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Written by Nataliia Peterheria — Project Manager at Django Stars. There’s a saying that goes “Go I know not whither and fetch I know not what” and usually, mostly ironically, this describes a poorly set task — something that we all know too well and had to suffer through more than once. But, after more than three years of working on projects of all levels of complexity, I’ve developed some special organizing skills and an in-depth know-how of working in a team. And, as a result, is ready to work more efficiently than ever. the development team I work with Pitfalls Of Wrongly Set Tasks Communication within any team is one of its strongest pillars. The outcomes of the team member’s joint efforts depend on how well they can discuss parts of the process, ideas and suggestions. But the most important is the way the initial tasks are communicated. Also, if everyone understands what their role is, and what part of the product they are developing, it will be easier to put these parts together, when the time comes. On top of it, Clear, transparent tasks are easier to understand, which means that the team can start working sooner and not waste a lot of time asking questions in the process. communicating the value of a certain task or the whole product right away will improve team spirit and motivation. If you think of the development team as a precious watch, In order for the watch to function properly, all parts should be in their right places, fulfilling their roles. It’s a bit more complicated with people, but the principle is the same. And communication is what helps grease the wheels in the human mechanism. if speak clearly and logically, your watch, I mean, each member is a valuable part. If you set the tasks right, your team will serve you well and loyal for years to come. The truth is miscommunication in setting tasks is a bigger problem than we thought. According to the Project Management Institute’s , unsuccessful communication causes one out of five projects to fail. data Causes and Consequences of Miscommunication Sadly, , Product Owners or Business Analysts Even experienced business people occasionally fall victim to bureaucracy and extended hierarchy. Product Owners are supposed to be the link between the business side and the development team. Their main task is to keep all the features requested by the business side in one place and to communicate product requirements to the developers. This, however, doesn’t always happen as it’s supposed to. there are business people who write tasks for the development teams and don’t even know they have a communication problem. Sometimes, Product Owners simply don’t play their role to the fullest. If this is the case, two scenarios are possible. Either the Product Owner isn’t even aware of problems in communicating tasks, or this complicated process is the usual way they conduct business. However, we all have to face the fact that Which leads to exceeded budgets and broken deadlines (which can also lead to penal fines). And, of course, we waste a lot of time explaining requirements again and again. miscommunicated goals can lead to stress and tension within the development team while wrongly or irrationally set tasks often require more effort (and money) to be completed. Let’s take a closer look at what’s going on. What are the underlying issues that can cause miscommunication between a development team and a client? Most of them can be roughly divided into three sub-issues: After we’ve identified these three directions, it will be easier to understand what exactly clients can do to become better at setting tasks to the development teams they work with, saving time, money, and energy. Most importantly, remember that where there’s a problem, there’s always a solution. How to Set Tasks Right So, what do you do if they have to work with? the development team doesn’t know the ins and outs of the domain Make a Presentation of the Project Before launching the development process, of the future product’s set of features. Describe in detail what problem it’s going to solve, as well as its business expectations. , if there are any. These can be either the ones promised to the stakeholders, or associated with a professional exhibition.* begin your cooperation with a presentation Give examples of competitors and set deadlines *For instance, if there’s a startup exhibition in six months that you definitely want to be part of, let the devs know about it, and set your scope for the development team in advance to leave them enough time to work. Having this information, the development team can start efficiently working on architectural solutions already in early stages, which can help them understand how much time it will take and what approaches they should use, as well as to see the value their work has for the business. Provide a Business Roadmap This will help to define a more reasonable and aligned developmental approach. Most importantly, it will help developers in which all features have to be realized, how they all work together and what their dependencies are — whether on each other, parallel execution, or on important contracts.* understand the order * , If you’re working on anything that requires integration with a Bank or a payment system for instance, keep in mind that banks are quite bureaucratic, so don’t count on signing all the necessary contracts quickly. And if you’re working on a complex banking service solution, paperwork can significantly affect the deadline. Find the Common Language When collaborating with a development team, what can you do to prevent this from corrupting your communication? Business language and technical language are different. No matter how good the developers are in their field, it may be challenging for them to understand some of the client’s requirements. Especially if they use As a client of a development company, or a Product Owner working with one, you should keep this in mind and keep it simple. The tasks should be written in a language understandable for everyone. Or, if you feel like there’s no way around such terms, both sides have to stipulate and agree on what vocabulary you’re going to use during the project. highly specific terminology from the field the product is going to be used in. If, after all of this, there are still issues that remain unclear, the development team may send their inquiries to the client. It’s important to keep them as well as using business terms and phrases like “Did I/we understand it correctly, that…”, or “…to be on the same page”. Under no circumstances should the client feel inferior due to not understanding a technical term. But if both sides find an understanding, and the development team fully understands the client’s business needs, they could even suggest a better approach to fulfilling them. This, however, can only be achieved under the conditions of open and trust-based communication. clearly formulated and professional, Organize Communication To conclude this part, we recommend This will help you keep all discussions ordered and easy to find, so nothing will get lost. In this way, if a team member, someone outside the team, or maybe someone new on the project will want to dig in, they will have Finally, maintaining one source of information on the project will prevent your team from losing data if someone leaves the project and takes all their chats and correspondence with them. keeping all communication in one place. access to all the information pertaining to the project. Badly explained tasks are probably the most common problem that puts success at risk, not only in working with or managing (remote) development teams, but in any type of venture. In software development, there’s the notion of Ready for Development. This, essentially, describes an agreement between the development team and the product owner on what a full task description is, so that the team can start working on it. At this point, we’ve talked a lot about the dont’s so it’s probably time to start talking about the do’s of writing tasks for developers. What’s the correct structure? What does a well-explained and complete task actually look like? Types of Tasks to Remember for Effective Setting Which is why, I think, it’s important for the team to settle on the types and content of tasks they’re going to work with in advance. A task that has structure and focuses on the important is easier to grasp and to realize. In my view, there are three types of tasks: developing new features, bug fixes and investigations. These all have their own distinct features. To maintain a good task structure, focus on these, and on what’s really important. Many approaches to formulating tasks exist, but their common goal is to They usually consist of: describe features in detail and provide valuable information. Title — an on-point, short description of the task that answers the questions What? Where? When? Description — the body of the task and the actual set of goals to be reached. — additions that help understand the description: Bonus! A screenshot with markings concerning the task Dependencies and effects on other parts of the application A file with stored formulas (if it’s a calculation) A clickable prototype to show how to navigate between pages A link to a competitor , these tasks require slightly different information. You have to state explicitly what went wrong, where, when, and under which circumstances. To keep it clear and transparent, use these parts: If you have to report a bug Title — this part is the same as with (a) — in short form, you say what happened, where, and when. Description. Apart from steps to reproduce, the perfect description contains User data of who experienced the bug, and the bug’s environment; Тime of the occurrence; Additional conditions, typical of this particular application; Expected and actual result; Links to original requirements, screenshots, etc… Not all clients realize the importance of a well-written bug report. Consequently, they don’t take the time to write down the steps to reproduce. Sometimes, they simply don’t understand the value of a detailed task, but still get the bug fixed as soon as possible. However, this only leads to the contrary — an insufficiently described bug that ultimately takes ages to get investigated, reproduced, and, finally, fixed. There’s also another problem that may arise when clients don’t realize the importance of the bug’s environment or exact location. This is when clients may report the problematic button by simply sending a screenshot of the button, but not of the whole screen showing the URL, time on the computer screen, etc. This data can increase fixing time substantially. To save everyone’s time, both sides should talk about and agree on the process of reporting bugs in advance. The outcome of a spike is that valuable information is received based on the research conducted. When a client needs to make up their mind about what system to integrate with, a certain analysis should be conducted in order to make an optimal decision. This is why investigation tasks — spikes — exist. Tasks like these result not in lines of code, but in data on which the client can make an informed decision or prepare the next development. Spikes are the tasks that have to be investigated. General Recommendations and Tips on Setting Tasks Like many things in life, tiny little details can make a big difference. Similarly, , and keep the whole development process transparent and in good order. there are features that will help make a task clearer to everyone — the person assigned with the task and responsible for completion. Someone the client can approach with questions concerning this particular part of the process. Assignee — optimizing the development process through setting task priority and minimizing unnecessary communication. Clients have to decide what feature and what task is more important to them at the given moment. Priority — of course, the team must know the time frame assigned to a task — especially if it wasn’t decided or agreed beforehand. Due date We recommend a unified status description — three phases that can be subdivided into substages, if necessary. These will help maintain transparency and give an overall understanding of what is going on: To help all participants see where everyone stands at any given time, it is important to include status updates of every task. Working out business requirements. Stage 1. Development process. Stage 2. Accepted by the client and deployed. Stage 3. If you get into detail of these steps, it looks something like this: When you start a project, you need information on the product. As soon as all the requirements are complete, the task is ready for development. From a task in To Do, you can progress onto the task in review. After it’s been tested, it’s either done and ready for deployment or re-opened for improvement and, only when finished, marked as ready to be deployed. Communication Is Gold All this proves that any project requires structured communication and a clear understanding between the client and the realizer, project owner and vendor. Badly explained tasks and vaguely put requirements can put the brakes on any project, substantially delaying product deployment and significantly increasing development costs. By settling on the vocabulary to be used in the project, you can clear up any terms that may cause problems. Finally, it is vital to discuss deadlines and other possible restrictions. On top of all this, there should be a discussed efficient task structure, as well as a way to report bugs within the application. It may seem like nothing, but in the end, this is what will make the experience for both the client and the development team as smooth as possible. To avoid any possible miscommunication, both sides have to be aware of what the pain points might be in the future and talk them through in advance.

