IT consulting and software development company. Since 2010, we’ve been supporting businesses worldwide in gaining competitive advantage by means of modern technology. We advise on digitalization, develop and implement high-quality solutions, and augment our clients’ teams with skilled software developers.

Codete

<h2 style="text-align:justify;">In this project, our main goal was to review and improve the viability of the client system’s infrastructure.&nbsp;</h2><p style="text-align:justify;">&nbsp;</p><h3 style="text-align:justify;">Challenge: Collecting and monitoring data smoothly</h3><p style="text-align:justify;">Aside from using Prometheus as the main data collector for monitoring data, we were aiming at measuring services performance to predict and track bottlenecks. To do so, we've co-worked with development teams implementing /metrics endpoint for each service. This approach allowed us to collect more useful data from each application. And, to make it even more detailed and trackable, we've added OpenTelemetry solutions to the services.&nbsp;</p><figure class="image" height="631" width="1201"><img src="https://storage.googleapis.com/codete-live-strapi-uploads/codete_case_study_data_monitoring_service_1_61692eb7bc/codete_case_study_data_monitoring_service_1_61692eb7bc.png"></figure><p style="text-align:justify;">&nbsp;</p><h3 style="text-align:justify;">Solution: Implementing tools for data aggregation, visualization and alerting</h3><p style="text-align:justify;">A monitoring system won't be complete without aggregating logs and trying to parse them to get the businesses logic information from them. That’s why we suggested FleuntBit as a log delivery tool, combined with storing outputs in ES cluster and S3 storage as an archive. What’s crucial,&nbsp; adding different kinds of storage to ElasticSearch cluster and applying retention policy helped us cut down the costs.&nbsp;&nbsp;</p><p style="text-align:justify;">Being able to collect the data is one thing, and being able to visualize it is a different challenge. To fix that, we recommend picking Grafana (perfect to draw metrics) along with Kibana – a top tool for browsing logs and visualizing the content of them on the graphs.</p><p style="text-align:justify;">We had the data, we were able to monitor it but we were still missing alerting. The client asked us to set alerts via the Opsgenie tool and enable them on Slack. To make this feature even more flexible, we decided to use Ansible to generate both Prometheus alert rules and Grafana dashboards. Thanks to that, adding a new application to the customer stack doesn’t require manual work on a monitoring site anymore.</p><p style="text-align:justify;">&nbsp;</p><blockquote><p style="text-align:justify;"><strong>Results in numbers:</strong></p><ul><li>gathering monitoring data from 5 Kubernetes clusters</li><li>counting SLO based on SLI for more than 40 services</li><li>aggregating 20G of logs daily</li></ul></blockquote><p style="text-align:justify;">&nbsp;</p><h3>Tech stack</h3><figure class="image" height="81" width="942"><img src="https://storage.googleapis.com/codete-live-strapi-uploads/codete_case_study_data_monitoring_service_tech_stack_222fe118f5/codete_case_study_data_monitoring_service_tech_stack_222fe118f5.png"></figure><p>Prometheus, Grafana, Elasticsearch, Kibana, Fluentbit, OpenTelemetry</p><p>&nbsp;</p><h3>Tell us about your project</h3><p>Can we offer you a hand in developing your product? Once you let us know about your requirements, our DevOps experts will prepare an initial estimation, schedule a call and discuss your project in detail. All information will be kept confidential. <a href="/estimation" target="_blank">Let's get in touch &gt;</a></p>

Case Study: Data Monitoring Service | Codete Blog

Case Study: Data Monitoring Service

Dawid Pacholczyk

<p><strong>Design methodologies</strong> is a term that may sound a little vague but if we summon up things like Lean Startup, or Design Sprint approaches, everything becomes much clearer. Of course, there are many more items on the product development methodologies list. Using each one of them may be very beneficial for developers and save the day or, at least, a lot of time, money, and effort.</p><p>Increased efficiency and team members’ motivation as well as providing better products and more reliable software may be in the cards. But of course, the devil is in the details, and it’s necessary to know all the intricacies, pros and cons, highlights, and downsizes of all those design methodologies before deciding to choose one of them for your project. Also, knowing the use cases of particular methods may be crucial to assess things right.</p><p>&nbsp;</p><p>Table of contents:</p><p>1. <a href="#trends">Design methodologies – top 2021 trends</a></p><p>2. <a href="#key-methodologies">5 design methodologies you should know</a></p><p>3. <a href="#choosing">How to choose the right design methodology for your project?</a></p><div class="raw-html-embed"><section id="trends" style="height: 20px;"></section></div><h2>Design methodologies – top 2021 trends</h2><p>Design Methodology ideas and developing digital products are what go hand in hand together very well. In the extremely competitive IT market, nothing should be left to chance, and selecting the right approach, philosophy or model, can tip the scales and make a given application, tool, or solution stand out, and in a good way. Moreover, they can make a business, especially a new one, stay afloat or go down. Certainly, being swift, flexible, willing to learn new things, and adapt to changing circumstances is on top of everything else.</p><p>For this reason, what’s still on track and very much up-to-date in terms of the product design process are solutions that are flexible, agile, and based on feedback and time-boxed iterations. All those can make digital product design more efficient, speedy, and aligned to the ever-changing circumstances of the hasty times we are living in. Whatever happens within or outside the project, it’s good to be able to change the course of action accordingly.</p><p>For those reasons, along with those product design approaches, Agile methodologies or Waterfall methodology for project management may be used once you decide which products or solutions to develop.</p><div class="raw-html-embed"><section id="key-methodologies" style="height: 20px;"></section></div><h2>5 design methodologies you should know</h2><p>Among a plethora of project management tools and solutions available, there are some we should pay special attention to. What do those design methodologies look like in detail? Let’s see.</p><p>&nbsp;</p><h3>1. Design Sprint methodology</h3><p>Reducing risk before a new product hits the market or a new feature is introduced is more than welcome in virtually any industry. And this is when Design Sprint comes into play, offering a five-phase process encompassing stages like Understand, Diverge, Converge, Prototype, and Test. Interestingly, this method of addressing strategic issues draws upon both design thinking and Agile methodologies – and time-boxed sprints as for the latter. Within the cycle, a <a href="https://ajsmart.com/design-sprints/" target="_blank" rel="nofollow">high-fidelity interactive prototype gets tested by real users</a>. The bottom line is that guesswork is eliminated and you may find out within a few days, and not months, if the product in question is worth developing, or not.</p><p>&nbsp;</p><h3>2. Lean Startup methodology</h3><p><a href="http://theleanstartup.com/principles" target="_blank" rel="nofollow">Eliminating uncertainty</a> startups inevitably have to deal with is a hallmark of another design methodology – Lean Startup. It was born out of the willingness to engineer the startup success, by following the process suggested. It all started in the year 2011 when the book „The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses” by Eric Ries was published. But it was based on the author’s experience and failure to succeed with launching a new start-up enterprise. This led him to the conclusion that more emphasis should be put on understanding the needs of prospective customers, and not on the act of product launch – one that people may actually don’t want – per se. Moreover, by testing their visions continuously, new businesses may choose order instead of chaos.</p><p>&nbsp;</p><h3>3. Product discovery</h3><p>This approach also puts attention to the greater importance of things like preparatory and preliminary actions and continuous learning about users. <a href="https://www.productboard.com/blog/step-by-step-framework-for-better-product-discovery/" target="_blank" rel="nofollow">Researching and validating ideas upfront</a> may be the new enterprise’s salvation. In short, users’ true needs or problems should be identified first, and next, solutions to them should be designed, developed, and delivered collaboratively. Not the other way round. Product discovery is to weaken risks involved that concern value, usability, feasibility, and business viability, and risk management, in fact, is product management.</p><p>&nbsp;</p><h3>4. Wizard of Oz prototyping</h3><p>Trying to figure out what customers might think about given products is in the center of the Wizard of Oz (WOZ) prototyping. This method <a href="https://searchcio.techtarget.com/definition/Wizard-of-Oz-prototyping" target="_blank" rel="nofollow">involves some role-playing</a> with the use of a prototype test – a physical product or working model. There are two roles to be filled – of an end-user and the person that is to enact the completed product’s performance. The <a href="https://www.designthinking-methods.com/en/5Testen/wizardofOzTE.html" target="_blank" rel="nofollow">motive behind those actions</a> – which can only take one hour in some cases – is to test functionalities before they exist and find out which ones are necessary.</p><p>&nbsp;</p><h3>5. Concierge testing</h3><p>This down-to-earth methodology is about immersing into potential customers’ natural environment (like shops or cafes) for gathering their insights on hypothetical products. Participants’ answers to directly asked questions as well as their emotional responses are collected. <a href="https://kromatic.com/blog/concierge-vs-wizard-of-oz-test/" target="_blank" rel="nofollow">Concierge testing is sometimes confused with WOZ</a> but the difference between them is that the former is designed for generating ideas, and the latter – for testing hypotheses.</p><div class="raw-html-embed"><section id="choosing" style="height: 20px;"></section></div><h2>How to choose the right design methodology for your project?</h2><p>Because <a href="https://www.wsj.com/articles/SB10000872396390443720204578004980476429190" target="_blank" rel="nofollow">three out of four startups fail</a>, their originators need to thread carefully from the very beginning of their ways. Design methodologies may be very helpful not only in avoiding the disaster but also in shaping the future right. They may be proper both before launching a new product or service and in the next phases of the company’s existence when new features or functionalities are considered. If design methodologies are chosen well, they may obviously tip the scales in the world of similar companies offering similar apps or services.</p><p>Developing digital products is something that requires being flexible on one hand and firm support on the other. And the latter can take the form of an efficient product design methodology. And choosing the right one can simply make your project flourish or turn it into a failure.</p><p>A properly selected design method can make it or break it in the case of the majority of tech products’ development. During a decision making process, it’s good for a product designer to pay attention to the methods’ objectives, conditions, and use cases. But, first and foremost, it’s crucial to get to know all the ins and outs, benefits, and restrictions of using particular design methodologies.</p><p><strong>And you, which type of design methodologies in software development do you find the most proper for start-ups? Which kind is the most versatile and useful for product designers? Which methodologies are trending in the year 2021?</strong></p>

