Author Posts - Programming

Odoo is one of the fastest growing open source, business application development software products available. It comes with: Powerful GUI, Performance optimization, Integrated in-app purchase features Fast-growing community to transform and modernize businesses We recently interviewed Yenthe Van Ginneken, an Odoo developer, highly active in the Odoo community and recipient of Odoo best contributor of the year 2016 and Odoo community hero 2017. He spoke to us about his journey with Odoo, his thoughts on Odoo’s past, present and future, and the Odoo community. Expert's Bio Yenthe Van Ginneken, currently the technical team leader at Odoo Experts, has been an Odoo developer for over four years. He has won two awards, “Best contributor of the year 2016” and the “Odoo community hero” award in 2017. He loves improving software and teaching other people the best practices for Odoo development on his blog. You can read his Odoo blog, follow him on Twitter or reach out to him on LinkedIn. Key Takeaways Odoo is scalable and flexible to the extent that everyone, from a small startup to a giant tech company can benefit from it. It is ahead of quite a lot of ERP systems with its clean UI, advanced modules integration and the flexibility of its technical framework. Python is the preferred language of choice among most developers that want to use the Odoo framework, especially for automating and scaling tasks. The Odoo community is diverse and vast. By contributing and regularly interacting with other members, you will gain deeper insights into many different aspects of Odoo development. A great way to learn to develop in Odoo and quickly grow is actually by helping in the community. Odoo 12 will reportedly improve data processing, better report insights, and support for OCR (Optical Character Recognition) for handling documents among other exciting updates. Full Interview On who should use Odoo Odoo is more than an ERP tool. According to you, What is Odoo? Who will benefit from adopting Odoo? What made you choose Odoo?   For me, Odoo is more than an ERP. Odoo literally allows me to make any module or functionality that I can think of. Since Odoo is so flexible and scalable I believe that almost everybody can benefit from adopting Odoo. Whether you’re a small start-up or a giant tech company. The most important part to be able to benefit from adopting Odoo is adjusting the processes and mindset to use Odoo, not adjusting Odoo for the company. The projects that work the best and have the best benefit are those that don’t over-engineer and try to focus on the main company processes. I personally chose Odoo after I got an opportunity to become an Odoo developer at a company in Belgium. After the job offer I visited Odoo.com and saw the massive amount of functionalities in Odoo (while being free!) and I was genuinely amazed. After looking at the technical framework and all the default options provided by the framework I was sure that I would love to develop and implement in Odoo. Since that day I never stopped working with Odoo. On journey from OpenERP to Odoo Odoo started off as OpenERP and then in 2014, it moved beyond just ERP and was renamed Odoo. How has Odoo’s journey been so far since then? What do you think are the key milestones achieved by Odoo till date? Since the renaming from OpenERP to Odoo the company has seen a rapid growth. A bit after changing the name Odoo also introduced the enterprise version which was, in my opinion, the turning point for Odoo S.A. It allowed Odoo to keep its open source strength and market share while also gathering funds to fund the ongoing growth of the product. The big investments that are being made in the Research and Development team allow them to keep improving year after year. The main strengths and key milestones from Odoo are absolutely its flexibility, a great framework and the fact that most of the possibilities are already in Odoo by default. On the drive behind contributing to the Odoo community You are highly active in the Odoo community. How did you get into contributing for Odoo? How has this experience improved you as a developer? According to you, what are the key challenges the Odoo community is facing currently? My very first contribution started in the second half of 2014 and weren’t very significant at first. I noticed that Odoo 8, at that point the newest version, was not very well translated and had a lot of inconsistency so I started translating it in Dutch. From there on I noticed that it could have had quite a big impact and in fact could improve the ERP. It didn’t take long before I started contributing in other ways. Reporting issues, fixing bugs, maintaining bug reports and helping other people on the official help forums. By contributing to all these different subjects I got introduced to more domains and gained more insights. Thanks to my involvement with the community, I’ve learned that there is more than one side to developing and implementing projects. I believe it made me a better programmer and made me think a lot more about ways to code custom development for projects. Without being active in a community and contributing you’ll be blindsided by your own perspective. It is a great way to get challenged and you’ll see more cases by being active in the community than you could ever see on your own. The Odoo community faces a few challenges at this point. It is difficult to maintain the right balance between the enterprise version and community (free) version. There are not a lot of very active contributors to the official Odoo code and Odoo is behind on handling fixes/bug reports made by community members. This results in some community members not feeling appreciated or heard. Hiring a second community manager might be a good way to resolve these issues though. The most difficult challenge for both Odoo and the Odoo community is to make everybody feel heard and give every person the ability to contribute in the way he or she can. When there is enough help from Odoo and the community feels supported there is a possibility for a great and thriving community. On how to learn Odoo effectively As a person who has a strong hold over Odoo development, what is the typical learning curve for someone getting into Odoo, as a consultant? What is the best way to start developing in Odoo? What should one watch out for while learning? The learning curve can be quite long and can have its challenges. Usually, if you don’t have any experience with Odoo and only know basic Python it’ll take about six months before you really get to know the ins and outs of Odoo. The best way to