top Blockchain coding languages with a blistering success.
The language is not just easy to comprehend, but also comes with the best features of JavaScript and Python such as user-friendliness, scalability, flexibility, and speed. Something that makes it the right option to deliver bespoke Blockchain solutions.
Two of the best Go-based Blockchain solutions prevalent in the market are Go-Ethereum and Hyperledger Fabric.
9. Simplicity
Created by Russell O’ Connor, Simplicity is a high-level Blockchain coding language that hit the market in November 2017.
The Simplicity programming language is based on Ivy and work with a Haskell-like syntax which makes coding easier and effective. Besides, it is highly mathematical in nature and makes the codeline human-readable. Because of which, it is highly used for developing Smart Contracts and blockchain solutions that works with both Bitcoin and Ethereum Virtual Machine (EVM).
10. Ruby
Ruby is yet another top Blockchain development language to headstart your career with.
Developed by Yukihiro “Matz” in the mid-1990s, this high-level and general purpose programming language empowers developers to prototype their vision effectively and effortlessly through open-source third party APIs and plugins. The language also gives developers an opportunity to mix its features with that of other languages to build an enhanced platform.
It is highly considered by Asian developers for building Blockchain-based software and platforms.
11. Rust
Though newbie in the Blockchain ecosystem, Rust is also being widely considered for building innovative, immutable, and secure solutions.
The language enables open-source developers to create quick and effective Blockchain frameworks. It also serves them with highly-capable mechanism of managing mutable states, amazing code optimization, better memory options, and concurrency-based opportunities.
12. SQL
SQL (Structured Query Language) is also one of the top blockchain programming languages to consider in 2020.
The language was designed by IBM to make communication with databases like MySQL, SQL Server, PostgreSQl, and Oracle easier and efficient. It has more than 7M developers in the industry and is used for building secure and effective enterprise solutions in Blockchain domain. A clear evidence of which is Aergo.
13. Erlang
Erlang is another top Blockchain coding language you must consider for a brighter future ahead.
The language, though less popular than reputed names like Java, JavaScript, and Python, serves Blockchain development companies with options like:-
Unparalleled backend facility,
Higher scalability,
Immutability
Inherent fault tolerance, and more.
Something that makes it the right choice for building peer-to-peer networks in a Blockchain environment.
14. Rholang
Rholang is yet another impressive addition in the list of Blockchain programming languages. The language, unlike C++ or Python, operates with functional approach over Object-oriented. It also assess the whole app as a series of functions which are then solved in a sequential manner.
Because of this, it is a favorite of developers when they wish to build a high-level project like Smart Contracts.
15. CX
CX has also entered the list of top Blockchain programming languages.
The language has the potential to work as a contractual digital intermediary, and comes loaded with features like simple error control process, and opportunity to use propelled cuts, pointers, and arrays. It also assembles over Go and give users an escape from executing discretionary codes, which has been a critical issue for present day businesses.
What’s more, the language integrates with OpenGL (Open Graphics Library) efficiently and helps developers reap better benefits in terms of GPU’s capacity.
So, these were some of the programming languages that can be considered for entering the Blockchain world and make the best of the flourishing opportunity. These languages, as already covered in this article, holds different potential and thus, can be used for building different forms of Blockchain and cryptocurrency-based solutions. It implies that you must know which language is best for what type of Blockchain development and eventually, polish your skills in the same.
Now, while learning through online tutorials and training programs is a good effort to be well-versed with its theoretical concepts, if you wish to do some practical stuff under the shade of a reputed Blockchain development company, connect our recruitment team for an internship opportunity today.
Kafka is a distributed publish-subscribe messaging system that is designed to be fast, scalable, and durable. It was developed by LinkedIn and open-sourced in the year 2011. It makes an extremely desirable option for data integration with the increasing complexity in real-time data processing challenges. It is a great solution for applications that require large-scale message processing.
Components of Kafka are :
Zookeeper
Kafka Cluster – which contains one or more servers called brokers
Producer – which publishes messages to Kafka
Consumer – which consumes messages from Kafka.
Components :
It saves messages on a disk and allows subscribers to read from it. Communication between producers, Kafka clusters, and consumers takes place with the TCP protocol. All the published messages will be retained for a configurable period of time. Each Kafka broker may contain multiple topics into which producers publish messages. Each topic is broken into one or more ordered partitions. Partitions are replicated across multiple servers for fault tolerance. Each partition has one Leader server and zero or more follower servers depending upon the replication factor of the partition.