Top Design Methodologies - The 2021 Overview | Codete Blog

5 Popular Types of Design Methodologies You Should Know

IT Content Writer with 12 years of professional writing experience. Prefers facts and figures to any kind of fiction.

Dominika Reszke

Software Developer. Passionate about creating readable and testable code and architecture. Happy dad and traveller.

Mateusz Angulski

<p>Node.js has been in the limelight for over a decade and utilizing<strong> Node.js as backend </strong>is much more common than making use of it in the frontend of applications. A <a href="https://nodejs.org/en/user-survey-report/" target="_blank" rel="nofollow">2018 Node.js User Survey Report</a> indicated that while 37% of Node.js users are focused primarily on the back-end, and 39% - on full-stack development, only 14% use it first and foremost for front-end purposes.</p><blockquote><p>This lightweight, efficient, fast, multi-purpose, and extremely versatile JavaScript environment is immensely popular, outshining many other well-known technologies. In Stack Overflow’s annual Developer Survey for 2020, <a href="https://insights.stackoverflow.com/survey/2020#technology-other-frameworks-libraries-and-tools" target="_blank" rel="nofollow">Node.js came first</a> in the „Other Frameworks, Libraries, and Tools” category, with over a half of professional developers (51.9%) utilizing it.</p></blockquote><p>What’s more, over two-thirds (66.8%) of programmers who already use it want to continue doing so in the future, making Node.js one of the <a href="https://insights.stackoverflow.com/survey/2020#technology-most-loved-dreaded-and-wanted-other-frameworks-libraries-and-tools-loved3" target="_blank" rel="nofollow">technologies that are the most „loved”</a> in this category. Microsoft, PayPal, Netflix, eBay, General Electric, and Yahoo! are all where we can find Node’s trace. Another Node.js backend example? NASA, Netflix, Uber, Twitter, Trello, PayPal, LinkedIn, and Groupon are also on the list.</p><p>Is Node.js backend only? Using Node.js as backend may be more obvious as Node.js is most commonly referred to as a backend JavaScript runtime environment. However, not only Node.js server side but also Node.js client side applications are possible to design and implement. But let’s focus on the main topic, which is Node.js backend applications.</p><p>&nbsp;</p><p>Table of contents:</p><p>1. <a href="#when-why">Node.js as backend – when and why develop with it</a></p><p>2. <a href="#pros-cons">Node.js backend: pros and cons</a></p><p>3. <a href="#wrap-up">Node.js as backend wrapped up</a></p><div class="raw-html-embed"><section id="when-why" style="height: 20px;"></section></div><h2>1. Node.js as backend – when and why develop with it</h2><p>On the website devoted to it, Node.js is called a „<a href="https://nodejs.dev/learn" target="_blank" rel="nofollow">popular tool for almost any kind of project</a>”. However, its definition published <a href="https://nodejs.dev/" target="_blank" rel="nofollow">in the same source</a> reads that this JavaScript run-time environment lets programmers „write command line tools and server-side scripts outside of a browser”, with the back-end side of Node.js emphasized from the very beginning. But what kind of server-side tasks it is best suited to? When to use Node.js as backend, to take advantage of it fully?</p><p>Building highly scalable applications, even data-heavy ones, is one of the major use cases of Node.js. In particular, this event-driven environment based on a non-blocking I/O model is perfect for developing real-time solutions, being famous for quick client-server interactions, no latency, and push capabilities. Online gaming and single-page applications are also often in the mix.</p><p>In general, many of the backend use cases of Node.js include web applications that have to do with things like <a href="https://www.credencys.com/blog/node-js-development-use-cases/" target="_blank" rel="nofollow">multiple concurrent requests, heavy client-side rendering, and frequent shuffling of data</a>.&nbsp;</p><blockquote><p>What companies that take advantage of Node.js <a href="https://www.techmagic.co/blog/companies-that-use-node-js-for-backend-how-do-big-players-benefit-from-it/" target="_blank" rel="nofollow">may gain by utilizing</a> it are, among others, scalability, transparency, improved user experience, decreased number of servers needed, immense connectivity, increased traffic capacity and loading speed, reduced response time, and decreased loading time, and thus lowered expenses.</p></blockquote><p>The <a href="https://nodejs.org/en/user-survey-report/" target="_blank" rel="nofollow">2018 Node.js User Survey Report</a> indicated that for many users, Node.js entails a positive business impact. As much as 68% said it increased developer productivity, 62% that it improved developer satisfaction, 56% that it reduced development costs and 48% that it increased application performance. As for the latter, it was the case of eBay who switched to Node.js from Java due to its „<a href="https://www.techmagic.co/blog/companies-that-use-node-js-for-backend-how-do-big-players-benefit-from-it/" target="_blank" rel="nofollow">long startup times and poor performance</a>”.</p><div class="raw-html-embed"><section id="pros-cons" style="height: 20px;"></section></div><h2>2. Node.js backend: pros and cons</h2><p>An impressive number of Node’s advantages explains the reasons why it has taken the software development world by storm. Some of the pros of making use of it include the possibility to use JavaScript also on the server side. In short, front-end developers who already know JavaScript don’t have to learn a new programming language if they wish to write some code for server-side purposes. Of course, it works both ways, making Node.js an exceptionally advantageous technology with code universality as its hallmark.</p><blockquote><p>Those two-way connections between server and client are one thing, and the fact that they are event-driven is another. For this reason, Node.js is a perfect solution for those who want to develop things like real-time collaboration tools, and real-time chat applications as well as <a href="https://www.credencys.com/blog/node-js-development-use-cases/" target="_blank" rel="nofollow">streaming web apps and microservices architecture</a>.</p></blockquote><p>Node.js is simply known for being very fast – not only in terms of the development process but also data processing. Another Node’s advantage is the <a href="https://nodejs.org/en/user-survey-report/" target="_blank" rel="nofollow">ease of learning it</a>. Interestingly, about half of programmers utilizing Node.js praise this feature, and this is the case of 50% of those who use it primarily for backend purposes. As for those who focus on front-end development, 42% say that it was easy to learn Node.js. A strong community and huge Node.js ecosystem certainly facilitate it.</p><p>As for the downsides, <a href="https://snipcart.com/blog/javascript-nodejs-backend-development" target="_blank" rel="nofollow">some of the developers</a> emphasize the fact that although Node.js gives programmers a lot of freedom in terms of decision-making, this also entails greater responsibility and the risk of choosing the wrong path. Moreover, building a massive web server as well as debugging may be somewhat demanding with Node. Specifically, this platform is ideal for I/O-bound work but not really for CPU-intensive tasks. In other words, it is fast when the work associated with each request is small in terms of processor time needed to handle it.</p><div class="raw-html-embed"><section id="wrap-up" style="height: 20px;"></section></div><h2>3. Node.js as backend wrapped up</h2><p>Node.js, an open source, cross-platform JavaScript runtime environment built on Chrome’s V8 JS engine, is primarily used in backend applications. Obviously, this trending technology for building cutting-edge web applications is great for full-stack developers, too. Some software developers even argue that it’s worth going the extra mile to learn Node despite developing the frontend only to know how the backend works. Also, most of the tooling for frontend frameworks these days is based on the Node.js platform.</p><p>Node.js significantly speeds up the development as well as the team’s efficiency and performance, and one of the reasons for that is that it makes use of JavaScript on both the front end and the back end. And because time is money, we may expect that this technology’s huge popularity will continue to grow.</p><p><strong>And how would you comment on that? What are your experiences with Node.js as backend? To you, what are the challenges of developing with it? What kind of projects or content type is it best suited to? Can you spot any significant limitations of using it?</strong></p>