learn to develop Odoo is probably the same as with most things in technology: dive in! Make sure you get the basics right and understand how the main functionalities work before going deeper. A great way to learn to develop in Odoo and to quickly grow is actually by helping in the community. You can get insight and help from experienced developers while also contributing to the community, it’s a win-win. Start small and build your way up to the details. It is important to find good documentation and tutorials though. At the moment there are still quite some blog posts and tutorials that are from quite a low quality. Because of this I actually started writing my own tutorials, which explain concepts step by step with samples. You can find it at https://odoo.yenthevg.com Editor’s note: Check out our collection of Odoo Books and Videos to master Odoo development. On the upcoming Odoo 12 release Odoo 12 is expected to be released later this year. What’s got you excited about this new release? Quite a lot! Every release has loads of new features that are announced and it’s an exciting time, every time. The introduction of a report designer for functional people is one of the best (known) new features. The improved reporting tools for data insight will become a great improvement too. The biggest announcements are made at Odoo Experience in October and are not publicly available yet so we’ll have to wait for that. On the future of ERP There is a lot happening in the area of ERP and BI: self-service analytics, real-time analytics, agile BI development etc. Where do you foresee the ERP market headed? We've seen ERP/CRM systems getting powerful inbuilt analytics systems, what do you think is next for the industry? What is Odoo’s role here? As with any sector in IT, a lot is becoming very data-driven. In the future integration and usage of data will only grow. I expect the combination of BI and AI to become a powerful way to process and handle data on unseen scales. Odoo itself has already hinted at improved data processing, better report insights and support for OCR (Optical Character Recognition) for handling documents. Odoo has been ahead of quite a lot of ERP systems with its clean UI, advanced modules integration and the flexibility of its technical framework for years. I expect Odoo will also be leading the way for handling all this data and getting important statistics out of it. I’m quite sure it is only a matter of time before Odoo starts working on even better BI reporting and tools. On Python and automation Automation is everywhere today and becoming an integral part of organizations and processes. Python and automation have gone hand in hand since Python’s early days. Today Python is one of the top programming languages. How do you see Python’s evolution over the years in the area of automation? What are the top ways you use Python for automation, today? It is for a reason that Python is so popular. It is flexible, quite quick to program with and the options are virtually endless. In the next years, Python will only become more popular and this will also be the case for automation projects made with Python. I personally use the Odoo framework with Python as a backbone for nearly everything that I automate (and in fact also for non-automated tasks). The projects vary from automatically handling stock moves to automatically updating remote instances to automatically getting full diagnostic reports. The combination of the programming language and the framework from Odoo allows me to automate tasks and deploy them on a big scale. ERP tool in focus: Odoo 11 How to Scaffold a New module in Odoo 11 A step by step guide to creating Odoo Addon Modules

Despite considerable hype, chaos engineering doesn’t appear to have yet completely captured the imagination of the wider software engineering world. According to this year’s Skill Up survey, when asked, only 13% of developers said they were excited about it. But that doesn’t mean we should disregard - far from it. Like many of the best trends, it might blow up when we least expect. It might find its way onto your CTOs eyes in just a few months. As site reliability engineering grows as a discipline, and as businesses start to put a value on downtime, chaos engineering is likely to become a big part of the reliability and resilience toolkit. Gremlin, chaos engineering, and the end of the age of downtime “People are expected to always be up” says Matt Fornaciari, co-founder and CTO of Gremlin, a product that offers “failure as a service” to businesses. I spoke to Fornaciari last month to get a deeper insight on Gremlin and the team and ideas behind it. He believes the world has changed in recent years, and the days of service windows when sites would just be taken down for an hour or two for an update or change is over: “that’s unacceptable to people these days.” Fornaciari isn’t an unbiased observer, of course. The success of Gremlin depends on chaos engineering’s adoption and acceptance. However, he’s not going out on a limb; there’s clear VC interest in Gremlin. At the end of 2017 the company received their first round of funding - more than 7 million USD. It’s a cliche but money does talk - and in this instance it seems to be saying that this approach might change the way we think about building our software. Arguably, chaos engineering - and by extension Gremlin - is a response to other trends in software. “I’ve seen a lot of signals that this is the way the world’s going”, Fornaciari says. He’s referring here to broader trends like cloud and microservices. He explains that because microservices is all about modularity, and breaking aspects of your software infrastructure into smaller pieces “you end up with nodes in this network” which “adds network complexity.” Consequently, this additional complexity means there is more that can go wrong - it becomes more unreliable. Gremlin’s bid to democratize chaos engineering It’s important to note here that chaos engineering has been around for some time - it’s not a radically new methodology. But it’s largely been locked away in some of the world’s biggest tech companies, like Netflix and Amazon. Many of Gremlin’s leaders actually worked at those companies - Fornaciari has worked at Salesforce and Amazon, for example. “The main goal was to democratize chaos engineering… we’ve [the Gremlin team] done it at the bigger companies and we’re like you know what, everyone can benefit from this”. That is the essential point around chaos engineering. If it’s going to catch on in the mainstream tech world, it needs to be more accessible to different businesses. Fornaciari