How to Successfully Set Tasks and Boost Your Development Team’s Productivity

This article about AI in fintech services is originally written for Django Stars blog. Artificial Intelligence is not a new kid on the block, but rather an integral part of a growing number of industries. Forward-thinking executive managers and business owners actively explore new AI use in finance and other areas to get a competitive edge on the market. First used mostly in computer science, AI now has advanced to the most important areas of our life, e.g.: Transportation Education Health care . Financial services The rise of AI in the shows how fast it’s gaining traction, even in traditionally conservative areas, and how quickly it’s changing the business landscape. Here are just some of the most popular examples of AI in finance. financial industry 1. AI and Credit Decisions Artificial Intelligence provides a faster, more accurate assessment of a potential borrower, at less cost, and accounts for a wider variety of factors, which leads to a better-informed, data-backed decision. Credit scoring provided by AI is based on more complex and sophisticated rules compared to those used in traditional credit scoring systems. It helps lenders distinguish between high default risk applicants and those who are credit-worthy but lack an extensive credit history. Objectivity is another benefit of the AI-powered mechanism. Unlike a human being, a machine is not likely to be biased. Digital banks, loan-issuing apps and use machine learning algorithms to use alternative data (e.g., smartphone data) to evaluate loan eligibility and provide personalized options. online mortgage platforms Automobile lending companies in the U.S. have reported success with AI for their needs as well. For example, this report that bringing AI on board cut losses by 23% annually. shows 2. AI and Risk Management It’s difficult to overestimate the impact of AI in financial services when it comes to risk management. Enormous processing power allows vast amounts of data to be handled in a short time, and cognitive computing helps to manage both structured and unstructured data, a task that would take far too much time for a human to do. Algorithms analyze the history of risk cases and identify early signs of potential future issues. Artificial intelligence in fintech is a powerful ally when it comes to analyzing real-time activities in any given market or environment; the accurate predictions and detailed forecasts it provides are based on multiple variables and vital to business planning. A US leasing company, Crest Financial, employed artificial intelligence on the Amazon Web Services platform and immediately saw a significant improvement in risk analysis, without the deployment delays associated with traditional data science methods. You May Also Like: _The thing I like about finance is that this industry is as old as time - and yet, few people dare enter it. Luckily…_djangostars.com What You Need To Consider Before Building a Fintech Product - Django Stars Blog _One of the most famous travellers of all times, Christopher Columbus, made only 4 journeys during all his life. One of…_djangostars.com Machine Learning and Data Analytics in the Travel Industry 3. AI and Fraud Prevention For a number of years now, artificial intelligence has been very successful in battling financial fraud — and the future is looking brighter every year, as machine learning is catching up with the criminals. AI is especially effective at preventing credit card fraud, which has been growing exponentially in recent years due to the increase of e-commerce and online transactions. Fraud detection systems analyze clients’ behavior, location, and buying habits and trigger a security mechanism when something seems out of order and contradicts the established spending pattern. Banks also employ artificial intelligence to reveal and prevent another infamous type of financial crime: money laundering. Machines recognize suspicious activity and help to cut the costs of investigating the alleged money-laundering schemes. One reported a 20% reduction in the investigative workload. Case study Aggregators like (which works with financial giants like CITI, Goldman Sachs and American Express) take pride in their fraud-detection capabilities. Its complex algorithms can analyze interactions under different conditions and variables and build multiple unique patterns that are updated in real time. Plaid that connects a bank with the client’s app to ensure secure financial transactions. Plaid works as a widget 4. AI and Trading Data-driven investments have been rising steadily over the last 5 years and . It’s also called algorithmic, quantitative or high-frequency trading. closed in on a trillion dollars in 2018 This kind of trading has been expanding rapidly across the world’s stock markets, and for good reason: artificial intelligence offers multiple significant benefits. Intelligent Trading Systems monitor both structured (databases, spreadsheets, etc.) and unstructured (social media, news, etc.) data in a fraction of the time it would take for people to process it. And nowhere is the saying “time is money” truer than in trading: faster processing means faster decisions, which in turn mean faster transactions. offer more accurate predictions for stock performance due to the fact that algorithms can test trading systems based on past data and bring the validation process to a whole new level before pushing it live. Online investment platforms AI puts together recommendations for the strongest portfolios depending on a specific investor’s short- and long-term goals; multiple financial institutions also trust AI to manage their entire portfolios. The business news outlet, Bloomberg, recently launched , a price-forecasting application for investors powered by AI. It combines real-time market data provided by Bloomberg with an advanced learning engine to identify patterns in price movements for high-accuracy market predictions. Alpaca Forecast AI Prediction Matrix 5. AI and Personalized Banking Artificial intelligence truly shines when it comes to exploring new ways to provide additional benefits and comfort to individual users. In the banking sector, AI powers the smart chatbots that provide clients with comprehensive self-help solutions while reducing the call-centers’ workload. Voice-controlled virtual assistants powered by smart tech like Amazon’s Alexa are also gaining traction fast, which is no surprise: boasting a self-education feature, they get smarter every day, so you should expect tremendous improvements here. Both tools can check balances, schedule payments, look up account activity and more. A number of apps offer personalized financial advice and help individuals achieve their financial goals. These intelligent systems track income, essential recurring expenses, and spending habits and come up with an optimized plan and financial tips. The biggest US banks, such as Wells Fargo, Bank of America and Chase, have launched mobile banking apps that provide clients with reminders to pay bills, plan their expenses and interact with their bank in an easier and more streamlined way, from getting information to completing transactions. 6. AI and Process Automation Forward-thinking industry leaders look to robotic process automation when they want to cut operational costs and boost productivity. Intelligent character recognition makes it possible to automate a variety of mundane, time-consuming tasks that used to take thousands of work hours and inflate payrolls. Artificial intelligence-enabled software verifies data and generates reports according to the given parameters, reviews documents, and extracts information from forms (applications, agreements, etc.). Employing robotic process automation for high-frequency repetitive tasks eliminates the room for human error and allows a financial institution to refocus workforce efforts on processes that require human involvement. Ernst & Young has a 50%-70% cost reduction for these kinds of tasks, and Forbes it a “Gateway Drug To Digital Transformation”. reported calls A leading financial firm, JP Morgan Chase, has been successfully leveraging Robotic Process Automation (RPA) for a while now to perform tasks such as extracting data, comply with Know Your Customer regulations, and capture documents. RPA is one of ‘ ‘ JP Morgan Chase uses to enhance the cash management process. five emerging technologies What to Expect in The Future From AI in the Financial Industry Predictions for the soon-to-come AI applications in financial services is a hot topic these days but one thing is for sure: AI is rapidly reshaping the business landscape of the financial industry. There are high hopes for increased transactional and account security, especially as the adoption of blockchains and cryptocurrency expands. In turn, this might drastically reduce or eliminate transaction fees due to the lack of an intermediary. All kinds of digital assistants and apps will continue to perfect themselves thanks to cognitive computing. This will make managing personal finances exponentially easier, since the smart machines will be able to plan and execute short- and long-term tasks, from paying bills to preparing tax filings. We can also expect to see better customer care that uses sophisticated self-help VR systems, as natural-language processing advances and learns more from the expanding data pool of past experience. A new level of transparency will stem from more comprehensive and accurate know-your-client reporting and more thorough due-diligence checks, which now would be taking too many human work hours. Conclusion As we can see, the benefits of AI in financial services are multiple and hard to ignore. According to , 65% of senior financial management expects positive changes from the use of AI in financial services. Forbes This said, as of late 2018, only a third of companies have taken steps to implement artificial intelligence into their company processes. Many still err on the side of caution, fearing the time and expense such an undertaking will require — , and there will be challenges to implementing AI in financial services. However, one can’t shy away forever from technological progress and not facing it now may cost more in the long run.