Node.js as Backend - Why, When and How to Use It | Codete Blog

Node.js as Backend - We Are Explaining Why, When and How to Use It

<h2>We assisted People Analytix in implementing modern DevOps practices.&nbsp;</h2><p>The company was facing problems caused by being hosted by a Swiss-based cloud provider, known for its limited services. To overcome that, we’ve been tasked to implement a large number of services in-house, maintain them, and prepare for scaling up without the assistance of cloud autoscaling solutions.</p><figure class="image" height="631" width="1201"><img src="https://storage.googleapis.com/codete-live-strapi-uploads/codete_case_study_people_analytix_1_4a78ccdff1/codete_case_study_people_analytix_1_4a78ccdff1.png"></figure><p>&nbsp;</p><h3>Challenge: Introducing DevOps best practices</h3><p>Before we jumped into the infrastructure, our client was forced to update it manually, causing bottlenecks in the CI/CD process. The development team has been dependent on an administrator, who was the only person in the company who could run deployments onto production services.&nbsp;</p><p>Thanks to Codete DevOps assistance, we made it possible to simply offload such tasks to the dev team, with proper orchestration in place. As for now, every developer with the ability to perform deployments or rollbacks can do so without extensive training.</p><p>&nbsp;</p><h3>Solution: Smooth transition to GCP</h3><p>As our client grew with us, they began to use Google Cloud Platform to perform some of the big data tasks. Once again, we’ve managed &nbsp;to onboard them on the GCP cloud in a transparent manner, with no disruption to the customer. Currently, the company is utilizing a multi-cloud setup (Swiss Exoscale and GCP).&nbsp;</p><p>&nbsp;</p><blockquote><p><strong>Results in numbers:</strong></p><ul><li>more than 20 virtual machines</li><li>60 big data batch jobs being managed as a code</li><li>4 environments, total of 100 running microservices</li><li>all microservices are deployable by the dev team and managed as a code</li><li>12 databases (some of them around 1 TB in size)</li><li>14 infrastructure services, which support actual product services</li></ul></blockquote><h3>&nbsp;</h3><h3>Tech stack</h3><figure class="image" height="81" width="2092"><img src="https://storage.googleapis.com/codete-live-strapi-uploads/codete_case_study_people_analytix_tech_71a1157fe8/codete_case_study_people_analytix_tech_71a1157fe8.png"></figure><p>GCP, Exoscale, Terraform, Ansible, Prometheus, Jenkins, Hasicorp Vault, Python, Docker and Docker-compose, OpenVPN and IPsec tunnels</p><p>&nbsp;</p><h3>Tell us about your project</h3><p>Can we offer you a hand in developing your product? Once you let us know about your requirements, our DevOps experts will prepare an initial estimation, schedule a call and discuss your project in detail. All information will be kept confidential. <a href="/estimation" target="_blank">Let's get in touch &gt;</a></p>

Case Study: DevOps Services for People Analytix | Codete Blog

Case Study: People Analytix

Managing Director at Codete. He is a Master of Law and has a Harvard Business School degree. A business leader with extensive experience in finance and team management. Specialist in startups and business development.

Grzegorz Śmiałek

CTO at Codete. In 2015, he received his Ph.D. from the Institute of Fundamental Technological Research of the Polish Academy of Sciences. His area of expertise is artificial intelligence.