explains that many of Gremlin’s customers are larger organizations. These are companies for whom downtime is of utmost importance, where a site outage that lasts just an hour could cost thousands of dollars. That said, from a cultural perspective, many organizations find it difficult to adopt this sort of mindset. “Proving the value of something that doesn’t happen,” Fornaciari says, is one of the biggest challenges for Gremlin. This is particularly true when selling their tool. Pager pain: How Gremlin sells chaos engineering to customers This is how Gremlin does it: “We have three qualifying questions: do you measure your downtime? Do you have somebody who’s responsible for downtime? And do you actually have a dollar amount tied to it?” Presumably, for many organizations at least one answer to these questions is “no”. That’s why customer support is so important for Gremlin. “Customer success and developer advocacy are two of our biggest initiatives… I’ve told people as we’re recruiting them that half of our goal as a company is to educate people.” Gremlin’s challenges as a product and as a business reflect the wider difficulties of managing upwards. The tension between those ‘on the ground’ and those at a more senior and managerial level is one that Gremlin is acutely aware of. This is where a lot of push back comes from, Fornaciari explains: What we’ve seen so far is just push back from top down - like, why do we need this? We use the term pager pain to define the engineer on call - the closer you are to the ground the closer you are to the on call rotation and the more you feel those pains and the more you believe in this but as you raise up a couple of levels you maybe don’t feel that as much… if you don’t have that measure on uptime - unless someone is on the hook for that at a higher level there’s oftentimes a why do we need this, why are we going to spend money on breaking things. Pager pain is a nice concept - it captures the tension between different layers of management. It highlights the conflict between ‘what do we need?’ and ‘what can we do?’ Read next: Blockchain can solve tech's trust issues  Safety, simplicity and security To successfully sell Gremlin, the way the product is designed is everything. For that reason, the Gremlin team have three tenets built into their product: safety, security, simplicity. When you’ve got a “potentially dangerous tool,” as Fornaciari himself describes it, making sure things are safe and secure is absolutely essential. Arguably, the fact that chaos engineering is so hard to do well might be something that Gremlin can use to its advantage. “One thing we hear when we talk to companies about it is ‘well we’ll go build this ourselves’ and the fact is it’s a really hard thing to do, and a hard thing to do well.” Gremlin is walking on a bit of a tightrope. On the one hand chaos engineering is for everyone, but on the other it’s difficult and dangerous. It should be accessible, but not too accessible. “One of the reasons we don’t have a free offering is because we are a little worried about protecting our customers not doing any harm to people… I mean, this is essentially giving somebody a potentially dangerous tool.. If they’re not given the proper education then that could be a problem, right?” Gremlin aren’t the only chaos engineering product out there. As with any trend, there are plenty of software platforms and tools emerging for technologically forward thinking businesses. Fornaciari doesn’t see these as a threat - he’s confident, bullish even, about Gremlin’s place in the market. “There are a lot of tools out there that people can go and use but they really lack the safety and simplicity.” Alongside its philosophy of safety, security and simplicity, a big selling point, according to Fornaciari, is the experience and expertise that is built into Gremlin’s DNA. “We’ve got fifteen years of combined expertise in this space” he says. “Being the experts on it and having built it 3 or 4 times already in different big companies, it sort of gave us this leg up to go out there in the world.” But while Fornaciari is eager to assert Gremlin’s knowledge, there’s no trace of elitism - sharing knowledge is a core part of the product offering. “We actually built out customer success tooling so we can see if particular attacks fail for them we can actually proactively reach out and be like ‘hey we saw you were trying to do this, maybe you meant to do this’” Fornaciari explains. Controlled chaos: chaos engineering and the scientific method Control is central to Gremlin’s philosophy - it’s a combination of the team’s commitment to safety, security and simplicity. In fact, this element of control that distinguishes chaos engineering today, from what went before. Central to Gremlin’s mission to make chaos engineering accessible, is also redefining how it’s done. “If you’re familiar with the netflix chaos monkey mentality of randomly terminating services, well that’s a good start, but safety is really lacking. We talked more about this controlled chaos… this idea that you start fairly small with this small blast radius and then as you become more confident you grow it out and grow it out as opposed to just like ‘cool, let’s just chuck a grenade in here and see what happens.’” Fornaciari goes on to describe this ‘controlled chaos’ in a surprising way. “It’s much more like the scientific method actually. Applying that method to your infrastructure and your reliability in general.” This approach is essential if you’re going to do chaos engineering well. How to do chaos engineering effectively When I ask Fornaciari how engineering teams and businesses can do chaos engineering well he emphasizes the importance of starting with a hypothesis: “You need to have a hypothesis that you’re trying to prove.Throwing random chaos at something is fine - it’ll sort of surface some of the unknown unknowns for you. But really having a hypothesis that you’re trying to prove is the best way to get value out of this [chaos engineering].” If you’re going to take a scientific approach to testing your infrastructure using ‘chaos experiments’, managing scale is also incredibly important. Don’t run before you can walk is the message. “Keep it very small initially, then you start to grow the blast radius. You definitely want to make sure that you’re starting off with the smallest modicum that you can.” Given the potential dangers of throwing metaphorical gremlins into your system, starting where your comfortable makes a lot of sense. “Start in staging, start where your comfortable, build your confidence. Make sure your system behaves well in front of