AI to Transform The Financial Services: Six Examples

Continue reading this article about on apps built with Python Django Stars blog . Over its almost 30 years of existence, has become one of the programming languages. But if most startups once used it because of its simplicity and low cost, modern giants like Instagram or Spotify use Python and the framework to create smooth working experiences. Famously, Django provides fast work processes, clean design, and transparent functionality, among advantages. It allows developers at all levels to focus on writing their apps instead of reinventing the wheel (or fixing it, for that matter). On top of that, it’s free, open source, and has gathered a mighty community of developers over the years. Large companies appreciate this. To give you an example, let’s take a look at some that you probably didn’t know about. Python most popular Django many other apps written in Python You May Also Like _Regardless of the sphere you work in, one of your most important tasks is to create a fast, good-looking website…_djangostars.com 10 Popular Websites Built With Django 1. Instagram As you know, this is the app that changed the world of digital photography, made it instant, more accessible and widespread, expanded lines of creativity and defined new rules in marketing. It allows users to take pictures, edit and share them online using a camera as simple as a smartphone. With 400 million active users per day, it obviously negates any notion that apps built in Python are not really scalable. According to Instagram engineer Hui Ding, Instagram’s engineering motto is “ — and this is what Python allows developers to do. For them, it’s user-friendly, simple, clean, and favors pure pragmatism. And since it’s so popular, growing an engineering team is a lot easier. Do the simple things first” 2. Pinterest Ranking third behind Facebook and Twitter, Pinterest is a social network that allows users to bookmark images, collect and share them with other users. As one of the web’s most-used apps, Pinterest relies on Python and Django to rapidly deal with large amounts of content. In fact, this website has used Python since day one. 3. Disqus This commenting plug-in is a simple and effective way to engage an audience and fuel discussion while controlling incoming content by efficiently moderating the comments. Allowing multiple sign-in options and cross-site notifications, this app serves audiences with all kinds of preferences. In this case, Python makes full use of Django’s security features and regular security patches. 4. Spotify Spotify is the world’s largest streaming service, with annual revenue of over . This makes it a major market player and also one of the top Python users among businesses. The company chose to work with Python because of the development speed and advanced data analytics that the language offers. This enables Spotify to manage functions such as Radio and Discover, which are based on the personal musical preferences of users. €4 billion 5. Dropbox Another top app built in Python is Dropbox. The popular file-hosting service recently moved from Python 2.7 to Python 3 in one of the largest Python 3 migrations ever. One of the most popular desktop apps in the world, Dropbox can be installed on Windows, macOS, and some flavors of Linux. It’s a good thing that Python is portable and works on many platforms, from PC and Linux to PlayStation. 6. Uber A ride-hailing service that also offers food delivery, peer-to-peer ridesharing and bicycle-sharing (among other services), Uber has a lot of calculations to do. Think about it: the company operates in 785 metropolitan areas worldwide and is estimated to have 100 million users. That’s a lot of math. But again, Python handles large amounts of data and is easy to learn and work with, which are two reasons why Python is so popular. These benefits make it an obvious choice for companies whose applications need to be reliable, secure and rely on developers around the world to maintain it. 7. Reddit The American social news aggregator and discussion website Reddit also runs on Python, even though originally it was written in Common Lisp. After looking for wider access to code libraries and greater development flexibility, Reddit made the switch. If you look at it, this website is somewhat of an anthill. With about as of February 2018, Reddit is one of the most impressive Python app examples. Registered users post content such as text, video, or images in thousands of categories, and vote it up and down. Using a localization management platform, users help translate Reddit into 89 different languages. Again, Python manages the workload and complex functionality thanks to its “batteries included” approach. 542 million monthly visitors What can we say? That’s a powerful portfolio! As we mentioned earlier, Python used to be a language for rough drafts and startup development because it was simple and cheap. But usually, the simplest solutions are the most reliable ones. The more parts a mechanism has, the higher the chances of something breaking or someone messing up — which many large companies learned the hard way. That’s why they chose to work with Python, and why so many of the world’s most popular apps are built in Python. Python has proven that you can build an amazing product with simple, time-honored tools — as long as you create it for the users and don’t have to dig into overcomplicated code. (Unless, of course, you want to.) This article about originally posted on apps built with Python Django Stars blog.

Top Seven Apps Built With Python

This article about is written by — PM at . Originally posted on Django Stars blog. creating an online mortgage service Nataliia Peterheria Django Stars Having started its rise in the 2010s, fintech has changed the image of traditional . With online banking, online investing, and online payments already existing, it has been only a matter of time for mortgage and loans to become digital products. They are becoming much more convenient than their traditional versions, more oriented at customers, and less time-consuming. And all these benefits are completed with the fact that millennials, one of the forces that powered the rise of fintech, are ready to become the As the demand for mortgages is growing and the market orients at the digital users, online mortgage services aim to meet the needs of the present and replace traditional loan services. financial services target clients of the housing market. Here, the essentials of building an online mortgage service are revealed: the pitfalls, recommendations, and best practices. Why online mortgages thrive My colleague once as a result of the never-ending struggle between the everyday need for financial activities and the difficulty with which we carry them out. We can conclude that one of the many factors that promoted fintech was the human unwillingness to deal with inconvenient and highly bureaucratic traditional financial institutions. wrote that fintech appeared In terms of mortgage automation software, a whole generation of people referred to as millennials has influenced the worldwide escalation of digital loan services. This is happening partly because millennials born between 1980 and 1999 are now mature enough to be the customers of such services, and partly because millennials comprise most of the purchasing population. As a result, businesses are shifting their strategies to satisfy the shopping habits of millennials by offering things like instant purchase, lower prices, and understandable products. Online mortgage platforms are (1) more understandable than traditional bricks-and-mortar mortgage services (brokers, banks, etc.), (2) likely to move faster than a bank, and (3) probably cheaper. , online loan services are experiencing a 30% higher loan growth rate compared to traditional institutions. The possibility of giving out 30% more loans should be sufficient motivation for companies to reevaluate their approaches and turn to a more customer-centric way of running their business. According to JD Power & Associates But this does not mean that starting an online mortgage service will instantly make you rich. There are many things to consider before and while creating such a service. In this article, I will share the experience my team and I had at Django Stars as we developed an online mortgage service for a client. I will start with what your should know beforehand and what to focus on when designing a user flow. Then I will discuss integrations with third-party services, and in the last part I will tell you about the peculiarities of UI/UX in fintech products. development team You May Also Like: _Some things just appear and change our lives. They are barely noticeable to us, but after they arrive we can't imagine…_djangostars.com Innovating the Mortgage Industry: The Why and the How Organize the work process with your technical partner Here is what your development team should know to build a successful mortgage platform and how to organize the working process if you have an international team. — that is, what inputs are important before the real work begins. I will focus on the pre-development stage Define the end-user(s) In “mortgage platform”, implies that the service will be available to many types of users. It can be an individual who wants to get a mortgage, or a company (or a sole trader) that issues mortgages. Either way, define the roles in your platform and create an image of your customer. platform Once you have them, you will answer two basic questions: Who do we do it for? How do these users interact with each other? Create a high-level flow When you know is going to use the platform, you can see how they are going to use it. Create a high-level user flow to mark the stages of using the mortgage service and predict possible integration with third-party services. In this case, most such services are banks. You may need to use them to identify clients and get their credit records. who For example, many users do not like to give out their personal and banking information. When you have identified the step in which this is necessary, you can think how to transform a negative experience — ”Somebody is going to see my credit record!” — into a positive one — “I will surely get a mortgage!” Based on the flow, you can see the user’s pain points and consider how to mend them. Remember that banks are still traditional financial institutions, so some processes are bound to be full of foot-dragging bureaucracy. Take this into account when estimating the time required for certain operations in the flow. Organize the work with international teams If you are setting up an online mortgage for U.S., it does not always mean that the development team will be in there. This brief section is about working with international development teams. To work efficiently, you need to remember the following things: So if you need the Barclays Bank API, you can access it only from 9 to 5 BST. When you plan weekly activities, schedule meetings with third parties in advance to avoid delays. Third-party services usually work only 9 to 5, local time. This is a pain when working with international teams. From my experience, it is best to schedule meetings and plan your activities so that you have at least three working hours overlap. The time zones can be up to 8 hours different. Ask your technical team about such dates. According to Murphy’s Law, they usually occur during the week of the first release. National holidays may be observed on a working day. Regarding methodologies, there are many approaches to managing the Software Development Life Cycle (SDLC). The most famous is Agile. I wrote an article on why for your startup. It will give you a basic understanding of Scrum and Kanban and when to apply one or the other. Agile SDLC model is the best Now let us go deeper into the study of user flows and integrations with third parties. Flows, third-party integrations, and servers How to ease the information gathering Along with other factors that I will mention later, the flow defines whether a user will turn into a customer. If your high-level flow seems too complicated, you need to optimize it.One specific trait of mortgage software development is that users have to provide lots of personal information, and developers must figure out how to make this process painless. The process of filling out the online forms is time-consuming and frustrating. Well-thought-out user flow predicts higher user engagement. Most users quit websites when they are asked to fill out forms. Caption: When working on Moneypark , we emphasized the importance of gathering only basic information in the first step To ease the process, ask only for necessary information during the first steps. After they get the early feedback — e.g., rough estimates on the mortgage — and are ready to continue, you can ask for more detailed information. If you divide one big step (gathering the information) into smaller steps, your user will feel less pressure. The forms should be organized from the most to the least important. If some fields are optional, let users know. Bank APIs | User flow Platforms make requests to retrieve user information such as IDs, customer emails, credit records and so on. Such requests often have a fixed fee per request — typically $1 to $10. To avoid wasting money, you need to build the flow in such a way so that you — only when you are sure that a customer is ready to use your service. Most third-party services integrated into online mortgages are banks. make as few requests as possible Here is what we did. When using our mortgage system, users have to go through a several stages of verification process to check whether they are eligible for a mortgage. When signing up for the service, users provide their full name and date of birth. The second step involves providing rough mortgage estimates for the user. If users want to continue using a service and get a real offer, they need to finish registration process. This flow allows us to and thus waste less money. reduce the number of paid requests to third parties’ API’s, Test bank APIs To avoid using your own credit cards, the developers can yield results from test data. Many banks provide such test data to check the various outcomes of using payment systems: and so on. You need to test as many cases as possible to avoid having to change the entire flow later. When you integrate a bank API into your service, you need to test the payment system. What to do if a card has expired, is lost or stolen; what happens when user enters invalid data Managing the database We decided to use two different cloud services, one for the platform, and another for the database. The mortgage application runs on AWS EC2, while the database is on a separate RDS server. RDS is great for databases since (1) it uses PIOPS to achieve fast and consistent request processing, and (2) has two types of backup mechanisms (automated and user initiated), which make data administration simple. UI/UX Design I will summarize the main design obstacles and how to deal with them in this short part. I will not talk about general design principles but focus on the needs of mortgage services instead. as So, to design well means to create a seamless (pardon the buzzword) flow. If we design it well enough, perhaps people will not know it is a financial service at all. Good design, Dieter Rams so aptly puts it, is as little design as possible. Read About UI/UX Development of Fintech Products _UI/UX development for fintech isn't the same as it is for other industries. Find out how to better build an app that's…_djangostars.com Five tips for UI/UX Development of Fintech Products Mobile version The first thing to consider is the mobile version. Since we are talking about an online-based application, many users will try to get a mortgage using their phones. The main trouble may be the data grid and how to display it on a 5-inch display. solves this problem by displaying a diagram rather than a grid. Visualization is what differentiates an Excel sheet (bad experience) from interactive data (good experience). Use it often. Mint App Decimals What we need to inherit from traditional banking is attention to details, especially when it comes to money. All fields where users can enter amounts of money must allow decimals because the number of cents influences the future benefits. You do not want your users to get bad mortgage conditions because your platform lacks a particular functionality. Changes to personal data I always recommend restricting the ability to change personal information. But there may be a situation in the future when some of it needs to be changed — if users get married and want to change their surnames, for example. and let them know when they sign up for an account that, once they create an account, they cannot change their personal information. For better security, decide which information users can and cannot change Listening to the customers When running complex systems, like online mortgages, be ready to get a huge flow of questions on your support channel. Your customers provide your best chance to improve something. Listen to them attentively, because they do know better. how-to I suggest that you set up an intranet website to test changes to the website using fake data before deploying it to live servers. You can validate the hypotheses received from the users, and by doing so regularly you will improve the UX until most of your users are happy. Speaking of an online mortgage platform Here are the main insights from our team achieved while . These statements summarize the main ideas in the article and are laid out as thoughts from our team members: working on the development of an online mortgage platform Since we are going to develop an online mortgage service, let’s first identify our target end-user and create a flow to define the principal stages and activities. Our technical team is in another time zone. We must schedule meetings in advance and pay attention to the client’s days off. We have to differentiate our product from the traditional mortgage issuing process. What if we don’t ask for all the information at once, but rather divide it into several steps? Only those who are eager to get a loan will have to provide their personal information. because they provide detailed information about a mortgage. Only Otherwise, we’ll go bankrupt very soon. Requests to bank APIs are expensive paid customers should be able to make them. Let’s separate the database processing server from the website server. It makes it easier to manage the servers. Millennials are crazy about the good design. If something can be the top priority here, it’s the design. If you find this post useful, please tap 👏 button below :)