Karol Przystalski

<p>Fintech is one of the hottest startup niches that attracts millions of funding dollars and has brought some of the most impressive unicorns all over the world. However, fintech solutions are usually very complex and often have to meet certain security and compliance standards. <internallink internallinkid="/blog/the-fintech-era-top-10-european-fintech-startups-to-watch-in-2019-and-growth-tips-for-the-future-market-leaders">Fintech startups</internallink> have to deal with state-level regulations, national regulations, integrations with various services and institutions, and banking API connections.&nbsp;</p><blockquote><p>For fintech companies, capturing the attraction and trust of their end-users is just one part of the equation. What they need is the highest level of security, outstanding functionality, and compliance.</p></blockquote><p>This is why so many fintech startups choose Python as the foundation of their technology stacks. This highly popular programming language allows building unique software that delivers value to users and is bound to stay relevant for a very long time. Python powered many successful fintech products - from digital payment solutions like Stripe and financial analytics software like Kensho to entire banking platforms (think Revolut) and stock marketplaces like Robinhood.&nbsp;</p><p>Keep on reading to find out why Python makes such great technology for fintech products and why so many fintech success stories were enabled by this powerful programming language.&nbsp;</p><p><br>&nbsp;</p><p><strong>Table of contents:</strong></p><ol><li><a href="#intro"><u>Finance and Python: why is it such a great combination?</u></a></li><li><a href="#examples"><u>Using Python in finance - examples</u></a></li><li><a href="#wrapup"><u>Python in finance - wrap up</u></a></li></ol><div class="raw-html-embed"><section id="intro" style="height: 20px;"></section></div><h2>Finance and Python: why is it such a great combination?&nbsp;</h2><p>Python has become a go-to technology perfect for startups and financial services enterprises experimenting with new technologies. Below are the most important factors that contribute to the growth of Python in this sector.&nbsp;<br>&nbsp;</p><h3>Python accelerates development for faster time to market&nbsp;</h3><p>Using Python in combination with <internallink internallinkid="/blog/choosing-the-best-framework-for-python-flask-vs-django">frameworks like Django</internallink>, you can build an MVP really fast to increase the chances of finding your startup's product-market fit. Fast time to market is essential because it enables a company to compete or collaborate with banking institutions.&nbsp;</p><p><strong>It's essential that you can adapt to the changes in customer demands, offer extra services and improvements, and constantly grow your product. That's why your technology stack needs to allow this flexibility and provide your team with a solid foundation for adding numerous extra services.&nbsp;</strong></p><p>Python is a great choice for <internallink internallinkid="/blog/building-a-minimum-viable-product">building an MVP</internallink>. It helps to avoid losing time on building things that are part of practically every financial services application, like authorization or user management from scratch. You can simply take whatever you need from the vast ecosystem of libraries and create your MVP.</p><p>&nbsp;</p><h3>Python is great for any mathematical functions</h3><p>The finance industry couldn't exist without mathematicians and economists using statistical methods, creating algorithms and formulas. Languages like R and Matlab used for such purposes are less common and more complex than Python.&nbsp;</p><p>That's why Python became the go-to technology for finance and the programming lingua franca of data science. Economists use Python to make their calculations today, so a piece of software developed in Python will be much easier to integrate with their insights.&nbsp;</p><p>&nbsp;</p><h3>Python works well in AI and machine learning</h3><p>The financial industry generates massive volumes of data. Many banks and startups capitalize on these datasets to develop algorithms and statistical models for making predictions based on the continuously received stream of new data.&nbsp;</p><p><strong>AI and machine learning are commonly found in fintech products in areas like cybersecurity (for instance, fraud detection), personal finance, customer service, risk management, automated trading, and more.&nbsp;</strong></p><p>Python is an excellent language for machine learning projects thanks to its readable code, high speed of execution, a rich ecosystem of specialized libraries, and extremely supportive community.&nbsp;</p><p>&nbsp;</p><h3>Python is a secure and mature technology</h3><p>In an industry like financial services, every piece of software needs to meet strict demands around architecture, quality, and security. Moreover, it needs to comply with international and local laws and regulations. Finally, in order to gain the trust of its users, a fintech product needs to provide a reliable and trustworthy experience.&nbsp;</p><p>Python was first released in 1991. Over the last 30 years, developers have been working hard to gradually improve and optimize it. So, we're not lying when we say that Python is a <i>mature</i> technology.&nbsp; There are many developers that worked with Python for years and know exactly what challenges it poses. Understanding the weak points of the software and fixing them before they snowball into a problem is one of the benefits coming from that experience.&nbsp;</p><blockquote><p>In financial services, you only get one chance to build an app that is both secure and safe to use. If a user loses money because of a bug in your system, your reputation will be forever tarnished, and rebuilding it is going to be very hard (or even impossible).&nbsp;</p></blockquote><p>Imagine that a person loses money because something goes wrong in your system. Why would they go back to you when there are so many alternatives? When using Python in financial products, you mitigate the risk of security issues because it's a mature technology supported by a vast group of developers who are ready to fix any issue.&nbsp;</p><p>&nbsp;</p><h3>Python is perfect for carrying out complex operations on large amounts of data</h3><p>Python comes with a rich academic background since it serves as a common technology for many scientists and researchers across all domains (not only computer science). Thanks to Python's human-readable syntax, it's great for performing complex calculations that involve a lot of data.&nbsp;</p><p>Just consider that Python is today the main language for the majority of machine learning and AI developers. You can be sure that they deal with massive volumes of data. Python comes with a great ecosystem of packages and libraries made for data processing and computations with Big Data specifically.&nbsp;</p><p>&nbsp;</p><h3>Simpler syntax means easier collaboration</h3><p>Thanks to its easy-to-understand syntax, Python can be read and understood by practically everyone. As a high-level language, Python is all about code readability. It allows programmers to express concepts within a few lines of code. So, Python isn't only understandable to technical specialists but clients as well. Different product stakeholders with different levels of technical understanding can understand it and, as a result, engineers find explaining the code easier.&nbsp;</p><p>&nbsp;</p><h3>Python comes with a rich ecosystem of libraries and packages&nbsp;</h3><p>The language is surrounded by an incredibly productive open-source developer community that contributed more than 140k custom-built software packages that cover everything from machine learning and game development to astronomy and Big Data operations.&nbsp;</p><p>Developers can insert them into any Python program within just a few seconds. Python also offers tools for API integration. This means the developers don't have to build tools from scratch and create a product that processes large amounts of data fast. This can save you a lot of time and money if you're building an MVP.&nbsp;</p><p>&nbsp;</p><h3>Python has all the integrations</h3><p>Thanks to Python libraries and packages, you can integrate your product with other systems through different APIs easily. In financial services, APIs are used to collect and analyze the data organizations need about users, organizations, real estate, and many other things. For example, in the UK, people's credit history is available via an API. This data might be required in order to proceed with certain financial operations, so your application needs to include an easy way to integrate with such APIs. This is what you get in Python.&nbsp;</p><p>&nbsp;</p><h3>Python is incredibly popular</h3><p>And his popularity is only growing. In the <a href="https://insights.stackoverflow.com/survey/2021" target="_blank" rel="nofollow"><u>Stack Overflow Developer Survey 2021</u></a>, Python ranked as:</p><ul><li>The 3rd most popular language,</li><li>The 6th most loved language,</li><li>The 1st among the most wanted programming languages.</li></ul><p>Python is surrounded by an incredibly large community of passionate developers who are ready to help others solve problems. Thanks to the vast and diverse user base, the chances that the solution to your problem can be found in the documentation are pretty high.&nbsp;</p><p>Python's popularity also means that sourcing specialists from the market will be easier – whether it's <internallink internallinkid="/blog/how-to-be-a-good-python-developer-8-essential-skills">a junior, mid-level, or senior Python expert</internallink>.&nbsp;</p><div class="raw-html-embed"><section id="examples" style="height: 20px;"></section></div><h2>Using Python in finance - examples</h2><h3>Analytics tools</h3><p>Python finds a lot of use in quantitative finance products. These are solutions that process and analyze large data sets. Libraries like Pandas help to simplify such processing and help to visualize data. Powerful machine learning algorithms that are part of such libraries enable all kinds of predictive analytics functions and come in handy to practically all financial services providers.&nbsp;</p><h3><br>Banking software</h3><p>Financial institutions and hedge funds build payment solutions and online banking platforms using Python as well. For example, Venmo grew from a payment tool into an incredible social network. The language is flexible and simple, so it's a great pick for developing ATM software that boosts payment processing.&nbsp;</p><h3><br>Stock trading apps</h3><p>Stock markets generate a lot of stock data, so it's only natural that Python helps here as well. Developers use it to build web solutions that identify the best stock trading strategies, carry out data analysis, and offer actionable and predictive analytical insights into the condition of particular markets or organizations. Examples of such products are Zipline or Quantopian.</p><div class="raw-html-embed"><section id="wrapup" style="height: 20px;"></section></div><h2>Python for finance - wrap up</h2><p>As you can see, Python is an incredibly valuable technology for any kind of financial services product – from an enterprise <internallink internallinkid="/blog/what-is-proof-of-concept-and-how-to-do-it-right-expert-explains">Proof of Concept</internallink> to a startup <internallink internallinkid="/blog/building-a-minimum-viable-product">MVP</internallink>.</p><p><strong>Are you building a fintech product right now? If so, are you planning to use Python? If you need some extra Python talent on board, reach out to us – our Python specialists have experience in developing successful digital products for the financial services sector.</strong></p>