non-customer facing traffic before you go out to the world.” That said, Gremlin have had “some pretty bold customers” who go straight ahead and start running chaos experiments in production. “That was cool. It’s a little scary, but they were confident and they’ve been using Gremlin as part of their system ever since.” Chaos engineering requires confidence and control Ultimately, if chaos engineering is going to take off - as Fornaciari believes it will - engineers will need to be incredibly confident. That’s true on a number of levels. You need confidence that you’ll be able to handle a range of experiments and deploy them wisely. But you’ll also need confidence that you can manage the expectations of those in senior management. It’s not hard to see the value of chaos engineering. As Fornaciari says “if you prevent one outage one time, you’ve saved that money to pay for the tool to make sure it doesn’t happen again.” But it might be hard to find time for it. It might be hard to get buy in and investment in the tools you need to do it. Gremlin are certainly going to play an important part in helping engineers do that. But one of its biggest challenges - and perhaps one of its most noble missions too - is transforming a culture where people don’t really appreciate ‘pager pain’. If Fornaciari and Gremlin can help solve that, good luck to them. You can follow Matt Fornaciari on Twitter: @callmeforni

Python is currently one of the most popular and desired programming languages. Primarily for its simplicity, agility and ability to be used across a variety of software development projects. Although an Object Oriented language, Python supports an array of programming paradigms, including Functional Programming. Functional Programming is a paradigm that treats computation as the evaluation of math functions. It’s quite advantageous as it allows for efficient parallel programming and error-free code. We recently interviewed Steven Lott, a true Python professional and best-selling author of a number of Python books. Steven talks a bit about modern Python and how the language adapts well to the Functional paradigm, offering developers a range of solutions to build modern, cloud based applications. He also talks about his most recent book, the second edition of his best seller, Functional Python Programming, and how it will benefit developers looking to enter the world of functional programming with Python. About Steven Steven F. Lott has been programming since the 70s, when computers were large, expensive, and rare. As a contract software developer and architect, he has worked on hundreds of projects, from very small to very large. He's been using Python to solve business problems for over 10 years. Steven is a technomad who lives in various places on the east coast of the U.S. Follow his technology blog to stay updated on the latest trends in tech. You may also connect with him on LinkedIn. Key Takeaways Why learn Python? One of the major reasons developers appreciate Python, is because it’s simple, and has the ability to create succinct and expressive programs. For example, data scientists prefer Python because they can build sophisticated analytical tools using simple functions and produce useful results. Why Functional programming? The functional programming paradigm forms the perfect foundation for developers and architects to build and design modern architectures like Serverless. But Python isn’t inherently functional. Although an object oriented language at heart, Python can create higher order functions and other functional features. Python 3 has made this easier. Steven’s Python 4 wish list: In future versions of Python, Steven hopes to see a wider use of Unicode operator characters like × in addition, * for multiplication, and ÷ in addition to / for division. Also, he expects PyPy and RPython projects to be more widely used; future Pythons versions will benefit from optimizations and restructuring the interpreter. One of the most helpful features of Python 3 are type hints, which allow one to write clear and implicitly documented code while preventing the invoking of methods with wrong data types. Steven’s latest edition of Functional programming with Python, explores type hints in depth along with core language features such as lambdas, generator expressions, functions, and callable objects. Full Interview Python is one of the top programming languages. List down top 3 features of Python that make programmers love it.. It seems like programmers love Python primarily because it allows them to create succinct, expressive programs. Before long, they learn the vast library of code - is another reason for Python's immense popularity. Many people adopt Python because of the low barrier to entry: it really is as simple as download and start working. You've been working with Python for over a decade. How has your experience been with Python as a primary development language? Over my 40-year career, I've used a variety of languages. And I've found Python to be extremely productive. A team can build and deploy microservices-based applications at a tremendous pace. Data scientists can build sophisticated analytical tools using simple functions to produce useful results without the overheads of complex compile and build environments. Back when Python 3 just came into existence, we saw certain resistance to the notion of Python being apt for functional programming. How would you say Python has progressed since then? At its core, Python is an object-oriented language. Consequently some functional features aren't central. One of the essential functional design tools -- creating higher-order functions -- has always been part of Python. The wider use of generator functions in Python 3 has made functional Python programming much more common. Many Python applications are hybrids, mixing object-oriented and functional features of the language. Now that type hints are available, it becomes practical to use mypy to confirm that the code is very likely to work properly. For a developer who's picking up the Functional Programming paradigm for the first time, what do you think are the prerequisites? Functional programming is closely aligned to the core mathematical ideas of functions and functional composition. As a consequence, a minimal background in programming could be advantageous to help leverage essential function definitions and avoid needless state change. For programmers already heavily invested in procedural programming, it may be helpful to set the idea of stateful objects aside. In the above context, how does your book, Functional Python Programming, Second