Creating an Online Mortgage Service: Tips and Insights

Nataliia Peterheria — Project Manager at Django Stars. Our experiences make us who we are. This guide is a set of personal findings and experiences the development team and I acquired while working on numerous projects. Like many other companies, we work in Scrum. But Scrum just gives us rules on how to organize the work process. By trial and error, I tried to polish formula to organize every sprint as efficiently as possible based on business demands and team capacities. By using the formula, we managed to create a smooth and harmonic process, the product was finished by the end of the project, no time was wasted during sprints, and no team member was left sitting on their thumbs. For example, as it often happens when teams use an ill-defined approach to planning sprints, developers do their jobs while testers just sit idly by because they have nothing to test yet. It’s not so with us. Why We Use Scrum and Why It’s Jira’s Best Friend Scrum has many advantages, but what I appreciate the most is its predictability when used together with Jira. Jira allows for all-round transparency on all activities and provides comprehensive reports — one can track the tasks remaining, understand the work completed or pushed back, predict releases. It is also easily controlled — one can check the work efficiency and whether all tasks are checked off after a sprint, and scheduled planning meetings allow all team members to be on the same page. On top of this, Scrum allows you to break complex projects into smaller parts. Each part is covered in a sprint. Consequently, This way, it’s easier for them to track work results and formulate and execute tasks. Because making a to-do list for 10 days and sticking to it is a lot easier than for 100 days. teams think in sprints, since they are benchmarks that have a beginning and an end. Meanwhile, we should keep our activities planned in advance and have predictions on project continuity. For Jira to provide correct reports, sprints should cover the entire process. To be clear, Jira works in two separate directions. One of them involves calculating finished tasks one by one; the other involves calculating Fix Versions — little events such as the first test version, the second version, product release, etc. In its backlog, Jira has a list of tasks, and if every single one is estimated in story points, Jira can predict the number of sprints we will need for this particular project based on our known working speed. Therefore, we can provide our clients with an approximate, yet very precise budget and deadline at the initial stages of our project discussions. No Gaps: Achieving a Continuous Workflow Now let’s see how we build our sprints. Having no gaps between sprints may seem like an easy thing to do, but the truth is, it’s not. Let’s not forget that every development team and its workflow heavily depend on how efficient the business provides requirements and approves sprint results. A sprint is a time unit in which project duration is measured. It usually lasts ten days. Why ten? It’s an optimal duration of an iteration, which is long enough to deliver a working increment, but short enough to be tangible, transparent, and understandable for everyone. are when development happens, when backend, frontend, and QA are working together, taking into account task priorities and blockers. At the same time, based on the change management principles, development team can deliver hot fixes and emergency changes on customer request. Days 1–7 However, in practice, it is a common situation when some team roles may be blocked by others in the development process (e.g., QA cannot start tests until engineers finish their part). During planning, it is necessary to take into account such situations and minimize chances for them to happen. By that mean, each spare moment in the development process can be used by the team members for an individual grooming. For example, frontend developers can only start working when the backend developers are done. This is why, while the backend developer is still coding, the frontend developer can do some grooming. As soon as the backend developer is done with the code, it’s his turn to groom. Later, on the last day of every sprint, team members report on the tasks they’ve previously groomed. This way, the team is ready for every successive sprint, and they don’t have to waste all day simultaneously grooming and planning. are the time for testing and technical tasks, i.e., no changes are being introduced to the Release Candidate build. This is called the code freeze. On days 8–9, the development team: Days 8–9 powered by quality assurance engineers; executes test cases if the project has enough funding or is at an advanced stage of development. writes automation tests or improves engineering Automation tests check the product and help accelerate the inspection. Manual checking can take quite long; automatic checking takes less than a day. However, this only makes sense when it’s clear which tests should be automated. Writing and supporting tests is expensive an process, but if a startup has enough funds and wants to get a top-notch product, reasonable automating at an earlier development stage is recommended. If the project reaches the automated testing stage, testing day is moved to Day 9. This means that the team can spend one more day for development — from Day 1 to Day 8.While the QAs are busy working, the rest of the team can perform technical tasks. They i.e can review old files, clean data, (re)organize folders, etc. They don’t change the code, but improve the overall workflow and structure. We’ve reached , the day when all the work done during the sprint is deployed on a stage server. The business team tests the features, revises and approves them for deployment. On this day, demo versions of more advanced stages are presented to the business side. Day 10 In addition, Day 10 is the time for retrospective, reporting, and the next sprint planning. Thus, on Day 10 you can look back at the work you’ve done, report on it, and plan new sprints. Note that Day 10 can never be a Friday. Deploying a product and leaving it unsupervised for two days can be dangerous. Someone has to be able to support it, just in case. Afterwards, a new sprint begins from Day 1, and I highly recommend to start on a Wednesday. Then, you can have a code freeze on Thursday night, spend Friday and Monday on testing and technical tasks, and present your demo on Tuesday — which in my opinion is the best organization approach. Mind The Gap Usually, the most common problem within a sprint are gaps. If a team consists of more than ten people, not all of them may be assigned tasks that correspond with their competences. The result is chaos. My goal, however, was to create a continuous workflow where everyone knows who does what and when. We ended up creating a system — shown above — that should help you (and us) avoid chaos and gaps. Besides, for a team to finish sprints in time, you have to solve two problems: Businesses should specify their demands, so that the team doesn’t fall behind in the sprint. The team should be ready: everyone must understand what the product is all about. If it’s a specific industry — like investments or medicine — they have to be fully prepared and knowledgeable before development starts. They won’t have the time to get into it later. Scrum Events and Work Correlation Scrum includes well known set of events that should be handled with an extreme care to achieve a success. They include meetings, planning, and similar get-togethers. Despite the fact that the main tool for the implementation of the project is work, Scrum events help organize and plan it. Which is why meetings are so important – , no matter which part of the project they’re covering. They all have to be on the same page. Otherwise, there’s no sense in planning. all team members should be present Effective Planning Of The Development Process The reason why our team works so efficiently is that we all have one main belief: Developers aren’t just coders or testers, they are engineers. It’s all about thinking, about architecture. Time spent thinking about how to make the product better is more important than the time spent coding. Out of their usual eight working hours per day, developers spend 5.5 hours coding at their computers. The other 2.5 hours we spend on daily tasks, groomings, calls with customers, hot fixes or in-between discussions. The truth is, tiny things like these — fixing a minor bug, understanding a task better, or discussing something with a colleague — are often overlooked during planning. They happen no matter what, and if you don’t count them in during planning, developers lose time and can’t finish the tasks for which they have only eight hours to accomplish. How do you figure out better ways to work with your team? I suggest that you write types of tasks on small sheets of paper, so everyone can move them around on a table. It’s better than writing on a whiteboard, which is messy, inconvenient, and only fun for the person holding the pen. You May Also Like: _There's a saying that goes "Go I know not whither and fetch I know not what" and usually, mostly ironically, this…_djangostars.com How to Successfully Set Tasks For a Development Team _A good team isn't something that happens on its own. But why do we need one at all? Don't good professionals form a…_djangostars.com How to Form a Successful Development Team The Secret Weapon: Grooming vs. Planning As promised, this is the part where we explain grooming in a little more detail. As you know, while the project is being planned, clients give a list of tasks to the team — not necessarily for the whole project, but at least for one or two sprints. Grooming is the process of getting deeper into a task that’s backlogged in Jira. To use time more efficiently, every team member picks a task one week before the sprint and asks clients all the right questions in advance, so they have more time to get answers. Afterwards, during sprint planning, everyone reports on their findings and shares their ideas on how to work on this particular assignment. Which, of course, makes it easier for the team to understand it, too. By the time a new sprint starts, all the tasks are clear and everyone knows what to do. Therefore, grooming is much more efficient than traditional planning sessions when all team members come together and try to plan tasks for a future sprint they don’t even fully understand. And while half of the team tries to figure out additional information, the other half doesn’t pay attention at all, because it’s out of their field of expertise. To put it bluntly, grooming is effective, equally involves everyone in planning, is less time-consuming, and enables non-stop sprints. On a side note, don’t forget to account for internal company events in planning — days off, sick leaves, or client visits. The Most Frequent Problems and How to Solve Them One problem many teams have is QA being forced to catch up with the rest of the team, since they can only start deep testing after backend and frontend are done. The main question is, what do you do to help team members plan their work and finish everything on schedule? Parallel processes are the solution. While QA is testing the built, developers complete technical tasks locally or spend time to automation. And while the developers do their magic on Day 1, QA can check deployed technical stuff. And by the time of the next development phase, everything is ready. I sincerely hope that you will learn something useful from our insights. To conclude, here are our most important tips in infographic. I strongly believe that sharing is caring, which is why I decided to share everything I know about how to better organize the development process. It’s always better to work with partners who know how to make their own work more efficient and not waste anyone’s time. I hope this guide will help you optimize your processes and win over some great collaborators and partners. This article about is written by Originally published on effective work planning in Scrum Nataliia Peterheria. Django Stars blog . If you find this post useful, please tap 👏 button below :)