Python in Finance & Fintech - Why It's the Best Choice

<p>One of the things developers love about Python is the fact that its syntax is so simple and concise. Python code is almost as easy to read as plain English. Python’s most distinctive features, such as dictionary comprehension, list comprehension, and generator expression are the source of this elegance. Developers can use these three methods to create powerful functionalities within a single line of code.&nbsp;</p><p>However, many software engineers still struggle to take full advantage of some more advanced features of list comprehension in Python. And others tend to use this too much and end up with code that is harder to read by others and less efficient.&nbsp;</p><p>In this article, I dive deep into <strong>list comprehension</strong>, <strong>dictionary comprehension</strong>, and <strong>generator expression</strong> to show you what they are, how they work, and what potential trade-offs come with using these features.&nbsp;</p><p>&nbsp;</p><p>Table of contents:</p><ol><li><a href="#basics">List and dictionary comprehensions in Python: the basics</a></li><li><a href="#key-info">Python dictionary comprehension, list comprehension, and generator expression - what do you need to know</a></li><li><a href="#wrap-up">Wrap up</a></li></ol><div class="raw-html-embed"><section id="basics" style="height: 20px;"></section></div><h2>List and dictionary comprehensions in Python: the basics</h2><p>In Python, dictionaries are used to store elements - just like you would in a regular list. But instead of accessing these elements with the help of an index, what you do is assign a fixed key to a value and then access it using that key. The key-value pair might sometimes be a better data structure than a list for some kinds of problems. For example, dictionaries are a common feature used by data scientists.&nbsp;</p><p>Note that all the keys in a dictionary need to be hashable. Hashing is the process of running an item through a particular kind of function called the hash function in Python. It returns a unique output for a unique input value. Just to give you an example, floating-point numbers, strings, and integers are all hashable. List, dictionaries, and sets aren’t.</p><p>&nbsp;</p><h3>So, why use comprehensions in Python?</h3><p>Good comprehension helps to develop code that is more expressive and easier to read. The primary thing you need to remember when creating a comprehension construct is to never allow it to become too complex – to the point where you’re not too sure about what exactly they’re doing anymore.</p><p>Dictionary comprehension refers to a method for turning one dictionary into another one. During this kind of transformation, you can conditionally include the items from the original dictionary into the new one.</p><p>Dictionary comprehensions come in handy if you want to substitute for loops or lambda functions in Python. Not all for loops can be written as dictionary comprehension, but all dictionary comprehension can be written with a for loop.&nbsp;</p><div class="raw-html-embed"><section id="key-info" style="height: 20px;"></section></div><h2>Python dictionary comprehension, list comprehension, and generator expression - what do you need to know</h2><h3>List comprehension</h3><p>This feature offers a more compact and elegant method for building a list than for loops.</p><p>What exactly is a for loop? In Python, a for loop is used to handle repetitive programming tasks. You can use it to iterate over a sequence such as a list, dictionary, or string. Here’s an example of a for loop to help you understand how it works:</p><pre><code class="language-python">animals = ['cat', 'dog', 'lion']
for animal in animals:
print(animal)</code></pre><p>A for loop takes the first element of the fragment and checks whether it exists. If it does, the for loop performs the required action – in our example, it’s printing. The loop starts again and looks for the next element. If it discovers that this element exists, it carries out the action again. This is repeated until the loop can’t find any more elements, and it ends.&nbsp;</p><p>Ok, back to list comprehension.</p><p>You can use it to create lists from an existing list. Developers construct list comprehensions from brackets that contain the expression followed by a for clause. Optionally, the for or if clause can come next.&nbsp;</p><p>Here is an example to show you how it works:</p><pre><code class="language-python">x = [i for i in range(10)]</code></pre><p>This generates the following result:</p><pre><code class="language-python">[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]</code></pre><p>It’s far more concise and readable than its for loop equivalents.&nbsp;</p><p>&nbsp;</p><h3>Dictionary comprehension</h3><p>As I explained before, dictionary comprehensions work very similarly to list comprehensions – only for dictionaries. They offer an elegant way for building a dictionary from an iterable or transforming one dictionary into another.&nbsp;</p><p>What is the syntax of dictionary comprehension? It’s very similar to the one you use for list comprehensions (more on that later on). However, you need to include the key-value pair in the expression. Here’s an example that shows you how it works:</p><pre><code class="language-python">{i: i+10 for i in range(4)}</code></pre><p>The return value will be as follows:</p><pre><code class="language-python">{0: 10, 1: 11, 2: 12, 3: 13}</code></pre><p>You can follow that basic syntax with an additional for or if clause if you need it. Dictionary comprehension is a powerful alternative to for loops and lambda functions.&nbsp;</p><p>More often than not, for loops or nested for loops can become very complicated and, as a result, become very confusing for the team. Dictionary comprehensions, on the other hand, provide a compact way of writing the same code, which makes it easier to read and understand by developers.</p><p>&nbsp;</p><h3>Generator expressions</h3><p>Finally, we have generator expressions - another high-performance method for writing code in Python. Generator expressions are far more efficient than traditional class-based iterators. In Python, class iterators are often verbose and require a lot of overhead from teams. Generators can perform the same function while reducing the overhead. And developers find creating generators relatively easy.&nbsp;</p><p>All you need to do is define a normal function with a yield statement rather than a return statement. The yield statement pauses the function and saves its local state so that successive calls can continue from where it left off.&nbsp;</p><p>Here’s how generators work:&nbsp;</p><ul><li>When you call a generator function, it doesn’t execute instantly but instead returns a generator object.</li><li>The code won’t execute until <i>next()</i> is called on that generator object.</li><li>When that happens, the control is passed temporarily to the caller, and the function is paused.</li><li>Local variables and their execution states will always be stored between calls.</li><li>Stop iteration will be raised automatically once the function is complete.</li></ul><p>&nbsp;</p><p>Generator expressions allow developers to build generators very quickly, without even having to use the yield keyword. They’re much more concise than generator functions.&nbsp;</p><p>Here’s an example:&nbsp;</p><pre><code class="language-python">g = (x**3 for x in range(20))</code></pre><p>What is the difference between generator expressions and list comprehensions?</p><p>If you take a look at these two, you might notice that their syntax is very similar. The only difference here is that they use round parentheses as opposed to square brackets.&nbsp;</p><p>A generator expression can be written in the following way:</p><pre><code class="language-python">(i ** 2 for i in range(10) if i % 2 == 0)</code></pre><p>Now compare it to list comprehensions which are written as follows:</p><pre><code class="language-python">[i ** 2 for i in range(10) if i % 2 == 0]</code></pre><p>However, the type of data they return is completely different. List comprehensions return the entire list, and the generator expression returns only the generator object. The values will be the same as those in the list, but they will be accessed one at a time by using the <i>next() </i>function.&nbsp;</p><p>This is what makes list comprehensions faster than generator expressions. That might not be the case if the size of the data being processed is larger than the available memory, though.&nbsp;</p><p>Since generator expressions produce value on-demand - contrary to list comprehensions that require memory for producing the entire list - generator expressions are more memory-efficient. It makes sense to use generator expressions if you’re working with large data sets and don’t need all of the results delivered to you at once.&nbsp;</p><p>Also, use generator expressions if you would like to avoid allocating memory to the results that will be produced. Another good use case for generator expressions is representing infinite streams of data since only one item will be produced at a time. That way, you eliminate the problem of storing an infinite streaming memory.&nbsp;</p><div class="raw-html-embed"><section id="wrap-up" style="height: 20px;"></section></div><h2>Wrap up</h2><p>Python’s for loops come in handy for dealing with repetitive tasks, but there are other options that Python grants to developers that help you achieve the same results - only faster and more efficiently. List and dictionary comprehensions are a powerful alternative to for loops and lambda functions. They make code more concise and easier to read.</p><p>However, it’s key that developers never let them become too complex to cross off all the benefits they chose them for in the first place. Similarly, generators and generator expressions provide teams with high performance and a simpler way of creating iterators. They might be similar to list comprehensions in their syntax, but they return value only when asked for that. Unlike list comprehensions, they don’t deliver the entire list. As a result, they consume less memory and are more suited for processing big data.&nbsp;</p><p><strong>Are you planning to use one of these constructs in your next Python project? Or do you have experience in using them for building real-life applications? Give us a shout-out in the comments; we look forward to learning how developers are taking advantage of these Python functionalities to build products today.</strong></p>

Python Basics: Generator Expressions & Comprehensions | Codete Blog

Python Basics: Generator Expressions & Comprehensions

In theory, a medical physicist with a love for coding.
In practice, a front-end developer who was absorbed by web technologies like they were Kirchhoff's perfect black body. He got his first job as a software developer in 2017 (with Angular2 and Typescript). With constant acceleration, he has moved to the event horizon of the “black hole” of IT. After being totally absorbed, he’s reached the excited state when he wants to radiate his passion and knowledge. A bit of a geek with a wide spectrum of interests from martial arts, through pixel art, to the game industry.


Borys Palka

Engineer passionate about building stuff displayed in the browser window but not only. Almost like Iron Man in software development, so maybe Software Man?