When a publisher publishes to a Kafka cluster, it queries which partitions exist for that topic and which brokers are responsible for each partition. Publishers send messages to the broker responsible for that partition (using some hashing algorithm).
Consumers keep track of what they consume (partition id) and store it in Zookeeper. In case of consumer failure, a new process can start from the last saved point. Each consumer in the group gets assigned a set of partitions to consume from.
Producers can attach key with messages, in which all messages with same key goes to same partition. When consuming from a topic, it is possible to configure a consumer group with multiple consumers. Each consumer in a consumer group will read messages from a unique subset of partitions in each topic they subscribe to, so each message is delivered to one consumer in the group, and all messages with the same key arrive at the same consumer.
Role of Zookeeper in –
It provides access to clients in a tree-like structure. It use ZooKeeper for storing configurations and use them across the cluster in a distributed fashion. It maintains information like topics under a broker, offset of consumers.
Start server – bin/kafka-server-start.sh config/server.properties
creating topic –bin/kafka-topics.sh –create –zookeeper localhost:2181 –replication-factor <your_replication_factor> –partitions <no._of_partitions> –topic <your_topic_name>
This will create a topic with specified name and will be replicated in to brokers based on replication factor and topic will be partitioned based on partition number. Replication factor should not be greater than no. of brokers available.
delete a topic – add this line to server.properties file delete.topic.enable=true
then fire this command after starting zookeeper bin/kafka-topics.sh –zookeeper localhost:2181 –delete –topic <topic_name>
alter a topic – bin/kafka-topics.sh –zookeeper localhost:2181 –alter –topic <topic_name>
Start producer – bin/kafka-console-producer.sh –broker-list localhost:9092 –topic <your_topic_name> and send some messages
If you want to have more than one server, say for ex : 4 (it comes with single server), the steps are:
create server config file for each of the servers : cp config/server.properties config/server-1.proeprties cp config/server.properties config/server-2.properties cp config/server.properties config/server-3.properties
Repeat these steps for all property files you have created with different brokerId, port. vi server-1.properties and set following properties broker.id = 1 port = 9093 log.dir = /tmp/kafka-logs-1
Now we have four servers running (server, server-1,server-2,server-3)
PROGRAMMING
The program in java includes producer class and consumer class.
Producer Class :
Producer class is used to create messages and specify the topic name with an optional partition.
The maven dependency jar to be included is
We need to define properties for a producer to find brokers, serialize messages, and sends them to the partitions it wants.
Once producer sends data, if we pass an extra item (say id) via data :
ex :
before publishing data to brokers, it goes to the partition class which is mentioned in the properties and selects the partition to which data has to be published.
Consumer Class :
Topic Creation :
It is a distributed commit log service that functions much like a publish/subscribe messaging system, but with better throughput, built-in partitioning, replication, and fault tolerance.
Python is a very popular programming language among developers. In fact, it was declared the top programming language for 2019 beating even the original coding language – Java. It has indeed facilitated the whole mobile app development process to a great extent and hence, won the above-mentioned title.
For decades now, technology has been going through makeovers, changing and improving a little every day. And as a result, we have SmartPhones, Supercomputers, Artificial Intelligence, a lot of amazingness like such.
So, let’s take the road of knowledge leading towards the answer regarding Python app development and the kind of applications that can be built on it.
What is Python?
To answer one of the most frequently asked questions “What is Python” in simple words – Python is object-oriented, interpreted, and a high-level programming language. It has incredible built-in data structures that are combined with the dynamic typing and binding to render hassle-free app development. It poses as a scripting or glue language to combine several components together.
Python is renowned for its simple and easy-to-learn syntax which supports readability and reduces the expenses incurred in the program maintenance. It also favors modules and packages, which in return promote modularity and code reusability. To add another jewel to its crown, it totally favors cross-platform, making Python ideal for mobile app development.
Now, merely saying that Python is a popular language will not suffice. So, let’s look at its features which played a crucial role in spreading its popularity like wildfire.
Why Python has Become Popular?
1. Python’s code is easy to read and understand
One of the most renowned features of Python is its syntax. The rules of its syntax enable developers to express concepts without writing additional code. Python has a way of making complex things simple; the reason why it is deemed suitable for beginners to learn.
Python is the only language to focus on code readability which is why it allows developers to use English keywords instead of punctuation. All these factors make Python perfect for mobile application custom applications. Moreover, the clear code base is going to help developers maintain and update the software without any extra efforts.