Scrum Project Management: Secrets of Effective Sprint Planning

This article about with react native is written by Julia Korsun. building a location-based app Read original article on Django Stars blog. What good can happen when we tap Allow on the pop-up that asks to access our location? Some apps provide a better experience, like Facebook suggesting events nearby. Others — can’t work properly without knowing device location, like Uber or Google Maps. These location-based apps use device location to enable and control some features. From wok delivery to Find My iPhone, location-based apps help us with our everyday tasks just by knowing where we are. Location can be either the primary function, like in Tinder; or auxiliary, like in Instagram: when uploading a photo, Instagram will suggest you a place so you can tag your location. Whether it’s the main function or not, location does improve the user experience. In this article, I’ll tell you about the main tech components of location-based apps, and you’ll learn how to develop one using React Native. First, I’ll briefly describe React Native and compare it to native app development. Then I’ll share approaches to gathering and displaying the location in an app, and finally, in a short passage I’ll describe some of the design challenges and how React Native copes with them. You May Also Like _If you make a quick review of apps in various categories — healthcare, games, finance, — it will show that the device’s…_djangostars.com What to Consider When Building the Backend for a Location-Based Service Tools For Location-Based Application Development: React Native In this part, I will briefly describe the React Native framework, its pros & cons, and why it’s great for building location-based apps. React Native is an open source JavaScript framework that allows developers to create cross-platform apps with their native behavior. What is behavior in this description? Let me explain. iOS and Android are different — their interface is different, their animation is different, lots of things are different. Having the same app for iOS and Android would require developing two separate apps. It used to be a laborious process, but using React Native, developers write one code, and it works correctly on both platforms. This allows businesses to offer their app to both iOS and Android users which means a bigger market share. That’s why many companies prefer React Native — they can’t afford developing two separate apps or are confident about whether their users have iOS or Android. And considering that the cross-platform market is likely to grow to $80 billion by 2020, it seems a rational choice for startups. Now, I’ll explain the pros and cons of React Native in terms of developing location-based apps. React Native Pros Rather than writing separate code for each system (iOS and Android), you build one to operate them both. Neither do you design different UI and UX. Cross-platform. React Native uses native controls and modules. The code interacts with the corresponding native iOS and Android components and renders the code to native APIs. Native API is the focus — by using a separate from UI thread, it increases the performance of the app. High performance. The React Native community grows every day, and so does the number of open-source components. This allows for sharing the experience among the community members, improving the framework, and finding the solutions to existing bugs. All this combined accelerates the development process. Open source. The three previous points conclude into a considerable advantage — React Native saves your money. It’s faster than building two separate apps and so it takes less time for testing and releasing an MVP. It saves money. However, there are cases when you might not want to use React Native. They include: If you know that your audience prefers a particular platform, I suggest you opt for native development. Firstly, the app will be tailored to match the specifics of the OS, and secondly, you’ll be able to use platform-specific features, like ARKit for iOS. You don’t need a cross-platform app. The one thing I particularly dislike is that React Native has a limited number of supported native APIs. There are enough to build a location-based app, though. In case you need others — you can bridge them using the native code. You need more APIs than React Native offers. How to gather and display user location This part is about gathering and displaying the location data. Depending on the specifics of your app, you will opt for a particular way. Gathering location data I single out three ways to gather device location. This is a generic overview for you to understand the cases when to opt for each case and the differences between them. Note: Using React Native API There’s a that identifies the location of a device. It’s easy to install and use, but there’s a ‘ ’ — it neither works on the background nor shows the location provider (3G, Wi-Fi, GPS). native JavaScript API but react-native-background-geolocation It’s a package that determines the location of a device from 0 to 1000 meters (0.6 miles). It takes more battery energy, but on the other hand, it’s up to you to configure how often to track the location. The package also integrates with SQLite — you can store the recorded location data and sync it to your database via HTTP. import { NativeModules, DeviceEventEmitter, PermissionsAndroid } from 'react-native'  import Config from 'react-native-config'  import get from 'lodash/get'  const { GeoLocation } = NativeModules

class BackgroundGeoLocation {    constructor(token, user_id) {    this.state = null  }  start(dispatch, nextState) {    this.dispatch = dispatch    const token = get(nextState, 'session.data.token')    const user_id = get(nextState, 'user.data.user_id')    const id = get(nextState, 'user.data.id')    this.state = {      user_id,      token,    }

return PermissionsAndroid.check(PermissionsAndroid.PERMISSIONS.ACCESS_COARSE_LOCATION)      .then(is_granted => is_granted === PermissionsAndroid.RESULTS.GRANTED        ? is_granted        : PermissionsAndroid.requestMultiple([          PermissionsAndroid.PERMISSIONS.ACCESS_FINE_LOCATION,          PermissionsAndroid.PERMISSIONS.ACCESS_COARSE_LOCATION,        ])      )      .then(_ => PermissionsAndroid.check(PermissionsAndroid.PERMISSIONS.ACCESS_COARSE_LOCATION))      .then(is_granted => is_granted === PermissionsAndroid.RESULTS.GRANTED ? true : new Error())      .then(_ => setTimeout(() => GeoLocation.startService(token, user_id, id, `${Config.API_URL}/live/car-tracking/gps-pos/`), 300))      .catch(e => console.log(e))  }  stop() {    return GeoLocation.stopService()      .then(_ => console.log(_))  }

handleLocationChange(geo) {    console.log(geo)  }}

export default BackgroundGeoLocation Being a package, it requires regular maintenance and updates, but there’s a support channel on GitHub from the creator of the package. Package price: iOS — free; Android — $300 for one app. Note: Combo: Bridge native code to JavaScript API The main issue with the first approach (to use native JavaScript API) can be solved by adding native code that will start a foreground service in a separate thread. That’s exactky what we did when . Partly, we chose this way because React Native made it easy to bridge native code to React Native components. developing our food delivery product Azyan package com.djangostars.azyan;

import android.app.Notification;  import android.app.NotificationChannel;  import android.app.NotificationManager;  import android.content.Context;  import android.content.Intent;  import android.content.pm.PackageManager;  import android.location.Criteria;  import android.location.Location;  import android.location.LocationManager;  import android.os.Build;  import android.support.v4.content.ContextCompat;

import com.facebook.react.bridge.Arguments;  import com.facebook.react.bridge.Promise;  import com.facebook.react.bridge.ReactApplicationContext;  import com.facebook.react.bridge.ReactContextBaseJavaModule;  import com.facebook.react.bridge.ReactMethod;  import com.facebook.react.bridge.WritableMap;  import com.facebook.react.bridge.WritableNativeMap;

/** * Created by AGulchenko on 5/7/18. */

public class GeoLocationModule extends ReactContextBaseJavaModule {      public static final String CHANNEL_ID = "ExampleService_Channel";    public GeoLocationModule(ReactApplicationContext reactContext) {        super(reactContext);        if(Build.VERSION.SDK_INT >= Build.VERSION_CODES.O) {            NotificationChannel channel = new NotificationChannel(CHANNEL_ID,"testName", NotificationManager.IMPORTANCE_DEFAULT);            NotificationManager manager = reactContext.getSystemService(NotificationManager.class);            manager.createNotificationChannel(channel);        }    }

@Override    public String getName() {        return "GeoLocation";    }

@ReactMethod    public void startService(String token, String user_id, String id, String url_string, Promise promise) {        WritableMap result = Arguments.createMap();        result.putString("ststus", "success");        try {            Intent serviceIntent = new Intent(getReactApplicationContext(), GeoLocationService.class);            serviceIntent.putExtra("token", token);            serviceIntent.putExtra("user_id", user_id);            serviceIntent.putExtra("id", id);            serviceIntent.putExtra("url_string", url_string);            getReactApplicationContext().startService(serviceIntent);            promise.resolve(result);        } catch (Exception e) {            e.printStackTrace();            promise.reject("rrrrr",e);            return;        }

}

@ReactMethod    public void stopService(Promise promise) {        String result = "Success";        try {            Intent serviceIntent = new Intent(getReactApplicationContext(), GeoLocationService.class);            getReactApplicationContext().stopService(serviceIntent);        } catch (Exception e) {            promise.reject(e);            return;        }        promise.resolve(result);    }