Szymon Oleszek

<p><strong>React.js</strong> is making headlines, and more and more people, intrigued with its possibilities and immense popularity, ask questions like „What is React?”, „What is React used for”, and, first and foremost, „Is React a framework or library?”.</p><blockquote><p>As Stack Overflow’s annual 2020 Developer Survey indicated, React belongs to the most popular technologies software developers utilize. It ranked second in the „Web Frameworks” category, with as much as <a href="https://insights.stackoverflow.com/survey/2020#technology-web-frameworks-professional-developers2" target="_blank" rel="nofollow"><u>36.8% of professional developers utilizing it</u></a>.</p></blockquote><p>Also, React.js was dubbed the second „most loved” web framework, with an impressive percent (68.9%) of software developers who are developing with it that <a href="https://insights.stackoverflow.com/survey/2020#technology-most-loved-dreaded-and-wanted-web-frameworks-loved2" target="_blank" rel="nofollow"><u>have expressed interest in continuing to do so</u></a> in the future.</p><p>&nbsp;</p><p>Table of contents:</p><p>1. <a href="#intro">What is React js? All you need to know about it</a></p><p>2. <a href="#features">React.js – the most important features</a></p><p>3. <a href="#apps">Apps that you can build in React.js</a></p><p>4. <a href="#use">How to use React in your projects best</a></p><p><br>&nbsp;</p><div class="raw-html-embed"><section id="intro" style="height: 20px;"></section></div><h2>1. What is React js? All you need to know about it</h2><p>Is react a framework, a library, or maybe another kind of technology? Well, the answer is quite unambiguous. React.js is a free open-source JavaScript library for building user interfaces in web applications. It was created by Facebook and Jordan Walke in 2013.</p><p>What sets this front-end library apart are low entry barriers and significant elasticity in use, which certainly add to its great popularity. Compared to Vue.js and Angular, the <a href="https://trends.google.com/trends/explore?cat=31&amp;q=Vue.js,React,Angular" target="_blank" rel="nofollow"><u>interest in React is way bigger in almost all world regions</u></a>. And, what’s crucial, it is on the sharp rise, as the <a href="https://gist.github.com/tkrotoff/b1caa4c3a185629299ec234d2314e190" target="_blank" rel="nofollow"><u>data on Stack Overflow trends</u></a> show.</p><p>But what are the reasons why React is king? Which features make React software so unique and handy, at the same time? Let’s check.</p><div class="raw-html-embed"><section id="features" style="height: 20px;"></section></div><h2>2. React.js – the most important features</h2><p>There are several features of React that can be regarded as especially useful and valuable for front-end developers taking advantage of this library. These are:</p><p>1. <a href="https://programmingwithmosh.com/react/react-virtual-dom-explained/" target="_blank" rel="nofollow"><u>Virtual DOM</u></a> (Document Object Model) tree – it is a representation of browser DOM objects in JavaScript that helps optimize the application’s performance. Based on the comparison (a process called reconciliation), it renders new objects in the browser or updates the old ones - because manipulation directly on DOM objects is inefficient.</p><p>2. <a href="https://www.geeksforgeeks.org/reactjs-components/" target="_blank" rel="nofollow"><u>Components</u></a> – this is the encapsulation of the code’s logic into smaller blocks upon which we may build the entire application later on. UI components may be divided into class and functional ones. Render method belongs to the most used ones in the case of React components.</p><p>3. <a href="https://www.w3schools.com/react/react_jsx.asp" target="_blank" rel="nofollow"><u>JSX</u></a> (JavaScript XML) – an embeddable XML-like syntax extension to ECMAScript, or the format of writing HTML and XML code within the JavaScript language. This syntax is to be concise and familiar, and it’s made for „<a href="https://facebook.github.io/jsx/" target="_blank" rel="nofollow"><u>defining tree structures with attributes</u></a>”.</p><p>4. <a href="https://pl.reactjs.org/docs/hooks-overview.html" target="_blank" rel="nofollow"><u>React hooks</u></a> – those are JavaScript functions that embed logic, and new functionalities in other hooks or functional components. They organize code within particular components and enable using React without classes. Previously, only class components had component lifecycle status and management. By the way, check out the React Hooks series on YouTube delivered by Codete developers. Here's the <a href="https://www.youtube.com/watch?v=GqDv-9e88AQ" target="_blank">intro to React Hooks &gt;</a>&nbsp;</p><div class="raw-html-embed"><section id="apps" style="height: 20px;"></section></div><h2>3. Apps that you can build in React.js</h2><p>React js development has been used in a number of commonly used apps. It’s not only Facebook, React’s originator, that makes use of this library. The list of <a href="https://brainhub.eu/library/famous-apps-using-reactjs/" target="_blank" rel="nofollow"><u>popular apps made in React.js</u></a> is much longer and encompasses household names such as Netflix, Instagram, WhatsApp, and Dropbox, to name but a few.</p><p>But there are many more use cases possible, and, in fact, any app can be built in React. However, React.js mainly focuses on building client-side applications, the so-called single-page applications. But it can also be used to create <a href="https://nextjs.org/" target="_blank" rel="nofollow"><u>server-side rendering applications</u></a>. What’s more, <a href="https://reactnative.dev/" target="_blank" rel="nofollow"><u>mobile applications for iOS and Android</u></a> and even <a href="https://microsoft.github.io/react-native-windows/" target="_blank" rel="nofollow"><u>desktop ones</u></a> can also be built with React - with user interface in mind.</p><div class="raw-html-embed"><section id="use" style="height: 20px;"></section></div><h2>4. How to use React in your projects best</h2><p>Have you ever wondered when to use React js, what types of projects it is best fitted to? Well, there are some insights that it’s good to get acquainted with before you switch to React and start using it in your endeavors.</p><p>Since it is a library, and not a full-featured and full-fledged framework, such as Angular, taking part in another project is often equal to applying different approaches and solutions. And this means more time to understand the application for new developers and increasing the chance of creating an anti-pattern in the project, which can also translate into less effective development. Plus, if someone doesn’t like to have a clear-cut architecture and rules for running projects, React may not be the best option.</p><p>On the other hand, when in the right hands, React’s flexibility offers many great possibilities, like the fact that we can use different libraries and packages more easily to create React apps. We can swiftly and freely apply various approaches, e.g. Styled components, <a href="https://cssinjs.org/?v=v10.7.1" target="_blank" rel="nofollow"><u>CSS-in-JS</u></a>, CSS modules or even plain CSS, Redux, Mobx, Recoil, and more.</p><p>The enormous React community and popularity of developing with it is certainly also a plus because it increases the probability that someone will help us with a problem that we may encounter one day. However, there are some voices that the documentation for React is rather poor and insufficient, and that <a href="https://www.knowledgehut.com/blog/web-development/pros-and-cons-of-react" target="_blank" rel="nofollow"><u>using JSX may be inconvenient</u></a>.</p><p><strong>And what are your experiences with React.js? To you, what are the challenges of developing with it? What kind of projects is it best suited to? Can you spot any significant limitations of using it?</strong></p>

What is React.js? Complete Overview | Codete Blog

What is React.js? Complete Overview

Michał gained his business experience at PZU, FedEx, and Revolut. He spent most of his professional time working as an analyst – he has always been fascinated with processing numbers, improving processes and company applications.  Currently, he works as Python Developer at Codete.

Michał Dycha