Edition, prepare its readers to be industry ready? What are the key takeaways for readers from your title and how does it help with the learning curve? The examples in the book are related to exploratory data analysis, an important skill in the broader area of data science. They also focus on the standard library, allowing someone to apply the functional design approach to other libraries and tools. I think a focus on the core language features (e.g., lambdas, generator expressions, functions, callable objects) provide a foundation that allows a programmer to apply the core ideas more widely to different kinds of problems and other software packages. What new and updated content is available in this edition, for developers who've purchased your previous book? Almost all of the examples have been rewritten to include type hints. This can be an important quality check helping to ensure the Python code works. When used with doctest examples, it becomes relatively easy to provide reliable, correct code. In a few cases, external packages (i.e., the pymonad library) don't have type hints and the examples reflect this gap. Can you throw some light on Functional Reactive Programming and how FRP with Python is boosting the implementation of modern architectures like Cloud Native and Serverless? The central idea of serverless programming -- a collection of isolated functions -- fits the functional programming paradigm very elegantly. The processing is generally stateless, with stand-alone functions waiting for their inputs. Ideas like "choreography" of web services work with this idea of stateless functions that respond to an input by producing an output. This leads to careful separation of persistence and state change from the other transformational processing. This helps create software with easy-to-understand behavior and implementation code that's very expressive of the algorithm. As Python inches towards a 4.0, what do you think should/can be changed/rectified in the language, for the better? At some point, I expect the PyPy and RPython projects to create some optimizations leading to a fundamental restructuring of the interpreter. Perhaps these changes could remove the need for the GIL (Global Interpreter Lock) by exposing a minimal kernel of code that requires exclusive access to internal data structures. Of more general interest, I'd hope to see wider use of Unicode operator characters like × in addition to * for multiplication, and ÷ in addition to / for division. Perhaps ∻ could be adopted for truncated division. This could also lead to use of ℝ instead of float and ℤ instead of int providing a more mathematical look to type hints. It would be nice to expand the use of the Unicode character set to create more readable programs. List down 3 reasons for developers to choose your book as the book of choice for Functional programming in Python. Programmers who want to create succinct and expressive code often find functional design to help them fulfill this. The Functional Python Programming book provides extensive examples that show multiple ways to achieve this goal. In many cases, generator functions and lazy processing can be a large performance improvement. A generator function can use less memory than a large data collection, and this change can be helpful. This book will provide number of examples of lazy processing to avoid creating large, in-memory collections. It can be difficult to get started with type hints. The use case in this book show type hints in somewhat more complex real-world situations. If you enjoyed this interview, head over to check out Steven’s latest edition of Functional Python Programming, He is leveraging Python to implement microservices and ETL pipelines. His other titles with Packt Publishing include Python Essentials, Mastering Object-Oriented Python, Functional Python Programming, and Python for Secret Agents. What is the difference between functional and object oriented programming? Building functional programs with F# Seven wrongs don’t make the one right: Solving a problem with Functional Javascript

Golang is currently one of the fastest growing programming languages in the software industry, finding its way into almost every nook and cranny of application development. Its speed, simplicity and reliability make it the perfect choice for all kinds of developers. We recently interviewed Mina Andrawos, an experienced Go engineer and the author of the book, Cloud Native programming with Golang.  Mina explains why Go is being rapidly adopted in various development areas and by leading projects like Docker and Ethereum, how it is evolving as a language and what makes it great for cloud development. He shares expert insights into Go’s adoption for mobile development, embedded systems and the serverless web. He has also thrown light on the new directions of cloud computing and how Go makes development a piece of cake. Author’s Bio Mina Andrawos is an experienced engineer who has developed deep expertise in Go by using it personally and professionally. He has written numerous Go applications with varying degrees of complexity. Other than Go, he has skills in Java, C#, Python, and C++. He has worked with various databases and software architectures and is skilled with the agile methodology for software development. Besides software development, he has working experience of scrum mastering, sales engineering, and software product management. Key Takeaways The 3 most notable features of Go are its concurrency model that sets it apart from mainstream languages, the fairly mature standard package which covers a wide range of use cases and its ease of deployment. Go is designed to be simple and intuitive, yet reliable and robust for application development. There are currently several mature tools to write Go programs, like VSCode, Vim, Atom or Sublime text. Mina’s book Cloud native programming with Golang helps you build production level cloud native microservices and covers a wide range of important topics in the space such as types of message queues, docker containers, how to monitor microservices, perform continuous integration and much more. Go can be viewed as a hybrid between mainstream statically typed languages like Java, and popular dynamic scripting languages like Javascript. Go was built with the goal of being fully cross-platform in mind, and it can work in smaller mobile processors like ARM. Full Interview Go is one of the most popular and fast growing programming languages. What according to you, are the 3 notable features of Go? Go is a very remarkable programming language. Numerous articles were written about the advantages of the language. Trying to gather notable features in Go can actually produce enough material to fill a number of white papers. However, having said that, let’s try to squeeze three out of them: 1. Concurrency: Go’s unique concurrency features are legendary. The language offers a concurrency model that stands apart from most mainstream programming languages. Go advocates a different way of thinking about concurrency problems in modern software. In one of the articles I wrote, I have described what concurrency means in the Go language. 