@ReactMethod    public void getLocation( Promise promise) {        WritableMap res = Arguments.createMap();        try {            LocationManager locationManager = null;

locationManager = (LocationManager) this.getReactApplicationContext().getSystemService(Context.LOCATION_SERVICE);            int permissionCheck = ContextCompat.checkSelfPermission(this.getReactApplicationContext(),                    android.Manifest.permission.ACCESS_FINE_LOCATION);            if (permissionCheck == PackageManager.PERMISSION_GRANTED) {                Criteria criteria = new Criteria();                String bestProvider = locationManager.getBestProvider(criteria, false);                Location location = locationManager.getLastKnownLocation(bestProvider);                if(location != null) {                    res.putDouble("latitude", location.getLatitude());                    res.putDouble("longitude", location.getLongitude());                    promise.resolve(res);                }

}        } catch (Exception e) {            promise.reject(e);            return;        }    }} Getting permission to access the location data sometimes causes troubles, but the troubles are bearable. React Native solves the problem without too much fuss. Different systems ask for the permission to access the location data on different stages: iOS requests the permission first time you open an app; Android — upon the download. It could cause trouble if we were using the native code, however, React Native simplifies this process using module. It allows access to location data without triggering the permission alert. the check access to location data Read Full Azyan Case Study: Displaying Location The location data isn’t always precise. You must have seen something like this: Here’s why it may happen: the device collects the location data from three sources: Wi-Fi, cellular and GPS, the latter being the least accurate. Our devices are in the constant state of checking if there’s good Internet connection. If there’s none, the device will enable GPS. And if there’s a quick leap from 4G to GPS, the device is _‘_lost’. To solve this problem, I recommend by Google. It allows you to set the time and distance at which the location data is updated: for instance, update the data every 50 meters and every 10 seconds. You will avoid the noisy data as this API matches all device locations to roads and sidewalk. However, if the device is far from either, it won’t be effective. Fused Location Client A Few Words About Design In this short part, I will tell you about obstacles that may arise with building location-based apps and how to solve them with React native components. React Native allows for simple ways of displaying maps. It UI components for simplify the job for engineers. We would use Material Design to create a Google Maps wrapper, and then React Native would adjust them to the specific features of each platform. Material Design is a React Native feature that makes an endless list of search results. In Uber, if you start typing an address, you will get all the destinations starting with what you’ve entered. So try , it will show all 3rd Aves around. Such lists aren’t really endless — they just load more results as we scroll down through them. another build-in UI component includes the fixed header, footer, and delimiters to the search. If you were to create such result lists from scratch, it would take you more time than building a complete React native app. Infinite List 3rd Ave Flat List — <FlatList          data={get(props, 'order.data.items', [])}        renderItem={listItem}        keyExtractor={({ id }) => id}        style={style.list}      />

function listItem({ item: { quantity, name } }) {    return (    <View style={style.main}>      <Text style={[style.count, style.listItemText]}>{quantity}</Text>      <Text style={[style.listItemText, style.name]}>{name}</Text>    </View>  )} Bottom Line React Native may be the right choice if you are going to build a location-based application. If most of the described advantages are true for you, go do deeper research on the technology and its capabilities. I now encourage you to pay more attention to the apps you use. You’ll be surprised to find out that of them ask to allow access to your location. For many companies, it’s crucial to know user location to provide quality and more user-oriented service. Why don’t you try? most If you find this post useful, please tap 👏 button below :)

Building a Location-based App with React Native

This article about is written by Iryna Meshchankina — QA Lead at Django Stars. how to build an investment platform Read original article on Django Stars blog. Investment advising is something we’ve all heard of — you find a trustworthy company, you sign a contract, you get advice on how to better invest your money. But what used to be done in offices just recently, is moving into the mobile world with an astonishing speed. No surprise there — with so many aspects of our lives already gone online (smart homes, pet entertainment, weight control, you name it!) as well. This is a global trend that is part of the dramatic growth process of fintech. Only in U.K., notes the following growth of online banking and others services. it was just a matter of time until investment companies shifted their focus to online wealth management platforms Statista Growth of online banking and other financial operations in U.K. Note that the platforms aren’t entirely autonomous and the analysis is still run by advisors, but t . he process has become a lot faster and more flexible Online advising develops at a different pace depending on the country and its financial tradition. (or this threshold is reachable for an average person) For example, in the US, you can start investing with as little as $50, as well as there are for individual investors to buy stocks. This results in 54 millions of active individual investors according to . Countries with investments easily accessible to a wide audience and no minimum investment have the most developed online investment platforms. numerous options Forbes Image source: Forbes Not every country is like this though. Many countries are yet to reach this stage. However, there are a couple of countries other than US that have . Which means that before you start working on your platform you have to loyal legislation for fintech products be sure about the situation on the market, so your platform can function properly and more importantly pays off. Remember that this isn’t the only thing you should consider when developing an investment platform. Here’s a list of advice we compiled based on our own experiences. You May Also Like _The thing I like about finance is that this industry is as old as time - and yet, few people dare enter it. Luckily…_djangostars.com What You Need To Consider Before Building a Fintech Product - Django Stars Blog _In the 21st century, we are feeling like we are finally living in the future that everyone's been waiting for, and…_djangostars.com Top Fintech Takeaways of 2018 Investment Management Platform Basics Generally, all investment platforms look the same. Customers open the website, register and fill in their information. Further on, they follow these steps. This data allows to be it real estate, materials, or something else. As soon as everything is set, the system does regular health checks on the user’s investment portfolio by matching investment results with the set goals. This way, users can get suggestions on whether it’s profitable to keep investing or if it’s better to pull out and wait. determine asset classes and markets that are most fitting for this particular customer, Important Parts of the Development Process Okay, let’s start. The project that we will draw our advice from is a B2C-oriented investment service. #1: Architecture Not all of the clients know their target audience right away, so you might have to build the architecture part by part. Some may turn out unusable and have to be refactored later on. It’s possible, but very tricky: when changing one element, you risk affecting another one that should remain unchanged. That is why, you need to — this will define the architecture of the platform depending on whether is B2B or B2C. Note that B2B is much more complicated and branched out. decide on who your target audience is As a matter of fact, the platform isn’t completely automated.Thus, we created based on income, credit history, and determine what’s the best way to invest and if it’s worth it at all. panels through which advisors can update investment funds lists, do risk assessment, calculate a client’s score #2: Bank Integration . Which is why, the service needs arrangements with banks. Also, bank connections allow to integrate exchange rates into the platform. Based on their bank data (credit score, reliability, etc.), customers get suggestions concerning their investments It’s important to decide how many banks you will connect with, as it’s vital for the architecture too. #3: Country and Time Zone Carefully consider the location of the integrated banks. But here’s a tip: if a user requests information on a holiday, the data can be extracted from the most recent updates. This way, you can make these little inconveniences invisible to the customers. For example, if they make an investment inquiry on Saturday, they will get investment rates from Friday Laws and regulations may vary, as well as operating hours. #4: Code Logging We, for instance, created a tool for error logging that logged all our enquiries to the third party (i.e. the bank), as well their responses. This way, every error was shown on the log list. To fix or prevent an error, you need to know what caused it. #5: Sandbox Environment A sandbox environment is an exact copy of the third party function set connected to the developed code without risking client data. When choosing a bank to work with, check if they have it, so you And when you’re done coding, you simply replace the sandbox URL with a real one, and you’re ready to go. don’t risk losing or corrupting any client information and avoid unwanted charges. #6: Development Flow Look at your platform from a customer’s perspective. Registration, background check, choice of market, and the investment itself. Example of the registration form Leave some space for a getaway in case the money doesn’t go through right away, and exchange rates change the day after. To do so, you can restrict investment portfolio usage — this way, a certain amount of user’s assets remains available at all times, in case of unexpected exchange rate changes or transfer fees. Suggestions on assets distribution Install notifications for the service app to interact with customers. This way, they won’t have to check the website all the time for stock market status. If there’s a good opportunity to sell or buy something, the app will send a notification. #7: Matching UX Don’t forget that you’ll have . It may get especially tricky with mobile devices due to their size. to squeeze in large amounts of data and large table sheets into small screens End users may have little to no knowledge about investments, or about some of the platform functions or fields. You can help your clients by sending them notifications and tips, but be careful as to not to overload in the interface. Be careful when using several languages. Some languages tend to have longer words and sentences — for instance, English words on average are shorter compared to most other European languages. Read More About UI/UX of Fintech Products: _UI/UX development for fintech isn't the same as it is for other industries. Find out how to better build an app that's…_djangostars.com Five tips for UI/UX Development of Fintech Products Things We’ve Learned From Developing an Investment Platform Sharing is caring, which is why we’d love to share all the useful things we’ve learned in the process of developing an investment platform. After the seven crucial elements of an investment platform, here come seven pieces of advice for smoother investment platform development. To build a wealth management platform, hire . developers with previous experience in the domain of investments To make the process more efficient, the to developers must be . data provided written down in formulas with specific examples Requirements, however, should be written down in both professional and simple language. used to calculate investor reliability coefficients, client risks — time of deposit, primary investments, and so on, should be . Or better yet, with examples. Formulas and algorithms as simple and logical as possible Don’t let other developers reuse your code. Every case is unique like a snowflake, thus, every code should be written from scratch. Everyone has to be on the same page about everything. , business processes, etc. Use a dictionary, conduct workshops to figure out vocabulary . All the formulas that calculate investment risks, distribute the portfolio, etc. need testing. Sometimes, a formula that works perfectly on paper, just doesn’t feel right in code. And trust me when I say, working code will be worth your while, even if you spend a lot of resources on testing. Don’t be afraid to spend money of testing That’s about it. Some things may sound obvious at first, but it’s always better to be overcautious, rather than miss something. And remember, you’re creating a service that should be understandable for every single client, even the least knowledgeable in investments. Which is why you have make sure all processes run smoothly, and every little feature works flawlessly, for you and for your clients. If you find this post useful, please tap 👏 button below :)