<p>As far as programming languages are concerned, Python belongs to all-time favorites. Many software developers are aware of Python advantages and don’t need any kind of encouragement to use it in daily tasks.</p><p>As <a href="https://insights.stackoverflow.com/survey/2020#technology-most-loved-dreaded-and-wanted-languages-wanted" target="_blank" rel="nofollow"><u>Stack Overflow Developer Survey 2020</u></a> indicates, Python has been dubbed the most „wanted” programming language by them, with as many as 30% of programmers who don’t use it, yet, expressing interest in developing with it in the future. Moreover, two-thirds (66.7%) of those who already develop with it, want to continue doing so – which is the third-best result among all languages or technologies ranked within this survey. And all these with Python not being a top paying programming language but offering earning a decent income, still.</p><p><strong>Python’s use cases are impressively versatile. They include data science, artificial intelligence, machine learning, the Internet of Things (IoT), web scraping,&nbsp; task automation, </strong><a href="https://wiki.python.org/moin/NumericAndScientific" target="_blank"><strong><u>scientific and numeric computing</u></strong></a><strong>, as well as websites, e-commerce systems, and other business applications.</strong></p><p>Among many obvious benefits and advantages the Python programming language offers, we may of course find a fly in the ointment. Surely, those who have worked with it for years can easily spot some scratches on its close-to-perfect image. Just like any other solution, Python comes with its limitations and can’t be used on all occasions. It all depends on the project, and knowing all Python advantages and disadvantages is crucial to decide if it's suitable in your particular case. So, let's go through Python's pros and cons to help you make the right choice.</p><p>&nbsp;</p><p>Table of contents:</p><p>1. <a href="#intro">Python pros and cons in a nutshell</a></p><p>2. <a href="#pros">Advantages of Python you simply must know</a></p><p>3. <a href="#cons">Disadvantages of Python you should be aware of</a></p><p>4. <a href="#projectuse">Working on a new project? Use Python!</a></p><div class="raw-html-embed"><section id="intro" style="height: 20px;"></section></div><h2>1. Python pros and cons in a nutshell</h2><p>Python’s immense success and impressive popularity simply make this programming language worth knowing. But is it also worth implementing and developing with it? Well, firstly we should be well aware of all pros and cons of Python, and know what it actually is. And it is an open-source programming language that can be described with such attributes as <strong>general-purpose</strong>, <strong>dynamically-typed</strong>, and <strong>object-oriented</strong>.</p><p>What’s important, it’s proper for both small and large projects, and – despite being 30 years old – it’s perfect for many present-day applications, including ultra-modern ones. There are some important constraints, though. Anyway, those new to programming may easily get attracted to Python. And what's important, they can count on the support of a vast and active community of fellow developers willing to give them a helping hand in polishing their coding skills and solving Python problems.</p><div class="raw-html-embed"><section id="pros" style="height: 20px;"></section></div><h2>2. Advantages of Python you simply must know</h2><p>Python’s <strong>versatility</strong> is one thing, but this programming language has much more to offer.&nbsp;</p><p><strong>First and foremost, Python is exceptionally easy to read but also to learn, and then produce logical, clear code.</strong> It enables even business users to utilize it to a basic extent. And this is one of the reasons why it is so immensely popular among applications used in companies. Users with only basic knowledge of this language can write – on their own – a script that will automate their day-to-day tasks.</p><p>The language itself, or its syntax, is similar to English. Code can be written fast and efficiently. On the one hand, using Python decreases the production cost (due to quickness of writing and low barriers for entry), but on the other – in the case of advanced calculations – it can be left far behind other languages. Python is a <strong>scripting language</strong> which makes it slow, and Java or C++ perform the majority of operations way faster.</p><p>However, taking into account that contemporary computers have high computing power, one doesn’t need to keep an eye on performance that much, and more and more often attention is paid to the high speed of writing programs, and not to performance. The latter, however, is not that bad in the case of Python.</p><p>Moreover, <strong>analytics and data scientists simply like this language</strong> – it’s proper for writing code or performing data analysis fast. As for this area, environments such as <strong>Jupyter</strong> are popular – with convenient code editors that enable code execution in parts, viewing the script results on the fly, or drawing charts.</p><blockquote><p>To sum up, the pros of Python are:</p><ul><li>Easy syntax (similar to English)</li><li>Quick coding</li><li>Fast data analysis</li><li>Great community support</li><li>Various types of code editors</li></ul></blockquote><div class="raw-html-embed"><section id="cons" style="height: 20px;"></section></div><h2>3. Disadvantages of Python you should be aware of</h2><p>And now comes the second part of the enumeration of the advantages and disadvantages of Python.&nbsp;</p><p><strong>Some of the most-known downsides to Python include insufficient speed and runtime errors. </strong>Also, it’s not considered as perfect for mobile development or game development. But what do developers often complain about, in detail?</p><p>Python is a <strong>dynamically-typed</strong> language, which means that one doesn’t have to declare variables nor their type. It’s very convenient because it requires less effort from a software developer who has a bit less code to write. However, there are some risks involved, and some programmers may get lost easily in their variables. Moreover, a simple spelling mistake can make a program work the way it shouldn’t. It’s enough if we write new_varable instead of new_var<i>ia</i>ble – something that it’s difficult to trace. In most cases, though, such errors won’t cause the program’s stopping.</p><p>And because Python is a scripting language, it enables quick modifications. Due to that, we may occasionally experience some problems with end-users. In general, the code of scripts or programs is open so <strong>the user can make changes easily.</strong> They may accidentally add a letter, a comma, a period, or any other character, and this can disable using a particular tool. Of course, an executable file for the user <i>can</i> be prepared but it’s usually not very practical.</p><blockquote><p>To cut the long story short, some basic Python cons are:</p><ul><li>Relatively slow performance</li><li>Unsuitable for mobile &amp; games development</li><li>Highly error-sensitive (mind the typos!)</li><li>End-users may easily modify (and break) the code</li></ul></blockquote><div class="raw-html-embed"><section id="projectuse" style="height: 20px;"></section></div><h2>4. Working on a new project? Use Python!</h2><p>There are certainly many reasons why you should at least consider using the Python programming language. But if you still aren’t an avid Python supporter, the numerous benefits of learning Python described above may surely convince you to start using this programming language.</p><p>Developers with a good command of Python are in high demand these days, and there are many directions where this programming language may take us. Apart from web or software development, they include areas such as data science, ML and IA, task automation, the Internet of Things, and more.</p><p><strong>Some of the industries Python is utilized in include finance, insurance, retail banking, healthcare, and aviation, to name but a few. </strong>Python is also proper for educational purposes, namely being regarded as a „<a href="https://www.python.org/about/apps/"><u>superb language for teaching programming</u></a>”. And among successful companies that decided to implement Python, we may find high-profile brands such as Google, Facebook, Instagram, Amazon, Netflix, Reddit, Uber, and Dropbox.&nbsp;</p><p><strong>And you, what other Python advantages and disadvantages can you spot? Do the benefits of using Python outweigh its downsides, to you? How do you utilize Python in your daily duties?</strong></p>