2.  The Standard package: Go has the advantage of being coupled with a fairly mature standard package, which covers tons of key features for building modern software. This means that once you install Go, you can build production level software that can cover a wide range of use cases from Restful web APIs to encryption software, before needing to consider any third party packages. 3.  Ease of deployment: A program written in pure Go code typically compiles to a single native binary, which basically makes deploying an application written in Go as easy as copying the application file to the destination server. In other words, there is no special software needed to run Go applications in production servers like language runtimes \ virtual machines (As an example, for Java programs, we need to install the Java runtime environment in our production servers to run our programs) . Go is also cross platform, so you can target an operating system of your choice when compiling a piece of code. You have been developing software for quite some time now. What tools do you use on a day-to-day basis? Programming is a very fun craft, and the tools we use in our development are integral to making the environment enjoyable. For me, because I work with multiple programming languages, I use different tools based on the project. My current tool of choice for the Go programming language is VSCode, combined with its Go Plugin by lukehoban.  This is just my preference however. There are lots of other tools that could be used to write Go programs. Some developers prefer Vim with all it’s popular features, while others prefer Atom or sublime text. There is also a Go plugin for the IntelliJ IDE, which I had used in the past and really liked. What kind of learning plan would you suggest to web developers who are interested in using Go as their main development tool to build Cloud Native Applications? What aspects do you feel are tricky to get past? The plan would include three steps: Get comfortable with Go. Learn the design patterns, the software tools, and the technologies of cloud native applications. Get familiar with a cloud service provider (like AWS, Azure, or Google cloud) Go is designed from the grounds up to be simple and intuitive. This makes learning Go a better and more straight forward experience compared to many other languages. For developers new to Go, one of the best resources to start learning Go, is the Go tour. Once the developer is familiar with Go, then they are ready to move to the next step of the learning plan, which is to learn the design patterns of cloud native applications, as well as the software technologies needed to build and deploy such applications. A good way to start is to check out my newly published book: Cloud Native Programming with Go. One major advantage of the book is that it not only covers the technologies and design patterns associated with cloud native applications, but it also connects these technologies and design patterns with Go, which makes it an excellent resource for Go developers looking to build cloud native software. This, in my opinion, is the trickiest aspect a software professional needs to get past to acquire the necessary skills to build cloud native applications. For the third step, the execution will depend on the cloud service provider that you or your business would like to work with. Some enterprises like to utilize their own private clouds, while others are tied to a mainstream cloud provider due to existing contracts or executive preferences. For AWS, my book should provide enough insights into  how to write Go cloud native applications, that are capable of making use of the cloud platform. In the context of all the above, how does your book, Cloud Native programming with Golang, prepare its readers to be industry ready? What are the key takeaways for readers from your title and how does your book help with the learning curve? The book was the product of great amount of research, sleepless nights, and focused effort. I am a coauthor of the book with Martin Helmich, who I enjoyed working with immensely. The book was designed from the get go to expose the reader to the practical experience needed to build production level cloud native microservices in Go, with the least amount of fat. It takes the reader into an expanding learning journey, which starts from the ten thousands foot view of cloud native microservices, then dives deep down into all the different aspects that need to work together in harmony in order to produce production level cloud native applications. It will prepare you to be industry ready by covering a wide array of topics that are vital in a production environment. Examples include: Different types of message queues found in production environments, docker containers, monitoring microservices via Prometheus, continuous integration, Restful APIs design, security and authentication, AWS Go APIs, NoSQL databases, ReactJS, and more. What makes it so special that it doesn’t shy away from covering sophisticated and diverse topics from scratch. For example, if you look at the Restful API chapter, we don’t assume that you already have knowledge of the HTTP protocol or web services design. Instead, we build the concepts with you from point zero up. The only knowledge you need before reading the book is some familiarity with the Go language. Another example is our message queues chapter, you can start reading the chapter knowing nothing about message queues, but then finish the chapter with more than enough knowledge to be very effective in utilizing message queues in your applications. The book is perfect for readers who want to begin learning how to build cloud native microservice applications. It will carry the reader from a beginner level to a point where they become capable of tackling advanced tools and design patterns in that space. You've been working with several other languages like Java, C++, C# and Python. How does Go compare to the other languages you've worked with? Go, in my opinion, could be viewed as a hybrid between mainstream statically