2. Python is Quick
In Python, the programs are added to the interpreter that runs them directly. This means there is no compiling, which happens for almost all the other languages. On the Python code, it is easy and quick to get your hands on the feedback on your Python code such as recognizing errors. With Python, you can finish and execute your programs (run them) faster than with other programming languages.
3. Python is Compatible
There are numerous operating systems such as Android, iOS and Windows which Python supports. In fact, you can use Python interpreters to use and run the code across platforms and tools. It also makes it possible to run the same code across multiple platforms and the modified app code without the need for recompilation. Moreover, if you wish to check the impact of changes made in the code and that too instantly, then Python is your choice.
4. Facilitates Test-Driven Development
Creating prototypes of software applications has never been easier. All thanks to Python app development. Python fully supports the development of prototypes and even allows you to build applications directly from the prototypes by refactoring the code.
Coding and testing can now go hand-in-hand, thanks to Python. It has adopted the methodology called TDD, acronymous of Test-Driven Development.
5. Strong Standard Library
Python has a pretty robust standard library that gives it an edge over other languages. Python’s standard library enables you to select modules from a wide range as per your requirements. Now, each module allows you to add functionalities later in the process without extra coding.
This point can be cleared with an example. Suppose you are writing a web application, now you can employ certain modules in Python to implement web services or manage OS interface. Just browse through Python’s library and even gather information related to modules.
6. Python Supports Big Data
Big Data is another emerging technology and Python is one of the most used languages for its development. It is because Python possesses a huge number of libraries to work on Big Data. Moreover, it is easier and faster to code with Python for Big data projects as compared to other languages, making it a popular choice of developers around the globe.
7. Strong Supportive Community and Corporate Sponsors
Another prominent element that decides the popularity of any programming language is its community support. Unlike many languages out there, Python has a very active community providing impeccable guides and tutorials, and other forms of documentation for a better understanding of the language. Moreover, having a sponsor like Google only adds up to the list of reasons for Python’s popularity.
Popular Python Frameworks for App Development
1. Django
Django is a high-level and open-source Python framework that streamlines web app development by providing access to different features. It is perfect as it allows developers to create complex codes and Python web applications efficaciously.
A few features that make Django one of the best frameworks for Python are its authentication mechanism, database schema migration implements ORM for mapping its objects to database tables and template engine.
2. Flask
Another extremely reliable Python framework is Flask, developed on Werkzeug and Jinja 2. It is denoted as a microframework because it does not require tools and libraries like other frameworks. Due to its features like integrated support for unit testing, RESTful request dispatching, etc. it is considered an ideal option for small projects, as opposed to Django which is used in the development of big projects.
3. Web2Py
Web2Py is one of the most popular frameworks of Python for mobile app development, loaded with a debugger, and a deployment tool. It helps the developers in debugging and building the code effectively along with testing the apps.
Because Web2Py is a cross-platform framework, it is compatible with Mac, Windows, Linux, Android, etc. It follows the Model View Controller design. One element which impresses the developers most is its ticketing framework, a component that issues a ticket whenever a mistake is made.
4. Pyramid
Pyramid is a highly adaptable Python framework for app development that works incredibly for both easy and complicated applications of Python. It is useful in creating prototypes of applications and also for developers to chip away at API projects.
A majority of Python developers admire this framework simply for its transparency and high-quality features. One other feature that is worth mentioning is Pyramid’s transversal framework used for mapping URLs for coding, making it easier to create RESTful APIs. In fact, some tech industry giants like Mozilla, Dropbox, and Yelp have used it in their processes.
5. CherryPy
Another Python app development framework is CherryPy. It is an open-source framework that is capable of implanting its own multi-strung server. This framework possesses features like setup framework, thread-pooled web server, and module framework.
Moreover, it doesn’t demand you to use any particular and specific ORM or template engine. In fact, it allows developers to utilize different technologies for data access, templating and whatnot, making it a preferred choice of developers to build applications in python.
What Type of Apps Can You Build in Python?
1. Blockchain Applications
Blockchain, being one of the hottest trends of this decade in technology has swept the market of its feet. From the developers’ point of view, Blockchain development was not as easy as shelling peas. However, Python has literally made it so. Because Python is a very understandable language, the process of building blockchain applications is a lot more facilitated.
By employing Python frameworks like Flask, developers can use HTTP requests to interact with their blockchain over the Internet and create endpoints for distinct functions of blockchain. Developers are also able to run the scripts on multiple machines for developing a decentralized network – all with the help of Python.
2. Command-line Applications
Command-line applications and Console Applications are the same. It is a computer program created to be utilized from the command line or a shell and does not have any graphical user interface.