Python Advantages & Disadvantages You Must Know | Codete Blog

Python - Advantages and Disadvantages Every Developer Must Know

<p>So, you have an amazing <internallink internallinkid="/blog/how-to-find-a-new-app-idea">idea for an app</internallink>, and now you'd like to bring it to life. Or you came up with a great solution that will take your enterprise process to the next level, and now you're ready to make it happen. In both cases, to realize your plan, you'll need to hire a development team.&nbsp;</p><p><strong>But how do you assemble the right team members? What is the best software development team structure?&nbsp;What are the roles and responsibilities in an IT project?</strong></p><p>Many of our clients ask us these questions, so we decided to share our insights from over a decade of providing <a href="/services" target="_blank">software development services</a> and setting up product development teams.&nbsp;Keep on reading this article to learn how to structure a successful development team and who does what to contribute to its success.&nbsp;</p><p>&nbsp;</p><p>Table of contents:</p><ol><li><a href="#teamstructure">Everything about software development team structure</a></li><li><a href="#agilevswaterfall">Agile vs. Waterfall and the software development team structure</a></li><li><a href="#roles">Roles in a software development team</a></li><li><a href="#projectsuccess">The right software development team structure brings success to every project</a></li></ol><div class="raw-html-embed"><section id="teamstructure" style="height: 20px;"></section></div><h2>Everything about software development team structure</h2><p>Every digital product starts with the right people. You need to map your business objectives to the roles in the software development team. When designing the team's structure, make sure that it reflects key factors related to your project, such as its type and complexity.&nbsp;</p><p>Before stepping into the recruitment phase or hiring an <internallink internallinkid="/blog/team-extension-model">outsourcing contractor</internallink>, determine the scope of your project. For example, if you're going to build a product prototype, a team of four people might be enough to accomplish that. But if you're planning to launch a brand-new application that has multiple features and third-party integrations, the number of people in your team will be higher.&nbsp;</p><p>Just to give you an idea, here are a few examples of product types and the correlating software development team structure:</p><ul><li><strong>A discovery or </strong><internallink internallinkid="/blog/what-is-proof-of-concept-and-how-to-do-it-right-expert-explains"><strong>Proof of Concept</strong></internallink><strong> project</strong> might take up to 5 specialists consisting of product manager, product owner (on the client-side), business analyst, software architect, and UX/UI designer.</li><li><strong>For developing an </strong><internallink internallinkid="/blog/building-a-minimum-viable-product"><strong>MVP</strong></internallink>, you're likely to have more than six specialists - among them the product owner, product manager, business analyst, UX/UI designer, software engineers, and software testers.</li><li><strong>A product development project</strong> will require more specialists - but that depends on your methodology. If you're using an agile approach, the team will usually include up to nine specialists. If your project is large-scale, then several agile things might work together. For a waterfall project, there's no size limit, and the number of people in your team will depend on the type and complexity of your application. Apart from the specialists listed in the previous point, you might want to add test automation engineers, performance engineers, DevOps, and security engineers.</li></ul><p>As you can see, the nature of your product will determine the shape and size of your software development team. There are two key factors you need to take into account here.&nbsp;</p><p>&nbsp;</p><h3>Your project timeline</h3><p>The speed with which you need to turn your product around will impact the team structure as well. With fewer team members, completing the project might take longer. So, if you have an idea for an impactful app that needs to be developed from scratch within a very tight deadline, you might have to assemble a larger team of senior engineers who can cover all your needs and bring results quickly.&nbsp;</p><p>&nbsp;</p><h3>Your budget</h3><p>Naturally, your budget plays a key role as well. It will affect every decision you make about how many team members you can hire and the seniority of these specialists. To reduce product expenses, opt for agile product management methodologies that allow delivering software in increments and focus on high-priority tasks first to give you more cost flexibility.</p><div class="raw-html-embed"><section id="agilevswaterfall" style="height: 20px;"></section></div><h2>Agile vs. Waterfall and the software development team structure</h2><p>The methodology you select will impact your work process and the software development team roles. The project methodology shapes the size of your team but also the responsibilities of individual team members and relations within the team. Just to give you an idea, here are some key facts about waterfall and agile approaches.&nbsp;</p><p>&nbsp;</p><h3>Waterfall</h3><p>In the Waterfall model, the development process is divided into distinct phases, and its scope is always defined in advance. This gives the team a limited amount of potential changes to apply. The features are prioritized at the start of the project, and the team is focused on completing the project. Quality assurance is provided by software testing that follows software engineering.&nbsp;</p><p>&nbsp;</p><h3>Agile</h3><p>Within agile methodology, the development process is broken into smaller increments (called <i>sprints</i>) that usually last from 2 to 4 weeks. Scope changes is the daily bread of such teams. Features are always prioritized at the beginning of each sprint, and issues are managed according to their priority. The team has a different approach – a product mindset that focuses on delivering value to the customer. Another important difference is that testing is always performed in parallel with the development work.</p><p>&nbsp;</p><h3>How do these models influence the team structure?&nbsp;</h3><p>In the waterfall model, the team is based on hierarchical relations between team members. There are project managers and subordinates who have well-defined responsibilities. The team structure offers the managers more control over the work, and they are the ones responsible for making critical decisions.&nbsp;</p><p>Let’s take a look at Agile now. One of the more popular Agile frameworks is Scrum, which prioritizes a self-managed and -organized Scrum team supported by the Scrum Master. The latter focuses on fostering relationships within the team and creating a good working environment that allows the members to be productive. This doesn’t mean that Agile prevents any form of management - just like a waterfall doesn’t prevent self-organizing teams.&nbsp;</p><p>Still, Agile teams count no more than 9 to 10 people. They allow a certain level of autonomy as team members have the freedom to prioritize their workloads and carry out the work as they see fit.</p><div class="raw-html-embed"><section id="roles" style="height: 20px;"></section></div><h2>Roles in a software development team</h2><p>Here are the most common roles you can find across all development teams.&nbsp;</p><p>&nbsp;</p><h3>Frontend developers</h3><p>Frontend developers are tasked with creating the part of your application that users actually see and interact with - the user interface. Their job is to make sure that the experience is smooth and user-friendly.&nbsp;They work in line with the guidelines and recommendations of the UX and UI designers. The most programming languages for frontend developers are JavaScript, HTML, CSS. They often use JavaScript frameworks as well.&nbsp;</p><p>&nbsp;</p><h3>Backend developers</h3><p>A backend developer takes care of everything that goes "under the hood of an application". Backend engineers are the key problem solvers in the development process. They plan and develop the application architecture, make decisions about services and databases communication, establish how API and external integration will work, and ensure that the product is fully secure.&nbsp;</p><p>&nbsp;</p><h3>Quality assurance specialists and testers</h3><p>These team members are there to make sure that your application is bug-free and has adequate support across all the devices and browsers, meeting all of your key requirement. They pay a lot of attention to the application's performance, security, usability, and portability.&nbsp;</p><p>Naturally, a quality assurance engineer also looks at the application from the perspective of end users to make sure that all the implemented features meet the requirements. They write documentation and create test cases to help developers deliver a high-quality end product.&nbsp;</p><p>&nbsp;</p><h3>Quality assurance automation engineers</h3><p>Those engineers are tasked with writing automated tests. An automated test is a small piece of software that runs in the background and constantly tests the application. If something goes wrong, the project team knows what happened immediately. This is a key capability of agile teams where testing goes hand-in-hand with development.&nbsp;</p><p>&nbsp;</p><h3>DevOps engineers</h3><p>DevOps engineers ensure that the solution is available 24/7, cost-effective to maintain, and easy to upgrade. They also work hard to guarantee that they can handle sudden use or activity spikes or downtown. They basically take care of your infrastructure.&nbsp;</p><p>Their specialty is implementing solutions such as Infrastructure as Code, automated deployment processes, and robust <internallink internallinkid="/blog/what-is-cloud-computing-software-development-benefits-and-challenges-for-business-owners">cloud solutions</internallink>. Their work is all about making the application secure, reliable, available to everyone.&nbsp;</p><p>&nbsp;</p><h3>Product designers</h3><p>Product designers transform your product vision into user-friendly designs. They also develop user journeys optimized for the best experience and high conversion rates. In short, they make sure that the product reaches your business goals.&nbsp;They track all the necessary data to make conclusions and propose solutions to help you reach your business objectives and ensure that users fall in love with your product.&nbsp;</p><p>&nbsp;</p><h3>Project managers</h3><p>The project manager's responsibility is thinking about everything that could possibly go wrong in the project and then making sure that it doesn't. Their job is also to ensure that your product is delivered on time and within budget.&nbsp;</p><p>&nbsp;</p><h3>Business analysts</h3><p>Business analysts are responsible for verifying the business idea and checking whether you're investing your time and money into building the right solution. You need to verify that your app solves an existing user problem that is also in line with your business model and customer expectations – and that's what a business analyst (BA) can help you with.</p><p>&nbsp;</p><h3>Product owners</h3><p>In an agile team, the product owner is responsible for prioritizing tasks in the team's backlog to streamline their execution. All the while, this role keeps an eye on the conceptual and technical integrity of the features being implemented to make sure they're in line with the overall <internallink internallinkid="/blog/benefits-of-digital-transformation">business strategy</internallink>.</p><div class="raw-html-embed"><section id="projectsuccess" style="height: 20px;"></section></div><h2>The right software development team structure brings success to every project</h2><p>As you can see, software development teams are made of a variety of team roles and responsibilities. It's more than just a few developers who code. Writing the code is actually the easiest part of this equation.&nbsp;Successful projects require development teams composed of various people with different skill sets.&nbsp;</p><p>There are many other factors that contribute to the success or failure of an application - and many of them can be addressed by bringing the right people to your team. If you have the best specialists on board, you can be sure that your project is in good hands and gets the attention it needs.&nbsp;</p><p><strong>If you're looking to hire a dedicated software development team, get in touch with us and </strong><a href="/estimation" target="_blank"><strong>let's discuss your software project</strong></a><strong>. We know how to structure a team to deliver a successful project within the specified timeline and budget.</strong></p>

Software Development Team: Structure & Roles | Codete Blog

Software Development Team - Structure and Most Important Roles

<p style="text-align:justify;"><strong>Are you ready to put your knowledge and skills to work solving global problems and making an actual difference? Do you want to have a genuine impact on how the healthcare system works? Participate in the first edition of Hack4Med: CRACoV, co-organized by Codete and Krakow University Hospital!</strong></p><p style="text-align:justify;">Hack4Med is a game-changing event that bridges the gap between the worlds of medicine and emerging technology. It’s one of the first data-oriented hackathons in Europe, allowing participants to work conceptually on real (but fully anonymized) medical data from hundreds of COVID-19 patients - including results of laboratory testing and imaging diagnostics such as x-rays and computed tomography of the lungs.</p><h4 style="text-align:justify;"><strong>Hack4Med: CRACoV will be held in Krakow on the weekend of October 16-17, 2021, at the New Headquarters of the Krakow University Hospital, 2 Jakubowskiego Street.</strong></h4><p style="text-align:justify;">The main goal of this year's edition will be to create an innovative tool that will allow for the automation of COVID-19 risk prediction, known as a <i>covid risk calculator</i>, which will aid doctors in predicting the course of an individual's illness. The tool is intended to be used by the medical staff of the Krakow University Hospital (one of the event's main partners), so your efforts will have a real impact on people's lives.</p><blockquote><p style="text-align:justify;">"The goal of the hackathon is to produce a seed of solutions that will have a chance to become real software helping clinicians in the nearest future," said Marcin Jędrychowski, the Director of Krakow University Hospital.&nbsp;</p></blockquote><p style="text-align:justify;">And if you want to challenge yourself with a slightly different task, you can also try to create a program that estimates the likely degree of lung involvement in COVID-19 patients, or an app that informs users about the effects of COVID-19 on muscles.</p><blockquote><p style="text-align:justify;">"We hope that solutions presented by the participants of Hack4Med will allow a patient with COVID-19 to be quickly assigned to one of three groups: one with a mild course of the disease, one with a severe course of the disease, and one with a high risk of death," said Karol Przystalski, co-organizer of the event. “We intend to use modern solutions to identify non-obvious instances," he added.&nbsp;</p></blockquote><p style="text-align:justify;">The competition's jury and mentors include experts in programming, data science, and artificial intelligence, as well as Krakow University Hospital representatives from various medical disciplines who work with COVID-19 patients on a regular basis.</p><p style="text-align:justify;">The Hack4Med: CRACoV Hackathon final will feature the 25 best teams (limit of 5 people per team) - a total of over 120 high-level specialists. They will work in different rooms but will have access to the same data. Additional questions from participants will be answered by specialists.</p><p style="text-align:justify;">We're looking for people who are dedicated to finding long-term solutions. There is no requirement for prior medical experience. And, while money isn't everything, we're excited to tell you that the prize pool could be worth up to PLN 100,000!</p><h4>Registration for the Hack4Med: CRACoV medical hackathon to combat Covid-19 has already begun!</h4><p>So, are you a programmer, data scientist, user experience designer, or product manager? Do you have an interest in data analysis? Do you want to shape the future of medical technology? Register your team for the Hack4Med hackathon at <a href="https://www.hack4med.com/"><u>https://www.hack4med.com/</u></a>&nbsp;</p>

Case Study: Data Monitoring Service

Want to find out more?

Leave us your email address and you'll hear from us soon.