typed languages (like Java), and popular dynamic scripting languages (like Javascript). That is because Go doesn’t require the same level of verbosity that you would need in a Java program. However it’s still a bit more verbose than an equivalent Javascript or Python implementation, luckily, Go makes up for this extra verbosity compared to dynamic languages, by delivering software that is much faster than the equivalent Python or Javascript implementation. One very hotly debated feature that is missing in Go is generics. Some people in the community believe it’s a good thing Go doesn’t have generics, while others can’t wait till Go maintainers are convinced that generics need to be added. From my personal experience, I have come across situations where it would have been nice to have generics, however it never got to the point where I couldn’t complete the task at hand. Having said that, there are some situations where you can argue that a piece of Go code might be a bit more verbose than an equivalent piece of Java code that makes use of generics. As mentioned earlier, Go’s concurrency model is different than almost all mainstream programming languages. Once you master the building blocks of Go’s concurrency model (namely, Go channels and goroutines), you can build very powerful concurrent software with relative ease. I always find writing concurrent software in Go to be a much more smooth experience for me than writing concurrent software in other languages. Also another mention from earlier was the ease of deployment. I never tire from enjoying how easy it is to deploy my Go programs to production compared to other languages. One last notable mention is the tooling. Since Go is a relatively new programming language, the tooling is not yet as fancy as what’s available for older languages like C# or Java for example. However, having said that, the Go ecosystem is maturing nicely every day, and we have more than enough tools right now to build fairly sophisticated software in Go. There is no more proof of this fact than the uprise of advanced software projects written in Go like Docker and Ethereum. You've worked with JavaScript as well. What's your take on using Go for full-stack web development / Isomorphic web development, over JS? That is a very interesting question. For people not familiar with the term ‘isomorphic web development’, it basically means using the same programming language for most of the front-end and the back-end components of the web application (combined with CSS or LESS or some other front-end styling technology). There is an important distinction to make between ‘Isomorphic web development’, and ‘full-stack web development’. You can be a full-stack web developer, while using Javascript for the front-end in addition to another language like Go or Ruby for the backend. However, if you are building an ‘Isomorphic’ web application, the idea is that you make use of one language for almost all your code, whether it’s on the front-end or the backend. I think Go enjoys being in the sweet spot where simplicity meets performance. That is because, Go comes included with out-of-the-box packages, that make web development relatively smooth. Not to mention a growing third party ecosystem, that complements the standard package and further facilitates writing web applications in the Go programming language. Having said that, Javascript was built initially for the sole purpose of front-end web pages, but then grew in scope after the Node.Js project came into existence, which made Javascript a more than capable backend language as well. So for the sake of being neutral and impartial, I would like to cover some advantages and disadvantages of using Go for web development vs Javascript. Let’s start with the disadvantages of using Go for web development compared to Javascript: Javascript is a language that could natively be used in the frontend and the backend components of web applications, this will always be an advantage of using Javascript over any other programming language, when it comes to web development. However, in case of Go, this disadvantage is countered to some extent, by the existence of GopherJS . GopherJS converts Go code to Javascript code. This means that you can write front-end code in Go, then have it converted to Javascript in order to work on the browser, which will get you very close to the isomorphic web development experience you obtain from using Javascript on the frontend combined with Node.JS on the backend. GopherJS is a very popular project, with more than 6000 stars on Github. People use it and it delivers them results. Having said that, the disadvantage of GopherJS is that it’s not native, since it converts your Go code to Javascript code, which means that when tricky issues happen, you may need to troubleshoot the auto-generated Javascript code, which is not always a fun experience, especially if your reason for using GopherJS is to avoid Javascript in the first place. Your experience will vary based on your projects, and the goals you are trying to achieve. Where do you see the future of Go's development going? What changes or improvements can the community expect in future releases? Go is growing in popularity every day. I see an immensely positive outlook for the future of development in Go. I think the sky's the limit. Go currently powers some of the most exciting projects in the industry, like Docker, Kubernetes, and Ethereum, among many others. Not only that, but Go also became integral to the operations of major players in the software industry Like Google and Uber, among many others as well. All of this richness of the user base, provides Go unprecedented opportunities for growth and adoption. Engineers and maintainers who experienced Go first hand, tend to use it in their future endeavors, further enriching the ecosystem.  The language had been fairly stable and consistent for a while now, and no substantial language changes are to be expected in the near future. So if you start learning Go now, you skills will stay relevant for a long time. Most of the improvements currently getting added to Go are more related to it’s runtime performance as well as standard package enhancements. Are there any interesting areas of implementation you've noticed Go finding its way into? Do you think the language would be best fit for any specific kind of development? One interesting area for me that Go is starting to find it’s way into is mobile development. Since Go was built with the goal of being fully cross-platform in mind, it can work in smaller mobile processors like ARM for example. This means that programs written in Go not only can work in server and desktop operating systems -like Linux, MacOS, and Windows- but they also can function in mobile environments like Android and IOS.  