Python is deemed a suitable language for such applications because of its Read-Eval-Print-Loop (REPL) feature which enables developers to evaluate the language and identify new possibilities.
Since Python is a popular language globally, top app development companies have access to a sea of free Python libraries that they can use for building command-line apps.
3. Audio and Video Applications
Python app development helps in creating music and other types of audio and video applications. Since the internet is loaded with audio and video content, you can use Python for analyzing it all. Some Python libraries like PyDub and OpenCV help in the successful completion of the app development.
YouTube is one such application that is created using Python. So, you can easily surmise now how effective and incredible this language is in delivering apps with high performance.
4. Game App Development
For all the gaming enthusiasts, many games such as EVE Online and Battlefield 2 have been created using Python. Battlefield 2 game employs Python for all of its add-ons and functionalities and World of Tanks game uses it for basically the majority of its features. In fact, Disney’s Pirates of the Carribean game was written with the help of the Panda 3D game engine – whose game development language is Python.
Developers are given the facility to create a rapid game prototype and Pygame and Python can be used to test them in real-time. Additionally, Python in game development can be used to create game designing tools that assist in many tasks of the development process, namely, creating dialog trees and level designing.
5. System Administration Applications
We know how tedious system administration can get, given there are thousands of tasks to be completed and a sea of data to be managed. System Administration applications are a savior for the management, to say the least.
Python is regarded fit for creating system administration apps for it allows developers to easily communicate with the operating system via the ‘os’ module. It enables developers to interface with the OS on which Python is currently running. This language makes all the IO operations accessible which includes simple reading and writing to the file system.
6. Machine Learning Applications
Another inspiring tech trend of this decade has to be Machine learning development. Machine learning is an algorithm technology that feeds data to operating systems and enable them to make intelligent decisions. Before creating applications of machine learning was a tricky task, but now we have Python for machine learning applications.
Python comes loaded with libraries like Pandas and Scikit for machine learning that are available in the market for free and can be used under GNU license.
NLP (Natural Language Processing) is one branch of machine learning enabling a system to analyze, manipulate, and understand human language for the algorithm to work.
With the basic knowledge of Python, developers can create machine learning apps with the help of these highly competent and effective libraries.
7. Business Applications
Python highly supports practical agility, meaning it is capable of developing numerous kinds of applications. This is why Python also assists in ERP and E-Commerce app development solutions.
Odoo, an all-in-one management software is written in Python and provides a wide range of business apps forming a suite of business management apps. Another famous business application built with Python is Tryton which is a three-tier general-purpose and high-level application. It is so easy to create such apps with Python which is why app development companies choose it.
Other Use Cases of Python Language
1. Web and Software Development
Since Python has a code that is very simple and easy to understand, this uncomplicates the web and Software development services, making the process more efficient. Another charming feature of Python is its compatibility to integrate with other languages, making it a more flexible option.
Some effective frameworks like Django and Pyramid assist the developers in software development with Python and enable them to create web apps from scratch. The standard library of Python also supports numerous internet protocols including XML, JSON, and HTML. Instagram is one such application create with Django- a Python framework.
2. Image Processing and OCR
Python has this amazing ability of object detection and Image processing. With the help of a wide range of Python libraries such as PyTesseract for OCR (Optical Character Recognition), TensorFlow for object detection and the Python Imaging Library (PIL) for Image processing, it has become highly efficient for developers to create apps with self-contained deep learning and Computer Vision capabilities.
3. Automated Testing
When it comes to Automated Testing, Python is the language of choice. Automated testing is the process of execution of the apps’ features using a script rather than a human being. In this regard, Python along with Selenium (a web-based automation tool) provides a plethora of libraries and tools to perform automated tests. These tools are also known as CI/CD tools acronymous of “Continuous Integration” and “Continuous Deployment” and can run the tests, compile and publish applications along with deploying them into production.
4. Web Crawlers
Web Crawlers, also known as Spiderbot, are typically used to make a duplicate copy of all the visited pages of the world wide web for later preparation by a search engine. This will index the downloaded pages to render fast searches.
In fact, Crawlers are useful for automated maintenance tasks on a Website. For example, checking links or validating HTML code. Python is considered ideal for creating these Spiderbots because of its simple and fast code, and due to the availability of impeccable libraries.
Conclusion
All in all, we can see Python app development is really fast and flexible. It is very easy to create various types of applications because of the versatility of Python’s code. There are numerous types of libraries available for different kinds of applications – the reason why app development companies opt for Python over a sea of other languages.
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