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Note: the code samples may be displayed improperly because of markdown. We recommend to to make sure all the examples are displayed properly. continue reading the original article on our blog Development of products with Django framework is usually easy and straightforward; great documentation, many tools out of the box, plenty of open source libraries and big community. Django ORM takes full control about SQL layer protecting you from mistakes, and underlying details of queries so you can spend more time on designing and building your application structure in Python code. However, sometimes such behavior may hurt — for example, when you’re building a project related to data analysis. Building advanced queries with Django is not very easy; it’s hard to read (in Python) and hard to understand what’s going on in SQL-level without logging or printing generated SQL queries somewhere. Moreover, such queries could not be efficient enough, so this will hit you back when you load more data into DB to play with. In one moment, you can find yourself doing too much raw SQL through Django cursor, and this is the moment when you should do a break and take a look on another interesting tool, which is placed right between ORM layer and the layer of raw SQL queries. As you can see from the title of the article, we successfully mixed Django ORM and SQLAlchemy Core together, and we’re very satisfied with results. We built an application which helps to analyze data produced by EMR systems by aggregating data into charts and tables, scoring by throughput/efficiency/staff cost, and highlighting outliers which allows to optimize business processes for clinics and save money. What is the point of mixing Django ORM with SQLAlchemy? There are a few reasons why we stepped out from Django ORM for this task: For ORM world, one object is one record in the database, but here we deal only with aggregated data. Some aggregations are very tricky, and Django ORM functionality is not enough to fulfill the needs. To be honest, sometimes in some simple cases it’s hard (or even impossible) to make ORM produce the SQL query exactly the way you want, and when you’re dealing with a , it will affect performance a lot. big data If you’re building advanced queries via Django ORM, it’s hard to read and understand such queries in Python, and hard to predict which SQL query will be generated and treated to the database. It’s worth saying that we also set up a second database, which is handled by Django ORM to cover other web application related tasks and business-logic needs, which it perfectly does. Django ORM is evolving from version to version, giving more and more features. For example, in recent releases, a bunch of neat features were added like support of or and many others, which you should definitely try before doing raw SQL or looking at the tools like SQLAlchemy if your problem is more complex than fixing a few queries. Subquery expressions Window functions So that’s why we decided to take a look at SQLAlchemy. It consists of two parts — ORM and Core. SQLAlchemy ORM is similar to Django ORM, but at the same time, they differ. SQLAlchemy ORM uses a different concept, Data Mapper, compared to Django’s Active Record approach. As far as you’re building projects on Django, you definitely should not switch ORM (if you don’t have very special reasons to do so), as you want to use Django REST framework, Django-admin, and other neat stuff which is tied to Django models. The second part of SQLAlchemy is called Core. It’s placed right between high-level ORM and low-level SQL. The Core is very powerful and flexible; it gives you the ability to build any SQL-queries you wish, and when you see such queries in Python, it’s easy to understand what’s going on. For example, take a look into a sample query from the documentation: q = session.query(User).filter(User.name.like('e%')).\      limit(5).from_self().\    join(User.addresses).filter(Address.email.like('q%')).\    order_by(User.name) Which will result into SELECT anon_1.user_id AS anon_1_user_id,         anon_1.user_name AS anon_1_user_nameFROM (SELECT "user".id AS user_id, "user".name AS user_name  FROM "user"  WHERE "user".name LIKE :name_1   LIMIT :param_1) AS anon_1JOIN address ON anon_1.user_id = address.user_id  WHERE address.email LIKE :email_1 ORDER BY anon_1.user_name Note: with such tricks, we don’t fall into : makes an additional wrapper around the query, so we reduce the amount of rows at first (via and ) and only then we join the address information. N+1 problem from_select SELECT LIKE LIMIT How to mix Django application and SQLALchemy So if you’re interested and want to try to mix SQLAlchemy with Django application, here are some hints which could help you. First of all, you need to a global variable with Engine, but the actual connection with DB will be established on first or call. create connect execute sa_engine = create_engine(settings.DB_CONNECTION_URL, pool_recycle=settings.POOL_RECYCLE) Create_engine accepts additional configuration for connection. MySQL/MariaDB/AWS Aurora(MySQL compatible) have an interactive_ timeout setting which is 8h by default, so without pool_recycle extra parameter you will get annoying . So the should be smaller than . For example a half of it: SQLError: (OperationalError) (2006, ‘MySQL server has gone away’) POOL_RECYCLE interactive_timeout POOL_RECYCLE = 4 * 60 * 60 Next step is to build your queries. Depending on your application architecture, you can declare tables and fields and classes (which also can be used with ORM), or if your application already stores tables and columns names in another way, you can do it in place, via table ( ) and column ( ) functions (as shown ). using Table Column table_name col_name here In our app, we picked the second option, as we stored information about aggregations, formulas, and formatting in our own declarative syntax. Then we built a layer which read such structures and executed queries based on the provided instructions. When your query is ready, simply call . The cursor would be opened until you read all the data or if you close it explicitly. sa_engine.execute(query) There is one very annoying thing worth mentioning. As a , SQLAlchemy has limited ability to do query stringification, so it’s not so easy to get a final query which will be executed. You can print query by itself: documentation says print(query)

SELECT  role_group_id, role_group_name, nr_patients  FROM "StaffSummary"  WHERE day >= :day_1 AND day <= :day_2 AND location_id = :location_id_1 AND service_id = :service_id_1 (This one looks not so scary, but with more complex queries it could be about 20+ placeholders, which are very annoying and time-expensive to fill manually to play later in SQL console.) If you have only strings and numbers to be inserted into query, this will work for you print(s.compile(compile_kwargs={"literal_binds": True})) For dates, such a trick will not work. There is on StackOverflow on how to achieve the desired results, but solutions look unattractive. a discussion Another option is to enable queries logging into the file via database configuration, but in this case, you could face another issue; it becomes hard to find a query you want to debug if Django ORM connected to this database too. You May Also Like: _Whether you're planning to expand your programming skills or get a fresh career start as a software developer, learning…_djangostars.com Best Python & Django Books And Tutorials For Beginners _I frequently face a recurring situation when developers receive a task to make a performance optimization on Django…_djangostars.com Django Performance Optimization Tips Testing Note: Pytest says “Currently pytest-django does not specifically support Django’s multi-database support. You can however use normal Django TestCase instances to use it’s multi_db support.” multidb note So what does it mean — not support? By default, Django will create and remove (at the end of all tests) a test-database for each db listed in definition. This feature works perfectly with also. DATABASES pytests Django and with enables erasing of data in multiple databases between tests. Also it enables data loading into second database via , but it’s much better to use instead, which are not affected by this attribute. TestCase TransactionTestCase multi_db=True django-fixtures model_mommy_ or _factory_boy There are a few hacks suggested in how to work around the issue and enable to continue pytesting. pytest-django discussion multi_db There is one important advice — for tables that have Django-models, you should save data to DB via Django-ORM. Otherwise, you will face issues during writing tests. will not be able to rollback other transactions which happened outside from Django DB connection. If you have such a situation, you may use with for tests which trigger functionality, which produces DB writes through SQLAlchemy connection, but remember that such tests are slower than regular . TestCase TransactionalTestCase multi_db=True TestCase Also, another scenario is possible — you have Django-models only in one database and you’re working with the second database via SQLAlchemy. In this case, doesn’t affect you at all. In such cases, you need to write a pytest-fixture (or do it as a mixin and trigger logic in if you’re using unittests) which will create DB structure from SQL file. Such a file should contain statements before . This fixture should be applied to each test case which manipulates with this database. Other fixture could load data into created tables. multi_db setUp DROP TABLE IF EXISTS CREATE TABLE Note: Such tests will be slower as tables will be recreated for each test. Ideally, tables should be created once (declared as ), and each transaction should rollback data for each test. It’s not easy to achieve because of different connections: Django & SQLAlchemy or different connections of SQLAlchemy connection-pool, e.g in your tests you start the transaction, fill DB with test data, then run test and rollback transaction (it wasn’t committed). But during the test, your application code may do queries to DB like connection.execute(query) which performed outside of transaction which created test data. So with default transaction isolation level, the application will not see any data, only empty tables. It’s possible to change transaction isolation level to for SQLAlchemy connection, and everything will work as expected, but it’s definitely not a solution at all. @pytest.fixture(scope='session', autouse=True) READ UNCOMMITTED Conclusion To sum up everything above, SQLAlchemy Core is a great tool which brings you closer to SQL and gives you understanding and full control over the queries. If you’re building the application (or a part of it) which requires advanced aggregations, it is worth it to check out SQLAlchemy Core capabilities as an alternative to Django ORM tools. Read on to learn how to make building advanced queries for data analysis projects easier. Find out how we managed to mix Django ORM and SQLAlchemy Core and what we got from it. This article about is written by — Senior Software Developer at Merging Django ORM Gleb Pushkov Django Stars If you find this post useful, please tap 👏 button below :)