Having said that, it is important to mention that the ecosystem for developing Go apps on mobile devices is still young and maturing. If curious, you can check https://github.com/golang/mobile for Go’s mobile tools. There is also an interesting Go framework that is still in early development but looks extremely promising as a tool to write mobile applications in Go, you can find it here: https://gomatcha.io Regarding best fit use cases for the language, I see Go as a powerhouse for backend software development. Especially the kind of modern backend that relies on microservices and distributed architectures. The power that Go gives you in the world of the server backend is indisputable. Can you give developers 3 reasons why they should pick up your book? This book Cloud Native programming with Golang covers a diverse set of practical topics from scratch, that can help the reader build production level cloud native microservices. We did a lot of research to put all these topics together. I honestly doubt you would find another resource that would cover all those topics in one place. Example of topics covered are: Restful APIs, Secure microservices, message queues (Kafka, RabbitMQ, and AWS SQS), ReactJS, MongoDB, DynamoDB, Docker, Kubernetes, AWS, microservices monitoring with Prometheus, and continuous delivery, among others. Additionally it covers the topics in a logical top-down order, which solidifies the learning process. So we start the journey by covering the 10,000 foot view about how a cloud native architecture looks like, the design, the thinking process, the scalability, and more. From there, we take satisfying deep dives into the different aspects of cloud native applications. Towards the end of the learning journey, we don’t just leave the reader with no direction. Instead, we offer a path forward to where they should take their learning journey to the next level. Amazon recently added Lambda support for Go. What's your opinion on Serverless Go? Would it go hand in hand with Cloud Native development? It was a very exciting announcement indeed. I believe serverless support is a powerful tool in the developer’s toolbox to build cloud native applications in Go. The option to include a serverless component in your application, allows you to automate very focused triggered tasks that are not supposed to run forever. This ability helps you build better cloud native applications in the long run. Microservices, on the other hand, are better suited for tasks and operations that are expected to run continuously. If you enjoyed this interview, do head over to check out Mina’s book, Cloud Native programming with Golang.

To celebrate the launch of Python Interviews, we ran a Q&A session on Twitter with some of the key contributors to the book. Author and interviewer Mike Driscoll (@driscollis), and experienced Python contributors Steve Holden (@holdenweb), and Alex Martelli (@aleaxit) got together to respond to your questions. Here's what happened... https://twitter.com/PacktPub/status/979055321959358465 https://twitter.com/aleaxit/status/979055993874104321 https://twitter.com/holdenweb/status/979056136199593984 https://twitter.com/driscollis/status/979056963987361793 The future of Python We then asked Mike, Steve and Alex what they thought the future of Python is going to look like. https://twitter.com/aleaxit/status/979057847660003328 https://twitter.com/holdenweb/status/979059669699309569 https://twitter.com/holdenweb/status/979059813459034112 https://twitter.com/driscollis/status/979059276017815554 How to get involved with the Python community We then asked what our experts think is the best way for someone new to the Python community to get involved. With the language growing at an immense rate, more people are (hopefully) going to want to contribute to the project. https://twitter.com/aleaxit/status/979059707389231105 https://twitter.com/holdenweb/status/979060708276137985 Advice for anyone new to programming Programmings popularity as a career choice is growing. That's not just true of new graduates but people looking to retrain and take on a new challenge in their career. But what should anyone new to programming know when starting out? https://twitter.com/aleaxit/status/979063034202107905 https://twitter.com/holdenweb/status/979061878554054658 https://twitter.com/driscollis/status/979061529575346177 Switching from Python 2.7 to Python 3 There's been considerable discussion within the community on the merits of shifting from Python 2.7 to Python 3. But whatever the obvious advantages are, there will always be resistance to change when it requires an investment of time and effort. And if you don't need to switch then why would you? Here's what Mike, Steve and Alex had to say... https://twitter.com/aleaxit/status/979063346665107457 https://twitter.com/holdenweb/status/979062974450192384 https://twitter.com/driscollis/status/979062547935571969 What gives Python an advantage over other programming languages? Why is Python so popular exactly? If it's growing at such a fantastic rate, why are developers and engineers turning to it? What does it have that other languages don't? https://twitter.com/aleaxit/status/979063792276471808 https://twitter.com/holdenweb/status/979064210608001025 https://twitter.com/driscollis/status/979063896173699072 Future Python releases If Python's going to remain popular, it's going to need to adapt and evolve with the needs of the developers of the future. So what capabilities and features would our experts like to see from Python in the future? https://twitter.com/driscollis/status/979064329864695813 https://twitter.com/aleaxit/status/979064880757063680 https://twitter.com/holdenweb/status/979064474496913408 What problems does Python face as a language? https://twitter.com/driscollis/status/979065953949552640 https://twitter.com/aleaxit/status/979065864539357184 https://twitter.com/holdenweb/status/979066065706725376 Why is Python so useful for AI and Machine learning? AI is a growing area that has expanded beyond the confines of data science into just about every corner of modern software engineering. Python has been a core part of this, and in part it explains part of the rise of Python's popularity - people want to build algorithms in a way that's relatively straightforward. https://twitter.com/driscollis/status/979066778771914752 https://twitter.com/holdenweb/status/979069094862389253 https://twitter.com/holdenweb/status/979069100831006721