Merging Django ORM with SQLAlchemy for Easier Data Analysis

The article about is written by Arthur Bachinskiy — COO at . financial products Django Stars . Read full article on Django Stars blog How do you find your way and stay afloat in fintech? This new technology took the world by storm, but it’s complexity is still hard to compete with. First of all, there are state-level regulations, integrations with different services and institutions, bank API connections, etc. to deal with. The second step is to conquer the hearts and the trust of the end users — running finance, mortgages, investments and so forth isn’t a child’s play. And to be able to do it, you need the highest level of security, functionality, and correspondence with requirements. All this basically means that you need something really unique — a one of a kind technology that offers a trustworthy solution. Obviously, the more unique your software is, the higher it’s valued. And without properly working and solid software, any financial venture will die down and lose worth. No matter the background, everyone wants their money to be safe. Which is why people are looking for a financial technology that will last, and I’d like to tell you about how we achieved all this by using the Python/Django technological stack while developing . I hope it’ll be especially useful for you now that Python has become . fintech products the world’s most popular coding language Standing Out In The Age Of Millennial Finance The modern world of finance houses two worlds that still coexist. For once, there are millennials who swipe themselves through life while mastering contactless payments, using on-line banking and all kinds of digital financing services. Their new world is built on new technology that despises old-school bureaucracy. The other world belongs to the good old traditional finance. Sadly, this is an extremely old and rusty machine that can’t be stopped on a whim. Even if it accepts the new technology and its effect on finance, it still doesn’t see it as neither as a threat, nor as a worthy competitor. Such an imperturbable policy is only to find in the most developed countries of the G7 — where all the old money is located, as well as the most people that are ready to operate highly technological startups. But sadly, changing their hard-shelled financial system is going to be a hell of a challenge. In their Deloitte shows, for example, G7’s habits when it comes to financial technology, as opposed to the rest of the world. Deloitte researchers note: statistics for 2017 Surprisingly, with regard to mobile payments, 40 percent of executives from the United States expect little to no impact to their industry. With the caveat that the samplesize is relatively small, 7 out of the 17 US banks (41 percent) saw little tono impact from mobile wallets and other payment technologies, vs. 14 out of 36(37 percent) of the nonbanks. Developing countries present an entirely different picture. Lacking a hardened, tradition ruled financial sector, they allow more space for fintech to grow and develop. Which, in turn, gives people more opportunities and ways to easily work with developed countries and get paid more securely. To be honest, this is what I love most about fintech — it removes financial borders! Usage of emerging technologies: G7 vs rest of the world (ROW) The G7 may remain skeptical about fintech, but technology keeps changing finance. The thing is — everything in this world changes fast, and so does technology. It’s , it is able to to the new users’ needs — it’s exactly what millennials want. Their new habits, high digital sensitivity, digital presence — all this is part of the millennial way of life that doesn’t leave them any time to waste and requires them to be productive 24/7. Which is why they value financial freedom anywhere anytime. flexible adapt To confirm my thoughts, here’s a blog by the , that deals with mobile payments and financial literacy. Apparently, the ease of payments attracts people that are comfortable with technology and have a busy lifestyle. Mobile payment users are mostly highly educated and employed full-time, predominantly male and very active financially. Compared to non-users, they are more likely to have bank accounts, retirement accounts and/or own homes, as well as make use of auto loans and mortgages. Wall Street Journal What conclusion can we make? WSJ stats show that users of mobile payments earn more than non-users, they are more financially active and financially literate, i.e. they use a wider variety of financial products. At the same time, they’re more careless about their expenses and more likely to go into debt. Sometimes, they can even take money from their retirement accounts. Which calls for a whole new fintech wave of simple tools that will help millennials get their money in order. Despite high incomes and education levels, millennials who use mobile payments are reported to have a and mismanagement. greater risk of financial distress Finance is an industry that has to be especially sensitive towards new customer demands. But in the era of digital disruption, even more so. There’s always a danger that customers will stop using your service when it becomes more common and necessary. How do you prevent that? And can you create a product that will stand the test of time and serve millennials when they grow up and start earning really big money? I mean, like the generation at which the current financial system is aimed. Branches like mortgages, investments, and wealth management should be especially cautious. now later This is the time when I’m going back to what I said earlier. To survive, to get a strong following and clients who rely on it, your technology has to be unique, sturdy, safe and custom tailored to your customers’ needs. At this point, it won’t be possible to avoid integration with traditional financial and state institutions. Which is why you have to make sure the cooperation runs flawlessly, and you seem a reliable business partner in the eyes of the latter, and they use your technology, and not someone else’s. Or worse, create a technology of their own! More about fintech takeways: _In the 21st century, we are feeling like we are finally living in the future that everyone's been waiting for, and…_djangostars.com Top Fintech Takeaways of 2018 A great example of a unique technology that totally paid off is our client — formerly a startup, and now Switzerland’s largest technology-based mortgage intermediary. Thanks to their convincing technological solution and business approach, the company became part of . MoneyPark Helvetia Insurance Read the Full Money Park Case Study: Python: The Finance & Fintech Secret Weapon So, what do we need? A technology sturdy enough to withstand the stress of worldwide financial perturbations, but still flexible enough to adapt to the challenges of the new world and the customers’ growing needs. As for us, we chose to work with Django framework within Python — it proved to be a great choice, and we’re still discovering all the possibilities this combo gives us. We’re not trying to sell you Python as the solution to all of your problems, but we certainly know what kind of advantages Python has for finance. It’s quite simple: with the Python/Django stack, you can build an MVP quite fast, which increases your chances to find your product/market fit. 1. Faster way to market with Python/Django stack. The only way fintech will be able to compete and/or collaborate with traditional banking and finance is adapting to changes and customer’s demands, offering additional services and improvements according to customer’s wishes. Your technology must be flexible and offer solid ground for numerous additional services. The Python/Django framework combo takes into account the needs of an MVP and allows to save some time developing it. They basically work like a Lego — you don’t need to develop small things like autorisation or user management tools from scratch. You just take whatever you need from the Python libraries (Nimpy, Scipy, Scikit-learn, Statsmodels, Pandas, Matplotlib, Seaborn, etc.) and build an MVP. Another big advantage that Django gives you at the MVP stage is a simple admin panel or CRM — it’s built-in; you just have to set it up for your product. Of course, at the MVP stage, the product isn’t complete, but you can test and easily finish it, as it’s very flexible. After the MVP is done, this tech stack allows to adapt parts of code. This means that after you validate the MVP, you can either easily change some code lines or even write new ones, if this is required for the product to function flawlessly. Millennials are used to living in a fast-paced world and the need to be productive 24/7. What they expect from everyone else and from services they use is maximum transparency and only high-quality service. This is why customer development is so important — a whole generation depends on it. Consequently, the sooner you get your product to market, the quicker you collect feedback and improve your product. Python programming in finance allows you to do this with your hands behind your back. Obviously, fintech can’t exist without mathematicians and economists who calculate their algorithms and formulas using Python. Languages like R and Matlab are less common among economists, and Python became the most useful programming language for finance, as well as . Economists use it to make their calculations, so obviously it’s easier to integrate them with a Python based product. However, sometimes even pieces of code that are written in the same language are hard to integrate, which is why the presence and communication with your tech partner is crucial. 2. Mathematical and economical use of Python. the programming “lingua franca” of data science Simplicity is genius. Due to its simplicity and easy-to-understand syntax, Python is very legible and everyone can learn it. Which is why, becoming the “lingua franca”, in my opinion, was just a matter of time. Python creator confirms my thoughts describing it as a 3. Simpler syntax — easier collaboration. Guido van Rossum “high-level programming language, and its core design philosophy is all about code readability and a syntax which allows programmers to express concepts in a few lines of code.” So, the good thing about is that Python is easily understandable not only for technical specialists, but for clients as well. People involved in the development process from both sides have different levels of technical understanding. With Python, engineers can explain the code much easier, and clients can better understand how the development is progressing. See, it’s a win-win. As The Economist says about Python: The language’s two main advantages are its simplicity and flexibility. Its straightforward syntax and use of indented spaces make it easy to learn, read and share. Its avid practitioners, known as Pythonistas, have uploaded 145,000 custom-built software packages to an online repository. These cover everything from game development to astronomy, and can be installed and inserted into a Python program in a matter of seconds. Which brings us to the next point. Thanks to Python’s open libraries, you don’t have to build your tools from scratch and develop the product and analyze large amounts of data in the shortest amounts of time. If you’re in the MVP stage, this can save you a lot of time and money.As I mentioned before, fintech products require a lot of integrations with third parties. Python libraries make integrating your product with other systems through different API a lot easier. In finance, API can help you collect and analyze the required data about users, real estate, and organizations. For instance, in the UK, you can get people’s credit history by API, which is required to proceed further financial operations. By using API in the online mortgage industry, you check real estate data and verify someone’s identity. On top of it, you can get the data or filter it in one click without having to develop new tools for that by using and combining different libraries/packages. 4. Python’s open libraries include tools for API integration. Django Stars, for instance, use the to build APIs or to integrate with external ones, as well as Celery to queue or distribute tasks. Django Rest Framework According to the , Python is the second language coders are going to learn next and is among TOP-3 languages in financial services and other progressive industries. Which is great, because Python will continue developing, giving access to more and more specialists, which, in turn, guarantees enough people to develop and maintain our products in the future. 5. Python popularity grows. HackerRank 2018 Developer Skills Report Python wins the heart of developers across all ages, according to our Love-Hate index. Python is also the most popular language that developers want to learn overall, and a significant share already knows it. — HackerRank Python has more uses than you may think: from traditional ones like web development to cutting edge, like AI. It’s incredibly flexible and versatile it has that let you build your product like a Lego. It’s the go-to language for data analysis, which makes it attractive for non-technical fields like business, and the best programming language for financial analysis. over 125,000 third-party Python libraries Again, I’m not trying to say that Python is the only way to go. I’m only describing my own experience, quite successful ones, I might add. I saw Python do wonder when applied within the Django Framework. And this is what you need to make in it fintech — an extraordinary tool that will make your product trustworthy, fully secure and functional. Adhering to state regulations, dealing with integration with services, institutions, and bank API connections — all this requires attention to detail and longevity of software to support the new generations of millennials who are taking over the future. Get to the top, be among the ones who change the financial market, better yet, who change the world. Be unique, efficient, user-oriented, and open for the future. This is what Python is all about. If you find this post useful, please tap 👏 button below :)

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